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1. Clinico-histopathologic and single-nuclei RNA-sequencing insights into cardiac injury and microthrombi in critical COVID-19

Author

Michael I. Brener, Michelle L. Hulke, Nobuaki Fukuma, Stephanie Golob, Robert S. Zilinyi, Zhipeng Zhou, Christos Tzimas, Ilaria Russo, Claire McGroder, Ryan D. Pfeiffer, Alexander Chong, Geping Zhang, Daniel Burkhoff, Martin B. Leon, Mathew S. Maurer, Jeffrey W. Moses, Anne-Catrin Uhlemann, Hanina Hibshoosh, Nir Uriel, Matthias J. Szabolcs, Björn Redfors, Charles C. Marboe, Matthew R. Baldwin, Nathan R. Tucker, and Emily J. Tsai

Subjects
COVID-19, Cardiology, Medicine
Abstract

Acute cardiac injury is prevalent in critical COVID-19 and associated with increased mortality. Its etiology remains debated, as initially presumed causes — myocarditis and cardiac necrosis — have proved uncommon. To elucidate the pathophysiology of COVID-19–associated cardiac injury, we conducted a prospective study of the first 69 consecutive COVID-19 decedents at CUIMC in New York City. Of 6 acute cardiac histopathologic features, presence of microthrombi was the most commonly detected among our cohort. We tested associations of cardiac microthrombi with biomarkers of inflammation, cardiac injury, and fibrinolysis and with in-hospital antiplatelet therapy, therapeutic anticoagulation, and corticosteroid treatment, while adjusting for multiple clinical factors, including COVID-19 therapies. Higher peak erythrocyte sedimentation rate and C-reactive protein were independently associated with increased odds of microthrombi, supporting an immunothrombotic etiology. Using single-nuclei RNA-sequencing analysis on 3 patients with and 4 patients without cardiac microthrombi, we discovered an enrichment of prothrombotic/antifibrinolytic, extracellular matrix remodeling, and immune-potentiating signaling among cardiac fibroblasts in microthrombi-positive, relative to microthrombi-negative, COVID-19 hearts. Non–COVID-19, nonfailing hearts were used as reference controls. Our study identifies a specific transcriptomic signature in cardiac fibroblasts as a salient feature of microthrombi-positive COVID-19 hearts. Our findings warrant further mechanistic study as cardiac fibroblasts may represent a potential therapeutic target for COVID-19–associated cardiac microthrombi.

Published
2022
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2. A single-cell atlas of the mouse and human prostate reveals heterogeneity and conservation of epithelial progenitors

Author

Laura Crowley, Francesco Cambuli, Luis Aparicio, Maho Shibata, Brian D Robinson, Shouhong Xuan, Weiping Li, Hanina Hibshoosh, Massimo Loda, Raul Rabadan, and Michael M Shen

Subjects
epithelial heterogeneity, multipotent progenitor, organoids, renal grafts, Medicine, Science, Biology (General), QH301-705.5
Abstract

Understanding the cellular constituents of the prostate is essential for identifying the cell of origin for prostate adenocarcinoma. Here, we describe a comprehensive single-cell atlas of the adult mouse prostate epithelium, which displays extensive heterogeneity. We observe distal lobe-specific luminal epithelial populations (LumA, LumD, LumL, and LumV), a proximally enriched luminal population (LumP) that is not lobe-specific, and a periurethral population (PrU) that shares both basal and luminal features. Functional analyses suggest that LumP and PrU cells have multipotent progenitor activity in organoid formation and tissue reconstitution assays. Furthermore, we show that mouse distal and proximal luminal cells are most similar to human acinar and ductal populations, that a PrU-like population is conserved between species, and that the mouse lateral prostate is most similar to the human peripheral zone. Our findings elucidate new prostate epithelial progenitors, and help resolve long-standing questions about anatomical relationships between the mouse and human prostate.

Published
2020
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3. Differential requirements of androgen receptor in luminal progenitors during prostate regeneration and tumor initiation

Author

Chee Wai Chua, Nusrat J Epsi, Eva Y Leung, Shouhong Xuan, Ming Lei, Bo I Li, Sarah K Bergren, Hanina Hibshoosh, Antonina Mitrofanova, and Michael M Shen

Subjects
prostate, progenitor, androgen receptor, cell of origin, mouse models, Medicine, Science, Biology (General), QH301-705.5
Abstract

Master regulatory genes of tissue specification play key roles in stem/progenitor cells and are often important in cancer. In the prostate, androgen receptor (AR) is a master regulator essential for development and tumorigenesis, but its specific functions in prostate stem/progenitor cells have not been elucidated. We have investigated AR function in CARNs (CAstration-Resistant Nkx3.1-expressing cells), a luminal stem/progenitor cell that functions in prostate regeneration. Using genetically--engineered mouse models and novel prostate epithelial cell lines, we find that progenitor properties of CARNs are largely unaffected by AR deletion, apart from decreased proliferation in vivo. Furthermore, AR loss suppresses tumor formation after deletion of the Pten tumor suppressor in CARNs; however, combined Pten deletion and activation of oncogenic Kras in AR-deleted CARNs result in tumors with focal neuroendocrine differentiation. Our findings show that AR modulates specific progenitor properties of CARNs, including their ability to serve as a cell of origin for prostate cancer.

Published
2018
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4. Decreased BECN1 mRNA Expression in Human Breast Cancer is Associated With Estrogen Receptor-Negative Subtypes and Poor Prognosis

Author

Hao Tang, Salwa Sebti, Rossella Titone, Yunyun Zhou, Ciro Isidoro, Theodora S. Ross, Hanina Hibshoosh, Guanghua Xiao, Milton Packer, Yang Xie, and Beth Levine

Subjects
BECN1, BRCA1, Breast cancer, Autophagy, Medicine, Medicine (General), R5-920
Abstract

Both BRCA1 and Beclin 1 (BECN1) are tumor suppressor genes, which are in close proximity on the human chromosome 17q21 breast cancer tumor susceptibility locus and are often concurrently deleted. However, their importance in sporadic human breast cancer is not known. To interrogate the effects of BECN1 and BRCA1 in breast cancer, we studied their mRNA expression patterns in breast cancer patients from two large datasets: The Cancer Genome Atlas (TCGA) (n = 1067) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1992). In both datasets, low expression of BECN1 was more common in HER2-enriched and basal-like (mostly triple-negative) breast cancers compared to luminal A/B intrinsic tumor subtypes, and was also strongly associated with TP53 mutations and advanced tumor grade. In contrast, there was no significant association between low BRCA1 expression and HER2-enriched or basal-like subtypes, TP53 mutations or tumor grade. In addition, low expression of BECN1 (but not low BRCA1) was associated with poor prognosis, and BECN1 (but not BRCA1) expression was an independent predictor of survival. These findings suggest that decreased mRNA expression of the autophagy gene BECN1 may contribute to the pathogenesis and progression of HER2-enriched, basal-like, and TP53 mutant breast cancers.

Published
2015
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5. Modulation of ErbB2 blockade in ErbB2-positive cancers: the role of ErbB2 Mutations and PHLDA1.

Author

Guangyuan Li, Xiaoqi Wang, Hanina Hibshoosh, Cheng Jin, and Balazs Halmos

Subjects
Medicine, Science
Abstract

We set out to study the key effectors of resistance and sensitivity to ErbB2 tyrosine kinase inhibitors, such as lapatinib in ErbB2-positive breast and lung cancers. A cell-based in vitro site-directed mutagenesis lapatinib resistance model identified several mutations, including the gatekeeper ErbB2 mutation ErbB2-T798I, as mediating resistance. ErbB2-T798I engineered cell models indeed show resistance to lapatinib but remain sensitive to the irreversible EGFR/ErbB2 inhibitor, PD168393, suggestive of potential alternative treatment strategies to overcome resistance. Gene expression profiling studies identified a select group of downstream targets regulated by ErbB2 signaling and define PHLDA1 as an immediately downregulated gene upon oncogenic ErbB2 signaling inhibition. We find significant down-regulation of PHLDA1 in primary breast cancer and PHLDA1 is statistically significantly less expressed in ErbB2 negative compared with ErbB2 positive tumors consistent with its regulation by ErbB2. Lastly, PHLDA1 overexpression blocks AKT signaling, inhibits cell growth and enhances lapatinib sensitivity further supporting an important negative growth regulator function. Our findings suggest that PHLDA1 might have key inhibitory functions in ErbB2 driven lung and breast cancer cells and a better understanding of its functions might point at novel therapeutic options. In summary, our studies define novel ways of modulating sensitivity and resistance to ErbB2 inhibition in ErbB2-dependent cancers.

Published
2014
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6. MammaPrint Feasibility in a Large Tertiary Urban Medical Center: An Initial Experience

Author

C. Francisco Espinel, Shaughn Keating, Hanina Hibshoosh, Bret Taback, Kathie-Ann Joseph, Mahmoud El-Tamer, and Sheldon Feldman

Subjects
Medicine, Science
Abstract

Background. The MammaPrint (MP) diagnostic assay stratifies breast cancer patients into high- and low-risk groups using mRNA analysis of a 70-gene profile. The assay is validated for assessment of patients with estrogen receptor positive or negative tumors less than 5 cm with 3 or fewer malignant lymph nodes. TargetPrint (TP) is an assay for assessing estrogen, progesterone, and HER2-neu receptor status based on mRNA expression. A potential limitation of these assays is that they require an evaluation of fresh tissue samples. There is limited published experience describing MP or TP implementation. Methods. Over 10 months, 4 breast surgeons obtained samples from 54 patients for MP/TP analysis. The samples were analyzed by Agendia Labs. The tumors were independently evaluated for receptor status using immunohistochemistry (IHC). Retrospectively, we identified patients who were assessed by MP/TP during this period. Patients who underwent OncotypeDx evaluation were also identified. Results. Of the 54 patients receiving MP, 4 were found ineligible for MP risk assessment because >3 lymph nodes were found to be malignant. Out of all eligible patients, 14/50 (28%) had samples whose quantity of tumor was not sufficient for analysis (QNS). Out of eligible patients with tumors

Published
2012
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7. Quantitative Multiplex Immunofluorescence Evaluation of the Tumor Microenvironment in Pretreatment Tumors of Patients with Metastatic Breast Cancer and Serous Ovarian Carcinoma Treated with Liposomal Eribulin

Author

Hua Guo, Douglas K. Marks, Yvonne M. Saenger, Hanina Hibshoosh, Eileen P. Connolly, Yan Lu, Thomas R. Jeffry Evans, Donian Chyong, John Kucharczyk, Juanita Lopez, Kevin Kalinsky, Rebecca Kristeleit, Robyn D. Gartrell, and Pan Kim

Subjects
0301 basic medicine, Cancer Research, CD3 Complex, CD8 Antigens, T-Lymphocytes, Fluorescent Antibody Technique, Phases of clinical research, Breast Neoplasms, Immunofluorescence, Microtubule polymerization, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Ovarian carcinoma, Biomarkers, Tumor, Tumor Microenvironment, Humans, Medicine, Neoplasm Metastasis, Furans, Phospholipids, Ovarian Neoplasms, Tumor microenvironment, Clinical Trials, Phase I as Topic, medicine.diagnostic_test, business.industry, Cystadenoma, Serous, General Medicine, Ketones, Middle Aged, medicine.disease, Survival Analysis, Metastatic breast cancer, Serous fluid, Treatment Outcome, 030104 developmental biology, Oncology, chemistry, 030220 oncology & carcinogenesis, Cancer research, Female, business, Eribulin
Abstract

Eribulin inhibits microtubule polymerization and suppresses epithelial-mesenchymal transition. Conventional pathology approaches have not identified a precise predictive biomarker for Eribulin. We performed qmIF on pre-treatment tissue from 11 patients (6 TNBC, 5 HGSOC) treated with Eribulin-LF. T-lymphocytes were the dominant immune-subset in TME, with higher levels detected in stroma vs tumor (9% vs 2%). Greater density of CD3+ (

Published
2021

8. A molecular single-cell lung atlas of lethal COVID-19

Author

Jay H. Lefkowitch, Samuel F. Bakhoum, George A. Alba, Denis Schapiro, Yaron Bram, Patricia Ho, Ajay Nair, Anjali Saqi, Yiping Wang, Robert E. Schwartz, Daniel T. Montoro, Armando Del Portillo, Jianwen Que, Alain C. Borczuk, Robert F. Schwabe, Sean W. Chen, André F. Rendeiro, Johannes C. Melms, Somnath Tagore, Hanina Hibshoosh, Adrienne M. Luoma, Adam E. Kornberg, Amit Dipak Amin, Mariano G. Clausi, Niroshana Anandasabapathy, Chris J. Frangieh, Stephen M. Lagana, Olivier Elemento, Yinshan Fang, Huachao Huang, Igor Katsyv, Mayte Suárez-Fariñas, Xinzheng V. Guo, Benjamin Izar, Emily J. Tsai, Charles C. Marboe, Mathieu F. Bakhoum, Aveline Filliol, Glen S. Markowitz, Hiranmayi Ravichandran, Arnold Han, Emmanuel Zorn, Meri Rogava, and Jana Biermann

Subjects
0301 basic medicine, Pathology, medicine.medical_specialty, Multidisciplinary, Lung, business.industry, T cell, Monocyte, Cell, Inflammation, medicine.disease, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, medicine.anatomical_structure, Single-cell analysis, Pulmonary fibrosis, medicine, Progenitor cell, medicine.symptom, business, 030217 neurology & neurosurgery
Abstract

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection1,2, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1+ pathological fibroblasts3 contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand–receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development. Lung samples collected soon after death from COVID-19 are used to provide a single-cell atlas of SARS-CoV-2 infection and the ensuing molecular changes.

Published
2021

9. Abstract PS3-10: Monitoring neoadjuvant chemotherapy using diffuse optical tomography breast imaging system

Author

Hua Guo, Katherine D. Crew, Alessandro Marone, Hyun K. Kim, Mirella L. Altoe, Kevin Kalinsky, Meghna S. Trivedi, Mariella Tejada, Melissa K. Accordino, Dawn L. Hershman, Andreas H. Hielscher, and Hanina Hibshoosh

Subjects
Cancer Research, Chemotherapy, medicine.medical_specialty, Oncology, Breast imaging, business.industry, medicine.medical_treatment, medicine, Radiology, business, Diffuse optical imaging
Abstract

Background: Optical based imaging modalities have shown promise for monitoring tumor response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. In this study, we evaluate whether changes in deoxy-hemoglobin concentration values acquired by a Diffuse Optical Tomography Breast Imaging System (DOTBIS) over different time points are associated with tumor response. Methods: This is a retrospective evaluation of 55 stage II-III BC patients in the neoadjuvant setting who received weekly paclitaxel x 12, followed by dose-dense adriamycin/cyclophosphamide every 2 weeks x 4. The patients were enrolled in this cohort study between 2011 and 2019, and DOTBIS images were acquired from the patient whole breast volume at 6 different time points: at baseline (TP0); two weeks after the first taxane infusion (TP1); after four infusions of taxane (TP2); at the end of the taxane regimen and before starting AC cycle (TP3); after two AC infusions (TP4); and at the end of NAC and before surgery (TP5). ctHHb tumor concentration was measured using low-intensity near-infrared light and normalized by the non-tumor region ctHHb mean value (ctHHbN). In order to evaluate whether pCR status, menopausal status, and molecular subtype classification influence the change of ctHHbN over time, we designed a multilevel mixed-effect statistical model. pCR was defined as no invasive tumor cells from the breast and axillary tissue at surgery (ypT0 ypN0). Results: 20 patients had pCR and 35 were classified as non-pCR. The estimate average ctHHbN for pCR tumors at baseline was 4.02. There was a significant reduction in ctHHbN levels for pCR group at TP1 (-1.31, p = .0001) and TP2 (-1.36, p = .0416). Changes in ctHHbN levels compared to baseline (TP0) values were statistically significant different between pCR and non-pCR at all time points except at the end of the taxane cycle (TP3), Table 1. No significant changes over time were identified between molecular subtypes groups, or between pre- and post-menopausal status. Conclusions: Our study adds to the body of evidence reported for diffuse optical imaging methods applied to breast cancer treatment response. These results show that DOTBIS measured features, such as ctHHbN, change in accordance with pCR status after 2 weeks under NAC, and there are differences in time evolution between the pCR groups. Reduction in ctHHbN levels represents the chemotherapeutic- induced changes in the tumor microvasculature: lower ctHHbN values associate with the reduction in tumor cell proliferation, and consequently in oxygen consumption. Future studies are warranted to evaluate whether early response prediction might determine if earlier treatment changes alter patient outcome. Table 1 - Changes in ctHHbN levels compared to baseline (TP0) values between pCR and non-pCR at all imaging time points. Bold values indicate statistical significance at p Citation Format: Mirella L Altoe, Kevin Kalinsky, Hua Guo, Hanina Hibshoosh, Mariella Tejada, Katherine D Crew, Melissa K Accordino, Meghna Trivedi, Alessandro Marone, Hyun K Kim, Andreas H Hielscher, Dawn L Hershman. Monitoring neoadjuvant chemotherapy using diffuse optical tomography breast imaging system [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-10.

