254 results on '"Beatrice S. Knudsen"'
Search Results
2. Predicting IHC staining classes of NF1 using features in the hematoxylin channel
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Wei Zhang, Mei Yee Koh, Deepika Sirohi, Jian Ying, Ben J. Brintz, and Beatrice S. Knudsen
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QuPath ,CytoMap ,Kidney cancer ,Prediction ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Pathology ,RB1-214 - Abstract
Immunohistochemistry (IHC) highlights specific cell types in tissues and traditionally involves antibody staining together with a hematoxylin counterstain. The intensity and pattern of hematoxylin staining differs between cell types and reveals morphological characteristics of cells. Here, we propose that features in the hematoxylin stain can be used to predict IHC labels, such as Neurofibromin (encoded by the gene NF1). The dataset consists of 7.2 million cells from benign and kidney cancer cores in a tissue microarray. Morphology and hematoxylin (H&M) features defined within QuPath are subjected to a clustering analysis in CytoMap. H&M features are also used to train 4 different XGBoost models to predict high, low, and negative NF1 stain classes in benign renal tubules, clear cell (ccRCC), papillary (PRCC), and chromophobe (ChRCC) renal carcinoma. The prediction accuracies of NF1 staining classes in benign, ccRCC, ChRCC, and PRCC range between 70% and 90% with areas under the precision recall curve PRAUCNF1-high = 0.82+0.12, PRAUCNF1-low = 0.62+0.25, and PRAUCNF1-negative = 0.83+0.16. The most important feature for predicting the NF1 class involves the minimum cellular hematoxylin staining intensity. Together, these results demonstrate the feasibility to predict NF1 expression solely from features in hematoxylin staining using open source software. Since the hematoxylin features can be obtained from regular H&E and IHC slides, the proposed workflow has broad applicability.
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- 2023
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3. Publisher Correction to: Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images
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Danielle J. Fassler, Shahira Abousamra, Rajarsi Gupta, Chao Chen, Maozheng Zhao, David Paredes, Syeda Areeha Batool, Beatrice S. Knudsen, Luisa Escobar-Hoyos, Kenneth R. Shroyer, Dimitris Samaras, Tahsin Kurc, and Joel Saltz
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Pathology ,RB1-214 - Abstract
An amendment to this paper has been published and can be accessed via the original article.
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- 2020
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4. Mutant POLQ and POLZ/REV3L DNA polymerases may contribute to the favorable survival of patients with tumors with POLE mutations outside the exonuclease domain
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Fangjin Huang, Hisashi Tanaka, Beatrice S. Knudsen, and Joanne K. Rutgers
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Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background Mutations in the exonuclease domain of POLE, a DNA polymerase associated with DNA replication and repair, lead to cancers with ultra-high mutation rates. Most studies focus on intestinal and uterine cancers with POLE mutations. These cancers exhibit a significant immune cell infiltrate and favorable prognosis. We questioned whether loss of function of other DNA polymerases can cooperate to POLE to generate the ultramutator phenotype. Methods We used cases and data from 15 cancer types in The Cancer Genome Atlas to investigate mutation frequencies of 14 different DNA polymerases. We tested whether tumor mutation burden, patient outcome (disease-free survival) and immune cell infiltration measured by ESTIMATE can be attributed to mutations in POLQ and POLZ/REV3L. Results Thirty six percent of colorectal, stomach and endometrial cancers with POLE mutations carried additional mutations in POLQ (E/Q), POLZ/REV3L (E/Z) or both DNA polymerases (E/Z/Q). The mutation burden in these tumors was significantly greater compared to POLE-only (E) mutant tumors (p
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- 2020
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5. Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images
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Danielle J. Fassler, Shahira Abousamra, Rajarsi Gupta, Chao Chen, Maozheng Zhao, David Paredes, Syeda Areeha Batool, Beatrice S. Knudsen, Luisa Escobar-Hoyos, Kenneth R. Shroyer, Dimitris Samaras, Tahsin Kurc, and Joel Saltz
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Multiplex immunohistochemistry ,Digital pathology image analysis ,Deep learning ,Tumor immune microenvironment ,Pathology ,RB1-214 - Abstract
Abstract Background Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel. Methods Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and ensemble methods that employ both ColorAE and U-Net, collectively referred to as (3) ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor). Results We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect 6 different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net into ensemble methods outperform using either ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). Summary We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also present a use case, wherein we apply the ColorAE:U-Net ensemble method across 3 mIHC WSIs and use the predictions to quantify all stained cell populations and perform nearest neighbor spatial analysis. Thus, we provide proof of concept that these methods can be employed to quantitatively describe the spatial distribution immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.
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- 2020
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6. Chromosomal instability in untreated primary prostate cancer as an indicator of metastatic potential
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Eric T. Miller, Sungyong You, Radu M. Cadaneanu, Minhyung Kim, Junhee Yoon, Sandy T. Liu, Xinmin Li, Lorna Kwan, Jennelle Hodge, Michael J. Quist, Catherine S. Grasso, Michael S. Lewis, Beatrice S. Knudsen, Michael R. Freeman, and Isla P. Garraway
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Prostate cancer ,Metastases ,Chromosomal instability ,CIN ,Prostate needle biopsies ,TCGA ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Background Metastatic prostate cancer (PC) is highly lethal. The ability to identify primary tumors capable of dissemination is an unmet need in the quest to understand lethal biology and improve patient outcomes. Previous studies have linked chromosomal instability (CIN), which generates aneuploidy following chromosomal missegregation during mitosis, to PC progression. Evidence of CIN includes broad copy number alterations (CNAs) spanning > 300 base pairs of DNA, which may also be measured via RNA expression signatures associated with CNA frequency. Signatures of CIN in metastatic PC, however, have not been interrogated or well defined. We examined a published 70-gene CIN signature (CIN70) in untreated and castration-resistant prostate cancer (CRPC) cohorts from The Cancer Genome Atlas (TCGA) and previously published reports. We also performed transcriptome and CNA analysis in a unique cohort of untreated primary tumors collected from diagnostic prostate needle biopsies (PNBX) of localized (M0) and metastatic (M1) cases to determine if CIN was linked to clinical stage and outcome. Methods PNBX were collected from 99 patients treated in the VA Greater Los Angeles (GLA-VA) Healthcare System between 2000 and 2016. Total RNA was extracted from high-grade cancer areas in PNBX cores, followed by RNA sequencing and/or copy number analysis using OncoScan. Multivariate logistic regression analyses permitted calculation of odds ratios for CIN status (high versus low) in an expanded GLA-VA PNBX cohort (n = 121). Results The CIN70 signature was significantly enriched in primary tumors and CRPC metastases from M1 PC cases. An intersection of gene signatures comprised of differentially expressed genes (DEGs) generated through comparison of M1 versus M0 PNBX and primary CRPC tumors versus metastases revealed a 157-gene “metastasis” signature that was further distilled to 7-genes (PC-CIN) regulating centrosomes, chromosomal segregation, and mitotic spindle assembly. High PC-CIN scores correlated with CRPC, PC-death and all-cause mortality in the expanded GLA-VA PNBX cohort. Interestingly, approximately 1/3 of M1 PNBX cases exhibited low CIN, illuminating differential pathways of lethal PC progression. Conclusions Measuring CIN in PNBX by transcriptome profiling is feasible, and the PC-CIN signature may identify patients with a high risk of lethal progression at the time of diagnosis.
