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While next-generation sequencing (NGS) is used to guide therapy in patients with metastatic lung adenocarcinoma (LUAD), use of NGS to determine pathologic LN metastasis prior to surgery has not been assessed. To bridge this knowledge gap, we performed NGS using MSK-IMPACT in 426 treatment-naive patients with clinical N2-negative LUAD. A multivariable logistic regression model that considered preoperative clinical and genomic variables was constructed. Most patients had cN0 disease (85%) with pN0, pN1, and pN2 rates of 80%, 11%, and 9%, respectively. Genes altered at higher rates in pN-positive than in pN-negative tumors were STK11 (p = 0.024), SMARCA4 (p = 0.006), and SMAD4 (p = 0.011). Fraction of genome altered (p = 0.037), copy number amplifications (p = 0.001), and whole-genome doubling (p = 0.028) were higher in pN-positive tumors. Multivariable analysis revealed solid tumor morphology, tumor SUVmax, clinical stage, SMARCA4 and SMAD4 alterations were independently associated with pathologic LN metastasis. Incorporation of clinical and tumor genomic features can identify patients at risk of pathologic LN metastasis; this may guide therapy decisions before surgical resection.

A normal sagittal vertical axis (SVA) after spinal deformity correction can yield mechanical complications of up to 30%. Post-operative compensatory pelvic orientation can produce a normal SVA. We assess relative pelvic version (RPV), an individualised measure, for persistent post-operative compensatory measures.Adult spinal deformity (ASD) patients who were treated operatively, with a normal SVA ( ± 50 mm) at 6-week follow-up were included, who were then followed-up after 2 years. These only included patients with fusion of 4 vertebrae extending to L5 or below. Six-week subgroups were made regarding pelvis orientation, relative pelvic version (RPV: anteversion, aligned, moderate or severe retroversion) with analysis of patient-related outcome measures (PROMs), complications and spino-pelvic sagittal parameters.At 6 weeks, 140 patients met the inclusion criteria, 5 (3.6%) patients had anteversion, 59 (42.1%) were aligned, 60 (42.9%) had moderate retroversion and 16 (11.4%) patients had severe retroversion. Follow-up after 2 years demonstrated increased RPV in all groups except the severe RPV group who were more likely to develop SVA 50 mm. Complications occurred in all groups. Significant 2-year differences were observed between moderate and severe RPV for back pain and PROMs but not between other RPV groups.Adult spinal deformity patients with a normal SVA after spino-pelvic instrumentation carry a significant risk of retroversion progression post-operatively, followed by increased positive sagittal balance. Relative pelvic version (RPV) measurements when categorised into anteversion, aligned, moderate retroversion and severe retroversion at 6 weeks were predictive of PROMs at 2 years.

Purpose: KRAS G12C is the most common KRAS mutation in primary lung adenocarcinoma. Phase I clinical trials have demonstrated encouraging clinical activity of KRASG12C inhibitors in the metastatic setting. We investigated disease-free survival (DFS) and tumor genomic features in patients with surgically resected KRASG12C-mutant lung adenocarcinoma. Experimental Design: Patients who underwent resection of stage I–III lung adenocarcinoma and next-generation sequencing (NGS) were evaluated. Exclusion criteria were receipt of induction therapy, incomplete resection, and low-quality NGS. Mutations were classified as KRAS wild-type (KRASwt), G12C (KRASG12C), or non-G12C (KRASother). DFS was compared between groups using the log-rank test; factors associated with DFS were assessed using Cox regression. Mutual exclusivity and cooccurrence, tumor clonality, and mutational signatures were assessed. Results: In total, 604 patients were included: 374 KRASwt (62%), 95 KRASG12C (16%), and 135 KRASother (22%). Three-year DFS was not different between KRAS-mutant and KRASwt tumors. However, 3-year DFS was worse in patients with KRASG12C than KRASother tumors (log-rank P = 0.029). KRASG12C tumors had more lymphovascular invasion (51% vs. 37%; P = 0.032) and higher tumor mutation burden [median (interquartile range), 7.0 (5.3–10.8) vs. 6.1 (3.5–9.7); P = 0.021], compared with KRASother tumors. KRASG12C mutation was independently associated with worse DFS on multivariable analysis. Our DFS findings were externally validated in an independent The Cancer Genome Atlas cohort. Conclusions: KRAS G12C mutations are associated with worse DFS after complete resection of stage I–III lung adenocarcinoma. These tumors harbor more aggressive clinicopathologic and genomic features than other KRAS-mutant tumors. We identified a high-risk group for whom KRASG12C inhibitors may be investigated to improve survival.

INTRODUCTION: The purpose of the study is to genomically characterize the biology and related therapeutic opportunities of prognostically important predominant histological subtypes in lung adenocarcinoma (LUAD). METHODS: We identified 604 patients with stage I-III LUAD who underwent complete resection and targeted next-generation sequencing using the MSK-IMPACT platform. Tumors were classified according to predominant histologic subtype and grouped by architectural grade (lepidic [LEP], acinar or papillary [ACI/PAP], and micropapillary or solid [MIP/SOL]). Associations between clinicopathologic factors, genomic features, mutational signatures, and recurrence were examined within subtypes and, when appropriate, quantified using competing-risks regression, with adjustment for pathologic stage and extent of resection. RESULTS: MIP/SOL tumors had higher tumor mutational burden (p

Resumen Introduccion La pancreatectomia total (PT) es una intervencion infrecuente, con unas indicaciones no claramente definidas y unos resultados postoperatorios no estandarizados. Presentamos un estudio multicentrico nacional sobre PT y una comparacion con la literatura existente. Metodos Estudio prospectivo observacional realizado mediante el registro nacional de pacientes operados de duodenopancreatectomia cefalica y PT realizadas por cualquier indicacion durante el periodo comprendido entre el 1 enero y el 31 diciembre del 2015. Resultados Se incluyo a 1.016 pacientes, pertenecientes a 73 centros; de ellos, 112 correspondian a PT. El porcentaje de PT/numero total de casos es del 11%. La edad media fue 63,5 anos y eran varones un 57,2%. El diagnostico radiologico de sospecha mas frecuente fue cancer de pancreas (58/112 casos). La tecnica de la PT mas habitual fue «arteria mesenterica primero» (43/112 casos). Se efectuaron resecciones venosas en 23 pacientes (20,5%). El porcentaje de complicaciones postoperatorias a 90 dias fue 50%, pero las complicaciones mayores (> IIIA) solo el 20,7%. La mortalidad global a 90 dias fue del 8% (9 pacientes). La estancia media fue 20,7 dias. Los 3 diagnosticos histologicos definitivos mas frecuentes fueron: adenocarcinoma de pancreas, neoplasia mucinosa papilar intraductal y pancreatitis cronica. La tasa de R0 fue del 67,8%. Conclusiones Este estudio demuestra que los resultados de morbimortalidad de la PT en Espana son similares o superiores a los publicados previamente. Es necesario un estudio mas especifico sobre PT centrado en complicaciones especificas, como la insuficiencia endocrina.

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.

Primary pulmonary melanoma (PPM) is an entity recognized by the thoracic WHO classification. However, given the absence of native melanocytes in the lung and the known phenomenon of regression of cutaneous melanomas, the existence of PPM has remained controversial. Herein we investigate clinicopathologic and genomic features of lung-only melanomas with the goal to clarify their site of origin. We identified 10 melanomas involving exclusively lung with no current or previous cutaneous, uveal, or mucosal primaries. Four patients had solitary lesions with mean size of 5.1 cm (range 3.0–10.1 cm), meeting the criteria of PPM. Four patients had 2–3 lesions and 2 patients had >10 lesions. All cases underwent targeted next-generation sequencing interrogating up to 468 cancer genes, which revealed mean tumor mutation burden of 42.6 per megabase (range 1.8 to 126) and frequent mutations involving BRAF, NRAS, NF1, KIT, and KRAS – a genomic profile typical of UV-associated cutaneous melanoma. Mutational signature was assessable for eight cases harboring >20 mutations. This revealed that all evaluable cases harbored a dominant UV signature. In addition, one nonevaluable case harbored a GG > AA TERT promoter variant that is highly specific for UV-mutagenesis. As control groups, using the same methodology, a dominant UV signature was identified in 97% (470/486) of cutaneous melanomas, whereas no lung adenocarcinoma (n = 291) exhibited this signature. Notably, the clinical and pathologic features of solitary melanomas, especially those with large size and epithelioid morphology, closely mimicked primary lung carcinomas, highlighting a major potential for misdiagnosis. In conclusion, presence of a UV signature provides direct evidence that nearly all lung-only melanomas in this series, including solitary lesions meeting the strict criteria of PPM, represent metastases from occult cutaneous melanomas. This suggests that lung-only melanomas should be considered as likely metastatic even in the absence of a known primary melanoma elsewhere.

Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are highly genetically complex soft tissue sarcomas. Up to 50% of patients develop distant metastases, but current systemic therapies have limited efficacy. MFS and UPS have recently been shown to commonly harbor copy number alterations or mutations in the tumor suppressor genes RB1 and TP53. As these alterations have been shown to engender dependence on the oncogenic protein Skp2 for survival of transformed cells in mouse models, we sought to examine its function and potential as a therapeutic target in MFS/UPS. Comparative genomic hybridization and next-generation sequencing confirmed that a significant fraction of MFS and UPS patient samples (n = 94) harbor chromosomal deletions and/or loss-of-function mutations in RB1 and TP53 (88% carry alterations in at least one gene; 60% carry alterations in both). Tissue microarray analysis identified a correlation between absent Rb and p53 expression and positive expression of Skp2. Downregulation of Skp2 or treatment with the Skp2-specific inhibitor C1 revealed that Skp2 drives proliferation of patient-derived MFS/UPS cell lines deficient in both Rb and p53 by degrading p21 and p27. Inhibition of Skp2 using the neddylation-activating enzyme inhibitor pevonedistat decreased growth of Rb/p53-negative patient-derived cell lines and mouse xenografts. These results demonstrate that loss of both Rb and p53 renders MFS and UPS dependent on Skp2, which can be therapeutically exploited and could provide the basis for promising novel systemic therapies for MFS and UPS. Significance: Loss of both Rb and p53 renders myxofibrosarcoma and undifferentiated pleomorphic sarcoma dependent on Skp2, which could provide the basis for promising novel systemic therapies. See related commentary by Lambert and Jones, p. 2437

Somatic alterations in cancer genes are being detected in normal and premalignant tissue, placing greater emphasis on gene-environment interactions that enable disease phenotypes. By combining early genetic alterations with disease-relevant exposures, we developed an integrative mouse model to study gastric premalignancy. Deletion of Trp53 in gastric cells confers a selective advantage and promotes the development of dysplasia in the setting of dietary carcinogens. Organoid derivation from dysplastic lesions facilitated genomic, transcriptional, and functional evaluation of gastric premalignancy. Cell cycle regulators, most notably Cdkn2a, were upregulated by p53 inactivation in gastric premalignancy, serving as a barrier to disease progression. Co-deletion of Cdkn2a and Trp53 in dysplastic gastric organoids promoted cancer phenotypes but also induced replication stress, exposing a susceptibility to DNA damage response pathway inhibitors. These findings demonstrate the utility of mouse models that integrate genomic alterations with relevant exposures and highlight the importance of gene-environment interactions in shaping the premalignant state.