Published
2021

10. Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes

Author

Mariella Tejada, Hua Guo, Mirella L. Altoe, Melissa K. Accordino, Dawn L. Hershman, Hanina Hibshoosh, Kevin Kalinsky, Alessandro Marone, Katherine D. Crew, Hyun K. Kim, Meghna S. Trivedi, and Andreas H. Hielscher

Subjects
Adult, Change over time, Cancer Research, Receptor, ErbB-2, Breast imaging, medicine.medical_treatment, Breast Neoplasms, Tumor response, 01 natural sciences, Article, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, 0103 physical sciences, medicine, Humans, Tomography, Optical, In patient, Aged, Neoplasm Staging, Chemotherapy, business.industry, Middle Aged, medicine.disease, Neoadjuvant Therapy, Diffuse optical imaging, Oncology, Chemotherapy, Adjuvant, 030220 oncology & carcinogenesis, Female, business, Nuclear medicine, Breast carcinoma
Abstract

Purpose: This study's primary objective was to evaluate the changes in optically derived parameters acquired with a diffuse optical tomography breast imaging system (DOTBIS) in the tumor volume of patients with breast carcinoma receiving neoadjuvant chemotherapy (NAC). Experimental Design: In this analysis of 105 patients with stage II–III breast cancer, normalized mean values of total hemoglobin (ctTH{b_N}$), oxyhemoglobin (ct{O_2}H{b_N}$), deoxy-hemoglobin concentration (ctHH{b_N}$), water, and oxygen saturation (St{O_2}_N$) percentages were collected at different timepoints during NAC and compared with baseline measurements. This report compared changes in these optical biomarkers measured in patients who did not achieve a pathologic complete response (non-pCR) and those with a pCR. Differences regarding molecular subtypes were included for hormone receptor–positive and HER2-negative, HER2-positive, and triple-negative breast cancer. Results: At baseline, ctHH{b_N}$ was higher for pCR tumors (3.97 ± 2.29) compared with non-pCR tumors (3.00 ± 1.72; P = 0.031). At the earliest imaging point after starting therapy, the mean change of ctHH{b_N}$ compared with baseline ({\Delta _{TP1}}ctHH{b_N}$) was statistically significantly higher in non-pCR (1.23 ± 0.67) than in those with a pCR (0.87 ± 0.61; P < 0.0005), and significantly correlated to residual cancer burden classification (r = 0.448; P < 0.0005). {\Delta _{TP1}}ctHH{b_N}$ combined with HER2 status was proposed as a two-predictor logistic model, with AUC = 0.891; P < 0.0005; and 95% confidence interval, 0.812–0.969. Conclusions: This study demonstrates that DOTBIS measured features change over time according to tumor pCR status and may predict early in the NAC treatment course whether a patient is responding to NAC.

Published
2021

11. Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography

Author

Katherine D. Crew, Hua Guo, Alessandro Marone, Mirella L. Altoe, Melissa K. Accordino, Kevin Kalinsky, Andreas H. Hielscher, Meghna S. Trivedi, Mariella Tejada, Dawn L. Hershman, Hyun K. Kim, and Hanina Hibshoosh

Subjects
Oncology, Contralateral breast, medicine.medical_specialty, medicine.medical_treatment, Breast Neoplasms, 01 natural sciences, lcsh:RC254-282, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, pCR, Surgical oncology, Internal medicine, Antineoplastic Combined Chemotherapy Protocols, 0103 physical sciences, Biomarkers, Tumor, Image Processing, Computer-Assisted, medicine, Humans, Tomography, Optical, Stage (cooking), skin and connective tissue diseases, Chemotherapy, Non tumor bearing, Taxane, NAC, business.industry, Disease Management, medicine.disease, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Neoadjuvant Therapy, Diffuse optical imaging, Tumor Burden, Treatment Outcome, Diffuse optical tomography, 030220 oncology & carcinogenesis, Female, Menopausal status, business, Algorithms, Research Article
Abstract

Background The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR). Methods In this retrospective evaluation of 105 patients with stage II–III breast cancer, oxy-hemoglobin (ctO2Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2–3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO2Hb changes across chemotherapy when corrected for pCR status, age, and BMI. Results Patients who achieved pCR to NAC had an overall decrease of 3.88 μM for ctO2Hb (95% CI, 1.39 to 6.37 μM), p = .004, after 2–3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 μM (95% CI, − 1.30 to 1.58 μM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO2Hb levels with BMI and age. Conclusions This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2–3 weeks of chemotherapy.

Published
2021

12. A MYC and RAS co-activation signature in localized prostate cancer drives bone metastasis and castration resistance

Author

Mohammed Alshalalfa, Peter A. Sims, Ilsa Coleman, Jaime Yeji Kim, Angelo M. De Marzo, Onur Ertunc, Junfei Zhao, Renu K. Virk, Felix Y. Feng, Min Zou, Antonina Mitrofanova, Jun Luo, Antonio Rodriguez, Cory Abate-Shen, R. Jeffrey Karnes, Julia Fountain, Hanina Hibshoosh, Juan Arriaga, Sukanya Panja, Peter S. Nelson, Raul Rabadan, Emmanuel S. Antonarakis, Arianna Giacobbe, Busra Ozbek, Chioma J. Madubata, and Mark A. Rubin

Subjects
Male, Cancer Research, Prostatic Neoplasms, Bone metastasis, Bone Neoplasms, Biology, medicine.disease, Primary tumor, Article, Metastasis, Gene Expression Regulation, Neoplastic, Androgen receptor, Mice, Prostate cancer, Oncology, Castration Resistance, In vivo, medicine, Cancer research, Animals, Humans, Castration, 610 Medicine & health, Ex vivo, Transcription Factors
Abstract

Understanding the intricacies of lethal prostate cancer poses specific challenges due to difficulties in accurate modeling of metastasis in vivo. Here we show that NPKEYFP mice (for Nkx3.1CreERT2/+; Ptenflox/flox; KrasLSL-G12D/+; R26R-CAG-LSL-EYFP/+) develop prostate cancer with a high penetrance of metastasis to bone, thereby enabling detection and tracking of bone metastasis in vivo and ex vivo. Transcriptomic and whole-exome analyses of bone metastasis from these mice revealed distinct molecular profiles conserved between human and mouse and specific patterns of subclonal branching from the primary tumor. Integrating bulk and single-cell transcriptomic data from mouse and human datasets with functional studies in vivo unravels a unique MYC/RAS co-activation signature associated with prostate cancer metastasis. Finally, we identify a gene signature with prognostic value for time to metastasis and predictive of treatment response in human patients undergoing androgen receptor therapy across clinical cohorts, thus uncovering conserved mechanisms of metastasis with potential translational significance. Using lineage tracing and molecular profiling, Abate-Shen and colleagues identify a Ras and Myc co-activation signature that predicts metastasis and castration resistance in localized prostate cancer.

Published
2020

13. Harmonic motion imaging of human breast masses: an in vivo clinical feasibility

Author

Xiaoyue Judy Li, Hermes A. S. Kamimura, Stephen A. Lee, Bret Taback, Rachel Weber, Vittorio Gatti, Niloufar Saharkhiz, Richard Ha, Hanina Hibshoosh, Elisa E. Konofagou, and Alireza Nabavizadeh

Subjects
medicine.medical_specialty, Transducers, lcsh:Medicine, Breast Neoplasms, Diagnostic accuracy, Article, 030218 nuclear medicine & medical imaging, Motion, 03 medical and health sciences, Breast cancer, 0302 clinical medicine, In vivo, Ultrasound, medicine, Humans, Breast, lcsh:Science, Multidisciplinary, Breast tissue, business.industry, lcsh:R, Histology, Translational research, Middle Aged, medicine.disease, Clinical Practice, 030220 oncology & carcinogenesis, Elasticity Imaging Techniques, Feasibility Studies, High-Intensity Focused Ultrasound Ablation, Female, lcsh:Q, Radiology, business, Biomedical engineering, Human breast, Ex vivo
Abstract

Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses.

Published
2020

14. Fully Automated Postlumpectomy Breast Margin Assessment Utilizing Convolutional Neural Network Based Optical Coherence Tomography Image Classification Method

Author

Brigid Angelini, Yu Gan, Diana Mojahed, Peter Chang, Xinwen Yao, Christine P. Hendon, Hanina Hibshoosh, Bret Taback, and Richard Ha

Subjects
Computer science, medicine.medical_treatment, Breast Neoplasms, Mastectomy, Segmental, Convolutional neural network, Article, Optical coherence tomography, Margin (machine learning), Image Processing, Computer-Assisted, medicine, Humans, Radiology, Nuclear Medicine and imaging, Breast, Postoperative Period, Contextual image classification, medicine.diagnostic_test, business.industry, Lumpectomy, Margins of Excision, Pattern recognition, Ductal carcinoma, Magnetic Resonance Imaging, Binary classification, Female, Neural Networks, Computer, Artificial intelligence, F1 score, business, Algorithms, Tomography, Optical Coherence
Abstract

Background The purpose of this study was to develop a deep learning classification approach to distinguish cancerous from noncancerous regions within optical coherence tomography (OCT) images of breast tissue for potential use in an intraoperative setting for margin assessment. Methods A custom ultrahigh-resolution OCT (UHR-OCT) system with an axial resolution of 2.7 μm and a lateral resolution of 5.5 μm was used in this study. The algorithm used an A-scan-based classification scheme and the convolutional neural network (CNN) was implemented using an 11-layer architecture consisting of serial 3 × 3 convolution kernels. Four tissue types were classified, including adipose, stroma, ductal carcinoma in situ, and invasive ductal carcinoma. Results The binary classification of cancer versus noncancer with the proposed CNN achieved 94% accuracy, 96% sensitivity, and 92% specificity. The mean five-fold validation F1 score was highest for invasive ductal carcinoma (mean standard deviation, 0.89 ± 0.09) and adipose (0.79 ± 0.17), followed by stroma (0.74 ± 0.18), and ductal carcinoma in situ (0.65 ± 0.15). Conclusion It is feasible to use CNN based algorithm to accurately distinguish cancerous regions in OCT images. This fully automated method can overcome limitations of manual interpretation including interobserver variability and speed of interpretation and may enable real-time intraoperative margin assessment.

Published
2020

15. Abstract P3-09-17: Preoperative pembrolizumab increases sTILs in treatment naïve stage I/IIA TNBC patients in a window of opportunity trial

Author

Rami Vanguri, Tahsin Kurc, Joel H. Saltz, Rajarsi Gupta, Dimitris Samaras, Shahira Abousamra, Kevin Gardner, Han Le, Hua Guo, Kevin Kalinsky, Shuobo Boboila, Le Hou, Hanina Hibshoosh, and Eileen P. Connolly

Subjects
Oncology, Cancer Research, Window of opportunity, medicine.medical_specialty, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Lumpectomy, Cancer, Pembrolizumab, medicine.disease, Breast cancer, Internal medicine, Biopsy, medicine, Stage (cooking), business, Triple-negative breast cancer
Abstract

Background: High levels of stromal tumor-infiltrating lymphocytes (sTILs) are significantly associated with chemosensitivity and improved overall survival for patients with triple negative breast cancer (TNBC). Our aim is to determine if we can significantly increase sTILs from biopsy to lumpectomy in a presurgical window of opportunity trial with pembrolizumab and intraoperaperative radiation (IORT) in treatment-naïve early stage TNBC compared to matched IORT only controls. We also evaluate the changes in the spatial distribution of intraepithelial TILs (iTILs) by utilizing a deep learning algorithm. Our secondary aim is to characterize the tumor immune microenvironment (TME) using quantitative multiplex immunofluorescence (qmIF) and transcriptomic analysis of tumor-associated and immune genes. Methods: Seven women with node negative TNBC Results: Seven patients were enrolled between Nov 2017-Apr 2019; 3 patients received pembrolizumab+IORT; and 4 patients received IORT alone. Initial pathology assessment of sTILs demonstrated no significant change between biopsy and lumpectomy in control patients. No consistent patterns of iTILs dispersion were observed in the control patients. Out of the 3 pembrolizumab treated patients, one patient demonstrated a marked increase in sTILs (20% to 60%) with a shift from a neutrophil rich to lymphoplasmacytic stromal infiltrate where the mean dispersion of the iTILs doubled (180 to 360). In the other 2 pembrolizumab patients, one remained stable and one showed a slight increase in sTILs. The iTILs dispersion increased significantly in these patients (from 40 to 90 and 10 to 280, respectively). A corresponding spatial analysis of sTILs is ongoing. Additionally, qmIF and transcriptomic analysis of tumor-associated and immune genes is currently underway to compare biopsy and surgical specimens. Conclusion: In this preliminary analysis, we observe preoperative pembrolizumab-induced increases in sTILs with increased mean dispersion of iTILs in treatment naïve TNBC. Our initial analysis in this ongoing trial appears promising after examining changes in both the density and spatial structure of TILs. Further investigation is warranted to elucidate the impact of preoperative pembrolizumab in the TME of early stage TNBC and other potential therapeutic implications. Citation Format: Rami Vanguri, Hua Guo, Shuobo Boboila, Tahsin Kurc, Han Le, Shahira Abousamra, Le Hou, Dimitris Samaras, Rajarsi Gupta, Joel Saltz, Kevin Gardner, Hanina Hibshoosh, Kevin Kalinsky, Eileen Connolly. Preoperative pembrolizumab increases sTILs in treatment naïve stage I/IIA TNBC patients in a window of opportunity trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-09-17.

Published
2020

16. Abstract P6-10-25: Characterization of the tumor immune microenvironment (TME) in early stage HR-positive HER2-positive breast cancer

Author

Douglas K. Marks, Hanina Hibshoosh, Hua Guo, Kathleen Fenn, Eileen P. Connolly, Kevin Kalinsky, Shuobo Boboila, and Rami Vanguri

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Chemotherapy, Tumor-infiltrating lymphocytes, business.industry, Immune microenvironment, medicine.medical_treatment, Cancer, medicine.disease, Breast cancer, Hormone receptor, Internal medicine, HER2 Positive Breast Cancer, medicine, Stage (cooking), business
Abstract

Background: In patients (pts) with early stage HER2-positive breast cancer (BC) who are treated with combination neoadjuvant chemotherapy (NAC) and HER2-targeted therapy, recent studies report that increased tumor infiltrating lymphocyte (TIL) density is associated with higher rates of pathologic complete response (pCR) and improved overall survival. However, in the subset of HER2-positive pts who are hormone receptor (HR)-positive, less is known about the relationship between the composition of the tumor immune infiltrate and clinical outcomes. In this study, we sought to characterize the TME of pts with early stage HR+ HER2+ BC using H&E-based TIL scoring and multiplex immunohistochemistry to assess for characteristics associated with achievement of pCR after neoadjuvant therapy. Patients & Methods: We identified 25 pts with HR+ HER2+ early stage BC who were treated with NAC at our institution between 2005 and 2016 for whom pretreatment tissue was available for analysis. Twenty-two pts (88%) received neoadjuvant HER2 antibody therapy along with NAC. Twelve pts (48%) received neoadjuvant pertuzumab in addition to trastuzumab. At the time of surgery, 11 pts achieved pCR and 14 had residual carcinoma (RC). H&E slides from pretreatment biopsy samples were scored for both stromal and intratumoral TILs by a BC pathologist using established guidelines. Additionally, quantitative immunofluorescence (qmIF) was performed on pretreatment biopsy samples for 20 pts (9 with pCR, 11 with RC) using an OPAL antibody panel targeting CD3, CD8, CD68, HLADR, FOXP3, and pancytokeratin. Images were analyzed with the Vectra/inForm software platform (Perkin Elmer) to allow for multiparameter phenotyping. Nearest neighbor analysis to assess median distance between immune cell subtypes and tumor cells was performed using phenoptr software. Results: Per TIL scoring, mean stromal TIL (sTIL) density was 28% in the pCR group and 17% in the RC group (p=0.05). Using a cutoff of ≥10% sTIL density, high sTILs were seen in pretreatment samples in 100% (11/11) of pCR pts and in 57% (8/14) of RC pts (p=0.05). Intraepithelial TIL density was not significantly associated with pCR (p=0.12). Per qmIF analysis, there was a numerical but not statistically significant increase in mean stromal CD3+CD8+ cell density (18% vs 11%) and decrease in stromal CD68+ cell density (10% vs 14%) in the pCR group compared to the RC group. Nearest neighbor analysis revealed that the median distance from tumor cells to CD68+ cells was significantly higher in pts with pCR vs. RC (p=0.02). No significant differences in median distance between CD3+CD8+ cells and tumor or CD3+CD8+ cells and CD68+ cells were detected among the two groups. Conclusions: In a population of early stage HR+ HER2+ breast cancer pts who received neoadjuvant therapy, sTIL density by pathology assessment was associated with increased rates of pCR, supporting the hypothesis that the nature of the TME is biologically significant in the subset of HER2+ pts who are also HR+. qmIF is a useful tool to further characterize the density of specific immune cell subtypes and spatial relationships between cell types in the TME. Further studies in larger cohorts are needed to determine more specific immune biomarkers that predict response to combined chemotherapy and HER2-targeted therapy in pts with HR+ HER2+ BC. Citation Format: Kathleen M. Fenn, Douglas K Marks, Rami Vanguri, Shuobo Boboila, Hua Guo, Hanina Hibshoosh, Kevin Kalinsky, Eileen Connolly. Characterization of the tumor immune microenvironment (TME) in early stage HR-positive HER2-positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-10-25.

Published
2020

17. Pre-clinical validation of an RNA-based precision oncology platform for patient-therapy alignment in a diverse set of human malignancies resistant to standard treatments

Author

Prabhjot S. Mundi, Filemon S. Dela Cruz, Adina Grunn, Daniel Diolaiti, Audrey Mauguen, Allison R. Rainey, Kristina C. Guillan, Armaan Siddiquee, Daoqi You, Ronald Realubit, Charles Karan, Michael V. Ortiz, Melissa Accordino, Suzanne Mistretta, Frances Brogan, Jeffrey N. Bruce, Cristina I. Caescu, Richard Carvajal, Katherine Crew, Guarionex Decastro, Mark Heaney, Brian Henick, Dawn Hershman, June Hou, Fabio Iwamoto, Joseph Jurcic, Ravi P. Kiran, Michael Kluger, Teri Kreisl, Nicole Lamanna, Andrew Lassman, Emerson Lim, Gulam A. Manji, Guy McKhann, James McKiernan, Alfred Neugut, Kenneth Olive, Todd Rosenblat, Gary K. Schwartz, Catherine Shu, Michael Sisti, Ana Tergas, Reena Vattakalam, Mary Welch, Sven Wenske, Jason D. Wright, Hanina Hibshoosh, Kevin Kalinsky, Mahalaxmi Aburi, Peter A. Sims, Mariano J. Alvarez, Andrew L. Kung, and Andrea Califano

Subjects
Drug, Oncology, medicine.medical_specialty, business.industry, media_common.quotation_subject, Master regulator, RNA, Joint analysis, Mechanism of action, Precision oncology, Internal medicine, medicine, medicine.symptom, Set (psychology), business, Objective response, media_common
Abstract

Predicting tumor sensitivity to antineoplastics remains an elusive challenge, with no methods demonstrating predictive power. Joint analysis of tumors—from patients with distinct malignancies who had progressed on multiple lines of therapy—and drug perturbation transcriptional profiles predicted sensitivity to 28 of 350 drugs, 26 of which (93%) were confirmed in low-passage, patient-derived xenograft (PDX) models. Drugs were prioritized based on their ability to either invert the activity of individual Master Regulator proteins, with available high-affinity inhibitors, or of the modules they comprise (Tumor-Checkpoints), based on de novo mechanism of action analysis. Of 138 PDX mice enrolled in 16 single and 18 multi-protein treatment arms, a disease control rate (DCR) of 68% and 91 %, and an objective response rate (ORR) of 12% and 17%, were achieved respectively, compared to 6% and 0% in the negative controls arm, with multi-protein drugs achieving significantly more durable responses. Thus, these approaches may effectively complement and expand current precision oncology approaches, as also illustrated by a case study.