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- 2020
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7. A Non-integrating Lentiviral Approach Overcomes Cas9-Induced Immune Rejection to Establish an Immunocompetent Metastatic Renal Cancer Model
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Junhui Hu, Shiruyeh Schokrpur, Maani Archang, Kip Hermann, Allison C. Sharrow, Prateek Khanna, Jesse Novak, Sabina Signoretti, Rupal S. Bhatt, Beatrice S. Knudsen, Hua Xu, and Lily Wu
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Genetics ,QH426-470 ,Cytology ,QH573-671 - Abstract
The CRISPR-based technology has revolutionized genome editing in recent years. This technique allows for gene knockout and evaluation of function in cell lines in a manner that is far easier and more accessible than anything previously available. Unfortunately, the ability to extend these studies to in vivo syngeneic murine cell line implantation is limited by an immune response against cells transduced to stably express Cas9. In this study, we demonstrate that a non-integrating lentiviral vector approach can overcome this immune rejection and allow for the growth of transduced cells in an immunocompetent host. This technique enables the establishment of a von Hippel-Lindau (VHL) gene knockout RENCA cell line in BALB/c mice, generating an improved model of immunocompetent, metastatic renal cell carcinoma (RCC). Keywords: immunocompetent mouse model, ccRCC, RENCA, kidney cancer, CRISPR/Cas9, non-integrated lentivirus, immunotherapy
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- 2018
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8. A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome
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Nathan Ing, Fangjin Huang, Andrew Conley, Sungyong You, Zhaoxuan Ma, Sergey Klimov, Chisato Ohe, Xiaopu Yuan, Mahul B. Amin, Robert Figlin, Arkadiusz Gertych, and Beatrice S. Knudsen
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Medicine ,Science - Abstract
Abstract Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a spatially informed, prognostic gene signature. The trained algorithms classify endothelial cells and generate a vascular area mask (VAM) in H&E micrographs of clear cell renal cell carcinoma (ccRCC) cases from The Cancer Genome Atlas (TCGA). Quantification of VAMs led to the discovery of 9 vascular features (9VF) that predicted disease-free-survival in a discovery cohort (n = 64, HR = 2.3). Correlation analysis and information gain identified a 14 gene expression signature related to the 9VF’s. Two generalized linear models with elastic net regularization (14VF and 14GT), based on the 14 genes, separated independent cohorts of up to 301 cases into good and poor disease-free survival groups (14VF HR = 2.4, 14GT HR = 3.33). For the first time, we successfully applied digital image analysis and targeted machine learning to develop prognostic, morphology-based, gene expression signatures from the vascular architecture. This novel morphogenomic approach has the potential to improve previous methods for biomarker development.
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- 2017
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9. Data integration from pathology slides for quantitative imaging of multiple cell types within the tumor immune cell infiltrate
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Zhaoxuan Ma, Stephen L. Shiao, Emi J. Yoshida, Steven Swartwood, Fangjin Huang, Michael E. Doche, Alice P. Chung, Beatrice S. Knudsen, and Arkadiusz Gertych
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Quantitative imaging ,Tumor immune infiltrate ,Immunohistochemistry ,Image analysis ,Breast cancer ,Pathology ,RB1-214 - Abstract
Abstract Background Immune cell infiltrates (ICI) of tumors are scored by pathologists around tumor glands. To obtain a better understanding of the immune infiltrate, individual immune cell types, their activation states and location relative to tumor cells need to be determined. This process requires precise identification of the tumor area and enumeration of immune cell subtypes separately in the stroma and inside tumor nests. Such measurements can be accomplished by a multiplex format using immunohistochemistry (IHC). Method We developed a pipeline that combines immunohistochemistry (IHC) and digital image analysis. One slide was stained with pan-cytokeratin and CD45 and the other slide with CD8, CD4 and CD68. The tumor mask generated through pan-cytokeratin staining was transferred from one slide to the other using affine image co-registration. Bland-Altman plots and Pearson correlation were used to investigate differences between densities and counts of immune cell underneath the transferred versus manually annotated tumor masks. One-way ANOVA was used to compare the mask transfer error for tissues with solid and glandular tumor architecture. Results The overlap between manual and transferred tumor masks ranged from 20%–90% across all cases. The error of transferring the mask was 2- to 4-fold greater in tumor regions with glandular compared to solid growth pattern (p
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- 2017
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10. Spatial Mapping of Myeloid Cells and Macrophages by Multiplexed Tissue Staining
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Joshua Saylor, Zhaoxuan Ma, Helen S. Goodridge, Fangjin Huang, Anne E. Cress, Stephen J. Pandol, Stephen L. Shiao, Adriana C. Vidal, Lily Wu, Nicholas G. Nickols, Arkadiusz Gertych, and Beatrice S. Knudsen
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multiplex ,immunofluorescence ,immunohistochemistry ,macrophage ,myeloid ,spatial profiling ,Immunologic diseases. Allergy ,RC581-607 - Abstract
An array of phenotypically diverse myeloid cells and macrophages (MC&M) resides in the tumor microenvironment, requiring multiplexed detection systems for visualization. Here we report an automated, multiplexed staining approach, named PLEXODY, that consists of five MC&M-related fluorescently-tagged antibodies (anti - CD68, - CD163, - CD206, - CD11b, and - CD11c), and three chromogenic antibodies, reactive with high- and low-molecular weight cytokeratins and CD3, highlighting tumor regions, benign glands and T cells. The staining prototype and image analysis methods which include a pixel/area-based quantification were developed using tissues from inflamed colon and tonsil and revealed a unique tissue-specific composition of 14 MC&M-associated pixel classes. As a proof-of-principle, PLEXODY was applied to three cases of pancreatic, prostate and renal cancers. Across digital images from these cancer types we observed 10 MC&M-associated pixel classes at frequencies greater than 3%. Cases revealed higher frequencies of single positive compared to multi-color pixels and a high abundance of CD68+/CD163+ and CD68+/CD163+/CD206+ pixels. Significantly more CD68+ and CD163+ vs. CD11b+ and CD11c+ pixels were in direct contact with tumor cells and T cells. While the greatest percentage (~70%) of CD68+ and CD163+ pixels was 0–20 microns away from tumor and T cell borders, CD11b+ and CD11c+ pixels were detected up to 240 microns away from tumor/T cell masks. Together, these data demonstrate significant differences in densities and spatial organization of MC&M-associated pixel classes, but surprising similarities between the three cancer types.
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- 2018
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11. Unsupervised Domain Adaptation for Semantic Segmentation Under Target Data Scarcity.
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Tushar Kataria, Beatrice S. Knudsen, and Shireen Y. Elhabian
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- 2024
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12. DuoFormer: Leveraging Hierarchical Visual Representations by Local and Global Attention.
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Xiaoya Tang, Bodong Zhang, Beatrice S. Knudsen, and Tolga Tasdizen
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- 2024
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13. CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification.
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Bodong Zhang, Hamid Manoochehri, Man Minh Ho, Fahimeh Fooladgar, Yosep Chong, Beatrice S. Knudsen, Deepika Sirohi, and Tolga Tasdizen
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- 2023
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14. Contextual Classification of Tumor Growth Patterns in Digital Histology Slides.
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Zaneta Swiderska-Chadaj, Zhaoxuan Ma, Nathan Ing, Tomasz Markiewicz, Malgorzata Lorent, Szczepan Cierniak, Ann E. Walts, Beatrice S. Knudsen, and Arkadiusz Gertych
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- 2019
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15. Semantic Segmentation of Colon Glands in Inflammatory Bowel Disease Biopsies.