Purpose: The majority of broad-panel tumor genomic profiling has used a gene-centric approach, although much of that data is unused in clinical decision making. We hypothesized that a pathway-centric approach using next-generation sequencing (NGS), combined with conventional clinicopathologic features, may better predict disease-free survival (DFS) in early stage lung adenocarcinoma. Experimental Design: Utilizing our prospectively maintained database, we analyzed 492 patients with primary, untreated, completely surgically resected lung adenocarcinoma. Ten canonical pathways were analyzed using broad-panel NGS. The correlations of DFS and number (and type) of pathway (NPA) were analyzed using the Kaplan–Meier method and log-rank test. Associations between altered pathways and clinicopathologic variables, as well as identification of actionable therapeutic strategies were explored. Results: Median NPA for the cohort was two (range, 0–5). Smoking status, solid morphologic appearance on preoperative CT, maximal standardized uptake value, pathologic tumor size, aggressive histologic subtype, lymphovascular invasion, visceral pleural invasion, and positive lymph nodes were significantly associated with NPA (P < 0.05). Of 543 actionable genetic alterations identified, 455 (84%) were within the RTK/RAS pathway. A total of 86 tumors had actionable therapeutic genomic alterations in >1 pathway. On multivariable analysis, higher NPA was significantly associated with worse DFS (HR, 1.31; P = 0.014). Conclusions: NPA and specific pathway alterations are associated with clinicopathologic features in patients with surgically resected lung adenocarcinoma. Cell cycle, Hippo, TGFβ, and p53 pathway alterations are associated with poor DFS. Finally, NPA is an independent risk factor for poor DFS in our cohort. See related commentary by Blakely, p. 7269

Simple Summary Next-generation sequencing (NGS) has revolutionized care for patients with advanced and metastatic non-small cell lung cancer through the identification of specific oncogenic driver mutations and pairing with matched targeted therapies. The application of NGS technologies also has the potential to improve outcomes in patients with earlier-stage disease who undergo surgery as their first line of treatment. We review clinically relevant topics in this patient cohort, for whom NGS technologies have spearheaded our understanding of tumor heterogeneity, the underlying genomic features associated with lung adenocarcinoma histologic subtypes, the prediction of recurrence after surgery, the identification of minimal residual disease by circulating tumor DNA, the discernment of intrapulmonary metastases versus synchronous or metachronous disease, and the identification of patients with early-stage non-small cell lung cancer who are likely to benefit from induction or adjuvant therapies. Abstract During the last two decades, next-generation sequencing (NGS) has played a key role in enhancing non-small cell lung cancer treatment paradigms through the application of “targeted therapy” in advanced and metastatic disease. The use of specific tyrosine kinase inhibitors in patients with oncogenic driver alterations, such as EGFR, ALK, ROS1, BRAF V600E, MET, and NTRK mutations, among others, has changed treatment approaches and improved outcomes in patients with late-stage disease. Although NGS technology has mostly been used in the setting of systemic therapy to identify targets, response to therapy, and mechanisms of resistance, it has multiple potential applications for patients with earlier-stage disease, as well. In this review, we discuss the emerging role of NGS technologies to better understand tumor biology in patients with non-small cell lung cancer who are undergoing surgery with curative intent. In this patient cohort, we examine tumor heterogeneity, the underlying tumor genomics associated with lung adenocarcinoma subtypes, the prediction of recurrence after complete surgical resection, the use of plasma circulating tumor DNA for detection of early cancers and monitoring for minimal residual disease, the differentiation of separate primaries from intrapulmonary metastases, and the use of NGS to guide induction and adjuvant therapies.

Background Resection of colorectal liver metastases (CLM) can cure disease, but many patients with extensive disease cannot be fully resected and others recur following surgery. Hepatic arterial infusion (HAI) chemotherapy can convert extensive liver disease to a resectable state or decrease recurrence risk, but response varies and no biomarkers currently exist to identify patients most likely to benefit. Methods We performed a retrospective cohort study of CLM patients receiving HAI chemotherapy whose tumors underwent MSK‐IMPACT sequencing. The frequency of oncogenic alterations and their association with overall survival (OS) and objective response rate were analyzed at the individual gene and signaling pathway levels. Results Three hundred and seventy patients met inclusion criteria: 189 (51.1%) who underwent colorectal liver metastasectomy followed by HAI + systemic therapy (Adjuvant cohort), and 181 (48.9%) with unresectable CLM (Metastatic cohort) who received HAI + systemic therapy, consisting of 63 (34.8%) with extrahepatic disease and 118 (65.2%) with liver‐restricted disease. Genomic alterations were similar in each cohort, and no individual gene or pathway was significantly associated with objective response. Patients in the adjuvant cohort with concurrent Ras/B‐Raf alteration and SMAD4 inactivation had worse prognosis while in the metastatic cohort patients with co‐alteration of Ras/B‐Raf and TP53 had worse OS. Similar findings were observed in a validation cohort. Conclusions Concurrently altered Ras/B‐Raf and SMAD4 mutations were associated with worse survival in resectable patients, while concurrent Ras/B‐Raf and TP53 alterations were associated with worse survival in unresectable patients. The mutual exclusivity of Ras/B‐Raf, SMAD4, and TP53 may have prognostic value for CLM patients receiving HAI., Patients with colorectal liver metastases receiving hepatic arterial infusion chemotherapy who have either resectable disease with concurrently altered Ras/B‐Raf and SMAD4 mutations, or unresectable disease with concurrent Ras/B‐Raf and TP53 alterations had worse survival. Mutual exclusivity of Ras/B‐Raf, SMAD4, and TP53 status may be useful for prognostic stratification in these patients.

Background Although EGFR mutant tumors exhibit low response rates to immune checkpoint blockade overall, some EGFR mutant tumors do respond to these therapies; however, there is a lack of understanding of the characteristics of EGFR mutant lung tumors responsive to immune checkpoint blockade. Patients and methods We retrospectively analyzed de-identified clinical and molecular data on 171 cases of EGFR mutant lung tumors treated with immune checkpoint inhibitors from the Yale Cancer Center, Memorial Sloan Kettering Cancer Center, University of California Los Angeles, and Dana Farber Cancer Institute. A separate cohort of 383 EGFR mutant lung cancer cases with sequencing data available from the Yale Cancer Center, Memorial Sloan Kettering Cancer Center, and The Cancer Genome Atlas was compiled to assess the relationship between tumor mutation burden and specific EGFR alterations. Results Compared with 212 EGFR wild-type lung cancers, outcomes with programmed cell death 1 or programmed death-ligand 1 (PD-(L)1) blockade were worse in patients with lung tumors harboring alterations in exon 19 of EGFR (EGFRΔ19) but similar for EGFRL858R lung tumors. EGFRT790M status and PD-L1 expression did not impact response or survival outcomes to immune checkpoint blockade. PD-L1 expression was similar across EGFR alleles. Lung tumors with EGFRΔ19 alterations harbored a lower tumor mutation burden compared with EGFRL858R lung tumors despite similar smoking history. Conclusions EGFR mutant tumors have generally low response to immune checkpoint inhibitors, but outcomes vary by allele. Understanding the heterogeneity of EGFR mutant tumors may be informative for establishing the benefits and uses of PD-(L)1 therapies for patients with this disease.

Purpose: Tumor mutation burden (TMB) is a biomarker of response to immune checkpoint blockade (ICB). The impact of TMB on outcomes with targeted therapies has not been explored. Experimental Design: We identified all patients with metastatic EGFR exon19del or L858R-mutant lung cancers treated with first/second-generation EGFR tyrosine kinase inhibitors (TKIs) with pretreatment next-generation sequencing data (MSK-IMPACT assay). The effect of TMB on time-to-treatment discontinuation (TTD) and overall survival (OS) were evaluated in univariate and multivariate analyses. EGFR wild-type lung adenocarcinoma samples were used for comparison. Results: Among 153 patients with EGFR-mutant lung cancer, TMB was lower compared with EGFR wild-type (n = 1,849; median 3.77 vs. 6.12 mutations/Mb; P < 0.0001) with a broad range (0.82–17.9 mutations/Mb). Patients with EGFR-mutant lung cancer whose tumors had TMB in the high tertile had shorter TTD (HR, 0.46; P = 0.0008) and OS (HR, 0.40; P = 0.006) compared with patients with low/intermediate TMB. Evaluating by median TMB, there was significantly shorter TTD and OS for patients with higher TMB (TTD, P = 0.006; OS, P = 0.03). In multivariate analysis, TTD and OS remained significantly longer in the low/intermediate tertile compared with high TMB (HR = 0.57, P = 0.01; HR = 0.50, P = 0.02, respectively). In paired pretreatment and postprogression samples, TMB was increased at resistance (median 3.42 vs. 6.56 mutations/Mb; P = 0.008). Conclusions: TMB is negatively associated with clinical outcomes in metastatic patients with EGFR-mutant lung cancer treated with EGFR-TKI. This relationship contrasts with that seen in lung cancers treated with immunotherapy. See related commentary by Cheng and Oxnard, p. 899

Somatic mutations in the KRAS oncogene are associated with poor outcomes in locally advanced rectal cancer but the underlying biologic mechanisms are not fully understood. We profiled mRNA in 76 locally advanced rectal adenocarcinomas from patients that were enrolled in a prospective clinical trial and investigated differences in gene expression between KRAS mutant (KRAS‐mt) and KRAS‐wild‐type (KRAS‐wt) patients. We found that KRAS‐mt tumors display lower expression of genes related to the tumor stroma and remodeling of the extracellular matrix. We validated our findings using samples from The Cancer Genome Atlas (TCGA) and also by performing immunohistochemistry (IHC) and immunofluorescence (IF) in orthogonal cohorts. Using in vitro and in vivo models, we show that oncogenic KRAS signaling within the epithelial cancer cells modulates the activity of the surrounding fibroblasts in the tumor microenvironment., Oncogenic KRAS is associated with poor outcomes in locally advanced rectal cancer (LARC) but the underlying biologic mechanisms are not fully understood. We investigated differences in gene expression profiles between KRAS mutant and KRAS wild‐type LARC tumors. We found that KRAS mutant tumors display lower expression of genes related to the tumor stroma and remodeling of the extracellular matrix.