Published
2021

18. Molecular Pathophysiology of Cardiac Injury and Cardiac Microthrombi in Fatal COVID-19: Insights from Clinico-histopathologic and Single Nuclei RNA Sequencing Analyses

Author

Robert Zilinyi, Emily J. Tsai, Alexander M. Chong, Nathan R. Tucker, Nobuaki Fukuma, Anne-Catrin Uhlemann, Zhipeng Zhou, Ryan D Pfeiffer, Matthias Szabolcs, Mathew S. Maurer, Christos Tzimas, Martin B. Leon, Michelle L Hulke, Geping Zhang, Stephanie Golob, Nir Uriel, Matthew R. Baldwin, Claire McGroder, Charles C. Marboe, Ilaria Russo, Michael I. Brener, Jeffrey W. Moses, Björn Redfors, Daniel Burkhoff, and Hanina Hibshoosh

Subjects
Pathology, medicine.medical_specialty, business.industry, medicine.medical_treatment, RNA, Inflammation, Pathophysiology, Extracellular matrix, Transcriptome, Fibrinolysis, Etiology, Medicine, medicine.symptom, business, Prospective cohort study
Abstract

Cardiac injury is associated with critical COVID-19, yet its etiology remains debated. To elucidate the pathogenic mechanisms of COVID-19-associated cardiac injury, we conducted a single-center prospective cohort study of 69 COVID-19 decedents. Of six cardiac histopathologic features, microthrombi was the most commonly detected (n=48, 70%). We tested associations of cardiac microthrombi with biomarkers of inflammation, cardiac injury, and fibrinolysis and with in-hospital antiplatelet therapy, therapeutic anticoagulation, and corticosteroid treatment, while adjusting for multiple clinical factors, including COVID-19 therapies. Higher peak ESR and CRP during hospitalization were independently associated with higher odds of microthrombi. Using single nuclei RNA-sequence analysis, we discovered an enrichment of pro-thrombotic/anti-fibrinolytic, extracellular matrix remodeling, and immune-potentiating signaling amongst cardiac fibroblasts in microthrombi-positive COVID-19 hearts relative to microthrombi-negative COVID-19. Non-COVID-19 non-failing hearts were used as reference controls. Our cumulative findings identify the specific transcriptomic changes in cardiac fibroblasts as salient features of COVID-19-associated cardiac microthrombi.

Published
2021

19. Total hemoglobin changes in the breast tumor volume of patients undergoing neoadjuvant chemotherapy: a longitudinal analysis

Author

Melissa K. Accordino, Alessandro Marone, Hua Guo, Dawn L. Hershman, Katherine D. Crew, Hanina Hibshoosh, Meghna S. Trivedi, Kevin Kalinsky, Mariella Tejada, Mirella L. Altoe, Hyun K. Kim, and Andreas H. Hielscher

Subjects
Chemotherapy, medicine.medical_specialty, Taxane, Cyclophosphamide, Breast imaging, business.industry, medicine.medical_treatment, Urology, Retrospective cohort study, medicine.disease, Regimen, Breast cancer, medicine, Stage (cooking), business, medicine.drug
Abstract

Optical imaging techniques have emerged as a possible alternative to predict pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). Our team developed a so-called diffuse optical tomographic breast imaging system (DOTBIS) which does not require the use of contrast agents or compression and enables imaging of the whole breast volume using low intensity near infrared light capable to measure tissue concentration of total hemoglobin (ctTHb). In this retrospective study, we evaluated 55 stage II-III BC patients in the neoadjuvant setting who received weekly paclitaxel x 12, followed by dose-dense adriamycin/cyclophosphamide every 2 weeks x 4. DOTBIS images were acquired from the patient whole breast volume at 6 different time points: at baseline (TP0); two weeks after the first taxane infusion (TP1); after four infusions of taxane (TP2); at the end of the taxane regimen and before starting AC cycle (TP3); after two AC infusions (TP4); and at the end of NAC and before surgery (TP5). In order to evaluate whether pCR status influences the change of ctTHb over time, we designed a multilevel mixed-effect model. pCR was defined as no invasive tumor cells from the breast and axillary tissue at surgery (ypT0 ypN0). Changes in ctTHb levels compared to baseline (TP0) values were statistically significant different between pCR (n = 20) and non-pCR (n=35) at all time points except at TP1 and at the end of the taxane cycle (TP3).

Published
2021

20. Generalizable convolutional neural network (CNN) classification of breast cancer using images from two optical coherence tomography (OCT) systems

Author

Diana Mojahed, Rohan Bareja, Christine P. Hendon, Theresa H. Lye, Richard Ha, and Hanina Hibshoosh

Subjects
medicine.medical_specialty, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Lumpectomy, Ductal carcinoma, medicine.disease, Convolutional neural network, Breast cancer, Optical coherence tomography, Tissue bank, medicine, Mucinous carcinoma, Radiology, skin and connective tissue diseases, business, Mastectomy
Abstract

The purpose of this study was to develop a generalizable convolutional neural network (CNN) classification technique of optical coherence tomography (OCT) images of breast tissue acquired from multiple OCT systems. We imaged lumpectomy and mastectomy specimens (acquired through the Columbia University Tissue Bank) from 31 patients. In our early results, we classified the images into healthy tissue (adipose and stroma) and diseased, which included ductal carcinoma in situ (DCIS), mucinous carcinoma, and invasive ductal carcinoma (IDC). Our goal is to expand our classification to differentiate the diseased tissue into subclasses of DCIS, IDC, mucinous carcinoma, and benign tissue.

Published
2021

21. NKX3.1 Localization to Mitochondria Suppresses Prostate Cancer Initiation

Author

Teresa A. Milner, Cory Abate-Shen, Antonio Rodriguez-Calero, Sukanya Panja, Michael M. Shen, Renu K. Virk, James M. McKiernan, Elvis A. Maliza, Sven Wenske, Alanna B. Williams, Mark A. Rubin, Aditya Dutta, Hanina Hibshoosh, Vinson Wang, Alexandros Papachristodoulou, Antonina Mitrofanova, Joseph M. Caputo, Matteo Di Bernardo, Jaime Y. Kim, Luis A. Pina Martina, Elizabeth Margolskee, Christopher R. Haas, and Guarionex Joel De Castro

Subjects
Male, Oxidative phosphorylation, Biology, Mitochondrion, medicine.disease_cause, urologic and male genital diseases, Prostate cancer, Cell Line, Tumor, medicine, Humans, 610 Medicine & health, HSPA9, Homeodomain Proteins, urogenital system, Cancer, Prostatic Neoplasms, medicine.disease, Subcellular localization, Mitochondria, Gene Expression Regulation, Neoplastic, Oncology, Cancer cell, Cancer research, 570 Life sciences, biology, Oxidative stress, Transcription Factors
Abstract

Mitochondria provide the first line of defense against the tumor-promoting effects of oxidative stress. Here we show that the prostate-specific homeoprotein NKX3.1 suppresses prostate cancer initiation by protecting mitochondria from oxidative stress. Integrating analyses of genetically engineered mouse models, human prostate cancer cells, and human prostate cancer organotypic cultures, we find that, in response to oxidative stress, NKX3.1 is imported to mitochondria via the chaperone protein HSPA9, where it regulates transcription of mitochondrial-encoded electron transport chain (ETC) genes, thereby restoring oxidative phosphorylation and preventing cancer initiation. Germline polymorphisms of NKX3.1 associated with increased cancer risk fail to protect from oxidative stress or suppress tumorigenicity. Low expression levels of NKX3.1 combined with low expression of mitochondrial ETC genes are associated with adverse clinical outcome, whereas high levels of mitochondrial NKX3.1 protein are associated with favorable outcome. This work reveals an extranuclear role for NKX3.1 in suppression of prostate cancer by protecting mitochondrial function. Significance: Our findings uncover a nonnuclear function for NKX3.1 that is a key mechanism for suppression of prostate cancer. Analyses of the expression levels and subcellular localization of NKX3.1 in patients at risk of cancer progression may improve risk assessment in a precision prevention paradigm, particularly for men undergoing active surveillance. See related commentary by Finch and Baena, p. 2132. This article is highlighted in the In This Issue feature, p. 2113

Published
2021
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22. A single-cell atlas of the mouse and human prostate reveals heterogeneity and conservation of epithelial progenitors

Author

Hanina Hibshoosh, Raul Rabadan, Maho Shibata, Weiping Li, Michael M. Shen, Francesco Cambuli, Shouhong Xuan, Laura Crowley, Brian D. Robinson, Massimo Loda, and Luis Aparicio

Subjects
0301 basic medicine, Male, Mouse, Cell of origin, Cell, Mice, 0302 clinical medicine, Prostate, Biology (General), Cells, Cultured, Cancer Biology, education.field_of_study, General Neuroscience, Stem Cells, epithelial heterogeneity, General Medicine, Hyperplasia, Stem Cells and Regenerative Medicine, Organoids, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Medicine, Stem cell, Single-Cell Analysis, Research Article, Human, QH301-705.5, Science, Population, Biology, General Biochemistry, Genetics and Molecular Biology, renal grafts, 03 medical and health sciences, Organoid, medicine, Animals, Humans, Progenitor cell, education, Progenitor, General Immunology and Microbiology, Epithelial Cells, medicine.disease, Epithelium, 030104 developmental biology, Cancer research, multipotent progenitor
Abstract

SummaryUnderstanding the cellular constituents of the prostate is essential for identifying the cell of origin for benign prostatic hyperplasia and prostate adenocarcinoma. Here we describe a comprehensive single-cell atlas of the adult mouse prostate epithelium, which demonstrates extensive heterogeneity. We observe distinct lobe-specific luminal epithelial populations (LumA, LumD, LumL, and LumV) in the distal region of the four prostate lobes, a proximally-enriched luminal population (LumP) that is not lobe-specific, as well as a periurethral population (PrU) that shares both basal and luminal features. Functional analyses suggest that LumP and PrU cells have multipotent progenitor activity in organoid formation and tissue reconstitution assays. Furthermore, we show that mouse distal and proximal luminal cells are most similar to human acinar and ductal populations, that a PrU-like population is conserved between species, and that the mouse lateral prostate is most similar to the human peripheral zone. Our findings elucidate new prostate epithelial progenitors, and help resolve long-standing questions about the anatomical relationships between the mouse and human prostate.

Published
2020

23. Akt Inhibition Is Associated With Favorable Immune Profile Changes Within the Tumor Microenvironment of Hormone Receptor Positive, HER2 Negative Breast Cancer

Author

Douglas K. Marks, Robyn D. Gartrell, Margueritta El Asmar, Shuobo Boboila, Thomas Hart, Yan Lu, Qingfei Pan, Jiyang Yu, Hanina Hibshoosh, Hua Guo, Eleni Andreopoulou, Lisa Wiechmann, Katherine Crew, Joseph Sparano, Dawn Hershman, Eileen Connolly, Yvonne Saenger, and Kevin Kalinsky

Subjects
0301 basic medicine, Cancer Research, medicine.medical_treatment, tumor immunobiology, medicine.disease_cause, lcsh:RC254-282, AKT inhibitor, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, breast cancer, medicine, tumor microenvironment, Protein kinase B, PI3K/AKT/mTOR pathway, Original Research, Tumor microenvironment, business.industry, pre-surgical, FOXP3, Immunotherapy, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, quantitative multiplex immunofluorescence, 030104 developmental biology, chemistry, Oncology, MK-2206, Hormone receptor, 030220 oncology & carcinogenesis, Cancer research, Carcinogenesis, business
Abstract

Background: The PI3K/Akt/mTOR pathway in part impacts tumorigenesis through modulation of host immune activity. To assess the effects of Akt inhibition on the tumor micro-environment (TME), we analyzed tumor tissue from patients with operable hormone receptor positive, HER2 negative breast cancer (BC) treated on a presurgical trial with the Akt inhibitor MK-2206.Methods: Quantitative multiplex immunofluorescence (qmIF) was performed using CD3, CD8, CD4, FOXP3, CD68, and pancytokeratin on biopsy and surgical specimens of MK-2206 and untreated, control patients. nanoString was performed on surgical specimens to assess mRNA expression from MK-2206-treated vs. control patients.Results: Increased CD3+CD8+ density was observed in post vs. pre-treatment tissue in the MK-2206-treated vs. control patients (87 vs. 0.2%, p < 0.05). MK-2206 was associated with greater expression of interferon signaling genes (e.g., IFI6, p < 0.05) and lower expression of myeloid genes (CD163, p < 0.05) on differential expression and gene set enrichment analyses. Greater expression of pro-apoptotic genes (e.g., BAD) were associated with MK-2206 treatment (p < 0.05).Conclusion: Akt inhibition in operable BC was associated with a favorable immune profile in the TME, including increased CD3+CD8+ density and greater expression of interferon genes. Additional studies are warranted, as this may provide rationale for combining Akt inhibition with immunotherapy.

Published
2020

24. Ultrahigh-speed, high-resolution, large-area optical coherence tomography (OCT) imaging for rapid evaluation of breast cancer surgical specimens (Conference Presentation)

Author

Matthew B. Applegate, Richard Ha, Christine P. Hendon, Diana Mojahed, and Hanina Hibshoosh

Subjects
genetic structures, medicine.diagnostic_test, business.industry, High resolution, Lobular hyperplasia, medicine.disease, Fibroadenoma, eye diseases, Image stitching, Breast cancer, Optical coherence tomography, medicine, sense organs, Stage (cooking), skin and connective tissue diseases, business, Nuclear medicine, Normal breast
Abstract

The purpose of this study was to develop an ultrahigh-speed, high-resolution, large imaging area optical coherence tomography (OCT) imaging system for improved evaluation of breast cancer surgical specimens. A 2-axis direct-drive servo motorized linear translation stage enables automatic acquisition and stitching of multiple OCT volumes, providing large-area imaging of tissue sizes up to 10cm x 10cm surface area x 2mm imaging depth. OCT images of breast specimens with this system will demonstrate normal breast parenchyma, cysts, radial scars, benign neoplasms such as fibroadenoma, atypical ductal/lobular hyperplasia, and carcinomas in situ and invasive.

Published
2020

25. Gene expression profiles for low-dose exposure to diethyl phthalate in rodents and humans: a translational study with implications for breast carcinogenesis

Author

Vasily N. Aushev, Fiorella Belpoggi, Gail C. Garbowski, Fabiana Manservisi, Humberto Parada, Jia Chen, Regina M. Santella, Hanina Hibshoosh, Simona Panzacchi, Susan L. Teitelbaum, Marilie D. Gammon, Laura Falcioni, Kalpana Gopalakrishnan, and Gopalakrishnan K, Aushev VN, Manservisi F, Falcioni L, Panzacchi S, Belpoggi F, Parada H Jr, Garbowski G, Hibshoosh H, Santella RM, Gammon MD, Teitelbaum SL, Chen J.

Subjects
0301 basic medicine, Metabolite, Phthalic Acids, Procollagen-Proline Dioxygenase, lcsh:Medicine, Breast Neoplasms, Biology, Diethyl phthalate, Amphiregulin, complex mixtures, Article, Andrology, Transcriptome, Androgen receptor binding, Rats, Sprague-Dawley, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Breast cancer, Gene expression, medicine, Biomarkers, Tumor, Animals, Humans, lcsh:Science, Transcription factor, Aged, Multidisciplinary, lcsh:R, Intracellular Signaling Peptides and Proteins, Membrane Proteins, Gene signature, Middle Aged, medicine.disease, 030104 developmental biology, chemistry, 030220 oncology & carcinogenesis, lcsh:Q
Abstract

Phthalates are commonly included as ingredients in personal care products such as cosmetics, shampoos and perfumes. Diethyl phthalate (DEP) has been found to be anti-androgenic and linked with adverse reproductive effects on males, but effects on females are poorly understood. We designed an integrative and translational study to experimentally examine the effects of DEP exposure at a human-equivalent dose on the mammary transcriptome in rats and to subsequently examine the DEP gene signature in breast tissues (both pre-malignant and tumor) from a population study. In Sprague-Dawley rats treated orally with DEP from birth to adulthood, we identified a signature panel of 107 genes predominantly down-regulated by DEP exposure. Univariate analysis of this 107 DEP gene signature in pre-malignant breast tissues revealed that six genes (P4HA1, MPZL3, TMC4, PLEKHA6, CA8, AREG) were inversely associated with monoethyl phthalate (MEP; the urinary metabolite of DEP) concentration (p

Published
2020

26. Ensemble deep learning for breast cancer segmentation in optical coherence tomography (OCT) images

Author

Diana Mojahed, Christine P. Hendon, Rohan Bareja, Theresa H. Lye, and Hanina Hibshoosh

Subjects
genetic structures, medicine.diagnostic_test, business.industry, Computer science, Deep learning, education, Image processing, medicine.disease, eye diseases, Breast cancer, Optical coherence tomography, medicine, Medical imaging, Segmentation, Computer vision, sense organs, Artificial intelligence, business
Abstract

An ensemble deep learning technique was developed for segmenting breast cancer in optical coherence tomography (OCT) images from two imaging systems and is trained on B-scan and en-face images to yield improved predictions.