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Zhaoxuan Ma, Zaneta Swiderska-Chadaj, Nathan Ing, Hootan Salemi, Dermot P. B. McGovern, Beatrice S. Knudsen, and Arkadiusz Gertych
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- 2018
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16. Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images.
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Wenyuan Li 0001, Jiayun Li, Karthik V. Sarma, King Chung Ho, Shiwen Shen, Beatrice S. Knudsen, Arkadiusz Gertych, and Corey W. Arnold
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- 2019
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17. An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies.
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Jiayun Li, William Speier, King Chung Ho, Karthik V. Sarma, Arkadiusz Gertych, Beatrice S. Knudsen, and Corey W. Arnold
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- 2018
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18. Machine Learning Can Reliably Distinguish Histological Patterns of Micropapillary and Solid Lung Adenocarcinomas.
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Nathan Ing, Sadri Salman, Zhaoxuan Ma, Ann E. Walts, Beatrice S. Knudsen, and Arkadiusz Gertych
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- 2016
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19. An attention-based multi-resolution model for prostate whole slide imageclassification and localization.
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Jiayun Li, Wenyuan Li 0001, Arkadiusz Gertych, Beatrice S. Knudsen, William Speier, and Corey W. Arnold
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- 2019
20. Figure S4 from Novel Regulation of Integrin Trafficking by Rab11-FIP5 in Aggressive Prostate Cancer
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Anne E. Cress, Cindy K. Miranti, Beatrice S. Knudsen, Colm Morrissey, Raymond B. Nagle, Rytis Prekeris, Jaime M.C. Gard, and Lipsa Das
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Supplementary Figure 4. α3 integrin recycled to lamellipodia. Surface α3 integrin was labelled with P1B5 rabbit antibody in adherent DU145 cell monolayer and allowed to internalize for 40 minutes at 37{degree sign}C. Uninternalized label remaining at the cell membrane is detected and blocked from internalization using Alexa 568 conjugated anti-rabbit secondary antibody. P1B5 antibody bound integrin protected inside the cells was allowed to recycle back and subsequently reacted with Alexa 488 conjugated anti-rabbit secondary antibody. (A) Total membrane and internalized intracellular α3 integrin in permeabilized cells shown as control (red). (B) Uninternalized α3 integrin (red) and recycled α3 integrin (green) at 0min, 10min and 40 minutes of recycling and 40min recycling with primaquine (PQ, recycling inhibitor) are shown in merged images with DAPI (blue) stained nucleus (left panel). Middle panel shows only the recycled α3 integrin label in grey. Right panel is magnified images of boxed sections marked for recycled integrin localized at lamellipodia at cell front (white arrows) or at cell- cell locations (closed white triangles) and uninternalized integrin at cell front (open white triangles). Images acquired by deconvolution microscopy and single Z-plane is shown. Bars, 20µm. Images are representative fields of view obtained in 3 independent experiments.
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- 2023
21. Data from Novel Regulation of Integrin Trafficking by Rab11-FIP5 in Aggressive Prostate Cancer
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Anne E. Cress, Cindy K. Miranti, Beatrice S. Knudsen, Colm Morrissey, Raymond B. Nagle, Rytis Prekeris, Jaime M.C. Gard, and Lipsa Das
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The laminin-binding integrins, α3β1 and α6β1, are needed for tumor metastasis and their surface expression is regulated by endocytic recycling. β1 integrins share the Rab11 recycling machinery, but the trafficking of α3β1 and α6β1 are distinct by an unknown mechanism. Using a mouse PDX tumor model containing human metastatic prostate cancer, Rab11 family interacting protein 5 (Rab11-FIP5) was identified as a lead candidate for α6β1 trafficking. Rab11-FIP5 and its membrane-binding domain were required for α6β1 recycling, without affecting the other laminin-binding integrin (i.e., α3β1) or unrelated membrane receptors like CD44, transferrin receptor, or E-cadherin. Depletion of Rab11-FIP5 resulted in the intracellular accumulation of α6β1 in the Rab11 recycling compartment, loss of cell migration on laminin, and an unexpected loss of α6β1 recycling in cell–cell locations. Taken together, these data demonstrate that α6β1 is distinct from α3β1 via Rab11-FIP5 recycling and recycles in an unexpected cell–cell location.Implications: Rab11-FIP5–dependent α6β1 integrin recycling may be selectively targeted to limit migration of prostate cancer cells into laminin-rich tissues. Mol Cancer Res; 16(8); 1319–31. ©2018 AACR.
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- 2023
22. Supplementary Table S3 from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
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The genes in the collection of pathway signatures used in this study.
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- 2023
23. Movie S2 from Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential
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Michael R. Freeman, Dolores Di Vizio, Andries Zijlstra, Edwin M. Posadas, Amy C. Rowat, Hsian-Rong Tseng, Beatrice S. Knudsen, Wei Yang, Hisashi Tanaka, Leland W.K. Chung, Chia-Yi Chu, Mirja Rotinen, Adel Eskaros, Navjot Kaur Gill, Kenneth Steadman, Samantha Morley, Sungyong You, Tatiana Novitskaya, Jie-Fu Chen, and Mariana Reis-Sobreiro
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Nuclear membrane blebbing in amoeboid cells. Time-lapse analysis of DU145 DIAPH3-depleted cells treated with EGF and IL6 (exacerbates amoeboid features (13)) and stained with lipid fluorescent dye CellMask Orange.
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- 2023
24. Supplementary Figure 3 from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
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Correlation of the PCS categories with clinical outcomes in individual cohorts displayed by Kaplan-Meier survival curves.
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- 2023
25. Legends for Supplementary Figures from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
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Legends for Supplementary Figures.
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- 2023
26. Supplementary Figures 1-3 from Differential Gene Expression in Benign Prostate Epithelium of Men with and without Prostate Cancer: Evidence for a Prostate Cancer Field Effect
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Daniel W. Lin, Peter S. Nelson, Lawrence D. True, Robert C. Gentleman, Nolwenn LeMeur, Alan R. Kristal, Ruth F. Dumpit, Ilsa Coleman, Beatrice S. Knudsen, and Michael C. Risk
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PDF file - 668K
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- 2023
27. Supplementary Figure 4 from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
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Selection of the 37-gene panel.
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- 2023
28. Data from Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential
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Michael R. Freeman, Dolores Di Vizio, Andries Zijlstra, Edwin M. Posadas, Amy C. Rowat, Hsian-Rong Tseng, Beatrice S. Knudsen, Wei Yang, Hisashi Tanaka, Leland W.K. Chung, Chia-Yi Chu, Mirja Rotinen, Adel Eskaros, Navjot Kaur Gill, Kenneth Steadman, Samantha Morley, Sungyong You, Tatiana Novitskaya, Jie-Fu Chen, and Mariana Reis-Sobreiro
- Abstract
Abnormalities in nuclear shape are a well-known feature of cancer, but their contribution to malignant progression remains poorly understood. Here, we show that depletion of the cytoskeletal regulator, Diaphanous-related formin 3 (DIAPH3), or the nuclear membrane–associated proteins, lamin A/C, in prostate and breast cancer cells, induces nuclear shape instability, with a corresponding gain in malignant properties, including secretion of extracellular vesicles that contain genomic material. This transformation is characterized by a reduction and/or mislocalization of the inner nuclear membrane protein, emerin. Consistent with this, depletion of emerin evokes nuclear shape instability and promotes metastasis. By visualizing emerin localization, evidence for nuclear shape instability was observed in cultured tumor cells, in experimental models of prostate cancer, in human prostate cancer tissues, and in circulating tumor cells from patients with metastatic disease. Quantitation of emerin mislocalization discriminated cancer from benign tissue and correlated with disease progression in a prostate cancer cohort. Taken together, these results identify emerin as a mediator of nuclear shape stability in cancer and show that destabilization of emerin can promote metastasis.Significance: This study identifies a novel mechanism integrating the control of nuclear structure with the metastatic phenotype, and our inclusion of two types of human specimens (cancer tissues and circulating tumor cells) demonstrates direct relevance to human cancer.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/21/6086/F1.large.jpg. Cancer Res; 78(21); 6086–97. ©2018 AACR.