INTRODUCTION The aim of the study is to compare clinical staging of anterior pelvic prolapse with magnetic resonance imaging (MRI) staging, using the pubococcygeal line (PCL), the midpubic line (MPL), and the H line as reference lines. Moreover, we aim to analyze interrater reliability of each reference line. MATERIAL AND METHODS Forty-two women with pelvic organ prolapse (POP) symptoms were studied using the pelvic organ prolapse quantification on physical examination. Two different observers calculated anterior POP using the three MRI reference lines, retrospectively. Agreement between MRI and clinical staging was estimated using Pearson correlation for the quantitative measurements and kappa index for the stages. Interrater reliability was estimated using the intraclass correlation coefficient (ICC). RESULTS Correlation between physical examination and the H line was high by both observers (r = 0.86 and r = 0.76, p

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living kidney donor biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomics analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for ten years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic pain are known sequelae of IPV; however, not all those who experience IPV develop chronic pain. To mitigate its development, it is critical to identify the factors that are associated with increased risk of pain after IPV. This proof-of-concept study used machine-learning strategies to predict pain severity and interference in 47 young women, ages 18 to 30, who experienced an incident of IPV (i.e., physical and/or sexual assault) within three months of their baseline assessment. Young women are more likely than men to experience IPV and to subsequently develop posttraumatic stress disorder (PTSD) and chronic pain. Women completed a comprehensive assessment of theory-driven cognitive and neurobiological predictors of pain severity and pain-related interference (e.g., pain, coping, disability, psychiatric diagnosis/symptoms, PTSD/trauma, executive function, neuroendocrine, and physiological stress response). Gradient boosting machine models were used to predict symptoms of pain severity and pain-related interference across time (Baseline, 1-,3-,6- follow-up assessments). Models showed excellent predictive performance for pain severity and adequate predictive performance for pain-related interference. This proof-of-concept study suggests that machine-learning approaches are a useful tool for identifying predictors of pain development in survivors of recent IPV. Baseline measures of pain, family life impairment, neuropsychological function, and trauma history were of greatest importance in predicting pain and pain-related interference across a 6-month follow-up period. Present findings support the use of machine-learning techniques in larger studies of post-IPV pain development and highlight theory-driven predictors that could inform the development of targeted early intervention programs. However, these results should be replicated in a larger dataset with lower levels of missing data.

Preemptive TIPS Individual Data Metanalysis, International Variceal Bleeding Study and Baveno Cooperation Study groups., [Background & Aims] Compared with drugs plus endoscopy, placement of transjugular portosystemic shunt within 72 hours of admission to the hospital (early or preventive transjugular intrahepatic portosystemic shunt [TIPS], also called preemptive TIPS) increases the proportion of high-risk patients with cirrhosis and acute variceal bleeding who survive for 1 year. However, the benefit of preemptive TIPS is less clear for patients with a Child-Pugh score of B and active bleeding (CP-B+AB). We performed an individual data meta-analysis to assess the efficacy of preemptive TIPS in these patients and identify factors associated with reduced survival of patients receiving preemptive TIPS., [Method] We searched publication databases for randomized controlled trials and observational studies comparing the effects of preemptive TIPS versus endoscopy plus nonselective beta-blockers in the specific population of high-risk patients with cirrhosis and acute variceal bleeding (CP-B+AB or Child-Pugh C, below 14 points), through December 31, 2019. We performed a meta-analysis of data from 7 studies (3 randomized controlled trials and 4 observational studies), comprising 1327 patients (310 received preemptive TIPS and 1017 received drugs plus endoscopy). We built adjusted models to evaluate risk using propensity score for baseline covariates. Multivariate Cox regression models were used to assess the factors associated with survival time. The primary endpoint was effects of preemptive TIPS versus drugs plus endoscopy on 1-year survival in the overall population as well as CP-B+AB and Child-Pugh C patients., [Results] Overall, preemptive TIPS significantly increased the proportion of high-risk patients with cirrhosis and acute variceal bleeding who survived for 1 year, compared with drugs plus endoscopy (hazard ratio [HR] 0.443; 95% CI 0.323–0.607; P < .001). This effect was observed in CP-B+AB patients (HR 0.524; 95% CI 0.307–0.896; P = .018) and in patients with Child-Pugh C scores below 14 points (HR 0.374; 95% CI 0.253–0.553; P < .001). Preemptive TIPS significantly improved control of bleeding and ascites without increasing risk of hepatic encephalopathy in Child-Pugh C and CP-B+AB patients, compared with drugs plus endoscopy. Cox analysis of patients who received preemptive TIPS showed that patients could be classified into 3 categories for risk of death, based on age, serum level of creatinine, and Child-Pugh score. In each of these risk categories, preemptive TIPS increased the proportion of patients who survived for 1 year, compared with drugs plus endoscopy., [Conclusions] In a meta-analysis of data from 1327 patients with cirrhosis, acute variceal bleeding, and Child-Pugh score between 10 and 13 points or CP-B+AB, preemptive TIPS increased the proportion who survived for 1 year, in both subgroups separately, compared with drugs plus endoscopy., Juan Carlos García-Pagán received support in part through grants from the Spanish Ministry of Education and Science (SAF-2016–75767-R and PIE 15/00027) and from the “Commissioner for Universities and Research of the Generalitat de Catalunya” (AGAUR SGR 2017). CIBERehd is funded by the Instituto de Salud Carlos III. Edilmar Alvarado-Tapias and Anna Baiges are recipients of a "Río Hortega" fellowship grant from the Instituto de Salud Carlos III. The study was partially supported by a GORE grant for statistical support.

IMPORTANCE: Recommendations for adjuvant therapy after surgical resection of lung adenocarcinoma (LUAD) are based solely on TNM classification but are agnostic to genomic and high-risk clinicopathologic factors. Creation of a prediction model that integrates tumor genomic and clinicopathologic factors may better identify patients at risk for recurrence. OBJECTIVE: To identify tumor genomic factors independently associated with recurrence, even in the presence of aggressive, high-risk clinicopathologic variables, in patients with completely resected stages I to III LUAD, and to develop a computational machine-learning prediction model (PRecur) to determine whether the integration of genomic and clinicopathologic features could better predict risk of recurrence, compared with the TNM system. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study included 426 patients treated from January 1, 2008, to December 31, 2017, at a single large cancer center and selected in consecutive samples. Eligibility criteria included complete surgical resection of stages I to III LUAD, broad-panel next-generation sequencing data with matched clinicopathologic data, and no neoadjuvant therapy. External validation of the PRecur prediction model was performed using The Cancer Genome Atlas (TCGA). Data were analyzed from 2014 to 2018. MAIN OUTCOMES AND MEASURES: The study end point consisted of relapse-free survival (RFS), estimated using the Kaplan-Meier approach. Associations among clinicopathologic factors, genomic alterations, and RFS were established using Cox proportional hazards regression. The PRecur prediction model integrated genomic and clinicopathologic factors using gradient-boosting survival regression for risk group generation and prediction of RFS. A concordance probability estimate (CPE) was used to assess the predictive ability of the PRecur model. RESULTS: Of the 426 patients included in the analysis (286 women [67%]; median age at surgery, 69 [interquartile range, 62-75] years), 318 (75%) had stage I cancer. Association analysis showed that alterations in SMARCA4 (clinicopathologic-adjusted hazard ratio [HR], 2.44; 95% CI, 1.03-5.77; P = .042) and TP53 (clinicopathologic-adjusted HR, 1.73; 95% CI, 1.09-2.73; P = .02) and the fraction of genome altered (clinicopathologic-adjusted HR, 1.03; 95% CI, 1.10-1.04; P = .005) were independently associated with RFS. The PRecur prediction model outperformed the TNM-based model (CPE, 0.73 vs 0.61; difference, 0.12 [95% CI, 0.05-0.19]; P

Purpose: To delineate recurrent oncogenic driver alterations and dysregulated pathways in esophageal adenocarcinoma and to assess their prognostic value. Experimental Design: We analyzed a large cohort of patients with lower esophageal and junctional adenocarcinoma, prospectively sequenced by MSK-IMPACT with high-quality clinical annotation. Patients were subdivided according to treatment intent, curative versus palliative, which closely mirrored clinical staging. Genomic features, alterations, and pathways were examined for association with overall survival using Cox proportional hazard models, adjusted for relevant clinicopathologic factors knowable at the time of diagnosis. Results: Analysis of 487 patients revealed 16 oncogenic driver alterations, mostly amplifications, present in ≥5% of patients. Patients in the palliative-intent cohort, compared with those in the curative-intent cohort, were more likely to have metastatic disease, ERBB2 amplifications, Cell-cycle and RTK–RAS pathway alterations, as well as a higher fraction of genome altered and rate of whole-genome doubling. In multivariable analyses, CDKN2A alterations, SMAD4 alterations, KRAS amplifications, Cell-cycle and TGFβ pathways, and overall number of oncogenic drivers were independently associated with worse overall survival. ERBB2 amplification was associated with improved survival, presumably due to trastuzumab therapy. Conclusions: Our study suggests that higher levels of genomic instability are associated with more advanced disease in esophageal adenocarcinoma. Furthermore, CDKN2A, KRAS, and SMAD4 represent prognostic biomarkers, given their strong association with poor survival.

Purpose: Cutaneous and unknown primary melanomas frequently harbor alterations that activate the MAPK pathway. Whether MAPK driver detection beyond BRAF V600 is clinically relevant in the checkpoint inhibitor era is unknown. Experimental Design: Patients with melanoma were prospectively offered tumor sequencing of 341–468 genes. Oncogenic alterations in 28 RTK-RAS-MAPK pathway genes were used to construct MAPK driver groups. Time to treatment failure (TTF) was determined for patients who received first-line programmed cell death protein 1 (PD-1) monotherapy, nivolumab plus ipilimumab, or subsequent genomically matched targeted therapies. A Cox proportional hazards model was constructed for TTF using driver group and clinical variables. Results: A total of 670 of 696 sequenced melanomas (96%) harbored an oncogenic RTK-RAS-MAPK pathway alteration; 33% had ≥1 driver. Nine driver groups varied by clinical presentation and mutational burden. TTF of PD-1 monotherapy (N = 181) varied by driver, with worse outcomes for NRAS Q61 and BRAF V600 versus NF1 or other alterations (median 4.2, 7.5, 22, and not reached; P < 0.0001). Driver group remained significant, independent of tumor mutational burden and clinical features. TTF did not vary by driver for nivolumab plus ipilimumab (N = 141). Among 172 patients with BRAF V600 wild-type melanoma who progressed on checkpoint blockade, 27 were treated with genomically matched therapy, and eight (30%) derived clinical benefit lasting ≥6 months. Conclusions: Targeted capture multigene sequencing can detect oncogenic RTK-RAS-MAPK pathway alterations in almost all cutaneous and unknown primary melanomas. TTF of PD-1 monotherapy varies by mechanism of ERK activation. Oncogenic kinase fusions can be successfully targeted in immune checkpoint inhibitor–refractory melanoma.