Published
2020

27. Aberrant Zip14 expression in muscle is associated with cachexia in a Bard1-deficient mouse model of breast cancer metastasis

Author

Matthias Szabolcs, Vanessa Chin, Ahmad Rushdi Shakri, Kurenai Tanji, Richard Baer, Anup K. Biswas, Hanina Hibshoosh, Rohaan Hegde, Courtney Coker, Wanchao Ma, Timothy James Zhong, Hanna Scholze, and Swarnali Acharyya

Subjects
0301 basic medicine, Cancer Research, Cachexia, Lung Neoplasms, Ubiquitin-Protein Ligases, Triple Negative Breast Neoplasms, lcsh:RC254-282, Metastasis, 03 medical and health sciences, Mice, 0302 clinical medicine, Breast cancer, breast cancer, BARD1, Cell Line, Tumor, medicine, Animals, metastasis, Radiology, Nuclear Medicine and imaging, mouse models, Muscle, Skeletal, Wasting, Cation Transport Proteins, Original Research, Cancer Biology, Lung, business.industry, BRCA1 Protein, Tumor Suppressor Proteins, Cancer, medicine.disease, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Metastatic breast cancer, BRCA mutations, Up-Regulation, Gene Expression Regulation, Neoplastic, Zinc, 030104 developmental biology, medicine.anatomical_structure, Oncology, 030220 oncology & carcinogenesis, Cancer research, Female, medicine.symptom, business, Norisoprenoids
Abstract

Nearly 80% of advanced cancer patients are afflicted with cachexia, a debilitating syndrome characterized by extensive loss of muscle mass and function. Cachectic cancer patients have a reduced tolerance to antineoplastic therapies and often succumb to premature death from the wasting of respiratory and cardiac muscles. Since there are no available treatments for cachexia, it is imperative to understand the mechanisms that drive cachexia in order to devise effective strategies to treat it. Although 25% of metastatic breast cancer patients develop symptoms of muscle wasting, mechanistic studies of breast cancer cachexia have been hampered by a lack of experimental models. Using tumor cells deficient for BARD1, a subunit of the BRCA1/BARD1 tumor suppressor complex, we have developed a new orthotopic model of triple‐negative breast cancer that spontaneously metastasizes to the lung and leads to systemic muscle deterioration. We show that expression of the metal‐ion transporter, Zip14, is markedly upregulated in cachectic muscles from these mice and is associated with elevated intramuscular zinc and iron levels. Aberrant Zip14 expression and altered metal‐ion homeostasis could therefore represent an underlying mechanism of cachexia development in human patients with triple‐negative breast cancer. Our study provides a unique model for studying breast cancer cachexia and identifies a potential therapeutic target for its treatment., In this study, we have developed a new orthotopic model of triple‐negative breast cancer that spontaneously metastasizes to the lung and leads to systemic muscle deterioration. We show that aberrant Zip14 expression and altered metal‐ion homeostasis represent an underlying mechanism of cachexia development in this triple‐negative breast cancer model.

Published
2019

28. The unusual suspects: A review of unusual benign and malignant male breast imaging cases

Author

Richard Ha, Sarah Goodman, Victoria L. Mango, Hanina Hibshoosh, Kim Clarkin, Lauren Friedlander, and Ralph Wynn

Subjects
Adult, Male, medicine.medical_specialty, Adolescent, Male breast, Breast Neoplasms, Transgender Persons, Breast Neoplasms, Male, 030218 nuclear medicine & medical imaging, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, Invasive breast carcinoma, Radiologists, Carcinoma, medicine, Humans, Radiology, Nuclear Medicine and imaging, Breast, skin and connective tissue diseases, Aged, Breast Hemangioma, business.industry, Middle Aged, medicine.disease, Gynecomastia, 030220 oncology & carcinogenesis, Male breast disease, Female, Radiology, Differential diagnosis, business
Abstract

Male breast disease is uncommon. Men presenting with breast symptoms may represent unique diagnostic challenges for the radiologist, particularly if imaging findings are not classic for gynecomastia or carcinoma. In this paper we review 10 unusual male breast cases, 5 benign and 5 malignant, including the radiologic findings, differential diagnosis, pathology and management.

Published
2018

29. Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer

Author

Dawn L. Hershman, Emerson A. Lim, Jacqueline Gunther, Mirella L. Altoe, Hyun K. Kim, Kevin Kalinsky, Andreas H. Hielscher, Molly Lara Flexman, Hanina Hibshoosh, Jessica Campbell, and Katherine D. Crew

Subjects
Adult, medicine.medical_specialty, medicine.medical_treatment, Breast Neoplasms, Sensitivity and Specificity, 01 natural sciences, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, 0103 physical sciences, Humans, Tomography, Optical, Medicine, Pathologic Response, Radiology, Nuclear Medicine and imaging, In patient, Breast, Longitudinal Studies, Original Research, Chemotherapy, Tomographic reconstruction, business.industry, Middle Aged, medicine.disease, Neoadjuvant Therapy, eye diseases, Diffuse optical imaging, Treatment Outcome, Chemotherapy, Adjuvant, 030220 oncology & carcinogenesis, Female, sense organs, Tomography, Radiology, business, After treatment
Abstract

PURPOSE: To identify dynamic optical imaging features that associate with the degree of pathologic response in patients with breast cancer during neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: Of 40 patients with breast cancer who participated in a longitudinal study between June 2011 and March 2016, 34 completed the study. There were 13 patients who obtained a pathologic complete response (pCR) and 21 patients who did not obtain a pCR. Imaging data from six subjects were excluded from the study because either the patients dropped out of the study before it was finished or there was an instrumentation malfunction. Two weeks into the treatment regimen, three-dimensional images of both breasts during a breath hold were acquired by using dynamic diffuse optical tomography. Features from the breath-hold traces were used to distinguish between response groups. Receiver operating characteristic (ROC) curves and sensitivity analysis were used to determine the degree of association with 5-month treatment outcome. RESULTS: An ROC curve analysis showed that this method could identify patients with a pCR with a positive predictive value of 70.6% (12 of 17), a negative predictive value of 94.1% (16 of 17), a sensitivity of 92.3% (12 of 13), a specificity of 76.2% (16 of 21), and an area under the ROC curve of 0.85. CONCLUSION: Several dynamic optical imaging features obtained within 2 weeks of NAC initiation were identified that showed statistically significant differences between patients with pCR and patients without pCR as determined 5 months after treatment initiation. If confirmed in a larger cohort prospective study, these dynamic imaging features may be used to predict treatment outcome as early as 2 weeks after treatment initiation. (©) RSNA, 2018 Online supplemental material is available for this article.

Published
2018

30. Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Author

Gregory P. Way, Francisco Sanchez-Vega, Konnor La, Joshua Armenia, Walid K. Chatila, Augustin Luna, Chris Sander, Andrew D. Cherniack, Marco Mina, Giovanni Ciriello, Nikolaus Schultz, Yolanda Sanchez, Casey S. Greene, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Carolyn M. Hutter, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, Gad Getz, David I. Heiman, Jaegil Kim, Michael S. Lawrence, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Vesteinn Thorsson, Wei Zhang, Rehan Akbani, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Han Liang, Shiyun Ling, Wenbin Liu, Yiling Lu, Gordon B. Mills, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, John N. Weinstein, Jiexin Zhang, Adam Abeshouse, Debyani Chakravarty, Ino de Bruijn, Jianjiong Gao, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Marc Ladanyi, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Joshua M. Stuart, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Katherine A. Hoadley, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Peter W. Laird, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, David A. Wheeler, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Li Ding, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Maciej Wiznerowicz, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Houtan Noushmehr, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Alexander J. Lazar, Christopher Logothetis, Funda Meric-Bernstam, Cesar Moran, Lois Ramondetta, David Rice, Anil Sood, Pheroze Tamboli, Timothy Thompson, Patricia Troncoso, Anne Tsao, Ignacio Wistuba, Candace Carter, Lauren Haydu, Peter Hersey, Valerie Jakrot, Hojabr Kakavand, Richard Kefford, Kenneth Lee, Georgina Long, Graham Mann, Michael Quinn, Robyn Saw, Richard Scolyer, Kerwin Shannon, Andrew Spillane, Jonathan Stretch, Maria Synott, John Thompson, James Wilmott, Hikmat Al-Ahmadie, Timothy A. Chan, Ronald Ghossein, Anuradha Gopalan, Douglas A. Levine, Victor Reuter, Samuel Singer, Bhuvanesh Singh, Nguyen Viet Tien, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair, Paul Drwiega, Judy Miller, Jennifer Smith, Howard Zaren, Joong-Won Park, Nguyen Phi Hung, Electron Kebebew, W. Marston Linehan, Adam R. Metwalli, Karel Pacak, Peter A. Pinto, Mark Schiffman, Laura S. Schmidt, Cathy D. Vocke, Nicolas Wentzensen, Robert Worrell, Hannah Yang, Marc Moncrieff, Chandra Goparaju, Jonathan Melamed, Harvey Pass, Natalia Botnariuc, Irina Caraman, Mircea Cernat, Inga Chemencedji, Adrian Clipca, Serghei Doruc, Ghenadie Gorincioi, Sergiu Mura, Maria Pirtac, Irina Stancul, Diana Tcaciuc, Monique Albert, Iakovina Alexopoulou, Angel Arnaout, John Bartlett, Jay Engel, Sebastien Gilbert, Jeremy Parfitt, Harman Sekhon, George Thomas, Doris M. Rassl, Robert C. Rintoul, Carlo Bifulco, Raina Tamakawa, Walter Urba, Nicholas Hayward, Henri Timmers, Anna Antenucci, Francesco Facciolo, Gianluca Grazi, Mirella Marino, Roberta Merola, Ronald de Krijger, Anne-Paule Gimenez-Roqueplo, Alain Piché, Simone Chevalier, Ginette McKercher, Kivanc Birsoy, Gene Barnett, Cathy Brewer, Carol Farver, Theresa Naska, Nathan A. Pennell, Daniel Raymond, Cathy Schilero, Kathy Smolenski, Felicia Williams, Carl Morrison, Jeffrey A. Borgia, Michael J. Liptay, Mark Pool, Christopher W. Seder, Kerstin Junker, Larsson Omberg, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. Chan, Philip Disaia, Pat Glenn, Robin K. Kelley, Charles N. Landen, Joanna Phillips, Michael Prados, Jeffry Simko, Karen Smith-McCune, Scott VandenBerg, Kevin Roggin, Ashley Fehrenbach, Ady Kendler, Suzanne Sifri, Ruth Steele, Antonio Jimeno, Francis Carey, Ian Forgie, Massimo Mannelli, Michael Carney, Brenda Hernandez, Benito Campos, Christel Herold-Mende, Christin Jungk, Andreas Unterberg, Andreas von Deimling, Aaron Bossler, Joseph Galbraith, Laura Jacobus, Michael Knudson, Tina Knutson, Deqin Ma, Mohammed Milhem, Rita Sigmund, Andrew K. Godwin, Rashna Madan, Howard G. Rosenthal, Clement Adebamowo, Sally N. Adebamowo, Alex Boussioutas, David Beer, Thomas Giordano, Anne-Marie Mes-Masson, Fred Saad, Therese Bocklage, Lisa Landrum, Robert Mannel, Kathleen Moore, Katherine Moxley, Russel Postier, Joan Walker, Rosemary Zuna, Michael Feldman, Federico Valdivieso, Rajiv Dhir, James Luketich, Edna M. Mora Pinero, Mario Quintero-Aguilo, Carlos Gilberto Carlotti, Jose Sebastião Dos Santos, Rafael Kemp, Ajith Sankarankuty, Daniela Tirapelli, James Catto, Kathy Agnew, Elizabeth Swisher, Jenette Creaney, Bruce Robinson, Carl Simon Shelley, Eryn M. Godwin, Sara Kendall, Cassaundra Shipman, Carol Bradford, Thomas Carey, Andrea Haddad, Jeffey Moyer, Lisa Peterson, Mark Prince, Laura Rozek, Gregory Wolf, Rayleen Bowman, Kwun M. Fong, Ian Yang, Robert Korst, W. Kimryn Rathmell, J. Leigh Fantacone-Campbell, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, John DiPersio, Bettina Drake, Ramaswamy Govindan, Sharon Heath, Timothy Ley, Brian Van Tine, Peter Westervelt, Mark A. Rubin, Jung Il Lee, Natália D. Aredes, Armaz Mariamidze, Cancer Genome Atlas Research Network, Caesar-Johnson, S.J., Demchok, J.A., Felau, I., Kasapi, M., Ferguson, M.L., Hutter, C.M., Sofia, H.J., Tarnuzzer, R., Wang, Z., Yang, L., Zenklusen, J.C., Zhang, J.J., Chudamani, S., Liu, J., Lolla, L., Naresh, R., Pihl, T., Sun, Q., Wan, Y., Wu, Y., Cho, J., DeFreitas, T., Frazer, S., Gehlenborg, N., Getz, G., Heiman, D.I., Kim, J., Lawrence, M.S., Lin, P., Meier, S., Noble, M.S., Saksena, G., Voet, D., Zhang, H., Bernard, B., Chambwe, N., Dhankani, V., Knijnenburg, T., Kramer, R., Leinonen, K., Liu, Y., Miller, M., Reynolds, S., Shmulevich, I., Thorsson, V., Zhang, W., Akbani, R., Broom, B.M., Hegde, A.M., Ju, Z., Kanchi, R.S., Korkut, A., Li, J., Liang, H., Ling, S., Liu, W., Lu, Y., Mills, G.B., Ng, K.S., Rao, A., Ryan, M., Wang, J., Weinstein, J.N., Zhang, J., Abeshouse, A., Armenia, J., Chakravarty, D., Chatila, W.K., de Bruijn, I., Gao, J., Gross, B.E., Heins, Z.J., Kundra, R., La, K., Ladanyi, M., Luna, A., Nissan, 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Mose, L.E., Perou, A.H., Perou, C.M., Roach, J., Shi, Y., Simons, J.V., Skelly, T., Soloway, M.G., Tan, D., Veluvolu, U., Fan, H., Hinoue, T., Laird, P.W., Shen, H., Zhou, W., Bellair, M., Chang, K., Covington, K., Creighton, C.J., Dinh, H., Doddapaneni, H., Donehower, L.A., Drummond, J., Gibbs, R.A., Glenn, R., Hale, W., Han, Y., Hu, J., Korchina, V., Lee, S., Lewis, L., Li, W., Liu, X., Morgan, M., Morton, D., Muzny, D., Santibanez, J., Sheth, M., Shinbrot, E., Wang, L., Wang, M., Wheeler, D.A., Xi, L., Zhao, F., Hess, J., Appelbaum, E.L., Bailey, M., Cordes, M.G., Ding, L., Fronick, C.C., Fulton, L.A., Fulton, R.S., Kandoth, C., Mardis, E.R., McLellan, M.D., Miller, C.A., Schmidt, H.K., Wilson, R.K., Crain, D., Curley, E., Gardner, J., Lau, K., Mallery, D., Morris, S., Paulauskis, J., Penny, R., Shelton, C., Shelton, T., Sherman, M., Thompson, E., Yena, P., Bowen, J., Gastier-Foster, J.M., Gerken, M., Leraas, K.M., Lichtenberg, T.M., Ramirez, N.C., Wise, L., Zmuda, E., Corcoran, N., 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Noushmehr, H., Scarpace, L., Girard, N., Aymerich, M., Campo, E., Giné, E., Guillermo, A.L., Van Bang, N., Hanh, P.T., Phu, B.D., Tang, Y., Colman, H., Evason, K., Dottino, P.R., Martignetti, J.A., Gabra, H., Juhl, H., Akeredolu, T., Stepa, S., Hoon, D., Ahn, K., Kang, K.J., Beuschlein, F., Breggia, A., Birrer, M., Bell, D., Borad, M., Bryce, A.H., Castle, E., Chandan, V., Cheville, J., Copland, J.A., Farnell, M., Flotte, T., Giama, N., Ho, T., Kendrick, M., Kocher, J.P., Kopp, K., Moser, C., Nagorney, D., O'Brien, D., O'Neill, B.P., Patel, T., Petersen, G., Que, F., Rivera, M., Roberts, L., Smallridge, R., Smyrk, T., Stanton, M., Thompson, R.H., Torbenson, M., Yang, J.D., Zhang, L., Brimo, F., Ajani, J.A., Gonzalez, AMA, Behrens, C., Bondaruk, J., Broaddus, R., Czerniak, B., Esmaeli, B., Fujimoto, J., Gershenwald, J., Guo, C., Lazar, A.J., Logothetis, C., Meric-Bernstam, F., Moran, C., Ramondetta, L., Rice, D., Sood, A., Tamboli, P., Thompson, T., Troncoso, P., Tsao, A., Wistuba, I., Carter, C., Haydu, L., Hersey, P., Jakrot, V., Kakavand, H., Kefford, R., Lee, K., Long, G., Mann, G., Quinn, M., Saw, R., Scolyer, R., Shannon, K., Spillane, A., Stretch, J., Synott, M., Thompson, J., Wilmott, J., Al-Ahmadie, H., Chan, T.A., Ghossein, R., Gopalan, A., Levine, D.A., Reuter, V., Singer, S., Singh, B., Tien, N.V., Broudy, T., Mirsaidi, C., Nair, P., Drwiega, P., Miller, J., Smith, J., Zaren, H., Park, J.W., Hung, N.P., Kebebew, E., Linehan, W.M., Metwalli, A.R., Pacak, K., Pinto, P.A., Schiffman, M., Schmidt, L.S., Vocke, C.D., Wentzensen, N., Worrell, R., Yang, H., Moncrieff, M., Goparaju, C., Melamed, J., Pass, H., Botnariuc, N., Caraman, I., Cernat, M., Chemencedji, I., Clipca, A., Doruc, S., Gorincioi, G., Mura, S., Pirtac, M., Stancul, I., Tcaciuc, D., Albert, M., Alexopoulou, I., Arnaout, A., Bartlett, J., Engel, J., Gilbert, S., Parfitt, J., Sekhon, H., Thomas, G., Rassl, D.M., Rintoul, R.C., Bifulco, C., Tamakawa, R., Urba, W., Hayward, N., Timmers, H., Antenucci, A., Facciolo, F., Grazi, G., Marino, M., Merola, R., de Krijger, R., Gimenez-Roqueplo, A.P., Piché, A., Chevalier, S., McKercher, G., Birsoy, K., Barnett, G., Brewer, C., Farver, C., Naska, T., Pennell, N.A., Raymond, D., Schilero, C., Smolenski, K., Williams, F., Morrison, C., Borgia, J.A., Liptay, M.J., Pool, M., Seder, C.W., Junker, K., Omberg, L., Dinkin, M., Manikhas, G., Alvaro, D., Bragazzi, M.C., Cardinale, V., Carpino, G., Gaudio, E., Chesla, D., Cottingham, S., Dubina, M., Moiseenko, F., Dhanasekaran, R., Becker, K.F., Janssen, K.P., Slotta-Huspenina, J., Abdel-Rahman, M.H., Aziz, D., Bell, S., Cebulla, C.M., Davis, A., Duell, R., Elder, J.B., Hilty, J., Kumar, B., Lang, J., Lehman, N.L., Mandt, R., Nguyen, P., Pilarski, R., Rai, K., Schoenfield, L., Senecal, K., Wakely, P., Hansen, P., Lechan, R., Powers, J., Tischler, A., Grizzle, W.E., Sexton, K.C., Kastl, A., Henderson, J., Porten, S., Waldmann, J., Fassnacht, M., Asa, S.L., Schadendorf, D., Couce, M., Graefen, M., Huland, H., Sauter, G., Schlomm, T., Simon, R., Tennstedt, P., Olabode, O., Nelson, M., Bathe, O., Carroll, P.R., Chan, J.M., Disaia, P., Glenn, P., Kelley, R.K., Landen, C.N., Phillips, J., Prados, M., Simko, J., Smith-McCune, K., VandenBerg, S., Roggin, K., Fehrenbach, A., Kendler, A., Sifri, S., Steele, R., Jimeno, A., Carey, F., Forgie, I., Mannelli, M., Carney, M., Hernandez, B., Campos, B., Herold-Mende, C., Jungk, C., Unterberg, A., von Deimling, A., Bossler, A., Galbraith, J., Jacobus, L., Knudson, M., Knutson, T., Ma, D., Milhem, M., Sigmund, R., Godwin, A.K., Madan, R., Rosenthal, H.G., Adebamowo, C., Adebamowo, S.N., Boussioutas, A., Beer, D., Giordano, T., Mes-Masson, A.M., Saad, F., Bocklage, T., Landrum, L., Mannel, R., Moore, K., Moxley, K., Postier, R., Walker, J., Zuna, R., Feldman, M., Valdivieso, F., Dhir, R., Luketich, J., Pinero, EMM, Quintero-Aguilo, M., Carlotti, C.G., Dos Santos, J.S., Kemp, R., Sankarankuty, A., Tirapelli, D., Catto, J., Agnew, K., Swisher, E., Creaney, J., Robinson, B., Shelley, C.S., Godwin, E.M., Kendall, S., Shipman, C., Bradford, C., Carey, T., Haddad, A., Moyer, J., Peterson, L., Prince, M., Rozek, L., Wolf, G., Bowman, R., Fong, K.M., Yang, I., Korst, R., Rathmell, W.K., Fantacone-Campbell, J.L., Hooke, J.A., Kovatich, A.J., Shriver, C.D., DiPersio, J., Drake, B., Govindan, R., Heath, S., Ley, T., Van Tine, B., Westervelt, P., Rubin, M.A., Lee, J.I., Aredes, N.D., Mariamidze, A., SAIC-F-Frederick, Inc, and Leidos Biomedical Research, Inc.