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- 2023
29. Supplementary Figure legends from Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential
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Michael R. Freeman, Dolores Di Vizio, Andries Zijlstra, Edwin M. Posadas, Amy C. Rowat, Hsian-Rong Tseng, Beatrice S. Knudsen, Wei Yang, Hisashi Tanaka, Leland W.K. Chung, Chia-Yi Chu, Mirja Rotinen, Adel Eskaros, Navjot Kaur Gill, Kenneth Steadman, Samantha Morley, Sungyong You, Tatiana Novitskaya, Jie-Fu Chen, and Mariana Reis-Sobreiro
- Abstract
Emerin deregulation links nuclear shape instability to metastatic potential
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- 2023
30. Data from Differential Gene Expression in Benign Prostate Epithelium of Men with and without Prostate Cancer: Evidence for a Prostate Cancer Field Effect
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Daniel W. Lin, Peter S. Nelson, Lawrence D. True, Robert C. Gentleman, Nolwenn LeMeur, Alan R. Kristal, Ruth F. Dumpit, Ilsa Coleman, Beatrice S. Knudsen, and Michael C. Risk
- Abstract
Background: Several malignancies are known to exhibit a “field effect,” whereby regions beyond tumor boundaries harbor histologic or molecular changes that are associated with cancer. We sought to determine if histologically benign prostate epithelium collected from men with prostate cancer exhibits features indicative of premalignancy or field effect.Experimental Design: Prostate needle biopsies from 15 men with high-grade (Gleason 8-10) prostate cancer and 15 age- and body mass index–matched controls were identified from a biospecimen repository. Benign epithelia from each patient were isolated by laser capture microdissection. RNA was isolated, amplified, and used for microarray hybridization. Quantitative PCR was used to determine the expression of specific genes of interest. Alterations in protein expression were analyzed through immunohistochemistry.Results: Overall patterns of gene expression in microdissected benign prostate-associated benign epithelium (BABE) and cancer-associated benign epithelium (CABE) were similar. Two genes previously associated with prostate cancer, PSMA and SSTR1, were significantly upregulated in the CABE group (false discovery rate ERG, HOXC4, HOXC5, and MME, were also increased in CABE by quantitative reverse transcription-PCR, although other genes commonly altered in prostate cancer were not different between the BABE and CABE samples. The expression of MME and PSMA proteins on immunohistochemistry coincided with their mRNA alterations.Conclusion: Gene expression profiles between benign epithelia of patients with and without prostate cancer are very similar. However, these tissues exhibit differences in the expression levels of several genes previously associated with prostate cancer development or progression. These differences may comprise a field effect and represent early events in carcinogenesis. Clin Cancer Res; 16(22); 5414–23. ©2010 AACR.
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- 2023
31. Supplementary Figures and Table from Emerin Deregulation Links Nuclear Shape Instability to Metastatic Potential
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Michael R. Freeman, Dolores Di Vizio, Andries Zijlstra, Edwin M. Posadas, Amy C. Rowat, Hsian-Rong Tseng, Beatrice S. Knudsen, Wei Yang, Hisashi Tanaka, Leland W.K. Chung, Chia-Yi Chu, Mirja Rotinen, Adel Eskaros, Navjot Kaur Gill, Kenneth Steadman, Samantha Morley, Sungyong You, Tatiana Novitskaya, Jie-Fu Chen, and Mariana Reis-Sobreiro
- Abstract
Emerin deregulation links nuclear shape instability to metastatic potential
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- 2023
32. Supplementary Figure 1 from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
- Abstract
Boxplots depict distinct pathway activities between the subtypes.
- Published
- 2023
33. Supplementary Figure 2 from Integrated Classification of Prostate Cancer Reveals a Novel Luminal Subtype with Poor Outcome
- Author
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Michael R. Freeman, Jayoung Kim, Isla P. Garraway, Edward M. Schaeffer, Ashley E. Ross, Robert B. Den, Eric A. Klein, R. Jeffrey Karnes, Elai Davicioni, Hussam Al-deen Ashab, Mandeep Takhar, Mohammed Alshalalfa, Nicholas Erho, Beatrice S. Knudsen, and Sungyong You
- Abstract
Differential enrichment of a benign prostate specific gene signature.
- Published
- 2023
34. Supplementary Tables 1-4 from Differential Gene Expression in Benign Prostate Epithelium of Men with and without Prostate Cancer: Evidence for a Prostate Cancer Field Effect
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Daniel W. Lin, Peter S. Nelson, Lawrence D. True, Robert C. Gentleman, Nolwenn LeMeur, Alan R. Kristal, Ruth F. Dumpit, Ilsa Coleman, Beatrice S. Knudsen, and Michael C. Risk
- Abstract
PDF file - 105K
- Published
- 2023
35. A Multi-scale U-Net for Semantic Segmentation of Histological Images from Radical Prostatectomies.
- Author
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Jiayun Li, Karthik V. Sarma, King Chung Ho, Arkadiusz Gertych, Beatrice S. Knudsen, and Corey W. Arnold