The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, does so in the context of the intact tissue, preserving spatial information that is frequently crucial to understanding a cell’s physiology, function, and behavior. However, the wide-scale adoption of tissue cytometry as a research tool has been limited by the fact that published examples utilize specialized techniques that are beyond the capabilities of most laboratories. Here we describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues. In this workflow, multiphoton microscopy of unlabeled tissue is first conducted to collect autofluorescence and second-harmonic images. The tissue is then labeled with eight fluorescent probes, and imaged using spectral confocal microscopy. The raw 16-channel images are spectrally deconvolved into 8-channel images, and analyzed using the Volumetric Tissue Exploration and Analysis (VTEA) software developed by our group. We applied this workflow to analyze millimeter-scale tissue samples obtained from human nephrectomies and from renal biopsies from individuals diagnosed with diabetic nephropathy, generating a quantitative census of tens of thousands of cells in each. Such analyses can provide useful insights that can be linked to the biology or pathology of kidney disease. The approach utilizes common laboratory techniques, is compatible with most commercially-available confocal microscope systems and all image and data analysis is conducted using the VTEA image analysis software, which is available as a plug-in for ImageJ. Tissue cytometry is a promising new microscopy technique that can be used to enumerate and characterize each cell in a tissue. Here the authors describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues.

Cancer-associated venous thromboembolism (CAT) is a well-described complication of cancer and a leading cause of death in cancer patients. The purpose of this study was to assess potential associations of molecular signatures with CAT, including tumor-specific mutations and the presence of clonal hematopoiesis. We analyzed deep-coverage targeted DNA-sequencing data of >14,000 solid tumor samples using the MSK-IMPACT™ platform to identify somatic alterations associated with VTE. Endpoint was defined as the first instance of cancer-associated pulmonary embolism and/or proximal/distal lower extremity deep vein thrombosis. Cause-specific Cox proportional hazards regression was used, adjusting for pertinent clinical covariates. Of 11,695 evaluable individuals, 72% had metastatic disease at time of IMPACT. Tumor-specific mutations in KRAS (HR=1.34 [1.09-1.64]; adjusted p=0.08), STK11 (HR=2.12 [1.55-2.89]; adjusted pKEAP1 (HR=1.84 [1.21-2.79]; adjusted p=0.07), CTNNB1 (HR=1.73 [1.15-2.60]; adjusted p=0.09), CDKN2B (HR= 1.45 [1.13-1.85], adjusted p=0.07) and MET (HR=1.83 [1.15-2.92]; adjusted p=0.09) were associated with a significantly increased risk of CAT independent of tumor type. Mutations in SETD2 were associated with a decreased risk of CAT (HR=0.35 [0.16-0.79], adjusted p=0.09). The presence of clonal hematopoiesis was not associated with an increased VTE rate. This is the first large-scale analysis to elucidate tumor-specific genomic events associated with CAT. Somatic tumor mutations of STK11, KRAS, CTNNB1, KEAP1, CDKN2B and MET were associated with an increased risk of VTE in solid tumor patients. Further analysis is needed to validate these findings and identify additional molecular signatures unique to individual tumor types.Key PointsTumor mutations in STK11, KRAS, CTNNB1, KEAP1, CDKN2B, MET and SETD2 modulate the risk of cancer-associated thrombosis.The presence of clonal hematopoiesis does not affect the risk of cancer-associated thrombosis.

Purpose: Evaluate response of mismatch repair–deficient (dMMR) rectal cancer to neoadjuvant chemotherapy. Experimental Design: dMMR rectal tumors at Memorial Sloan Kettering Cancer Center (New York, NY) were retrospectively reviewed for characteristics, treatment, and outcomes. Fifty patients with dMMR rectal cancer were identified by IHC and/or microsatellite instability analysis, with initial treatment response compared with a matched MMR-proficient (pMMR) rectal cancer cohort. Germline and somatic mutation analyses were evaluated. Patient-derived dMMR rectal tumoroids were assessed for chemotherapy sensitivity. Results: Of 21 patients receiving neoadjuvant chemotherapy (fluorouracil/oxaliplatin), six (29%) had progression of disease. In comparison, no progression was noted in 63 pMMR rectal tumors (P = 0.0001). Rectal cancer dMMR tumoroids reflected this resistance to chemotherapy. No genomic predictors of chemotherapy response were identified. Of 16 patients receiving chemoradiation, 13 (93%) experienced tumor downstaging; one patient had stable disease, comparable with 48 pMMR rectal cancers. Of 13 patients undergoing surgery, 12 (92%) had early-stage disease. Forty-two (84%) of the 50 patients tested positive for Lynch syndrome with enrichment of germline MSH2 and MSH6 mutations when compared with 193 patients with Lynch syndrome–associated colon cancer (MSH2, 57% vs 36%; MSH6, 17% vs 9%; P < 0.003). Conclusions: Over one-fourth of dMMR rectal tumors treated with neoadjuvant chemotherapy exhibited disease progression. Conversely, dMMR rectal tumors were sensitive to chemoradiation. MMR status should be performed upfront in all locally advanced rectal tumors with careful monitoring for response on neoadjuvant chemotherapy and genetic testing for Lynch syndrome in patients with dMMR rectal cancer.

Gene duplications are a feature of bacterial genomes. In the present work we analyze the extent of gene duplications in the genomes of three microorganisms that belong to the Firmicutes phylum and that are etiologic agents of several nosocomial infections: Staphylococcus aureus, Enterococcus faecium, and Enterococcus faecalis. In all three groups, there is an irregular distribution of duplications in the genomes of the strains analyzed. Whereas in some of the strains duplications are scarce, hundreds of duplications are present in others. In all three species, mobile DNA accounts for a large percentage of the duplicated genes: phage DNA in S. aureus, and plasmid DNA in the enterococci. Duplicates also include core genes. In all three species, a reduced group of genes is duplicated in all strains analyzed. Duplication of the deoC and rpmG genes is a hallmark of S. aureus genomes. Duplication of the gene encoding the PTS IIB subunit is detected in all enterococci genomes. In E. faecalis it is remarkable that the genomes of some strains encode duplicates of the prgB and prgU genes. They belong to the prgABCU cluster, which responds to the presence of the peptide pheromone cCF10 by expressing the surface adhesins PrgA, PrgB, and PrgC.