Subjects
0301 basic medicine, Neuroblastoma RAS viral oncogene homolog, Genetics and Molecular Biology (all), PATHOGENESIS, pan-cancer, PROTEIN, Cancer Genome Atlas Research Network, medicine.disease_cause, computer.software_genre, Genome, Biochemistry, Transcriptome, Gene expression, HRAS, KRAS, NF1, NRAS, Ras, TCGA, drug sensitivity, machine learning, Neoplasms, PRECISION ONCOLOGY, lcsh:QH301-705.5, Regulation of gene expression, PREVIOUSLY TREATED PATIENTS, 3. Good health, Gene Expression Regulation, Neoplastic, PHASE-II, Life Sciences & Biomedicine, Signal Transduction, Biology, Machine learning, General Biochemistry, Genetics and Molecular Biology, Article, BRAF, 03 medical and health sciences, Cell Line, Tumor, medicine, Biochemistry, Genetics and Molecular Biology (all), Humans, Gene, SIGNATURES, Science & Technology, business.industry, Genome, Human, MUTATIONS, EXPRESSÃO GÊNICA, Cell Biology, SELUMETINIB, GENE, 030104 developmental biology, lcsh:Biology (General), Selumetinib, ras Proteins, Artificial intelligence, business, computer
Abstract

SUMMARY Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these “hidden responders” may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders., In Brief Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines.

Published
2018

31. Optical Coherence Tomography

Author

Mary Ann Fitzmaurice, Brian C. Wilson, Sheldon Feldman, Hanina Hibshoosh, Victoria L. Mango, Lauren Friedlander, Richard Ha, Christine P. Hendon, Soojin Ahn, Margaret K. Akens, and Hank Schmidt

Subjects
0301 basic medicine, medicine.medical_specialty, Surgical margin, medicine.diagnostic_test, business.industry, Breast imaging, medicine.medical_treatment, Lumpectomy, Cancer, medicine.disease, Subspecialty, 3. Good health, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Breast cancer, Optical coherence tomography, 030220 oncology & carcinogenesis, medicine, Radiology, Nuclear Medicine and imaging, Radiology, business, Mastectomy
Abstract

Rationale and Objectives This study aimed to assess whether different breast cancer subspecialty physicians can be trained to distinguish non-suspicious from suspicious areas of post-lumpectomy specimen margin in patients with breast cancer using optical coherence tomography (OCT) images (a near-infrared based imaging technique) with final histology as the reference standard. Materials and Methods This institutional review board-exempt, Health Insurance Portability and Accountability Act-compliant study was performed on 63 surgically excised breast specimens from 35 female patients, creating a 90-case atlas containing both non-suspicious and suspicious areas for cancer. OCT images of the specimens were performed, providing 6.5–15 µm resolution with tissue visualization 1–2 mm subsurface. From the 90-case atlas, 40 cases were chosen for training and 40 were randomly selected for reader assessment. Three breast imaging radiologists, two pathologists, two breast surgeons, and one non-clinical reader were trained and assessed for ability to distinguish non-suspicious from suspicious findings blinded to clinical data and corresponding histology slides. Duration of training and assessment, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the curve for each reader were calculated as well as averages by subspecialty. Results The average training time was 3.4 hours (standard deviation, 1.2). The average assessment time was 1.9 hours (standard deviation, 0.7). The overall average reader sensitivity, specificity, and accuracy for detecting suspicious findings with histologic confirmation of cancer at the surgical margin for all eight readers were 80%, 87%, and 87%, respectively. Radiologists demonstrated the highest average among the disciplines, 85%, 93%, and 94%, followed by pathologists, 79%, 90%, and 84%, and surgeons, 76%, 84%, and 82% respectively. Conclusions With relatively short training (3.4 hours), readers from different medical specialties were able to distinguish suspicious from non-suspicious OCT imaging findings in ex vivo breast tissue as confirmed by histology. These results support the potential of OCT as a real-time intraoperative tool for post-lumpectomy specimen margin assessment.

Published
2018

32. p53 Maintains Baseline Expression of Multiple Tumor Suppressor Genes

Author

Sakellarios Zairis, Lao H. Saal, Francesco Abate, Tao Su, Sait Ozturk, Jia Xu, Hanina Hibshoosh, Lois Resnick-Silverman, Pamela Cheung, Stuart A. Aaronson, Kyrie Pappas, Ramon Parsons, Nicole Steinbach, Raul Rabadan, James J. Manfredi, and Hank Schmidt

Subjects
0301 basic medicine, Cancer Research, Tumor suppressor gene, Haploinsufficiency, Tumor initiation, Protein Serine-Threonine Kinases, Biology, medicine.disease_cause, Article, law.invention, 03 medical and health sciences, AMP-Activated Protein Kinase Kinases, law, Cell Line, Tumor, Neoplasms, medicine, Humans, PTEN, Molecular Biology, Histone Demethylases, Regulation of gene expression, Mutation, Reporter gene, Binding Sites, Forkhead Box Protein O1, Tumor Suppressor Proteins, PTEN Phosphohydrolase, Nuclear Proteins, Gene Expression Regulation, Neoplastic, MicroRNAs, Receptors, TNF-Related Apoptosis-Inducing Ligand, Cell Transformation, Neoplastic, 030104 developmental biology, Oncology, Cancer research, biology.protein, Suppressor, Tumor Suppressor Protein p53, Carcinogenesis, Protein Binding, Signal Transduction
Abstract

TP53 is the most commonly mutated tumor suppressor gene and its mutation drives tumorigenesis. Using ChIP-seq for p53 in the absence of acute cell stress, we found that wild-type but not mutant p53 binds and activates numerous tumor suppressor genes, including PTEN, STK11(LKB1), miR-34a, KDM6A(UTX), FOXO1, PHLDA3, and TNFRSF10B through consensus binding sites in enhancers and promoters. Depletion of p53 reduced expression of these target genes, and analysis across 18 tumor types showed that mutation of TP53 associated with reduced expression of many of these genes. Regarding PTEN, p53 activated expression of a luciferase reporter gene containing the p53-consensus site in the PTEN enhancer, and homozygous deletion of this region in cells decreased PTEN expression and increased growth and transformation. These findings show that p53 maintains expression of a team of tumor suppressor genes that may together with the stress-induced targets mediate the ability of p53 to suppress cancer development. p53 mutations selected during tumor initiation and progression, thus, inactivate multiple tumor suppressor genes in parallel, which could account for the high frequency of p53 mutations in cancer. Implications: In this study, we investigate the activities of p53 under normal low-stress conditions and discover that p53 is capable of maintaining the expression of a group of important tumor suppressor genes at baseline, many of which are haploinsufficient, which could contribute to p53-mediated tumor suppression. Mol Cancer Res; 15(8); 1051–62. ©2017 AACR.

Published
2017

33. Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT

Author

Yu Gan, Hanina Hibshoosh, Ernest W. Chang, Christine P. Hendon, Xinwen Yao, and Sheldon Feldman

Subjects
medicine.medical_specialty, genetic structures, medicine.medical_treatment, Adipose tissue, Image processing, Dermatology, 01 natural sciences, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Optical coherence tomography, 0103 physical sciences, Medicine, medicine.diagnostic_test, business.industry, Cancer, medicine.disease, eye diseases, Visualization, Feature (computer vision), 030220 oncology & carcinogenesis, Surgery, sense organs, Radiology, Breast reduction, business, Nuclear medicine
Abstract

Background and Objective Breast cancer is one of the most common cancers, and recognized as the third leading cause of mortality in women. Optical coherence tomography (OCT) enables three dimensional visualization of biological tissue with micrometer level resolution at high speed, and can play an important role in early diagnosis and treatment guidance of breast cancer. In particular, ultra-high resolution (UHR) OCT provides images with better histological correlation. This paper compared UHR OCT performance with standard OCT in breast cancer imaging qualitatively and quantitatively. Automatic tissue classification algorithms were used to automatically detect invasive ductal carcinoma in ex vivo human breast tissue. Study Design/Materials and Methods Human breast tissues, including non-neoplastic/normal tissues from breast reduction and tumor samples from mastectomy specimens, were excised from patients at Columbia University Medical Center. The tissue specimens were imaged by two spectral domain OCT systems at different wavelengths: a home-built ultra-high resolution (UHR) OCT system at 800 nm (measured as 2.72 μm axial and 5.52 μm lateral) and a commercial OCT system at 1,300 nm with standard resolution (measured as 6.5 μm axial and 15 μm lateral), and their imaging performances were analyzed qualitatively. Using regional features derived from OCT images produced by the two systems, we developed an automated classification algorithm based on relevance vector machine (RVM) to differentiate hollow-structured adipose tissue against solid tissue. We further developed B-scan based features for RVM to classify invasive ductal carcinoma (IDC) against normal fibrous stroma tissue among OCT datasets produced by the two systems. For adipose classification, 32 UHR OCT B-scans from 9 normal specimens, and 28 standard OCT B-scans from 6 normal and 4 IDC specimens were employed. For IDC classification, 152 UHR OCT B-scans from 6 normal and 13 IDC specimens, and 104 standard OCT B-scans from 5 normal and 8 IDC specimens were employed. Results We have demonstrated that UHR OCT images can produce images with better feature delineation compared with images produced by 1,300 nm OCT system. UHR OCT images of a variety of tissue types found in human breast tissue were presented. With a limited number of datasets, we showed that both OCT systems can achieve a good accuracy in identifying adipose tissue. Classification in UHR OCT images achieved higher sensitivity (94%) and specificity (93%) of adipose tissue than the sensitivity (91%) and specificity (76%) in 1,300 nm OCT images. In IDC classification, similarly, we achieved better results with UHR OCT images, featured an overall accuracy of 84%, sensitivity of 89% and specificity of 71% in this preliminary study. Conclusion In this study, we provided UHR OCT images of different normal and malignant breast tissue types, and qualitatively and quantitatively studied the texture and optical features from OCT images of human breast tissue at different resolutions. We developed an automated approach to differentiate adipose tissue, fibrous stroma, and IDC within human breast tissues. Our work may open the door toward automatic intraoperative OCT evaluation of early-stage breast cancer. Lasers Surg. Med. 49:258–269, 2017. © 2017 Wiley Periodicals, Inc.

Published
2017

34. Unbiased Assessment of H-STS cells as high-fidelity models for gastro-enteropancreatic neuroendocrine tumor drug mechanism of action analysis

Author

Paul E. Oberstein, Jeffrey W. Milsom, John A. Chabot, Mariano J. Alvarez, Charles Karan, Matthew H. Kulke, Michaela Bowden, Massimo Loda, Diane Reidy-Lagunes, Andrea Califano, Hanina Hibshoosh, Mary L. Alpaugh, Prabhjot S. Mundi, Pengrong Yan, Ewa Sicinska, Dirk Jäger, Antonio Tito Fojo, Ronald Realubit, Adina Grunn, Chensheng Zhou, and Gabriela Chiosis

Subjects
Drug, 0303 health sciences, media_common.quotation_subject, Cancer, Cell state, Computational biology, Biology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Mechanism of action, 030220 oncology & carcinogenesis, medicine, medicine.symptom, 030304 developmental biology, media_common
Abstract

Quantitative metrics to objectively assess the fidelity of cancer models, such as cell lines, organoids, or patient-derived xenografts (PDXs), remain elusive, with histological criteria or the presence of specific mutations often used as driving principles. We show that molecular criteria, based on the regulatory proteins responsible for maintaining transcriptional cell state and its regulatory network, are effective in identifying models that can recapitulate drug mechanism of action and drug sensitivity, independent of histological consideration.

Published
2019

35. Convolutional neural network (CNN) classification of breast cancer in optical coherence tomography (OCT) images

Author

Richard Ha, Diana Mojahed, Hanina Hibshoosh, Christine P. Hendon, Xinwen Yao, Brigid Angelini, Yu Gan, and Peter Chang

Subjects
medicine.diagnostic_test, Computer science, business.industry, Deep learning, medicine.medical_treatment, Image processing, Pattern recognition, Ductal carcinoma, medicine.disease, Convolutional neural network, Breast cancer, Optical coherence tomography, medicine, Breast reduction, Artificial intelligence, skin and connective tissue diseases, business, Mastectomy
Abstract

The purpose of this study was to develop and evaluate the performance of a convolutional neural network (CNN) that uses a novel A-line based classification approach to detect cancer in OCT images of breast specimens. Deep learning algorithms have been developed for OCT ophthalmology applications using pixel-based classification approaches. In this study, a novel deep learning approach was developed that classifies OCT A-lines of breast tissue. De-identified human breast tissues from mastectomy and breast reduction specimens were excised from patients at Columbia University Medical Center. A total of 82 specimens from 49 patients were imaged with OCT, including both normal tissues and non-neoplastic tissues. The proposed algorithm utilized a hybrid 2D/1D convolutional neural network (CNN) to map each single B-scan to a 1D label vector, which were derived from manual annotation. Each A-line was labelled as one of the following tissue types: ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), adipose, and stroma. Five-fold cross-validation Dice scores across tissue types were: 0.82-0.95 for IDC, 0.54-0.75 for DCIS, 0.67-0.91 for adipose, and 0.61-0.86 for stroma. In a second experiment, IDC and DCIS were combined as a single tissue class (malignancy) while stroma and adipose were combined as a second tissue class (non-malignancy). In this setup, the experiment yielded five-fold cross-validation Dice scores between 0.89-0.93, respectively. Future work includes acquiring more patient samples and to compare the algorithm to previous works, including both deep learning and traditional automatic image processing methods for classification of breast tissue in OCT images.

Published
2019

36. Monitoring total hemoglobin concentration changes across neoadjuvant chemotherapy in PgR-positive and PgR-negative breast cancer with diffuse optical tomography

Author

Andreas H. Hielscher, Hyun K. Kim, Mariella Tejada, Dawn L. Hershman, Hanina Hibshoosh, Kevin Kalinsky, Alessandro Marone, Katherine D. Crew, and Mirella L. Altoe

Subjects
Oncology, endocrine system, medicine.medical_specialty, PGR Negative, Chemotherapy, Breast imaging, business.industry, medicine.medical_treatment, Significant difference, PGR Positive, medicine.disease, eye diseases, Diffuse optical imaging, Total hemoglobin, Breast cancer, Internal medicine, Medicine, sense organs, skin and connective tissue diseases, business, hormones, hormone substitutes, and hormone antagonists
Abstract

The aim of this study was to investigate the optical chemotherapy changes induced by neoadjuvant chemotherapy (NAC) in PgR-positive and PgR-negative breast cancer subtypes using a diffuse optical tomographic breast imaging system (DOTBIS). ctTHb reduction in the tumor volume was greater for patients with PgR-negative, a statistically significant difference of 48.91μM, p = .022, which suggest that PgR-negative tumors are generally less resistant to NAC. These observations indicate that PgR negativity may be combined to optically derived biomarkers for predicting pCR during neoadjuvant chemotherapy.

Published
2019

37. Experimental microdissection enables functional harmonization of pancreatic cancer subtypes

Author

Pasquale Laise, Paul E. Oberstein, Sam R. Holmstrom, Antonia R. Sepulveda, Carlo Maurer, Jing He, Andrea Califano, Hanina Hibshoosh, Mukesh Bansal, Tao Su, Jiapeng Zhang, John A. Chabot, Aqeel Ahmed, Jeanine M. Genkinger, Alina Iuga, and Kenneth P. Olive

Subjects
Stromal cell, Gene Expression Profiling, Gastroenterology, Cancer, Computational biology, Biology, Adenocarcinoma, medicine.disease, Sensitivity and Specificity, Subtyping, Article, Extracellular Matrix, Gene Expression Regulation, Neoplastic, Pancreatic Neoplasms, Stroma, Pancreatic cancer, Case-Control Studies, Gene expression, medicine, Humans, Computer Simulation, Microdissection, Laser capture microdissection, Carcinoma, Pancreatic Ductal
Abstract

ObjectivePancreatic ductal adenocarcinoma (PDA) has among the highest stromal fractions of any cancer and this has complicated attempts at expression-based molecular classification. The goal of this work is to profile purified samples of human PDA epithelium and stroma and examine their respective contributions to gene expression in bulk PDA samples.DesignWe used laser capture microdissection (LCM) and RNA sequencing to profile the expression of 60 matched pairs of human PDA malignant epithelium and stroma samples. We then used these data to train a computational model that allowed us to infer tissue composition and generate virtual compartment-specific expression profiles from bulk gene expression cohorts.ResultsOur analysis found significant variation in the tissue composition of pancreatic tumours from different public cohorts. Computational removal of stromal gene expression resulted in the reclassification of some tumours, reconciling functional differences between different cohorts. Furthermore, we established a novel classification signature from a total of 110 purified human PDA stroma samples, finding two groups that differ in the extracellular matrix-associated and immune-associated processes. Lastly, a systematic evaluation of cross-compartment subtypes spanning four patient cohorts indicated partial dependence between epithelial and stromal molecular subtypes.ConclusionOur findings add clarity to the nature and number of molecular subtypes in PDA, expand our understanding of global transcriptional programmes in the stroma and harmonise the results of molecular subtyping efforts across independent cohorts.