- Published
- 2017
36. Rapid 3-D delineation of cell nuclei for high-content screening platforms.
- Author
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Arkadiusz Gertych, Zhaoxuan Ma, Jian Tajbakhsh, Adriana Velásquez-Vacca, and Beatrice S. Knudsen
- Published
- 2016
- Full Text
- View/download PDF
37. The Movember Global Action Plan 1 (GAP1): Unique Prostate Cancer Tissue Microarray Resource
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Erickson A, Carlos S. Moreno, Michelle M. Kouspou, Fred Saad, Michael S. Lewis, Onur Ertunc, Adeboye O. Osunkoya, Colm Morrissey, Bigler Sa, Tuomas Mirtti, Anne-Marie Mes-Masson, Stephen J. Freedland, Zhou X, Igor Vidal, Aud Svindland, Larry True, Tracy Jones, Ouellet, Mark Buzza, Wiley K, Tasken Ka, Pekka Taimen, Isla P. Garraway, Ariel H Achtman, Bova Sg, Angelo M. De Marzo, Bruce J. Trock, Dominique Trudel, Berge, Tarja Lamminen, Beatrice S. Knudsen, Tampere University, BioMediTech, and TAYS Cancer Centre
- Subjects
Male ,Oncology ,medicine.medical_specialty ,Epidemiology ,medicine.medical_treatment ,3122 Cancers ,Disease ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,Prostate ,Internal medicine ,medicine ,Humans ,Lymph node ,030304 developmental biology ,Prostatectomy ,0303 health sciences ,Tissue microarray ,business.industry ,medicine.disease ,3. Good health ,Androgen receptor ,Prostatic Neoplasms, Castration-Resistant ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Biomarker (medicine) ,3111 Biomedicine ,business - Abstract
Background: The need to better understand the molecular underpinnings of the heterogeneous outcomes of patients with prostate cancer is a pressing global problem and a key research priority for Movember. To address this, the Movember Global Action Plan 1 Unique tissue microarray (GAP1-UTMA) project constructed a set of unique and richly annotated tissue microarrays (TMA) from prostate cancer samples obtained from multiple institutions across several global locations. Methods: Three separate TMA sets were built that differ by purpose and disease state. Results: The intended use of TMA1 (Primary Matched LN) is to validate biomarkers that help determine which clinically localized prostate cancers with associated lymph node metastasis have a high risk of progression to lethal castration-resistant metastatic disease, and to compare molecular properties of high-risk index lesions within the prostate to regional lymph node metastases resected at the time of prostatectomy. TMA2 (Pre vs. Post ADT) was designed to address questions regarding risk of castration-resistant prostate cancer (CRPC) and response to suppression of the androgen receptor/androgen axis, and characterization of the castration-resistant phenotype. TMA3 (CRPC Met Heterogeneity)'s intended use is to assess the heterogeneity of molecular markers across different anatomic sites in lethal prostate cancer metastases. Conclusions: The GAP1-UTMA project has succeeded in combining a large set of tissue specimens from 501 patients with prostate cancer with rich clinical annotation. Impact: This resource is now available to the prostate cancer community as a tool for biomarker validation to address important unanswered clinical questions around disease progression and response to treatment.
- Published
- 2022
38. Machine learning approaches to analyze histological images of tissues from radical prostatectomies.
- Author
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Arkadiusz Gertych, Nathan Ing, Zhaoxuan Ma, Thomas J. Fuchs, Sadri Salman, Sambit Mohanty, Sanica Bhele, Adriana Velásquez-Vacca, Mahul B. Amin, and Beatrice S. Knudsen
- Published
- 2015
- Full Text
- View/download PDF
39. Semantic segmentation for prostate cancer grading by convolutional neural networks.
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Nathan Ing, Zhaoxuan Ma, Jiayun Li, Hootan Salemi, Corey W. Arnold, Beatrice S. Knudsen, and Arkadiusz Gertych
- Published
- 2018
- Full Text
- View/download PDF
40. Significant changes in macrophage and CD8 T cell densities in primary prostate tumors 2 weeks after SBRT
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Nathanael Kane, Tahmineh Romero, Silvia Diaz-Perez, Matthew B. Rettig, Michael L. Steinberg, Amar U. Kishan, Dorthe Schaue, Robert E. Reiter, Beatrice S. Knudsen, and Nicholas G. Nickols
- Subjects
Male ,Urologic Diseases ,Aging ,Cancer Research ,Prostate Cancer ,Urology ,Clinical Trials and Supportive Activities ,Oncology and Carcinogenesis ,Prostate ,Prostatic Neoplasms ,Cell Count ,CD8-Positive T-Lymphocytes ,Urology & Nephrology ,Radiosurgery ,Oncology ,Clinical Research ,Humans ,Cancer - Abstract
Background Radiotherapy impacts the local immune response to cancers. Prostate Stereotactic Body Radiotherapy (SBRT) is a highly focused method to deliver radiotherapy often used to treat prostate cancer. This is the first direct comparison of immune cells within prostate cancers before and after SBRT in patients. Methods Prostate cancers before and 2 weeks after SBRT are interrogated by multiplex immune fluorescence targeting various T cells and macrophages markers and analyzed by cell and pixel density, as part of a clinical trial of SBRT neoadjuvant to radical prostatectomy. Results Two weeks after SBRT, CD68, and CD163 macrophages are significantly increased while CD8 T cells are decreased. SBRT markedly alters the immune environment within prostate cancers.
- Published
- 2022
41. The intraprostatic immune environment after stereotactic body radiotherapy is dominated by myeloid cells
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Michael L. Steinberg, Christopher R. King, Ekambaram Ganapathy, Matthew Rettig, Beatrice S. Knudsen, Minsong Cao, Christine Nguyen, Ramin Nazarian, Fang-I Chu, David Elashoff, Vince Basehart, Tahmineh Romero, Care Felix, Silvia Diaz-Perez, Nicholas G. Nickols, Dörthe Schaue, Nazy Zomorodian, Jae Kwak, Nathanael Kane, Lin Lin, Robert E. Reiter, Colleen Mathis, Patrick A. Kupelian, and Amar U. Kishan
- Subjects
Male ,Oncology ,Cancer Research ,Myeloid ,medicine.medical_treatment ,030232 urology & nephrology ,Prostate cancer ,0302 clinical medicine ,Prostate ,Myeloid Cells ,Cancer ,Prostatectomy ,Prostate Cancer ,Urology & Nephrology ,Middle Aged ,Neoadjuvant Therapy ,6.5 Radiotherapy and other non-invasive therapies ,Intralymphatic ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Immunotherapy ,Urologic Diseases ,medicine.medical_specialty ,Urology ,Clinical Trials and Supportive Activities ,Oncology and Carcinogenesis ,Radiosurgery ,Article ,Injections ,Vaccine Related ,03 medical and health sciences ,Immune system ,Clinical Research ,Internal medicine ,medicine ,Humans ,business.industry ,Evaluation of treatments and therapeutic interventions ,Injections, Intralymphatic ,Prostatic Neoplasms ,medicine.disease ,Immune checkpoint ,Radiation therapy ,Quality of Life ,Neoplasm Grading ,business - Abstract
BackgroundHundreds of ongoing clinical trials combine radiation therapy, mostly delivered as stereotactic body radiotherapy (SBRT), with immune checkpoint blockade. However, our understanding of the effect of radiotherapy on the intratumoral immune balance is inadequate, hindering the optimal design of trials that combine radiation therapy with immunotherapy. Our objective was to characterize the intratumoral immune balance of the malignant prostate after SBRT in patients.MethodsSixteen patients with high-risk, non-metastatic prostate cancer at comparable Gleason Grade disease underwent radical prostatectomy with (n = 9) or without (n = 7) neoadjuvant SBRT delivered in three fractions of 8 Gy over 5 days completed 2 weeks before surgery. Freshly resected prostate specimens were processed to obtain single-cell suspensions, and immune-phenotyped for major lymphoid and myeloid cell subsets by staining with two separate 14-antibody panels and multicolor flow cytometry analysis.ResultsMalignant prostates 2 weeks after SBRT had an immune infiltrate dominated by myeloid cells, whereas malignant prostates without preoperative treatment were more lymphoid-biased (myeloid CD45+ cells 48.4 ± 19.7% vs. 25.4 ± 7.0%; adjusted p-value = 0.11; and CD45+ lymphocytes 51.6 ± 19.7% vs. 74.5 ± 7.0%; p = 0.11; CD3+ T cells 35.2 ± 23.8% vs. 60.9 ± 9.7%; p = 0.12; mean ± SD).ConclusionSBRT drives a significant lymphoid to myeloid shift in the prostate-tumor immune infiltrate. This may be of interest when combining SBRT with immunotherapies, particularly in prostate cancer.