MC3 Working Group: Rehan Akbani21, Pavana Anur22, Matthew H. Bailey1,2,3, Alex Buchanan9, Kami Chiotti9, Kyle Covington12,23, Allison Creason9, Li Ding1,2,3,20, Kyle Ellrott9, Yu Fan21, Steven Foltz1,2, Gad Getz8,14,15,16, Walker Hale12, David Haussler24,25, Julian M. Hess8,26, Carolyn M. Hutter27, Cyriac Kandoth28, Katayoon Kasaian29,30, Melpomeni Kasapi27, Dave Larson1 , Ignaty Leshchiner8, John Letaw31, Singer Ma32, Michael D. McLellan1,3,20, Yifei Men32, Gordon B. Mills33,34, Beifang Niu35, Myron Peto22, Amie Radenbaugh24, Sheila M. Reynolds36, Gordon Saksena8, Heidi Sofia27, Chip Stewart8, Adam J. Struck31, Joshua M. Stuart24,37, Wenyi Wang21, John N. Weinstein38, David A. Wheeler12,13, Christopher K. Wong24,39, Liu Xi12 & Kai Ye40,41 21Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 22Molecular and Medical Genetics, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 23Castle Biosciences Inc, Friendswood, TX 77546, USA. 24UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 25Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 26Massachusetts General Hospital Center for Cancer Research, Charlestown, MA 02114, USA. 27National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA. 28Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. 29Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada. 30Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC V5Z 4S6, Canada. 31Computational Biology Program, School of Medicine, Oregon Health and Science University, Portland, OR 97239, USA. 32DNAnexus Inc, Mountain View, CA 94040, USA. 33Department of Systems Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA. 34Precision Oncology, OHSU Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. 35Computer Network Information Center, Chinese Academy of Sciences, Beijing, China. 36Institute for Systems Biology, Seattle, WA 98109, USA. 37Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 38Department of Bioinformatics and Computational Biology and Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 39Biomolecular Engineering Department, University of California Santa Cruz, Santa Cruz, CA 95064, USA. 40School of Elect, PCAWG novel somatic mutation calling methods working group: Matthew H. Bailey1,2,3, Beifang Niu35, Matthias Bieg42,43, Paul C. Boutros6,44,45,46, Ivo Buchhalter43,47,48, Adam P. Butler49, Ken Chen50, Zechen Chong51, Li Ding1,2,3,20, Oliver Drechsel52,53, Lewis Jonathan Dursi6,7, Roland Eils47,48,54,55, Kyle Ellrott9, Shadrielle M. G. Espiritu6, Yu Fan21, Robert S. Fulton1,3,20, Shengjie Gao56, Josep L. l. Gelpi57,58, Mark B. Gerstein5,18,19, Gad Getz8,14,15,16, Santiago Gonzalez59,60, Ivo G. Gut52,61, Faraz Hach62,63, Michael C. Heinold47,48, Julian M. Hess8,26, Jonathan Hinton49, Taobo Hu64, Vincent Huang6, Yi Huang65,66, Barbara Hutter43,67,68, David R. Jones49, Jongsun Jung69, Natalie Jäger47, Hyung-Lae Kim70, Kortine Kleinheinz47,48, Sushant Kumar5,19, Yogesh Kumar64, Christopher M. Lalansingh6, Ignaty Leshchiner8, Ivica Letunic71, Dimitri Livitz8, Eric Z. Ma64, Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Michael D. McLellan1,3,20, Andrew Menzies49, Ana Milovanovic57, Morten Muhlig Nielsen73, Stephan Ossowski52,53,74, Nagarajan Paramasivam43,47, Jakob Skou Pedersen73,75, Marc D. Perry76,77, Montserrat Puiggròs57, Keiran M. Raine49, Esther Rheinbay8,14,72, Romina Royo57, S. Cenk Sahinalp62,78,79, Gordon Saksena8, Iman Sarrafi62,78, Matthias Schlesner47,80, Jared T. Simpson6,17, Lucy Stebbings49, Chip Stewart8, Miranda D. Stobbe52,61, Jon W. Teague49, Grace Tiao8, David Torrents57,81, Jeremiah A. Wala8,14,82, Jiayin Wang1,40,66, Wenyi Wang21, Sebastian M. Waszak60, Joachim Weischenfeldt60,83,84, Michael C. Wendl1,10,11, Johannes Werner47,85, Zhenggang Wu64, Hong Xue64, Sergei Yakneen60, Takafumi N. Yamaguchi6, Kai Ye40,41, Venkata D. Yellapantula20,86, Christina K. Yung76 & Junjun Zhang76, PCAWG Consortium: Lauri A. Aaltonen87, Federico Abascal49, Adam Abeshouse88, Hiroyuki Aburatani89, David J. Adams49, Nishant Agrawal90, Keun Soo Ahn91, Sung-Min Ahn92, Hiroshi Aikata93, Rehan Akbani21, Kadir C. Akdemir50, Hikmat Al-Ahmadie88, Sultan T. Al-Sedairy94, Fatima Al-Shahrour95, Malik Alawi96,97, Monique Albert98, Kenneth Aldape99,100, Ludmil B. Alexandrov49,101,102, Adrian Ally30, Kathryn Alsop103, Eva G. Alvarez104,105,106, Fernanda Amary107, Samirkumar B. Amin108,109,110, Brice Aminou76, Ole Ammerpohl111,112, Matthew J. Anderson113, Yeng Ang114, Davide Antonello115, Pavana Anur22, Samuel Aparicio116, Elizabeth L. Appelbaum1,117, Yasuhito Arai118, Axel Aretz119, Koji Arihiro93, Shun-ichi Ariizumi120, Joshua Armenia121, Laurent Arnould122, Sylvia Asa123,124, Yassen Assenov125, Gurnit Atwal6,126,127, Sietse Aukema112,128, J. Todd Auman129, Miriam R. Aure130, Philip Awadalla6,126, Marta Aymerich131, Gary D. Bader126, Adrian Baez-Ortega132, Matthew H. Bailey1,2,3, Peter J. Bailey133, Miruna Balasundaram30, Saianand Balu134, Pratiti Bandopadhayay8,135,136, Rosamonde E. Banks137, Stefano Barbi138, Andrew P. Barbour139,140, Jonathan Barenboim6, Jill Barnholtz-Sloan141,142, Hugh Barr143, Elisabet Barrera59, John Bartlett98,144, Javier Bartolome57, Claudio Bassi115, Oliver F. Bathe145,146, Daniel Baumhoer147, Prashant Bavi148, Stephen B. Baylin149,150, Wojciech Bazant59, Duncan Beardsmore151, Timothy A. Beck152,153, Sam Behjati49, Andreas Behren154, Beifang Niu35, Cindy Bell155, Sergi Beltran52,61, Christopher Benz156, Andrew Berchuck157, Anke K. Bergmann158, Erik N. Bergstrom101,102, Benjamin P. Berman159,160,161, Daniel M. Berney162, Stephan H. Bernhart163,164,165, Rameen Beroukhim8,14,82, Mario Berrios166, Samantha Bersani167, Johanna Bertl73,168, Miguel Betancourt169, Vinayak Bhandari6,44, Shriram G. Bhosle49, Andrew V. Biankin133,170,171,172, Matthias Bieg42,43, Darell Bigner173, Hans Binder163,164, Ewan Birney59, Michael Birrer72, Nidhan K. Biswas174, Bodil Bjerkehagen147,175, Tom Bodenheimer134, Lori Boice176, Giada Bonizzato177, Johann S. De Bono178, Arnoud Boot179,180, Moiz S. Bootwalla166, Ake Borg181, Arndt Borkhardt182, Keith A. Boroevich183,184, Ivan Borozan6, Christoph Borst185, Marcus Bosenberg186, Mattia Bosio52,53,57, Jacqueline Boultwood187, Guillaume Bourque188,189, Paul C. Boutros6,44,45,46, G. Steven Bova190, David T. Bowen49,191, Reanne Bowlby30, David D. L. Bowtell103, Sandrine Boyault192, Rich Boyce59, Jeffrey Boyd193, Alvis Brazma59, Paul Brennan194, Daniel S. Brewer195,196, Arie B. Brinkman197, Robert G. Bristow44,198,199,200,201, Russell R. Broaddus99, Jane E. Brock202, Malcolm Brock203, Annegien Broeks204, Angela N. Brooks8,24,37,82, Denise Brooks30, Benedikt Brors67,205,206, Søren Brunak207,208, Timothy J. C. Bruxner113,209, Alicia L. Bruzos104,105,106, Alex Buchanan9, Ivo Buchhalter43,47,48, Christiane Buchholz210, Susan Bullman8,82, Hazel Burke211, Birgit Burkhardt212, Kathleen H. Burns213,214, John Busanovich8,215, Carlos D. Bustamante216,217, Adam P. Butler49, Atul J. Butte218, Niall J. Byrne76, Anne-Lise Børresen-Dale130,219, Samantha J. Caesar-Johnson220, Andy Cafferkey59, Declan Cahill221, Claudia Calabrese59,60, Carlos Caldas222,223, Fabien Calvo224, Niedzica Camacho178, Peter J. Campbell49,225, Elias Campo226,227, Cinzia Cantù177, Shaolong Cao21, Thomas E. Carey228, Joana Carlevaro-Fita229,230,231, Rebecca Carlsen30, Ivana Cataldo167,177, Mario Cazzola232, Jonathan Cebon154, Robert Cerfolio233, Dianne E. Chadwick234, Dimple Chakravarty235, Don Chalmers236, Calvin Wing Yiu Chan47,237, Kin Chan238, Michelle Chan-Seng-Yue148, Vishal S. Chandan239, David K. Chang133,170, Stephen J. Chanock240, Lorraine A. Chantrill170,241, Aurélien Chateigner76,242, Nilanjan Chatterjee149,243, Kazuaki Chayama93, Hsiao-Wei Chen114,121, Jieming Chen218, Ken Chen50, Yiwen Chen21, Zhaohong Chen244, Andrew D. Cherniack8,82, Jeremy Chien245, Yoke-Eng Chiew246,247, Suet-Feung Chin222,223, Juok Cho8, Sunghoon Cho248, Jung Kyoon Choi249, Wan Choi250, Christine Chomienne251, Zechen Chong51, Su Pin Choo252, Angela Chou170,246, Angelika N. Christ113, Elizabeth L. Christie103, Eric Chuah30, Carrie Cibulskis8, Kristian Cibulskis8, Sara Cingarlini253, Peter Clapham49, Alexander Claviez254, Sean Cleary148,255, Nicole Cloonan256, Marek Cmero257,258,259, Colin C. Collins62, Ashton A. Connor255,260, Susanna L. Cooke133, Colin S. Cooper178,196,261, Leslie Cope149, Vincenzo Corbo138,177, Matthew G. Cordes1,262, Stephen M. Cordner263, Isidro Cortés-Ciriano264,265,266, Kyle Covington12,23, Prue A. Cowin267, Brian Craft24, David Craft8,268, Chad J. Creighton269, Yupeng Cun270, Erin Curley271, Ioana Cutcutache179,180, Karolina Czajka272, Bogdan Czerniak99,273, Rebecca A. Dagg274, Ludmila Danilova149, Maria Vittoria Davi275, Natalie R. Davidson276,277,278,279,280, Helen Davies49,281,282, Ian J. Davis283, Brandi N. Davis-Dusenbery284, Kevin J. Dawson49, Francisco M. De La Vega216,217,285, Ricardo De Paoli-Iseppi211, Timothy Defreitas8, Angelo P. Dei Tos286, Olivier Delaneau287,288,289, John A. Demchok220, Jonas Demeulemeester290,291, German M. Demidov52,53,74, Deniz Demircioğlu292,293, Nening M. Dennis221, Robert E. Denroche148, Stefan C. Dentro49,290,294, Nikita Desai76, Vikram Deshpande72, Amit G. Deshwar295, Christine Desmedt296,297, Jordi Deu-Pons298,299, Noreen Dhalla30, Neesha C. Dhani300, Priyanka Dhingra301,302, Rajiv Dhir303, Anthony DiBiase304, Klev Diamanti305, Li Ding1,2,3,20, Shuai Ding306, Huy Q. Dinh159, Luc Dirix307, HarshaVardhan Doddapaneni12, Nilgun Donmez62,78, Michelle T. Dow244, Ronny Drapkin308, Oliver Drechsel52,53, Ruben M. Drews223, Serge Serge49, Tim Dudderidge150,221, Ana Dueso-Barroso57, Andrew J. Dunford8, Michael Dunn309, Lewis Jonathan Dursi6,7, Fraser R. Duthie133,310, Ken Dutton-Regester311, Jenna Eagles272, Douglas F. Easton312,313, Stuart Edmonds314, Paul A. Edwards223,315, Sandra E. Edwards178, Rosalind A. Eeles178,221, Anna Ehinger316, Juergen Eils54,55, Roland Eils47,48,54,55, Adel El-Naggar99,273, Matthew Eldridge223, Kyle Ellrott9, Serap Erkek60, Georgia Escaramis53,317,318, Shadrielle M. G. Espiritu6, Xavier Estivill53,319, Dariush Etemadmoghadam103, Jorunn E. Eyfjord320, Bishoy M. Faltas280, Daiming Fan321, Yu Fan21, William C. Faquin72, Claudiu Farcas244, Matteo Fassan322, Aquila Fatima323, Francesco Favero324, Nodirjon Fayzullaev76, Ina Felau220, Sian Fereday103, Martin L. Ferguson325, Vincent Ferretti76,326, Lars Feuerbach205, Matthew A. Field327, J. Lynn Fink57,113, Gaetano Finocchiaro328, Cyril Fisher221, Matthew W. Fittall290, Anna Fitzgerald329, Rebecca C. Fitzgerald282, Adrienne M. Flanagan330, Neil E. Fleshner331, Paul Flicek59, John A. Foekens332, Kwun M. Fong333, Nuno A. Fonseca59,334, Christopher S. Foster335,336, Natalie S. Fox6, Michael Fraser6, Scott Frazer8, Milana Frenkel-Morgenstern337, William Friedman338, Joan Frigola298, Catrina C. Fronick1,262, Akihiro Fujimoto184, Masashi Fujita184, Masashi Fukayama339, Lucinda A. Fulton1 , Robert S. Fulton1,3,20, Mayuko Furuta184, P. Andrew Futreal340, Anja Füllgrabe59, Stacey B. Gabriel8, Steven Gallinger148,255,260, Carlo Gambacorti-Passerini341, Jianjiong Gao121, Shengjie Gao56, Levi Garraway82, Øystein Garred342, Erik Garrison49, Dale W. Garsed103, Nils Gehlenborg8,343, Josep L. l. Gelpi57,58, Joshy George110, Daniela S. Gerhard344, Clarissa Gerhauser345, Jeffrey E. Gershenwald346,347, Mark B. Gerstein5,18,19, Moritz Gerstung59,60, Gad Getz8,14,15,16, Mohammed Ghori49, Ronald Ghossein348, Nasra H. Giama349, Richard A. Gibbs12, Anthony J. Gill170,350, Pelvender Gill351, Dilip D. Giri348, Dominik Glodzik49, Vincent J. Gnanapragasam352,353, Maria Elisabeth Goebler354, Mary J. Goldman24, Carmen Gomez355, Santiago Gonzalez59,60, Abel Gonzalez-Perez298,299,356, Dmitry A. Gordenin357, James Gossage358, Kunihito Gotoh359, Ramaswamy Govindan3, Dorthe Grabau360, Janet S. Graham133,361, Robert C. Grant148,260, Anthony R. Green315, Eric Green27, Liliana Greger59, Nicola Grehan282, Sonia Grimaldi177, Sean M. Grimmond362, Robert L. Grossman363, Adam Grundhoff97,364, Gunes Gundem88, Qianyun Guo75, Manaswi Gupta8, Shailja Gupta365, Ivo G. Gut52,61, Marta Gut52,61, Jonathan Göke292,366, Gavin Ha8, Andrea Haake111, David Haan37, Siegfried Haas185, Kerstin Haase290, James E. Haber367, Nina Habermann60, Faraz Hach62,63, Syed Haider6, Natsuko Hama118, Freddie C. Hamdy351, Anne Hamilton267, Mark P. Hamilton368, Leng Han369, George B. Hanna370, Martin Hansmann371, Nicholas J. Haradhvala8,72, Olivier Harismendy102,372, Ivon Harliwong113, Arif O. Harmanci5,373, Eoghan Harrington374, Takanori Hasegawa375, David Haussler24,25, Steve Hawkins223, Shinya Hayami376, Shuto Hayashi375, D. Neil Hayes134,377,378, Stephen J. Hayes379,380, Nicholas K. Hayward211,311, Steven Hazell221, Yao He381, Allison P. Heath382, Simon C. Heath52,61, David Hedley300, Apurva M. Hegde38, David I. Heiman8, Michael C. Heinold47,48, Zachary Heins88, Lawrence E. Heisler152, Eva Hellstrom-Lindberg383, Mohamed Helmy384, Seong Gu Heo385, Austin J. Hepperla134, José María Heredia-Genestar386, Carl Herrmann47,48,387, Peter Hersey211, Julian M. Hess8,26, Holmfridur Hilmarsdottir320, Jonathan Hinton49, Satoshi Hirano388, Nobuyoshi Hiraoka389, Katherine A. Hoadley134,390, Asger Hobolth75,168, Ermin Hodzic78, Jessica I. Hoell182, Steve Hoffmann163,164,165,391, Oliver Hofmann392, Andrea Holbrook166, Aliaksei Z. Holik53, Michael A. Hollingsworth393, Oliver Holmes209,311, Robert A. Holt30, Chen Hong205,237, Eun Pyo Hong385, Jongwhi H. Hong394, Gerrit K. Hooijer395, Henrik Hornshøj73, Fumie Hosoda118, Yong Hou56,396, Volker Hovestadt397, William Howat352, Alan P. Hoyle134, Ralph H. Hruban149, Jianhong Hu12, Taobo Hu64, Xing Hua240, Kuan-lin Huang1,398, Mei Huang176, Mi Ni Huang179,180, Vincent Huang6, Yi Huang65,66, Wolfgang Huber60, Thomas J. Hudson272,399, Michael Hummel400, Jillian A. Hung246,247, David Huntsman401, Ted R. Hupp402, Jason Huse88, Matthew R. Huska403, Barbara Hutter43,67,68, Carolyn M. Hutter27, Daniel Hübschmann48,54,404,405,406, Christine A. Iacobuzio-Donahue348, Charles David Imbusch205, Marcin Imielinski407,408, Seiya Imoto375, William B. Isaacs409, Keren Isaev6,44, Shumpei Ishikawa410, Murat Iskar397, S. M. Ashiqul Islam244, Michael Ittmann411,412,413, Sinisa Ivkovic284, Jose M. G. Izarzugaza414, Jocelyne Jacquemier415, Valerie Jakrot211, Nigel B. Jamieson133,172,416, Gun Ho Jang148, Se Jin Jang417, Joy C. Jayaseelan12, Reyka Jayasinghe1 , Stuart R. Jefferys134, Karine Jegalian418, Jennifer L. Jennings419, Seung-Hyup Jeon250, Lara Jerman60,420, Yuan Ji421,422, Wei Jiao6, Peter A. Johansson311, Amber L. Johns170, Jeremy Johns272, Rory Johnson230,423, Todd A. Johnson183, Clemency Jolly290, Yann Joly424, Jon G. Jonasson320, Corbin D. Jones425, David R. Jones49, David T. W. Jones426,427, Nic Jones428, Steven J. M. Jones30, Jos Jonkers204, Young Seok Ju49,249, Hartmut Juhl429, Jongsun Jung69, Malene Juul73, Randi Istrup Juul73, Sissel Juul374, Natalie Jäger47, Rolf Kabbe47, Andre Kahles276,277,278,279,430, Abdullah Kahraman431,432,433, Vera B. Kaiser434, Hojabr Kakavand211, Sangeetha Kalimuthu148, Christof von Kalle405, Koo Jeong Kang91, Katalin Karaszi351, Beth Karlan435, Rosa Karlić436, Dennis Karsch437, Katayoon Kasaian29,30, Karin S. Kassahn113,438, Hitoshi Katai439, Mamoru Kato440, Hiroto Katoh410, Yoshiiku Kawakami93, Jonathan D. Kay117, Stephen H. Kazakoff209,311, Marat D. Kazanov441,442,443, Maria Keays59, Electron Kebebew444,445, Richard F. Kefford446, Manolis Kellis8,447, James G. Kench170,350,448, Catherine J. Kennedy246,247, Jules N. A. Kerssemakers47, David Khoo273, Vincent Khoo221, Narong Khuntikeo115,449, Ekta Khurana301,302,450,451, Helena Kilpinen117, Hark Kyun Kim452, Hyung-Lae Kim70, Hyung-Yong