Published
2019

38. NOTCH and EZH2 collaborate to repress PTEN expression in breast cancer

Author

Tiphaine Martin, Ramon Parsons, Tao Su, Hanina Hibshoosh, Jian Jin, Kyrie Pappas, Christie B. Nguyen, and Andrew Wolfe

Subjects
0301 basic medicine, Transcription, Genetic, QH301-705.5, Medicine (miscellaneous), Down-Regulation, Breast Neoplasms, macromolecular substances, General Biochemistry, Genetics and Molecular Biology, Article, Fusion gene, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Cell Line, Tumor, medicine, PTEN, Humans, Enhancer of Zeste Homolog 2 Protein, Epigenetics, Receptor, Notch2, Biology (General), Receptor, Notch1, Tumour-suppressor proteins, Psychological repression, Cell Proliferation, Gene knockdown, biology, EZH2, PTEN Phosphohydrolase, medicine.disease, Gene Expression Regulation, Neoplastic, 030104 developmental biology, 030220 oncology & carcinogenesis, Mutation, Cancer research, biology.protein, Female, Signal transduction, Gene Fusion, General Agricultural and Biological Sciences
Abstract

Downregulation of the PTEN tumor suppressor transcript is frequent in breast cancer and associates with poor prognosis and triple-negative breast cancer (TNBC) when comparing breast cancers to one another. Here we show that in almost all cases, when comparing breast tumors to adjacent normal ducts, PTEN expression is decreased and the PRC2-associated methyltransferase EZH2 is increased. We further find that when comparing breast cancer cases in large cohorts, EZH2 inversely correlates with PTEN expression. Within the highest EZH2 expressing group, NOTCH alterations are frequent, and also associate with decreased PTEN expression. We show that repression of PTEN occurs through the combined action of NOTCH (NOTCH1 or NOTCH2) and EZH2 alterations in a subset of breast cancers. In fact, in cases harboring NOTCH1 mutation or a NOTCH2 fusion gene, NOTCH drives EZH2, HES-1, and HEY-1 expression to repress PTEN transcription at the promoter, which may contribute to poor prognosis in this subgroup. Restoration of PTEN expression can be achieved with an EZH2 inhibitor (UNC1999), a γ-secretase inhibitor (Compound E), or knockdown of EZH2 or NOTCH. These findings elucidate a mechanism of transcriptional repression of PTEN induced by NOTCH1 or NOTCH2 alterations, and identifies actionable signaling pathways responsible for driving a large subset of poor-prognosis breast cancers., Pappas et al. show that the combination of NOTCH and EZH2 alterations drive transcriptional repression of PTEN through reversible epigenetic modification of the PTEN promoter. These results suggest an actionable target for treating poor-prognosis breast cancer.

Published
2018

39. Monitoring Metastasis and Cachexia in a Patient with Breast Cancer: A Case Study

Author

Courtney Coker, Kevin Kalinsky, Nikita Consul, Swarnali Acharyya, Sara López-Pintado, Binsheng Zhao, Hanina Hibshoosh, and Xiaotao Guo

Subjects
0301 basic medicine, Oncology, medicine.medical_specialty, Pathology, Case Report, vertebral metastasis, lcsh:RC254-282, cachexia, Cachexia, Metastasis, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, breast cancer, Weight loss, Internal medicine, medicine, Wasting, bone metastasis, business.industry, Cancer, Bone metastasis, medicine.disease, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, radiological quantification, Metastatic breast cancer, 3. Good health, 030104 developmental biology, 030220 oncology & carcinogenesis, medicine.symptom, weight loss, business
Abstract

Cachexia, a wasting syndrome associated with advanced cancer and metastasis, is rarely documented in breast cancer patients. However, the incidence of cachexia in breast cancer is now thought to be largely underestimated. In our case report of a breast cancer patient with bone metastasis monitored during the course of her treatment, we document the development of cachexia by image analysis in relation to her metastatic burden. Elucidation of the link between metastatic burden and cachexia could unveil a highly specific screening process for metastasis, by assessing true muscle mass loss. Our patient was a 49-year-old premenopausal woman, with metastatic invasive ductal breast carcinoma in the vertebral and iliac bones on presentation, which progressed with new metastases to her hips, thigh bones, and vertebrae. In the two-year period, that is between her diagnosis and death, she lost >10% of her baseline weight. During these two years, we retrospectively identified a decrease in paraspinal muscle (PM) at the third lumbar vertebra followed by a sharp decline in weight. The increased tumor burden over time in metastatic sites was accompanied by a decrease in abdominal muscle and visceral and subcutaneous fat and was followed by the patient's demise. The increasing tumor burden in the patient was correlated with the mass of other tissues to determine the tissue that could best serve as a surrogate marker to cachexia and tumor burden. We noted a strong negative correlation between PM area and metastatic tumor area at the third lumbar vertebral level, with PM loss correlating to increasing tumor burden. The monitoring of PM wasting may serve as a marker, and therefore a prognostic factor, for both cachexia and extent of metastatic disease, especially in breast cancer, where metastasis to bone is frequent. Based on our data and review of the literature in this case study, longitudinal monitoring of cachexia in the selected muscle groups can give clinicians early indications of the extent of cachexia in metastatic breast cancer patients.

Published
2016

40. Cytomorphology of Recurrent Osseous Extracranial Meningioma of Right Pubic Ramus

Author

Hanina Hibshoosh, Aqiba Bokhari, and Patricia G. Tiscornia-Wasserman

Subjects
Image-Guided Biopsy, Pathology, medicine.medical_specialty, Histology, Bone Neoplasms, Pubic symphysis, Meningothelial Meningioma, Pathology and Forensic Medicine, Meningioma, Lesion, 03 medical and health sciences, 0302 clinical medicine, Cytology, medicine, Humans, Hip pain, Pubic Bone, business.industry, General Medicine, Middle Aged, medicine.disease, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Right superior, Female, Histopathology, Biopsy, Large-Core Needle, Neoplasm Recurrence, Local, medicine.symptom, business, 030217 neurology & neurosurgery
Abstract

Meningiomas are well-recognized neoplasms of the central nervous system. Primary extracranial meningiomas (ECMs) are extremely rare and arise in various anatomic sites. We present a 56-year-old female with 13-year history of primary grade I meningothelial meningioma of right pubic symphysis, orthotopic heart transplant, and right total hip arthroplasty, who presented with progressive right hip pain for 3 weeks. Primary intracranial, intraspinal and other tumors were excluded. Imaging revealed a destructive lytic lesion at right superior and inferior pubic rami and body, associated with extensive bone destruction and soft tissue mass. Touch imprint (TI) cytology of computed tomography (CT)-guided core biopsy from the right pubic ramus (PRA) lesion showed a spindle cell neoplasm, with classical syncytial, lobular, and whorling cellular arrangement, composed of spindle, oval or round nuclei with occasional pseudoinclusions, consistent with known history of osseous meningioma. Tumor was further characterized by histopathology as grade 1 meningioma with meningothelial features. To our knowledge, primary osseous ECM arising specifically at the PRA has not been reported previously. ECM at this site may pose a diagnostic challenge for cytologists as its features may resemble other more commonly observed lesions. Accurate diagnosis requires awareness of occurrence of ECM at PRA and recognition of its characteristic cytomorphology. TI cytological features of our case are presented and previously described cytology of ECMs and diagnostic pitfalls are reviewed. Diagn. Cytopathol. 2016;44:618-622. © 2016 Wiley Periodicals, Inc.

Published
2016

41. Abstract P3-07-52: Identification of serum biomarkers associated with Akt inhibitor MK-2206-induced toxicity in a pre-surgical breast cancer (BC) trial

Author

Kevin Kalinsky, Matthew J. Maurer, P Ananthakrishnan, DL Hershman, Katherine D. Crew, Sheldon Feldman, Lisa Wiechmann, B Taback, Eleni Andreopoulou, Emily I. Chen, Prabhjot Mundi, Joseph A. Sparano, Hanina Hibshoosh, and Eileen P. Connolly

Subjects
Cancer Research, business.industry, Akt/PKB signaling pathway, Cancer, medicine.disease, Rash, chemistry.chemical_compound, Oncology, chemistry, MK-2206, Immunology, Toxicity, Maculopapular rash, Cancer research, Medicine, medicine.symptom, business, Protein kinase B, PI3K/AKT/mTOR pathway
Abstract

Background: The PI3K/Akt/mTOR pathway is an important oncogenic driver in BC. A major hurdle in clinical Akt inhibitor development has been dose-limiting toxicities, such as rash. To facilitate the risk assessment of Akt inhibitor associated toxicity, we hypothesize that circulating biomarkers can be identified in proteins secreted by the tumor or tumor microenvironment and systemic response after treatment. Exosomes are small membrane bound vesicles containing proteins, mRNA, miRNA, and lipids that are secreted from host cells and remain viable after long-term storage of blood. In this study, we focused on identifying biomarkers associated with drug rash from serum exosomes in BC patients treated with the Akt inhibitor MK-2206. Methods: In an open-label pre-surgical trial, 2 doses of weekly MK2206 were administered to patients (pts) with stage I-III invasive BC: first at day -9 and second at day -2 from surgery. Sera were collected before and after MK2206. 200 μL of serum was used to isolate total exosomes by precipitation and centrifugation, followed by trypsin digestion and multiplexing labeling analysis. The Orbitrap mass spectrometer was used to acquire LC-MS/MS data. 1,053 unique proteins were identified from the uniProt database. Maximum false discovery rate level (FDR) for predictive biomarkers was controlled at 26% (q Results: The study was discontinued after 12 pts were enrolled due to toxicity. Notably, an acneiform/maculopapular rash was observed in 5 pts. Unsupervised principal component analysis on the pre-MK-2206 specimens and the entire set of 1,053 proteins demonstrated that 4 of the 5 pts with rash formed a distinct cluster. 30 proteins were differentially expressed in pre-MK-2206 samples from pts who developed rash vs. no rash (q Conclusions: We demonstrated that mass spectrometry-based proteomic analysis of patient-derived serum exosomes is a promising approach to study drug-induced toxicity. We found significant changes of circulating proteins before and after MK-2206. Increased expression of different proteins involved in lipid metabolism appears to predict skin toxicity, commonly seen with PI3K/Akt pathway inhibitors. Since the PI3K/Akt signaling pathway plays a role in physiological regulation of lipid metabolism, lipid metabolic profiles of BC patients might be important for predicting the risk and controlling toxicity induced by Akt inhibitors. These toxicity-associated biomarkers should be validated and then assessed prospectively in clinical trials. Citation Format: Mundi PS, Chen E, Sparano J, Andreopoulou E, Taback B, Wiechmann L, Feldman S, Ananthakrishnan P, Hibshoosh H, Connolly E, Crew K, Maurer M, Hershman DL, Kalinsky K. Identification of serum biomarkers associated with Akt inhibitor MK-2206-induced toxicity in a pre-surgical breast cancer (BC) trial. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-52.

Published
2016

42. Phase Ib Randomized, Double-Blinded, Placebo-Controlled, Dose Escalation Study of Polyphenon E in Patients with Barrett's Esophagus

Author

Julian A. Abrams, Felice Schnoll-Sussman, Marjorie Perloff, Esther G. Akpa, Chung S. Yang, J. Jack Lee, Diane D. Liu, Tao Su, Andrew K. Joe, Michelle Bigg, Scott M. Lippman, Hanina Hibshoosh, Richard A. Friedman, Xiaomei Wang, Powel H. Brown, Robert S. Bresalier, Ginger L. Milne, Charles J. Lightdale, Kazeem Abdul, Ken Cheung, Alfred I. Neugut, Aqeel Ahmed, and Jessica T. Foreman

Subjects
Male, Cancer Research, Biopsy, Urine, Gastroenterology, Catechin, 80 and over, Chromatography, High Pressure Liquid, Cancer, Aged, 80 and over, Chromatography, medicine.diagnostic_test, Middle Aged, medicine.anatomical_structure, Oncology, High Pressure Liquid, 6.1 Pharmaceuticals, Female, Esophagoscopy, Drug, medicine.symptom, medicine.medical_specialty, Nausea, Clinical Trials and Supportive Activities, Clinical Sciences, Oncology and Carcinogenesis, Polyphenon E, Placebo, Article, Dose-Response Relationship, Barrett Esophagus, Rare Diseases, Double-Blind Method, Clinical Research, Internal medicine, Complementary and Integrative Health, medicine, Humans, Oncology & Carcinogenesis, Esophagus, Adverse effect, Aged, Dose-Response Relationship, Drug, business.industry, Evaluation of treatments and therapeutic interventions, medicine.disease, Surgery, Barrett's esophagus, Digestive Diseases, business, Phytotherapy
Abstract

This study was conducted to determine the safety and efficacy of the green tea–derived Polyphenon E (Poly E) in patients with Barrett's Esophagus (BE). Subjects were randomized to a 6-month, twice daily (BID) oral treatment of placebo or Poly E (200, 400, or 600 mg). Endoscopic evaluation, including biopsies, was performed before and after treatment. The primary objective was to demonstrate safety; secondary objectives investigated catechin accumulation and effects in clinical specimens. Of the 44 enrolled subjects, 11 received placebo, and 33 received Poly E. No dose-limiting toxicities were encountered, and a maximum tolerated dose (MTD) was not reached. The recommended phase II dose was 600 mg twice daily. The most common treatment-related adverse events (AE) in Poly E–treated subjects were grade I and II nausea, grade I belching, and grade I lactate dehydrogenase (LDH) elevation. No treatment-related AEs were reported in placebo-treated subjects, aside from grade I laboratory abnormalities. Pill counts and subject diaries were not consistently collected, and compliance was difficult to determine. However, on the basis of an intention-to-treat analysis, there was a significant relationship between Poly E dose and esophageal EGCG level—mean changes (pmol/g) of 0.79 (placebo), 6.06 (200 mg), 35.67 (400 mg), and 34.95 (600 mg); P = 0.005. There was a possible relationship between Poly E dose and urine PGE-M concentration. In conclusion, Poly E was well-tolerated, and treatment with Poly E (400 and 600 mg) but not Poly E (200 mg) or placebo resulted in clinically relevant and detectable EGCG accumulation in the target organ, esophageal mucosa. Cancer Prev Res; 8(12); 1131–7. ©2015 AACR.

Published
2015

43. An unusual presentation of a rare soft tissue tumor in the tongue: Inflammatory myofibroblastic tumor

Author

Marilyn Nedumcheril, David A. Gudis, Erik H. Waldman, Sonam Dodhia, Hanina Hibshoosh, Valeria Silva Merea, and Rahmatullah Rahmati

Subjects
Pathology, medicine.medical_specialty, Soft Tissue Neoplasm, business.industry, Soft tissue, 030206 dentistry, medicine.disease, 030207 dermatology & venereal diseases, 03 medical and health sciences, Pediatric patient, 0302 clinical medicine, medicine.anatomical_structure, Otorhinolaryngology, Tongue lesion, Tongue, Pediatrics, Perinatology and Child Health, cardiovascular system, medicine, Neoplasm, cardiovascular diseases, Differential diagnosis, Presentation (obstetrics), business
Abstract

Inflammatory myofibroblastic tumor (IMT) is a rare soft tissue neoplasm of intermediate biologic potential. Here, we describe an unusual presentation of IMT in the oral tongue of a pediatric patient. In contrast to other presentations in the literature suggestive of a malignant process, the presentation seen here appears benign. However, unlike the more common benign pediatric tongue lesions, IMT does have aggressive and even mortal potential. Though rare, it is important to keep in mind atypical presentations like the one described here and consider IMT on the differential diagnosis of a tongue lesion in a pediatric patient.