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- 2020
42. The Movember Prostate Cancer Landscape Analysis: an assessment of unmet research needs
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Sarah T.F. Hsiao, Charles J. Ryan, Beatrice S. Knudsen, Peter L. Choyke, Suneil Jain, Bertrand Tombal, Seanna L. Davidson, Jeremy L. Millar, Tony Crispino, Nadine Brew, Jenna E. Fong, Michelle M. Kouspou, Mark Buzza, Guido Jenster, Nicole Mittmann, Urology, UCL - SSS/IREC/CHEX - Pôle de chirgurgie expérimentale et transplantation, and UCL - (SLuc) Service de chirurgie et transplantation abdominale
- Subjects
0301 basic medicine ,Male ,medicine.medical_specialty ,Biomedical Research ,Urology ,MEDLINE ,Translational research ,Patient advocacy ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,Disease Screening ,SDG 3 - Good Health and Well-being ,medicine ,Humans ,Public health ,Health economics ,business.industry ,Consensus Statement ,Cancer ,Prostatic Neoplasms ,medicine.disease ,Health policy ,030104 developmental biology ,Prostate cancer screening ,030220 oncology & carcinogenesis ,Family medicine ,business ,Needs Assessment - Abstract
Prostate cancer is a heterogeneous cancer with widely varying levels of morbidity and mortality. Approaches to prostate cancer screening, diagnosis, surveillance, treatment and management differ around the world. To identify the highest priority research needs across the prostate cancer biomedical research domain, Movember conducted a landscape analysis with the aim of maximizing the effect of future research investment through global collaborative efforts and partnerships. A global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy. Men with prostate cancer and thought leaders from a variety of disciplines provided a range of key insights through a range of interviews. Insights were prioritized against predetermined criteria to understand the areas of greatest unmet need. From these efforts, 17 research needs in prostate cancer were agreed on and prioritized, and 3 received the maximum prioritization score by the LAC: first, to establish more sensitive and specific tests to improve disease screening and diagnosis; second, to develop indicators to better stratify low-risk prostate cancer for determining which men should go on active surveillance; and third, to integrate companion diagnostics into randomized clinical trials to enable prediction of treatment response. On the basis of the findings from the landscape analysis, Movember will now have an increased focus on addressing the specific research needs that have been identified, with particular investment in research efforts that reduce disease progression and lead to improved therapies for advanced prostate cancer., The Movember global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy to identify the highest priority research needs across the prostate cancer biomedical research domain. Findings from the landscape analysis illustrate the research priorities in prostate cancer and will enable Movember to focus on specific needs, with particular investment in research to reduce disease progression and improve therapies for advanced prostate cancer.
- Published
- 2020
43. Significant changes in macrophage and CD8 T cell densities in primary prostate tumors 2 weeks after SBRT
- Author
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Nathanael, Kane, Tahmineh, Romero, Silvia, Diaz-Perez, Matthew B, Rettig, Michael L, Steinberg, Amar U, Kishan, Dorthe, Schaue, Robert E, Reiter, Beatrice S, Knudsen, and Nicholas G, Nickols
- Abstract
Radiotherapy impacts the local immune response to cancers. Prostate Stereotactic Body Radiotherapy (SBRT) is a highly focused method to deliver radiotherapy often used to treat prostate cancer. This is the first direct comparison of immune cells within prostate cancers before and after SBRT in patients.Prostate cancers before and 2 weeks after SBRT are interrogated by multiplex immune fluorescence targeting various T cells and macrophages markers and analyzed by cell and pixel density, as part of a clinical trial of SBRT neoadjuvant to radical prostatectomy.Two weeks after SBRT, CD68, and CD163 macrophages are significantly increased while CD8 T cells are decreased. SBRT markedly alters the immune environment within prostate cancers.
- Published
- 2021
44. Tumor Heterogeneity in VHL Drives Metastasis in Clear Cell Renal Cell Carcinoma
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Hua Xu, Jacques Van Snick, Beatrice S. Knudsen, Shiruyeh Schokrpur, Moe Ishihara, Thomas G. Graeber, Lily Wu, Jeremy Reynoso, Parmjit S. Jat, Robert M. Prins, Ping Tan, Junhui Hu, Nicholas Bayley, and Arnold I. Chin
- Subjects
Clear cell renal cell carcinoma ,endocrine system diseases ,business.industry ,medicine ,Cancer research ,urologic and male genital diseases ,medicine.disease ,business ,neoplasms ,Tumor heterogeneity ,female genital diseases and pregnancy complications ,Metastasis - Abstract
To study the impact of intratumoral VHL heterogeneity observed in patient ccRCC primary tumors, we engineered VHL gene deletion in three RCC models, including a new primary tumor cell line derived from an aggressive metastatic ccRCC. The VHL gene-deleted (VHL-KO) cells underwent epithelial-to-mesenchymal transition (EMT) and showed diminished proliferation and tumorigenicity compared to the parental, VHL-expressing (VHL+) cells. Renal tumors with either VHL+ or VHL-KO cells alone exhibit minimal metastatic potential. Interestingly, tumors with both cells displayed rampant lung metastasis, highlighting a novel cooperative metastatic mechanism. The poorly proliferative VHL-KO cells stimulated the proliferation, EMT and motility of neighboring VHL+ cells. We found that periostin (POSTN), a protein product overexpressed and secreted by VHL- cells, promoted metastasis by enhancing the motility of VHL-WT cells and facilitating vascular escape of tumor cells. Genetic deletion or antibody blockade of POSTN dramatically suppressed lung metastases in our preclinical models. Our work suggests a new strategy to halt progression in ccRCC by disrupting the critical metastatic crosstalk between heterogeneous cell populations within a tumor.
- Published
- 2021
45. The Human Melanoma Proteome Atlas—Complementing the melanoma transcriptome
- Author
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Ethan Berge, Quimin Zhou, Peter Horvatovich, Marie Sjögren, Natália Pinto de Almeida, Erika Velasquez, Matilda Marko-Varga, Madalina Oppermann, Lázaro Betancourt, Jonatan Eriksson, Magdalena Kuras, Jeovanis Gil, Luciana Pizzatti, Yonghyo Kim, Fábio C. S. Nogueira, Indira Pla Parada, Nicole Woldmar, Jimmy Rodriguez Murillo, Viktória Doma, Gilberto B. Domont, István Németh, József Tímár, Sarolta Kárpáti, Leticia Szadai, Runyu Hong, Toshihide Nishimura, Johan Malm, Melinda Rezeli, Håkan Olsson, Charlotte Welinder, A. Marcell Szász, Henrik Lindberg, Uğur Çakır, Krzysztof Pawłowski, Christian Ingvar, Yutaka Sugihara, Elisabet Wieslander, Erik Steinfelder, Tasso Miliotis, Francesco Florindi, Ho Jeong Kwon, Ken Miller, David Fenyö, Peter Horvath, Boram Lee, György Marko-Varga, Bo Baldetorp, Aniel Sanchez, Lotta Lundgren, Henrik Ekedahl, Henriett Oskolas, Dasol Kim, Beáta Szeitz, Roger Appelqvist, Beatrice S. Knudsen, Harubumi Kato, Carina Eriksson, Analytical Biochemistry, and Medicinal Chemistry and Bioanalysis (MCB)
- Subjects
Proteomics ,Proto-Oncogene Proteins B-raf ,Medicine (General) ,Databases, Factual ,Proteome ,driver mutations ,Medicine (miscellaneous) ,Antineoplastic Agents ,Computational biology ,Biology ,Genome ,DNA sequencing ,Cell Line ,BRAF ,Transcriptome ,R5-920 ,Tandem Mass Spectrometry ,medicine ,Human proteome project ,Humans ,Melanoma ,Gene ,Research Articles ,Chromatography, High Pressure Liquid ,phosphorylation ,Blood Proteins ,Proteogenomics ,medicine.disease ,posttranslational‐modification ,proteogenomics ,Mutation ,histopathology ,Molecular Medicine ,Protein Processing, Post-Translational ,acetylation stoichiometry ,Research Article ,metastatic melanoma - Abstract
The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass‐spectrometry‐based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein‐coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease., The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. This data covers 65% and 74% of the predicted and identified human proteome, respectively.