Kim415, Hyunghwan Kim250, Jaegil Kim8, Jihoon Kim453, Jong K. Kim454, Youngwook Kim455,456, Tari A. King457,458,459, Wolfram Klapper128, Kortine Kleinheinz47,48, Leszek J. Klimczak460, Stian Knappskog49,461, Michael Kneba437, Bartha M. Knoppers424, Youngil Koh462,463, Jan Komorowski305,464, Daisuke Komura410, Mitsuhiro Komura375, Gu Kong415, Marcel Kool426,465, Jan O. Korbel59,60, Viktoriya Korchina12, Andrey Korshunov465, Michael Koscher465, Roelof Koster466, Zsofia Kote-Jarai178, Antonios Koures244, Milena Kovacevic284, Barbara Kremeyer49, Helene Kretzmer164,165, Markus Kreuz467, Savitri Krishnamurthy99,468, Dieter Kube469, Kiran Kumar8, Pardeep Kumar221, Sushant Kumar5,19, Yogesh Kumar64, Ritika Kundra114,121, Kirsten Kübler8,14,72, Ralf Küppers470, Jesper Lagergren383,471, Phillip H. Lai166, Peter W. Laird472, Sunil R. Lakhani473, Christopher M. Lalansingh6, Emilie Lalonde6, Fabien C. Lamaze6, Adam Lambert351, Eric Lander8, Pablo Landgraf474,475, Luca Landoni115, Anita Langerød130, Andrés Lanzós230,231,423, Denis Larsimont476, Erik Larsson477, Mark Lathrop189, Loretta M. S. Lau478, Chris Lawerenz55, Rita T. Lawlor177, Michael S. Lawrence8,72,183, Alexander J. Lazar99,108, Xuan Le479, Darlene Lee30, Donghoon Lee5, Eunjung Alice Lee480, Hee Jin Lee417, Jake June-Koo Lee264,266, Jeong-Yeon Lee481, Juhee Lee482, Ming Ta Michael Lee340, Henry Lee-Six49, Kjong-Van Lehmann276,277,278,279,430, Hans Lehrach483, Dido Lenze400, Conrad R. Leonard209,311, Daniel A. Leongamornlert49,178, Ignaty Leshchiner8, Louis Letourneau484, Ivica Letunic71, Douglas A. Levine88,485, Lora Lewis12, Tim Ley486, Chang Li56,396, Constance H. Li6,44, Haiyan Irene Li30, Jun Li21, Lin Li56, Shantao Li5, Siliang Li56,396, Xiaobo Li56,396, Xiaotong Li5, Xinyue Li56, Yilong Li49, Han Liang21, Sheng-Ben Liang234, Peter Lichter68,397, Pei Lin8, Ziao Lin8,487, W. M. Linehan488, Ole Christian Lingjærde489, Dongbing Liu56,396, Eric Minwei Liu88,301,302, Fei-Fei Liu201,490, Fenglin Liu381,491, Jia Liu492, Xingmin Liu56,396, Julie Livingstone6, Dimitri Livitz8, Naomi Livni221, Lucas Lochovsky5,19,110, Markus Loeffler467, Georgina V. Long211, Armando Lopez-Guillermo493, Shaoke Lou5,19, David N. Louis72, Laurence B. Lovat117, Yiling Lu38, Yong-Jie Lu162,494, Youyong Lu495,496,497, Claudio Luchini167, Ilinca Lungu144,148, Xuemei Luo152, Hayley J. Luxton117, Andy G. Lynch223,315,498, Lisa Lype36, Cristina López111,112, Carlos López-Otín499, Eric Z. Ma64, Yussanne Ma30, Gaetan MacGrogan500, Shona MacRae501, Geoff Macintyre223, Tobias Madsen73, Kazuhiro Maejima184, Andrea Mafficini177, Dennis T. Maglinte166,502, Arindam Maitra174, Partha P. Majumder174, Luca Malcovati232, Salem Malikic62,78, Giuseppe Malleo115, Graham J. Mann211,246,503, Luisa Mantovani-Löffler504, Kathleen Marchal505,506, Giovanni Marchegiani115, Elaine R. Mardis1,193,507, Adam A. Margolin31, Maximillian G. Marin37, Florian Markowetz223,315, Julia Markowski403, Jeffrey Marks508, Tomas Marques-Bonet61,81,386,509, Marco A. Marra30, Luke Marsden351, John W. M. Martens332, Sancha Martin49,510, Jose I. Martin-Subero81,511, Iñigo Martincorena49, Alexander Martinez-Fundichely301,302,451 Yosef E. Maruvka8,26,72, R. Jay Mashl1,2, Charlie E. Massie223, Thomas J. Matthew37, Lucy Matthews178, Erik Mayer221,512, Simon Mayes513, Michael Mayo30, Faridah Mbabaali272, Karen McCune514, Ultan McDermott49, Patrick D. McGillivray19, Michael D. McLellan1,3,20, John D. McPherson148,272,515, John R. McPherson179,180, Treasa A. McPherson260, Samuel R. Meier8, Alice Meng516, Shaowu Meng134, Andrew Menzies49, Neil D. Merrett115,517, Sue Merson178, Matthew Meyerson8,14,82, William U. Meyerson4,5, Piotr A. Mieczkowski518, George L. Mihaiescu76, Sanja Mijalkovic284, Ana Mijalkovic Mijalkovic-Lazic284, Tom Mikkelsen519, Michele Milella253, Linda Mileshkin103, Christopher A. Miller1 , David K. Miller113,170, Jessica K. Miller272, Gordon B. Mills33,34, Ana Milovanovic57, Sarah Minner520, Marco Miotto115, Gisela Mir Arnau267, Lisa Mirabello240, Chris Mitchell103, Thomas J. Mitchell49,315,352, Satoru Miyano375, Naoki Miyoshi375, Shinichi Mizuno521, Fruzsina Molnár-Gábor522, Malcolm J. Moore300, Richard A. Moore30, Sandro Morganella49, Quaid D. Morris127,490, Carl Morrison523,524, Lisle E. Mose134, Catherine D. Moser349, Ferran Muiños298,299, Loris Mularoni298,299, Andrew J. Mungall30, Karen Mungall30, Elizabeth A. Musgrove133, Ville Mustonen525,526,527, David Mutch528, Francesc Muyas52,53,74, Donna M. Muzny12, Alfonso Muñoz59, Jerome Myers529, Ola Myklebost461, Peter Möller530, Genta Nagae89, Adnan M. Nagrial170, Hardeep K. Nahal-Bose76, Hitoshi Nakagama531, Hidewaki Nakagawa184, Hiromi Nakamura118, Toru Nakamura388, Kaoru Nakano184, Tannistha Nandi532, Jyoti Nangalia49, Mia Nastic284, Arcadi Navarro61,81,386, Fabio C. P. Navarro19, David E. Neal223,352, Gerd Nettekoven533, Felicity Newell209,311, Steven J. Newhouse59, Yulia Newton37, Alvin Wei Tian Ng534, Anthony Ng535, Jonathan Nicholson49, David Nicol221, Yongzhan Nie321,536, G. Petur Nielsen72, Morten Muhlig Nielsen73, Serena Nik-Zainal49,281,282,537, Michael S. Noble8, Katia Nones209,311, Paul A. Northcott538, Faiyaz Notta148,539, Brian D. O’Connor76,540, Peter O’Donnell541, Maria O’Donovan282, Sarah O’Meara49, Brian Patrick O’Neill542, J. Robert O’Neill543, David Ocana59, Angelica Ochoa88, Layla Oesper544, Christopher Ogden221, Hideki Ohdan93, Kazuhiro Ohi375, Lucila Ohno-Machado244, Karin A. Oien523,545, Akinyemi I. Ojesina546,547,548, Hidenori Ojima549, Takuji Okusaka550, Larsson Omberg551, Choon Kiat Ong552, Stephan Ossowski52,53,74, German Ott553, B. F. Francis Ouellette76,554, Christine P’ng6, Marta Paczkowska6, Salvatore Paiella115, Chawalit Pairojkul523, Marina Pajic170, Qiang Pan-Hammarström56,555, Elli Papaemmanuil49, Irene Papatheodorou59, Nagarajan Paramasivam43,47, Ji Wan Park385, Joong-Won Park556, Keunchil Park557,558, Kiejung Park559, Peter J. Park264,266, Joel S. Parker518, Simon L. Parsons124, Harvey Pass560, Danielle Pasternack272, Alessandro Pastore276, Ann-Marie Patch209,311, Iris Pauporté251, Antonio Pea115, John V. Pearson209,311, Chandra Sekhar Pedamallu8,14,82, Jakob Skou Pedersen73,75, Paolo Pederzoli115, Martin Peifer270, Nathan A. Pennell561, Charles M. Perou129,518, Marc D. Perry76,77, Gloria M. Petersen562, Myron Peto22, Nicholas Petrelli563, Robert Petryszak59, Stefan M. Pfister426,465,564, Mark Phillips424, Oriol Pich298,299, Hilda A. Pickett478, Todd D. Pihl565, Nischalan Pillay566, Sarah Pinder567, Mark Pinese170, Andreia V. Pinho568, Esa Pitkänen60, Xavier Pivot569, Elena Piñeiro-Yáñez95, Laura Planko533, Christoph Plass345, Paz Polak8,14,15, Tirso Pons570, Irinel Popescu571, Olga Potapova572, Aparna Prasad52, Shaun R. Preston573, Manuel Prinz47, Antonia L. Pritchard311, Stephenie D. Prokopec6, Elena Provenzano574, Xose S. Puente499, Sonia Puig176, Montserrat Puiggròs57, Sergio Pulido-Tamayo505,506, Gulietta M. Pupo246, Colin A. Purdie575, Michael C. Quinn209,311, Raquel Rabionet52,53,576, Janet S. Rader577, Bernhard Radlwimmer397, Petar Radovic284, Benjamin Raeder60, Keiran M. Raine49, Manasa Ramakrishna49, Kamna Ramakrishnan49, Suresh Ramalingam578, Benjamin J. Raphael579, W. Kimryn Rathmell580, Tobias Rausch60, Guido Reifenberger475, Jüri Reimand6,44, Jorge Reis-Filho348, Victor Reuter348, Iker Reyes-Salazar298, Matthew A. Reyna579, Sheila M. Reynolds36, Esther Rheinbay8,14,72, Yasser Riazalhosseini189, Andrea L. Richardson323, Julia Richter111,128, Matthew Ringel581, Markus Ringnér181, Yasushi Rino582, Karsten Rippe405, Jeffrey Roach583, Lewis R. Roberts349, Nicola D. Roberts49, Steven A. Roberts584, A. Gordon Robertson30, Alan J. Robertson113, Javier Bartolomé Rodriguez57, Bernardo Rodriguez-Martin104,105,106, F. Germán Rodríguez-González83,332, Michael H. A. Roehrl44,123,148,234,585,586, Marius Rohde587, Hirofumi Rokutan440, Gilles Romieu588, Ilse Rooman170, Tom Roques262, Daniel Rosebrock8, Mara Rosenberg8,72, Philip C. Rosenstiel589, Andreas Rosenwald590, Edward W. Rowe221,591, Romina Royo57, Steven G. Rozen179,180,592, Yulia Rubanova17,127, Mark A. Rubin423,593,594,595,596, Carlota Rubio-Perez298,299,597, Vasilisa A. Rudneva60, Borislav C. Rusev177, Andrea Ruzzenente598, Gunnar Rätsch276,277,278,279,280,430, Radhakrishnan Sabarinathan298,299,599, Veronica Y. Sabelnykova6, Sara Sadeghi30, S. Cenk Sahinalp62,78,79, Natalie Saini357, Mihoko Saito-Adachi440, Gordon Saksena8, Adriana Salcedo6, Roberto Salgado600, Leonidas Salichos5,19, Richard Sallari8, Charles Saller601, Roberto Salvia115, Michelle Sam272, Jaswinder S. Samra115,602, Francisco Sanchez-Vega114,121, Chris Sander276,603,604, Grant Sanders134, Rajiv Sarin605, Iman Sarrafi62,78, Aya Sasaki-Oku184, Torill Sauer489, Guido Sauter520, Robyn P. M. Saw211, Maria Scardoni167, Christopher J. Scarlett170,606, Aldo Scarpa177, Ghislaine Scelo194, Dirk Schadendorf68,607, Jacqueline E. Schein30, Markus B. Schilhabel589, Matthias Schlesner47,80, Thorsten Schlomm84,608, Heather K. Schmidt1 , Sarah-Jane Schramm246, Stefan Schreiber609, Nikolaus Schultz121, Steven E. Schumacher8,323, Roland F. Schwarz59,403,405,610, Richard A. Scolyer211,448,602, David Scott428, Ralph Scully611, Raja Seethala612, Ayellet V. Segre8,613, Iris Selander260, Colin A. Semple434, Yasin Senbabaoglu276, Subhajit Sengupta614, Elisabetta Sereni115, Stefano Serra585, Dennis C. Sgroi72, Mark Shackleton103, Nimish C. Shah352, Sagedeh Shahabi234, Catherine A. Shang329, Ping Shang211, Ofer Shapira8,323, Troy Shelton271, Ciyue Shen603,604, Hui Shen615, Rebecca Shepherd49, Ruian Shi490, Yan Shi134, Yu-Jia Shiah6, Tatsuhiro Shibata118,616, Juliann Shih8,82, Eigo Shimizu375, Kiyo Shimizu617, Seung Jun Shin618, Yuichi Shiraishi375, Tal Shmaya285, Ilya Shmulevich36, Solomon I. Shorser6, Charles Short59, Raunak Shrestha62, Suyash S. Shringarpure217, Craig Shriver619, Shimin Shuai6,126, Nikos Sidiropoulos83, Reiner Siebert112,620, Anieta M. Sieuwerts332, Lina Sieverling205,237, Sabina Signoretti202,621, Katarzyna O. Sikora177, Michele Simbolo138, Ronald Simon520, Janae V. Simons134, Jared T. Simpson6,17, Peter T. Simpson473, Samuel Singer115,458, Nasa Sinnott-Armstrong8,217, Payal Sipahimalani30, Tara J. Skelly390, Marcel Smid332, Jaclyn Smith622, Karen Smith-McCune514, Nicholas D. Socci276, Heidi J. Sofia27, Matthew G. Soloway134, Lei Song240, Anil K. Sood623,624,625, Sharmila Sothi626, Christos Sotiriou244, Cameron M. Soulette37, Paul N. Span627, Paul T. Spellman22, Nicola Sperandio177, Andrew J. Spillane211, Oliver Spiro8, Jonathan Spring628, Johan Staaf181, Peter F. Stadler163,164,165, Peter Staib629, Stefan G. Stark277,279,618,630, Lucy Stebbings49, Ólafur Andri Stefánsson631, Oliver Stegle59,60,632, Lincoln D. Stein6,126, Alasdair Stenhouse633, Chip Stewart8, Stephan Stilgenbauer634, Miranda D. Stobbe52,61, Michael R. Stratton49, Jonathan R. Stretch211, Adam J. Struck31, Joshua M. Stuart24,37, Henk G. Stunnenberg396,635, Hong Su56,396, Xiaoping Su99, Ren X. Sun6, Stephanie Sungalee60, Hana Susak52,53, Akihiro Suzuki89,636, Fred Sweep637, Monika Szczepanowski128, Holger Sültmann67,638, Takashi Yugawa617, Angela Tam30, David Tamborero298,299, Benita Kiat Tee Tan639, Donghui Tan518, Patrick Tan180,532,592,640, Hiroko Tanaka375, Hirokazu Taniguchi616, Tomas J. Tanskanen641, Maxime Tarabichi49,290, Roy Tarnuzzer220, Patrick Tarpey642, Morgan L. Taschuk152, Kenji Tatsuno89, Simon Tavaré223,643, Darrin F. Taylor113, Amaro Taylor-Weiner8, Jon W. Teague49, Bin Tean Teh180,592,640,644,645, Varsha Tembe246, Javier Temes104,105, Kevin Thai76, Sarah P. Thayer393, Nina Thiessen30, Gilles Thomas646, Sarah Thomas221, Alan Thompson221, Alastair M. Thompson633, John F. Thompson211, R. Houston Thompson647, Heather Thorne103, Leigh B. Thorne176, Adrian Thorogood424, Grace Tiao8, Nebojsa Tijanic284, Lee E. Timms272, Roberto Tirabosco648, Marta Tojo106, Stefania Tommasi649, Christopher W. Toon170, Umut H. Toprak48,650, David Torrents57,81, Giampaolo Tortora651,652, Jörg Tost653, Yasushi Totoki118, David Townend654, Nadia Traficante103, Isabelle Treilleux655,656, Jean-Rémi Trotta61, Lorenz H. P. Trümper469, Ming Tsao124,539, Tatsuhiko Tsunoda183,657,658,659, Jose M. C. Tubio104,105,106, Olga Tucker660, Richard Turkington661, Daniel J. Turner513, Andrew Tutt323, Masaki Ueno376, Naoto T. Ueno662, Christopher Umbricht151,213,663, Husen M. Umer305,664, Timothy J. Underwood665, Lara Urban59,60, Tomoko Urushidate616, Tetsuo Ushiku339, Liis Uusküla-Reimand666,667, Alfonso Valencia57,81, David J. Van Den Berg166, Steven Van Laere307, Peter Van Loo290,291, Erwin G. Van Meir668, Gert G. Van den Eynden307, Theodorus Van der Kwast123, Naveen Vasudev137, Miguel Vazquez57,669, Ravikiran Vedururu267, Umadevi Veluvolu518, Shankar Vembu490,670, Lieven P. C. Verbeke506,671, Peter Vermeulen307, Clare Verrill351,672, Alain Viari177, David Vicente57, Caterina Vicentini177, K. Vijay Raghavan365, Juris Viksna673, Ricardo E. Vilain674, Izar Villasante57, Anne Vincent-Salomon635, Tapio Visakorpi190, Douglas Voet8, Paresh Vyas311,351, Ignacio Vázquez-García49,86,675,676, Nick M. Waddell209, Nicola Waddell209,311, Claes Wadelius677, Lina Wadi6, Rabea Wagener111,112, Jeremiah A. Wala8,14,82, Jian Wang56, Jiayin Wang1,40,66, Linghua Wang12, Qi Wang465, Wenyi Wang21, Yumeng Wang21, Zhining Wang220, Paul M. Waring523, Hans-Jörg Warnatz483, Jonathan Warrell5,19, Anne Y. Warren352,678, Sebastian M. Waszak60, David C. Wedge49,294,679, Dieter Weichenhan345, Paul Weinberger680, John N. Weinstein38, Joachim Weischenfeldt60,83,84, Daniel J. Weisenberger166, Ian Welch681, Michael C. Wendl1,10,11, Johannes Werner47,85, Justin P. Whalley61,682, David A. Wheeler12,13, Hayley C. Whitaker117, Dennis Wigle683, Matthew D. Wilkerson518, Ashley Williams244, James S. Wilmott211, Gavin W. Wilson6,148, Julie M. Wilson148, Richard K. Wilson1,684, Boris Winterhoff685, Jeffrey A. Wintersinger17,127,384, Maciej Wiznerowicz686,687, Stephan Wolf688, Bernice H. Wong689, Tina Wong1,30, Winghing Wong690, Youngchoon Woo250, Scott Wood209,311, Bradly G. Wouters44, Adam J. Wright6, Derek W. Wright133,691, Mark H. Wright217, Chin-Lee Wu72, Dai-Ying Wu285, Guanming Wu692, Jianmin Wu170, Kui Wu56,396, Yang Wu179,180, Zhenggang Wu64, Liu Xi12, Tian Xia693, Qian Xiang76, Xiao Xiao66, Rui Xing497, Heng Xiong56,396, Qinying Xu209,311, Yanxun Xu694, Hong Xue64, Shinichi Yachida118,695, Sergei Yakneen60, Rui Yamaguchi375, Takafumi N. Yamaguchi6, Masakazu Yamamoto120, Shogo Yamamoto89, Hiroki Yamaue376, Fan Yang490, Huanming Yang56, Jean Y. Yang696, Liming Yang220, Lixing Yang697, Shanlin Yang306, Tsun-Po Yang270, Yang Yang369, Xiaotong Yao408,698, Marie-Laure Yaspo483, Lucy Yates49, Christina Yau156, Chen Ye56,396, Kai Ye40,41, Venkata D. Yellapantula20,86, Christopher J. Yoon249, Sung-Soo Yoon463, Fouad Yousif6, Jun Yu699, Kaixian Yu700, Willie Yu701, Yingyan Yu702, Ke Yuan223,510,703, Yuan Yuan21, Denis Yuen6, Takashi Yugawa617, Christina K. Yung76, Olga Zaikova704, Jorge Zamora49,104,105,106, Marc Zapatka397, Jean C. Zenklusen220, Thorsten Zenz67, Nikolajs Zeps705,706, Cheng-Zhong Zhang8,707, Fan Zhang381, Hailei Zhang8, Hongwei Zhang494, Hongxin Zhang121, Jiashan Zhang220, Jing Zhang5, Junjun Zhang76, Xiuqing Zhang56, Xuanping Zhang66,369, Yan Zhang5,708,709, Zemin Zhang381,710, Zhongming Zhao711, Liangtao Zheng381, Xiuqing Zheng381, Wanding Zhou615, Yong Zhou56, Bin Zhu240, Hongtu Zhu700,712, Jingchun Zhu24, Shida Zhu56,396, Lihua Zou713, Xueqing Zou49, Anna deFazio246,247,714, Nicholas van As221, Carolien H. M. van Deurzen715, Marc J. van de Vijver523, L. van’t Veer716 & Christian von Mering433,717, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