Published
2017

44. Preoperative Pembrolizumab Treatment Changes Tils in Naïve Stage I/IIA TNBC Patients Within a Window of Opportunity Trial

Author

Joel H. Saltz, H. Guo, H. Le, Qi Wang, Rajarsi P. Gupta, Le Hou, Tahsin Kurc, Dimitris Samaras, Eileen P. Connolly, Kevin Gardner, Rami Vanguri, Hanina Hibshoosh, Kevin Kalinsky, Shuobo Boboila, and Shahira Abousamra

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Window of opportunity, Radiation, business.industry, Internal medicine, medicine, Radiology, Nuclear Medicine and imaging, Pembrolizumab, business
Published
2020

45. Abstract LB-003: OncoMatch: Unbiased, quantitative assessment of cancer model fidelity for drug sensitivity and mechanism of action elucidation

Author

Michaela Bowden, Diane Reidy-Lagunes, Charles Karan, Gabriela Chiosis, Mary L. Alpaugh, Chensheng W. Zhou, Mariano J. Alvarez, Jager Dirk, Matthew H. Kulke, Andrea Califano, Jeffrey W. Milsom, John A. Chabot, Adina Grunn, Ronald Realubit, Antonio Tito Fojo, Prabhjot S. Mundi, Hanina Hibshoosh, Paul E. Oberstein, Ewa Sicinska, Yan Pengrong, and Massimo Loda

Subjects
Drug, Cancer Research, media_common.quotation_subject, Cancer Model, Cancer, Fidelity, Context (language use), Computational biology, Biology, medicine.disease, Phenotype, Oncology, Mechanism of action, medicine, Epigenetics, medicine.symptom, media_common
Abstract

Quantitative metrics to objectively assess the fidelity of cancer models, such as cell lines, organoids, or patient-derived xenografts (PDXs), remain elusive, with histological criteria or the presence of specific mutations often used as driving principles. However, focusing on individual mutations inevitably ignores the effect of a large complement of additional, model-specific genetic and epigenetic events. As a result, effective model fidelity assessment is best performed a posteriori, for instance, by determining whether dependencies identified in a specific tumor model (e.g., a cell line or organoid) are recapitulated in vivo in PDXs or in patients, via pre-clinical or clinical trials. Unfortunately, such an approach is inefficient and time-consuming, creating an urgent need for methodologies capable of effectively and quantitatively assessing model fidelity a priori. This unmet need motivated us to develop and test a quantitative, molecular-level framework (OncoMatch), to assess the fidelity of a given tumor model in the context of a specific biological question, and in particular for addressing issues of drug sensitivity. We addressed this challenge by integrating two independent computational metrics to assess: (a) conservation of regulatory networks inferred from patient-derived samples in a model of interest, and; (b) overlap of master regulator (MR) proteins–i.e., proteins representing the mechanistic determinants of the transcriptional state associated with the phenotype of interest–as inferred from patient-derived and model-derived samples. We show that these molecular-level criteria can effectively identify cell lines that recapitulate patient-specific drug mechanism of action and drug sensitivity, independent of histological consideration. By leveraging gene expression profiles of drug-perturbations in primary cells and explants derived from gastroenteropancreatic-neuroendocrine tumor (GEP-NET) patients, we show that H-STS, an EBV-immortalized lymphoblastoid cell line, represents a high-fidelity model for the assessment of drug mechanism of action and drug sensitivity in these tumors. In particular, our analysis shows highly significant conservation of drug mechanism of action for 60 of 95 profiled drugs (63%, p < 10-10, Bonferroni's corrected), and higher conservation among drugs exhibiting greater bioactivity in this context. This rate is comparable and, in fact higher than what is achieved using tumor-type-matched cell line pairs representative of glioma, pancreatic and prostate carcinoma, and dramatically higher than the conservation observed between unrelated models, which we used as negative controls. Based on this systematic analysis, OncoMatch represents a valuable addition to our repertoire of tools for prioritizing cell lines, organoids and patient-derived xenograft models as high-fidelity human cancer models. We provide comprehensive prioritization of 921 cell lines as potential high-fidelity models for 10,024 human tumor samples in TCGA. This represents an actionable resource to guide selection of cell line models for specific drug mechanism of action and drug sensitivity studies. Citation Format: Mariano J. Alvarez, Yan Pengrong, Mary L. Alpaugh, Michaela Bowden, Ewa T. Sicinska, Chensheng W. Zhou, Charles Karan, Ronald B. Realubit, Prabhjot S. Mundi, Adina Grunn, Jager Dirk, John A. Chabot, Antonio T. Fojo, Paul E. Oberstein, Hanina Hibshoosh, Jeffrey W. Milsom, Matthew H. Kulke, Massimo Loda, Gabriela Chiosis, Diane L. Reidy-Lagunes, Andrea Califano. OncoMatch: Unbiased, quantitative assessment of cancer model fidelity for drug sensitivity and mechanism of action elucidation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-003.

Published
2020

46. Abstract P1-01-02: Early changes in diffuse optical tomography predicts pathologic complete response to neoadjuvant chemotherapy in triple-negative breast cancer

Author

Hua Guo, Andreas H. Hielscher, Dawn L. Hershman, Katherine D. Crew, Kevin Kalinsky, Melissa K. Accordino, Alessandro Marone, Mirella L. Altoe, Hyun K. Kim, Mariella Tejada, Hanina Hibshoosh, and Meghna S. Trivedi

Subjects
Oncology, Cancer Research, medicine.medical_specialty, Taxane, Cyclophosphamide, Breast imaging, business.industry, Cancer, medicine.disease, Breast cancer, Docetaxel, Internal medicine, medicine, Prospective cohort study, business, Triple-negative breast cancer, medicine.drug
Abstract

Background: Optical based imaging modalities have shown promise for monitoring tumor response to neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC). Patients with triple negative BC (TNBC) who achieve a pathologic complete response (pCR) have improved disease free and overall survival after NAC. In this study, we evaluated whether early changes in diffuse optical tomography breast imaging system (DOTBIS) parameters can predict a pCR. In particular, we studied total hemoglobin concentration (ctHbT) in the tumor region. Methods: This is a retrospective evaluation of 105 stage II-III BC patients enrolled in a prospective cohort study between 2011 and 2019. All patients received standard taxane-based chemotherapy in the neoadjuvant setting and pCR was defined as no invasive tumor cells from the breast and axillary tissue at surgery (ypT0 ypN0). Residual Cancer Burden (RCB) score was also calculated. By imaging the whole breast volume using low intensity near infrared light, we measured tissue concentration of oxy-hemoglobin (ctO2Hb) and deoxy-hemoglobin (ctHHb). After tumor volume segmentation, the mean ctHbT (ctO2Hb+ ctHHb) extracted from the region of interest was normalized by the non-tumor region ctHbT mean value. We conducted an independent-samples t-test to determine if there was a difference in changes in the normalized ctHbT levels at week 4 (w4) between patients with a pCR and non-pCR. A Pearson's correlation assessed for correlation between RCB score and changes in the normalized ctHbT level at w4 compared to baseline. Results: In total, 77 patients had complete data for the analysis. Of these, TNBC accounted for 18% (14/77) of BC cases. DOTBIS data was acquired at baseline for all patients. Twelve patients received weekly paclitaxel x 12, followed by dose-dense adriamycin/cyclophosphamide every 2 weeks x 4, and two received docetaxel/cyclophosphamide every 3 weeks x 6. Ten of 14 TNBC patients were imaged after four weeks of taxane-based NAC (w4). Of the 14 TNBC patients, 6 (43%) achieved pCR. Two patients were classified as RCB-I, 5 as RCB-II, and 1 non-pCR patient without an available RCB. After comparing normalized ctHbT levels at w4 to baseline, NAC was associated with an overall decrease of 28% for the pCR group (n=5) as opposed to an increase of 67% for non-pCR (n=5). The normalized ratio between ctHbT levels measured at w4 and baseline was statistically lower in the pCR group (0.72 ± 0.28) than non-pCR (1.67 ± 0.83) (95% CI, 0.17 to 2.09), p = .043. Changes in the normalized ctHbT levels after 4 weeks of NAC were strongly correlated to RCB score (r = .833, p = .005). Conclusions: This study demonstrates that changes as early as 4 weeks in DOTBIS-measured ctHbT levels in patients with TNBC receiving NAC correlate strongly with pathologic response. If further validated on a larger set, these data could potentially be used to optimize treatment outcomes or improve personalized therapeutic strategies. Citation Format: Mirella L Altoe, Kevin Kalinsky, Hua Guo, Hanina Hibshoosh, Mariella Tejada, Katherine D Crew, Melissa K Accordino, Meghna S Trivedi, Alessandro Marone, Hyun K Kim, Andreas H Hielscher, Dawn L Hershman. Early changes in diffuse optical tomography predicts pathologic complete response to neoadjuvant chemotherapy in triple-negative breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-01-02.

Published
2020

47. Obesity-associated Breast Inflammation among Hispanic/Latina Breast Cancer Patients

Author

Lisle A. Winston, Hanina Hibshoosh, Aqeel Ahmed, Domenick J. Falcone, Dawn L. Hershman, Andrew J. Dannenberg, Heather Greenlee, Samantha Williams, Neil M. Iyengar, Zaixing Shi, Dilip Giri, Xi Kathy Zhou, and Clifford A. Hudis

Subjects
0301 basic medicine, Oncology, Adult, Cancer Research, medicine.medical_specialty, medicine.medical_treatment, Adipose Tissue, White, Population, Adipose tissue, Breast Neoplasms, White adipose tissue, Article, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Breast cancer, Internal medicine, Adipocyte, medicine, Humans, Obesity, education, Aged, Retrospective Studies, Aged, 80 and over, Inflammation, education.field_of_study, business.industry, Hispanic or Latino, Middle Aged, medicine.disease, Prognosis, 030104 developmental biology, chemistry, 030220 oncology & carcinogenesis, Female, business, Body mass index, Mastectomy, Follow-Up Studies
Abstract

Breast white adipose tissue inflammation (BWATi) is associated with obesity and higher breast cancer risk among non-Hispanic white women. Obesity is prevalent in Hispanic/Latina patients with breast cancer, and the occurrence of BWATi in this population is not well-characterized. The association between BWATi and body mass index (BMI) was evaluated in Hispanic/Latina patients with breast cancer who underwent mastectomy. BWATi was defined as the presence of crown-like structures of the breast (CLS-B), detected by CD68 IHC in nontumor breast tissue. BWATi severity was quantified as number of CLS-B/cm2. Adipocyte diameter was measured using hematoxylin and eosin-stained breast tissue sections. Preoperative BMI (within 1 week prior to mastectomy) was categorized as normal (18.5–0.27 CLS-B/cm2) was associated with higher BMI (Ptrend = 0.046) and greater adipocyte diameter (P = 0.04). Adjusting for BMI, neoadjuvant chemotherapy, and elevated alanine aminotransferase were associated with severe BWATi, and current smoking was associated with mild BWATi (all P < 0.05). BWATi was associated with higher BMI in Hispanic/Latina patients with breast cancer, consistent with previously described associations in other populations.

Published
2018

48. Pre-Surgical Trial of the AKT inhibitor MK-2206 in patients with operable invasive breast cancer: A New York Cancer Consortium Trial

Author

Sheldon Feldman, Shing Mirn Lee, Katherine D. Crew, Douglas K. Marks, Prabhjot S. Mundi, P Ananthakrishnan, A. Ahmad, Matthew A. Maurer, Anthony N. Sireci, Dawn L. Hershman, J. R. Cross, Kevin Kalinsky, Serge Cremers, Bret Taback, Hanina Hibshoosh, Lisa S. Wiechmann, Xiaobo Zhong, Eileen P. Connolly, Eleni Andreopoulou, and Joseph A. Sparano

Subjects
0301 basic medicine, Oncology, Adult, Cancer Research, medicine.medical_specialty, Population, New York, Breast Neoplasms, Article, 03 medical and health sciences, chemistry.chemical_compound, Phosphatidylinositol 3-Kinases, 0302 clinical medicine, Breast cancer, Internal medicine, medicine, Clinical endpoint, Mucositis, Humans, education, PI3K/AKT/mTOR pathway, Aged, Neoplasm Staging, education.field_of_study, business.industry, Carcinoma, Ductal, Breast, Cancer, General Medicine, Middle Aged, medicine.disease, 030104 developmental biology, Editorial, chemistry, Tolerability, 030220 oncology & carcinogenesis, MK-2206, Drug Evaluation, Female, business, Heterocyclic Compounds, 3-Ring, Proto-Oncogene Proteins c-akt, Biomarkers, Signal Transduction
Abstract

INTRODUCTION: The PI3K/AKT/mTOR pathway is an oncogenic driver in breast cancer (BC). In this multi-center, pre-surgical study, we evaluated the tissue effects of the AKT inhibitor MK-2206 in women with stage I–III BC. MATERIALS AND METHODS: Two doses of weekly oral MK2206 were administered at days -9 and -2 before surgery. The primary endpoint was reduction of pAkt(Ser473) in breast tumor tissue from diagnostic biopsy to surgery. Secondary endpoints included changes in PI3K/AKT pathway tumor markers, tumor proliferation (ki-67), insulin-growth factor pathway blood markers, pharmacokinetics (PK), genomics, and MK-2206 tolerability. Paired-t tests were used to compare biomarker changes in pre- and post-MK-2206, and two-sample t-tests to compare with prospectively accrued untreated controls. RESULTS: Despite dose reductions, the trial was discontinued after 12 patients due to grade III rash, mucositis, and pruritus. While there was a trend to reduction in pAKT after MK-2206 (p=0.06), there was no significant change compared to controls (n=5, p=0.65). After MK-2206, no significant changes in ki-67, pS6, PTEN, or stathmin were observed. There was no significant association between dose level and PK (p=0.11). Compared to controls, MK-2206 significantly increased serum glucose (p=0.02), insulin (p

Published
2018

49. A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples

Author

Han Chen, Chunyan Li, Xinxin Peng, Zhicheng Zhou, John N. Weinstein, Han Liang, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Carolyn M. Hutter, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, Gad Getz, David I. Heiman, Jaegil Kim, Michael S. Lawrence, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Vesteinn Thorsson, Wei Zhang, Rehan Akbani, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Shiyun Ling, Wenbin Liu, Yiling Lu, Gordon B. Mills, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, Jiexin Zhang, Adam Abeshouse, Joshua Armenia, Debyani Chakravarty, Walid K. Chatila, Ino de Bruijn, Jianjiong Gao, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Konnor La, Marc Ladanyi, Augustin Luna, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Francisco Sanchez-Vega, Chris Sander, Nikolaus Schultz, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Joshua M. Stuart, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Andrew D. Cherniack, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Katherine A. Hoadley, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Peter W. Laird, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, David A. Wheeler, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Li Ding, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Maciej Wiznerowicz, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Houtan Noushmehr, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Alexander J. 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Seder, Kerstin Junker, Larsson Omberg, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. 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Aredes, Armaz Mariamidze, Chen H., Li C., Peng X., Zhou Z., Weinstein J.N., Caesar-Johnson S.J., Demchok J.A., Felau I., Kasapi M., Ferguson M.L., Hutter C.M., Sofia H.J., Tarnuzzer R., Wang Z., Yang L., Zenklusen J.C., Zhang J.J., Chudamani S., Liu J., Lolla L., Naresh R., Pihl T., Sun Q., Wan Y., Wu Y., Cho J., DeFreitas T., Frazer S., Gehlenborg N., Getz G., Heiman D.I., Kim J., Lawrence M.S., Lin P., Meier S., Noble M.S., Saksena G., Voet D., Zhang H., Bernard B., Chambwe N., Dhankani V., Knijnenburg T., Kramer R., Leinonen K., Liu Y., Miller M., Reynolds S., Shmulevich I., Thorsson V., Zhang W., Akbani R., Broom B.M., Hegde A.M., Ju Z., Kanchi R.S., Korkut A., Li J., Liang H., Ling S., Liu W., Lu Y., Mills G.B., Ng K.-S., Rao A., Ryan M., Wang J., Zhang J., Abeshouse A., Armenia J., Chakravarty D., Chatila W.K., de Bruijn I., Gao J., Gross B.E., Heins Z.J., Kundra R., La K., Ladanyi M., Luna A., Nissan M.G., Ochoa A., Phillips S.M., Reznik E., Sanchez-Vega F., Sander C., Schultz 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H., Zhou W., Bellair M., Chang K., Covington K., Creighton C.J., Dinh H., Doddapaneni H., Donehower L.A., Drummond J., Gibbs R.A., Glenn R., Hale W., Han Y., Hu J., Korchina V., Lee S., Lewis L., Li W., Liu X., Morgan M., Morton D., Muzny D., Santibanez J., Sheth M., Shinbrot E., Wang L., Wang M., Wheeler D.A., Xi L., Zhao F., Hess J., Appelbaum E.L., Bailey M., Cordes M.G., Ding L., Fronick C.C., Fulton L.A., Fulton R.S., Kandoth C., Mardis E.R., McLellan M.D., Miller C.A., Schmidt H.K., Wilson R.K., Crain D., Curley E., Gardner J., Lau K., Mallery D., Morris S., Paulauskis J., Penny R., Shelton C., Shelton T., Sherman M., Thompson E., Yena P., Bowen J., Gastier-Foster J.M., Gerken M., Leraas K.M., Lichtenberg T.M., Ramirez N.C., Wise L., Zmuda E., Corcoran N., Costello T., Hovens C., Carvalho A.L., de Carvalho A.C., Fregnani J.H., Longatto-Filho A., Reis R.M., Scapulatempo-Neto C., Silveira H.C.S., Vidal D.O., Burnette A., Eschbacher J., Hermes B., Noss A., Singh R., Anderson M.L., 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Subjects
Genetics and Molecular Biology (all), 0301 basic medicine, pan-cancer analysis, Cancer Genome Atlas Research Network, PD-L1 expression, medicine.disease_cause, Genome, Biochemistry, B7-H1 Antigen, Neoplasms, Databases, Genetic, LS2_1, LS4_6, CLASS DISCOVERY, 610 Medicine & health, 11 Medical and Health Sciences, GENE-EXPRESSION, Regulation of gene expression, Mutation, TRANSCRIPTIONAL ENHANCERS, Chromatin, GENOME, Gene Expression Regulation, Neoplastic, Survival Rate, enhancer expression, Enhancer Elements, Genetic, MAP, Immunotherapy, Life Sciences & Biomedicine, pan-cancer analysi, Biochemistry & Molecular Biology, aneuploidy, chromatin state, mutation burden, prognostic markers, The Cancer Genome Atlas, Biochemistry, Genetics and Molecular Biology (all), ORGANIZATION, Computational biology, Biology, General Biochemistry, Genetics and Molecular Biology, Article, NO, 03 medical and health sciences, medicine, Humans, Enhancer, Gene, Science & Technology, LANDSCAPE, IDENTIFICATION, Sequence Analysis, RNA, Biochemistry, Genetics and Molecular Biology(all), Cancer, Cell Biology, 06 Biological Sciences, medicine.disease, SUPER-ENHANCERS, 030104 developmental biology, PRINCIPLES, Expression quantitative trait loci, CROMATINA, prognostic marker, Developmental Biology, Genetics and Molecular Biology(all)
Abstract

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on “chromatin-state” to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers. Causal enhancer-target-gene relationships are inferred from a systematic analysis of 33 cancer types.