- Published
- 2021
46. A method of quantifying centrosomes at the single-cell level in human normal and cancer tissue
- Author
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Mengdie Wang, Beatrice S. Knudsen, Anne E. Cress, Raymond B. Nagle, and Gregory C. Rogers
- Subjects
Cell ,Cellular level ,03 medical and health sciences ,0302 clinical medicine ,Tubulin ,Neoplasms ,medicine ,Humans ,Molecular Biology ,Centrioles ,030304 developmental biology ,Centrosome ,0303 health sciences ,biology ,Brief Report ,Cancer ,Cell Biology ,medicine.disease ,3. Good health ,Cell biology ,medicine.anatomical_structure ,Tumor progression ,030220 oncology & carcinogenesis ,biology.protein ,Single-Cell Analysis ,Antibody ,Carrier Proteins ,Whole cell ,Function (biology) - Abstract
Centrosome abnormalities are emerging hallmarks of cancer. The overproduction of centrosomes (known as centrosome amplification) has been reported in a variety of cancers and is currently being explored as a promising target for therapy. However, to understand different types of centrosome abnormalities and their impact on centrosome function during tumor progression, as well as to identify tumor subtypes that would respond to the targeting of a centrosome abnormality, a reliable method for accurately quantifying centrosomes in human tissue samples is needed. Here, we established a method of quantifying centrosomes at a single-cell level in different types of human tissue samples. We tested multiple anti-centriole and pericentriolar-material antibodies to identify bona fide centrosomes and multiplexed these with cell border markers to identify individual cells within the tissue. High-resolution microscopy was used to generate multiple Z-section images, allowing us to acquire whole cell volumes in which to scan for centrosomes. The normal cells within the tissue serve as internal positive controls. Our method provides a simple, accurate way to distinguish alterations in centrosome numbers at the level of single cells.
- Published
- 2019
47. Clinical protein science in translational medicine targeting malignant melanoma
- Author
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József Tímár, Sarolta Kárpáti, Charlotte Welinder, Viktória Doma, György Marko-Varga, Lotta Lundgren, Elisabet Wieslander, Ho Jeong Kwon, Krzysztof Pawłowski, Melinda Rezeli, Henrik Lindberg, Zsolt Horvath, Toshihide Nishimura, Indira Pla, Göran Jönsson, A. Marcell Szász, Magdalena Kuras, Jimmy Rodriguez Murillo, Yonghyo Kim, Jeovanis Gil, Roger Appelqvist, Johan Malm, Håkan Olsson, Lázaro Betancourt, Garry L. Corthals, Beatrice S. Knudsen, Yutaka Sugihara, Elisabeth Burestedt, Ethan Berge, Christian Ingvar, Peter Horvatovich, István Németh, Jonatan Eriksson, Boram Lee, Tasso Miliotis, Henriette Oskolas, Aniel Sanchez, Bo Baldetorp, Analytical Biochemistry, and Medicinal Chemistry and Bioanalysis (MCB)
- Subjects
Proteomics ,0301 basic medicine ,Oncology ,medicine.medical_specialty ,Skin Neoplasms ,Pyridones ,Health, Toxicology and Mutagenesis ,Clinical proteomics ,Pyrimidinones ,Toxicology ,Translational Research, Biomedical ,03 medical and health sciences ,0302 clinical medicine ,Internal medicine ,Oximes ,Cancer moonshot ,Biomarkers, Tumor ,medicine ,Humans ,Vemurafenib ,Melanoma ,Protein Kinase Inhibitors ,Biological Specimen Banks ,Neoplasm Staging ,Trametinib ,Malignant melanoma ,business.industry ,Imidazoles ,Cancer ,Dabrafenib ,Cell Biology ,medicine.disease ,Proteogenomics ,3. Good health ,030104 developmental biology ,Drug Resistance, Neoplasm ,030220 oncology & carcinogenesis ,Original Article ,Translational medicine ,Cancer biomarkers ,Skin cancer ,business ,Post-translational modifications ,medicine.drug - Abstract
Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry-based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.
- Published
- 2019
48. A Circulating Tumor Cell-RNA Assay for Assessment of Androgen Receptor Signaling Inhibitor Sensitivity in Metastatic Castration-Resistant Prostate Cancer
- Author
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Pin Jung Chen, Sungyong You, Nu Yao, Jasmine J. Wang, Beatrice S. Knudsen, Hsian-Rong Tseng, Gina C.Y. Chu, Shirley Cheng, Michael R. Freeman, Minhyung Kim, Howard Chung, Yu Jen Jan, Edwin M. Posadas, Felix Y. Feng, Yi-Tsung Lu, Jie Fu Chen, Pai Chi Teng, Yi Te Lee, Yazhen Zhu, Isla P. Garraway, Allen C. Gao, Amber Lozano, Leland W.K. Chung, and Junhee Yoon
- Subjects
Male ,0301 basic medicine ,Aging ,Medicine (miscellaneous) ,Cancer RNA Profiling ,Drug resistance ,Drug Screening Assays ,Neoplastic Cells ,Castration-Resistant ,Androgen Receptor Signaling Inhibitors ,Prostate cancer ,0302 clinical medicine ,Circulating tumor cell ,Metastatic Castration-Resistant Prostate Cancer ,Circulating ,Circulating Tumor Cell ,Pharmacology, Toxicology and Pharmaceutics (miscellaneous) ,Cancer ,Prostate Cancer ,Neoplastic Cells, Circulating ,3. Good health ,Prostatic Neoplasms, Castration-Resistant ,030220 oncology & carcinogenesis ,Research Paper ,Signal Transduction ,Urologic Diseases ,Oncology and Carcinogenesis ,Antineoplastic Agents ,Castration resistant ,03 medical and health sciences ,Clinical Research ,Androgen Receptor Antagonists ,Genetics ,medicine ,Humans ,Gene ,business.industry ,Computational Biology ,Prostatic Neoplasms ,RNA ,Antitumor ,medicine.disease ,Androgen receptor ,030104 developmental biology ,Cell culture ,Cancer research ,Drug Screening Assays, Antitumor ,Transcriptome ,business - Abstract
Rationale: Our objective was to develop a circulating tumor cell (CTC)-RNA assay for characterizing clinically relevant RNA signatures for the assessment of androgen receptor signaling inhibitor (ARSI) sensitivity in metastatic castration-resistant prostate cancer (mCRPC) patients. Methods: We developed the NanoVelcro CTC-RNA assay by combining the Thermoresponsive (TR)-NanoVelcro CTC purification system with the NanoString nCounter platform for cellular purification and RNA analysis. Based on the well-validated, tissue-based Prostate Cancer Classification System (PCS), we focus on the most aggressive and ARSI-resistant PCS subtype, i.e., PCS1, for CTC analysis. We applied a rigorous bioinformatic process to develop the CTC-PCS1 panel that consists of prostate cancer (PCa) CTC-specific RNA signature with minimal expression in background white blood cells (WBCs). We validated the NanoVelcro CTC-RNA assay and the CTC-PCS1 panel with well-characterized PCa cell lines to demonstrate the sensitivity and dynamic range of the assay, as well as the specificity of the PCS1 Z score (the likelihood estimate of the PCS1 subtype) for identifying PCS1 subtype and ARSI resistance. We then selected 31 blood samples from 23 PCa patients receiving ARSIs to test in our assay. The PCS1 Z scores of each sample were computed and compared with ARSI treatment sensitivity. Results: The validation studies using PCa cell line samples showed that the NanoVelcro CTC-RNA assay can detect the RNA transcripts in the CTC-PCS1 panel with high sensitivity and linearity in the dynamic range of 5-100 cells. We also showed that the genes in CTC-PCS1 panel are highly expressed in PCa cell lines and lowly expressed in background WBCs. Using the artificial CTC samples simulating the blood sample conditions, we further demonstrated that the CTC-PCS1 panel is highly specific in identifying PCS1-like samples, and the high PCS1 Z score is associated with ARSI resistance samples. In patient bloods, ARSI-resistant samples (ARSI-R, n=14) had significantly higher PCS1 Z scores as compared with ARSI-sensitive samples (ARSI-S, n=17) (Rank-sum test, P=0.003). In the analysis of 8 patients who were initially sensitive to ARSI (ARSI-S) and later developed resistance (ARSI-R), we found that the PCS1 Z score increased from the time of ARSI-S to the time of ARSI-R (Pairwise T-test, P=0.016). Conclusions: Using our new methodology, we developed a first-in-class CTC-RNA assay and demonstrated the feasibility of transforming clinically-relevant tissue-based RNA profiling such as PCS into CTC tests. This approach allows for detecting RNA expression relevant to clinical drug resistance in a non-invasive fashion, which can facilitate patient-specific treatment selection and early detection of drug resistance, a goal in precision oncology.