PURPOSE Heterogeneity in tumor mutational burden (TMB) quantification across sequencing platforms limits the application and further study of this potential biomarker of response to immune checkpoint inhibitors (ICIs). We hypothesized that harmonization of TMB across platforms would enable integration of distinct clinical data sets to better characterize the association between TMB and ICI response. METHODS Cohorts of patients with non–small-cell lung cancer sequenced by 1 of 3 targeted panels or by whole-exome sequencing (WES) were compared (N = 7,297). TMB was calculated uniformly and compared across cohorts. TMB distributions were harmonized by applying a normal transformation followed by standardization to z scores. In subcohorts of patients treated with ICIs (Dana-Farber Cancer Institute n = 272; Memorial Sloan Kettering Cancer Center n = 227), the association between TMB and outcome was assessed. Durable clinical benefit (DCB) was defined as responsive/stable disease lasting ≥ 6 months. RESULTS TMB values were higher in the panel cohorts than in the WES cohort. Average mutation rates per gene were highly concordant across cohorts (Pearson’s correlation coefficients, 0.842-0.866). Subsetting the WES cohort by gene panels only partially reproduced the observed differences in TMB. Standardization of TMB into z scores harmonized TMB distributions and enabled integration of the ICI-treated subcohorts. Simulations indicated that cohorts > 900 are necessary for this approach. TMB did not associate with response in never-smokers or patients who harbor targetable driver alterations, although these analyses were underpowered. An increase of TMB thresholds increased DCB rate, but DCB rates within deciles varied. Receiver operating characteristic curves yielded an area under the curve of 0.614, with no natural inflection point. CONCLUSION The z score conversion harmonizes TMB values and enables integration of data sets derived from different sequencing panels. Clinical and biologic features may provide context to the clinical application of TMB and warrant additional study.