Published
2018

50. Comprehensive Characterization of Cancer Driver Genes and Mutations

Author

Matthew H. Bailey, Collin Tokheim, Eduard Porta-Pardo, Sohini Sengupta, Denis Bertrand, Amila Weerasinghe, Antonio Colaprico, Michael C. Wendl, Jaegil Kim, Brendan Reardon, Patrick Kwok-Shing Ng, Kang Jin Jeong, Song Cao, Zixing Wang, Jianjiong Gao, Qingsong Gao, Fang Wang, Eric Minwei Liu, Loris Mularoni, Carlota Rubio-Perez, Niranjan Nagarajan, Isidro Cortés-Ciriano, Daniel Cui Zhou, Wen-Wei Liang, Julian M. Hess, Venkata D. Yellapantula, David Tamborero, Abel Gonzalez-Perez, Chayaporn Suphavilai, Jia Yu Ko, Ekta Khurana, Peter J. Park, Eliezer M. Van Allen, Han Liang, Michael S. Lawrence, Adam Godzik, Nuria Lopez-Bigas, Josh Stuart, David Wheeler, Gad Getz, Ken Chen, Alexander J. Lazar, Gordon B. Mills, Rachel Karchin, Li Ding, Samantha J. Caesar-Johnson, John A. Demchok, Ina Felau, Melpomeni Kasapi, Martin L. Ferguson, Carolyn M. Hutter, Heidi J. Sofia, Roy Tarnuzzer, Zhining Wang, Liming Yang, Jean C. Zenklusen, Jiashan (Julia) Zhang, Sudha Chudamani, Jia Liu, Laxmi Lolla, Rashi Naresh, Todd Pihl, Qiang Sun, Yunhu Wan, Ye Wu, Juok Cho, Timothy DeFreitas, Scott Frazer, Nils Gehlenborg, David I. Heiman, Pei Lin, Sam Meier, Michael S. Noble, Gordon Saksena, Doug Voet, Hailei Zhang, Brady Bernard, Nyasha Chambwe, Varsha Dhankani, Theo Knijnenburg, Roger Kramer, Kalle Leinonen, Yuexin Liu, Michael Miller, Sheila Reynolds, Ilya Shmulevich, Vesteinn Thorsson, Wei Zhang, Rehan Akbani, Bradley M. Broom, Apurva M. Hegde, Zhenlin Ju, Rupa S. Kanchi, Anil Korkut, Jun Li, Shiyun Ling, Wenbin Liu, Yiling Lu, Kwok-Shing Ng, Arvind Rao, Michael Ryan, Jing Wang, John N. Weinstein, Jiexin Zhang, Adam Abeshouse, Joshua Armenia, Debyani Chakravarty, Walid K. Chatila, Ino de Bruijn, Benjamin E. Gross, Zachary J. Heins, Ritika Kundra, Konnor La, Marc Ladanyi, Augustin Luna, Moriah G. Nissan, Angelica Ochoa, Sarah M. Phillips, Ed Reznik, Francisco Sanchez-Vega, Chris Sander, Nikolaus Schultz, Robert Sheridan, S. Onur Sumer, Yichao Sun, Barry S. Taylor, Jioajiao Wang, Hongxin Zhang, Pavana Anur, Myron Peto, Paul Spellman, Christopher Benz, Joshua M. Stuart, Christopher K. Wong, Christina Yau, D. Neil Hayes, Joel S. Parker, Matthew D. Wilkerson, Adrian Ally, Miruna Balasundaram, Reanne Bowlby, Denise Brooks, Rebecca Carlsen, Eric Chuah, Noreen Dhalla, Robert Holt, Steven J.M. Jones, Katayoon Kasaian, Darlene Lee, Yussanne Ma, Marco A. Marra, Michael Mayo, Richard A. Moore, Andrew J. Mungall, Karen Mungall, A. Gordon Robertson, Sara Sadeghi, Jacqueline E. Schein, Payal Sipahimalani, Angela Tam, Nina Thiessen, Kane Tse, Tina Wong, Ashton C. Berger, Rameen Beroukhim, Andrew D. Cherniack, Carrie Cibulskis, Stacey B. Gabriel, Galen F. Gao, Gavin Ha, Matthew Meyerson, Steven E. Schumacher, Juliann Shih, Melanie H. Kucherlapati, Raju S. Kucherlapati, Stephen Baylin, Leslie Cope, Ludmila Danilova, Moiz S. Bootwalla, Phillip H. Lai, Dennis T. Maglinte, David J. Van Den Berg, Daniel J. Weisenberger, J. Todd Auman, Saianand Balu, Tom Bodenheimer, Cheng Fan, Katherine A. Hoadley, Alan P. Hoyle, Stuart R. Jefferys, Corbin D. Jones, Shaowu Meng, Piotr A. Mieczkowski, Lisle E. Mose, Amy H. Perou, Charles M. Perou, Jeffrey Roach, Yan Shi, Janae V. Simons, Tara Skelly, Matthew G. Soloway, Donghui Tan, Umadevi Veluvolu, Huihui Fan, Toshinori Hinoue, Peter W. Laird, Hui Shen, Wanding Zhou, Michelle Bellair, Kyle Chang, Kyle Covington, Chad J. Creighton, Huyen Dinh, HarshaVardhan Doddapaneni, Lawrence A. Donehower, Jennifer Drummond, Richard A. Gibbs, Robert Glenn, Walker Hale, Yi Han, Jianhong Hu, Viktoriya Korchina, Sandra Lee, Lora Lewis, Wei Li, Xiuping Liu, Margaret Morgan, Donna Morton, Donna Muzny, Jireh Santibanez, Margi Sheth, Eve Shinbrot, Linghua Wang, Min Wang, David A. Wheeler, Liu Xi, Fengmei Zhao, Julian Hess, Elizabeth L. Appelbaum, Matthew Bailey, Matthew G. Cordes, Catrina C. Fronick, Lucinda A. Fulton, Robert S. Fulton, Cyriac Kandoth, Elaine R. Mardis, Michael D. McLellan, Christopher A. Miller, Heather K. Schmidt, Richard K. Wilson, Daniel Crain, Erin Curley, Johanna Gardner, Kevin Lau, David Mallery, Scott Morris, Joseph Paulauskis, Robert Penny, Candace Shelton, Troy Shelton, Mark Sherman, Eric Thompson, Peggy Yena, Jay Bowen, Julie M. Gastier-Foster, Mark Gerken, Kristen M. Leraas, Tara M. Lichtenberg, Nilsa C. Ramirez, Lisa Wise, Erik Zmuda, Niall Corcoran, Tony Costello, Christopher Hovens, Andre L. Carvalho, Ana C. de Carvalho, José H. Fregnani, Adhemar Longatto-Filho, Rui M. Reis, Cristovam Scapulatempo-Neto, Henrique C.S. Silveira, Daniel O. Vidal, Andrew Burnette, Jennifer Eschbacher, Beth Hermes, Ardene Noss, Rosy Singh, Matthew L. Anderson, Patricia D. Castro, Michael Ittmann, David Huntsman, Bernard Kohl, Xuan Le, Richard Thorp, Chris Andry, Elizabeth R. Duffy, Vladimir Lyadov, Oxana Paklina, Galiya Setdikova, Alexey Shabunin, Mikhail Tavobilov, Christopher McPherson, Ronald Warnick, Ross Berkowitz, Daniel Cramer, Colleen Feltmate, Neil Horowitz, Adam Kibel, Michael Muto, Chandrajit P. Raut, Andrei Malykh, Jill S. Barnholtz-Sloan, Wendi Barrett, Karen Devine, Jordonna Fulop, Quinn T. Ostrom, Kristen Shimmel, Yingli Wolinsky, Andrew E. Sloan, Agostino De Rose, Felice Giuliante, Marc Goodman, Beth Y. Karlan, Curt H. Hagedorn, John Eckman, Jodi Harr, Jerome Myers, Kelinda Tucker, Leigh Anne Zach, Brenda Deyarmin, Hai Hu, Leonid Kvecher, Caroline Larson, Richard J. Mural, Stella Somiari, Ales Vicha, Tomas Zelinka, Joseph Bennett, Mary Iacocca, Brenda Rabeno, Patricia Swanson, Mathieu Latour, Louis Lacombe, Bernard Têtu, Alain Bergeron, Mary McGraw, Susan M. Staugaitis, John Chabot, Hanina Hibshoosh, Antonia Sepulveda, Tao Su, Timothy Wang, Olga Potapova, Olga Voronina, Laurence Desjardins, Odette Mariani, Sergio Roman-Roman, Xavier Sastre, Marc-Henri Stern, Feixiong Cheng, Sabina Signoretti, Andrew Berchuck, Darell Bigner, Eric Lipp, Jeffrey Marks, Shannon McCall, Roger McLendon, Angeles Secord, Alexis Sharp, Madhusmita Behera, Daniel J. Brat, Amy Chen, Keith Delman, Seth Force, Fadlo Khuri, Kelly Magliocca, Shishir Maithel, Jeffrey J. Olson, Taofeek Owonikoko, Alan Pickens, Suresh Ramalingam, Dong M. Shin, Gabriel Sica, Erwin G. Van Meir, Hongzheng Zhang, Wil Eijckenboom, Ad Gillis, Esther Korpershoek, Leendert Looijenga, Wolter Oosterhuis, Hans Stoop, Kim E. van Kessel, Ellen C. Zwarthoff, Chiara Calatozzolo, Lucia Cuppini, Stefania Cuzzubbo, Francesco DiMeco, Gaetano Finocchiaro, Luca Mattei, Alessandro Perin, Bianca Pollo, Chu Chen, John Houck, Pawadee Lohavanichbutr, Arndt Hartmann, Christine Stoehr, Robert Stoehr, Helge Taubert, Sven Wach, Bernd Wullich, Witold Kycler, Dawid Murawa, Maciej Wiznerowicz, Ki Chung, W. Jeffrey Edenfield, Julie Martin, Eric Baudin, Glenn Bubley, Raphael Bueno, Assunta De Rienzo, William G. Richards, Steven Kalkanis, Tom Mikkelsen, Houtan Noushmehr, Lisa Scarpace, Nicolas Girard, Marta Aymerich, Elias Campo, Eva Giné, Armando López Guillermo, Nguyen Van Bang, Phan Thi Hanh, Bui Duc Phu, Yufang Tang, Howard Colman, Kimberley Evason, Peter R. Dottino, John A. Martignetti, Hani Gabra, Hartmut Juhl, Teniola Akeredolu, Serghei Stepa, Dave Hoon, Keunsoo Ahn, Koo Jeong Kang, Felix Beuschlein, Anne Breggia, Michael Birrer, Debra Bell, Mitesh Borad, Alan H. Bryce, Erik Castle, Vishal Chandan, John Cheville, John A. Copland, Michael Farnell, Thomas Flotte, Nasra Giama, Thai Ho, Michael Kendrick, Jean-Pierre Kocher, Karla Kopp, Catherine Moser, David Nagorney, Daniel O’Brien, Brian Patrick O’Neill, Tushar Patel, Gloria Petersen, Florencia Que, Michael Rivera, Lewis Roberts, Robert Smallridge, Thomas Smyrk, Melissa Stanton, R. Houston Thompson, Michael Torbenson, Ju Dong Yang, Lizhi Zhang, Fadi Brimo, Jaffer A. Ajani, Ana Maria Angulo Gonzalez, Carmen Behrens, Jolanta Bondaruk, Russell Broaddus, Bogdan Czerniak, Bita Esmaeli, Junya Fujimoto, Jeffrey Gershenwald, Charles Guo, Christopher Logothetis, Funda Meric-Bernstam, Cesar Moran, Lois Ramondetta, David Rice, Anil Sood, Pheroze Tamboli, Timothy Thompson, Patricia Troncoso, Anne Tsao, Ignacio Wistuba, Candace Carter, Lauren Haydu, Peter Hersey, Valerie Jakrot, Hojabr Kakavand, Richard Kefford, Kenneth Lee, Georgina Long, Graham Mann, Michael Quinn, Robyn Saw, Richard Scolyer, Kerwin Shannon, Andrew Spillane, Jonathan Stretch, Maria Synott, John Thompson, James Wilmott, Hikmat Al-Ahmadie, Timothy A. Chan, Ronald Ghossein, Anuradha Gopalan, Douglas A. Levine, Victor Reuter, Samuel Singer, Bhuvanesh Singh, Nguyen Viet Tien, Thomas Broudy, Cyrus Mirsaidi, Praveen Nair, Paul Drwiega, Judy Miller, Jennifer Smith, Howard Zaren, Joong-Won Park, Nguyen Phi Hung, Electron Kebebew, W. Marston Linehan, Adam R. Metwalli, Karel Pacak, Peter A. Pinto, Mark Schiffman, Laura S. Schmidt, Cathy D. Vocke, Nicolas Wentzensen, Robert Worrell, Hannah Yang, Marc Moncrieff, Chandra Goparaju, Jonathan Melamed, Harvey Pass, Natalia Botnariuc, Irina Caraman, Mircea Cernat, Inga Chemencedji, Adrian Clipca, Serghei Doruc, Ghenadie Gorincioi, Sergiu Mura, Maria Pirtac, Irina Stancul, Diana Tcaciuc, Monique Albert, Iakovina Alexopoulou, Angel Arnaout, John Bartlett, Jay Engel, Sebastien Gilbert, Jeremy Parfitt, Harman Sekhon, George Thomas, Doris M. Rassl, Robert C. Rintoul, Carlo Bifulco, Raina Tamakawa, Walter Urba, Nicholas Hayward, Henri Timmers, Anna Antenucci, Francesco Facciolo, Gianluca Grazi, Mirella Marino, Roberta Merola, Ronald de Krijger, Anne-Paule Gimenez-Roqueplo, Alain Piché, Simone Chevalier, Ginette McKercher, Kivanc Birsoy, Gene Barnett, Cathy Brewer, Carol Farver, Theresa Naska, Nathan A. Pennell, Daniel Raymond, Cathy Schilero, Kathy Smolenski, Felicia Williams, Carl Morrison, Jeffrey A. Borgia, Michael J. Liptay, Mark Pool, Christopher W. Seder, Kerstin Junker, Larsson Omberg, Mikhail Dinkin, George Manikhas, Domenico Alvaro, Maria Consiglia Bragazzi, Vincenzo Cardinale, Guido Carpino, Eugenio Gaudio, David Chesla, Sandra Cottingham, Michael Dubina, Fedor Moiseenko, Renumathy Dhanasekaran, Karl-Friedrich Becker, Klaus-Peter Janssen, Julia Slotta-Huspenina, Mohamed H. Abdel-Rahman, Dina Aziz, Sue Bell, Colleen M. Cebulla, Amy Davis, Rebecca Duell, J. Bradley Elder, Joe Hilty, Bahavna Kumar, James Lang, Norman L. Lehman, Randy Mandt, Phuong Nguyen, Robert Pilarski, Karan Rai, Lynn Schoenfield, Kelly Senecal, Paul Wakely, Paul Hansen, Ronald Lechan, James Powers, Arthur Tischler, William E. Grizzle, Katherine C. Sexton, Alison Kastl, Joel Henderson, Sima Porten, Jens Waldmann, Martin Fassnacht, Sylvia L. Asa, Dirk Schadendorf, Marta Couce, Markus Graefen, Hartwig Huland, Guido Sauter, Thorsten Schlomm, Ronald Simon, Pierre Tennstedt, Oluwole Olabode, Mark Nelson, Oliver Bathe, Peter R. Carroll, June M. Chan, Philip Disaia, Pat Glenn, Robin K. Kelley, Charles N. Landen, Joanna Phillips, Michael Prados, Jeffry Simko, Karen Smith-McCune, Scott VandenBerg, Kevin Roggin, Ashley Fehrenbach, Ady Kendler, Suzanne Sifri, Ruth Steele, Antonio Jimeno, Francis Carey, Ian Forgie, Massimo Mannelli, Michael Carney, Brenda Hernandez, Benito Campos, Christel Herold-Mende, Christin Jungk, Andreas Unterberg, Andreas von Deimling, Aaron Bossler, Joseph Galbraith, Laura Jacobus, Michael Knudson, Tina Knutson, Deqin Ma, Mohammed Milhem, Rita Sigmund, Andrew K. Godwin, Rashna Madan, Howard G. Rosenthal, Clement Adebamowo, Sally N. Adebamowo, Alex Boussioutas, David Beer, Thomas Giordano, Anne-Marie Mes-Masson, Fred Saad, Therese Bocklage, Lisa Landrum, Robert Mannel, Kathleen Moore, Katherine Moxley, Russel Postier, Joan Walker, Rosemary Zuna, Michael Feldman, Federico Valdivieso, Rajiv Dhir, James Luketich, Edna M. Mora Pinero, Mario Quintero-Aguilo, Carlos Gilberto Carlotti, Jose Sebastião Dos Santos, Rafael Kemp, Ajith Sankarankuty, Daniela Tirapelli, James Catto, Kathy Agnew, Elizabeth Swisher, Jenette Creaney, Bruce Robinson, Carl Simon Shelley, Eryn M. Godwin, Sara Kendall, Cassaundra Shipman, Carol Bradford, Thomas Carey, Andrea Haddad, Jeffey Moyer, Lisa Peterson, Mark Prince, Laura Rozek, Gregory Wolf, Rayleen Bowman, Kwun M. Fong, Ian Yang, Robert Korst, W. Kimryn Rathmell, J. Leigh Fantacone-Campbell, Jeffrey A. Hooke, Albert J. Kovatich, Craig D. Shriver, John DiPersio, Bettina Drake, Ramaswamy Govindan, Sharon Heath, Timothy Ley, Brian Van Tine, Peter Westervelt, Mark A. Rubin, Jung Il Lee, Natália D. 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Subjects
0301 basic medicine, Oncology, Entropy, Programmed Cell Death 1 Receptor, biochemistry, genetics, molecular Biology (all), Biochemistry, B7-H1 Antigen, structure analysi, Principal Component Analysi, Neoplasms, Databases, Genetic, LS2_1, LS4_6, Missense mutation, Statistical analysis, 610 Medicine & health, Exome sequencing, Confusion, Principal Component Analysis, Melanoma, Sciences bio-médicales et agricoles, structure analysis, Algorithm, oncology, Cancer gene, Adenocarcinoma, Microsatellite Instability, ALGORITMOS, medicine.symptom, Algorithms, Human, medicine.medical_specialty, driver gene discovery, Computational biology, Biology, Characterization (mathematics), General Biochemistry, Genetics and Molecular Biology, Article, NO, 03 medical and health sciences, Internal medicine, medicine, Humans, mutations of clinical relevance, Gene, Biochemistry, Genetics and Molecular Biology(all), Microsatellite instability, Computational Biology, Cancer, medicine.disease, Cancérologie, 030104 developmental biology, Precision oncology, Mutation, Neoplasm, Human genome, Colon adenocarcinoma, human activities, Genetics and Molecular Biology(all)
Abstract

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%–85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors. A comprehensive analysis of oncogenic driver genes and mutations in >9,000 tumors across 33 cancer types highlights the prevalence of clinically actionable cancer driver events in TCGA tumor samples., 0, info:eu-repo/semantics/published

Published
2018

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