- Published
- 2019
49. Abstract 3810: Muscle invasion produced drug-resistant and bone metastatic prostate cancer
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Kendra D. Marr, Beatrice S. Knudsen, Jaime M. Gard, Malia Bird, Raymond B. Nagle, and Anne E. Cress
- Subjects
Cancer Research ,Oncology - Abstract
Overtreatment of prostate cancer is a significant source of patient morbidity and cost. The human prostate is bounded by a smooth muscle capsule, and aggressive tumors invade through the muscle layer, called extracapsular extension (ECE), to escape organ confinement. The presence of ECE defines pT3a pathologic stage and is associated with increased risk of biochemical recurrence, metastases, and cancer-specific mortality. Although muscle invasion is required for ECE and metastatic spread, both the invasive tumor network phenotypes and muscle responses are understudied. The goal was to probe the molecular events of ECE to understand this critical step in metastasis. Muscle invasion of prostate cancer cell lines was tested in vivo by injecting cells into the peritoneal cavity of male NSG mice. The cells colonize the inferior surface of the muscular respiratory diaphragm and invade through to the superior surface. To explore transcriptional regulators, we performed whole genome RNAseq on cells from three compartments: (1) “Inferior” non-invading cells on the underside of the diaphragm; (2) “Muscle-resident” cells that have invaded and now reside within the diaphragm muscle; and (3) “Superior” cells that have completely traversed the diaphragm. Tumors cells reaching the superior side of the diaphragm were established ex vivo as polyclonal cell lines termed the “KM” series. RNAseq reveals 1,482 differentially expressed sequences (DES) between Inferior and Muscle-resident cells, 253 DES between Muscle-resident and Superior cells, and 896 DES between Inferior and Superior cells (padj The gene expression patterns imply a dominant effect of the muscle microenvironment in evoking a new and transient tumor transcriptional response as revealed by the DESs. Independent of this response, the KM sub-populations successfully navigating the muscle were more aggressive in laboratory assays, including bone metastatic potential and chemotherapeutic resistance. These studies support the hypothesis that successful invasion into and through a contractile muscle layer results in aggressive cancer cells. Using the in vivo assay provides the unique ability to parse out unexplored patterns of changes that occur in early, muscle-invasive disease to improve prostate cancer patient selection for definitive treatment versus active surveillance. Citation Format: Kendra D. Marr, Beatrice S. Knudsen, Jaime M. Gard, Malia Bird, Raymond B. Nagle, Anne E. Cress. Muscle invasion produced drug-resistant and bone metastatic prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3810.
- Published
- 2022
50. Abstract 3835: Kindlin-2 complexes containing α6β1 integrin are responsive to hypoxia
- Author
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Daniel Hernandez-Cortes, Jaime M.C. Gard, Beatrice S. Knudsen, Noel A. Warfel, and Anne E. Cress
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Cancer Research ,Oncology - Abstract
The laminin-binding integrins are mechanosensory receptors critical for cell adhesion and structural organization that link the extracellular matrix (ECM) to the cytoskeleton. Integrin α6β1 is associated with prostate cancer (PCa) migration, invasion, metastasis, and decreased cancer-specific survival. Kindlin-2 (FERMT2) is a β1 integrin adaptor and mechanosensory focal adhesion (FA) protein that activates and clusters integrins in response to structural ECM alterations in the tumor microenvironment. Our goal was to determine if integrin-kindlin-2 adhesion complexes (kindlin-2:α6β1) were responsive to hypoxia, a physiologically relevant and altered microenvironment in PCa progression. Five different endpoints were tested including the biochemical analysis of kindlin-2 complexes, qRT-PCR, immunoblotting, immunocytochemistry, and electric cell impedance sensing (ECIS). Using DU145 prostate cancer cells grown under hypoxia (1% O2) for up to 16 hours, the results showed a reversible increase in kindlin-2:α6β1 complexes with maximal assembly within 4 hours and disassembly starting by 8 hours. Notably, kindlin-2:α6β1 complexes were found exclusively within membrane projections and were not observed within hypoxia-inducible paxillin (PXN)-containing FAs. The hypoxia induced kindlin-2:α6β1 complexes and classical FAs were dependent on kindlin-2 as determined by CRISPR-Cas9 heterozygous deletion of FERMT2. Protein co-localization of α6 integrin and PXN with kindlin-2 within membrane projections and FAs, respectively, was also induced under hypoxia. Further, non-invasive ECIS measurements in live cells confirmed functional cell-cell and cell-ECM dynamics driven by hypoxia and requiring kindlin-2. Our results indicate that the kindlin-2:α6β1 complexes are uniquely associated with FA-independent membrane projections induced by hypoxia, a tumor microenvironment associated with aggressive prostate cancer. The novel kindlin-2:α6β1 complexes may represent an actionable pharmacological target for blocking escape of organ confined disease and metastasis promoting steps of human prostate cancer. (Partially supported by NIH grants CA P30 23074, DOD W81XWH-19-1-0455, and NCI R01 CA242226). Citation Format: Daniel Hernandez-Cortes, Jaime M.C. Gard, Beatrice S. Knudsen, Noel A. Warfel, Anne E. Cress. Kindlin-2 complexes containing α6β1 integrin are responsive to hypoxia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3835.
- Published
- 2022
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