BACKGROUND: Trastuzumab with cisplatin and fluoropyrimidine is the standard treatment in metastatic HER2-positive gastric or gastroesophageal (GE) junction adenocarcinoma, however there is limited data on the efficacy of trastuzumab in combination with a three-drug regimen in this setting. We examined the efficacy and safety of modified docetaxel, cisplatin and 5 fluorouracil (mDCF) plus trastuzumab in a single-arm multicenter phase II trial. METHODS: Previously untreated patients with HER2-positive metastatic gastric or GE junction adenocarcinoma were treated with mDCF and trastuzumab every 2 weeks. The primary endpoint was 6-month progression free survival (PFS); secondary endpoints included objective response rate, overall survival (OS), and toxicity. RESULTS: We enrolled 26 patients with metastatic HER2-positive gastric or GE junction adenocarcinoma between February 2011 and June 2015. The median age of patients was 62 years; 96% had a Karnofsky performance status equal to or greater than 80%. With a median follow-up of 25.4 months, the 6-month PFS was 73% (95% CI, 51% - 86%). The objective response rate was 65%, the median PFS was 13 months (95% CI, 6.4 – 20.7) and the median OS was 24.9 months (95% CI, 14.4 – 42.5). Grade 3/4 toxicities included neutropenia (42%), fatigue (23%), and hypophosphatemia (15%). There were no episodes of febrile neutropenia. CONCLUSION: The combination of mDCF and trastuzumab is effective and safe in patients with metastatic HER2-positive gastric or GE junction adenocarcinoma and can be considered as an option for selected patients. This trial is registered at ClinicalTrials.gov, number .

Estrogen receptor alpha (ERα) is a ligand-activated nuclear receptor that directs proliferation and differentiation in selected cancer cell types including mammary-derived carcinomas. These master-regulatory functions of ERα require trans-acting elements such as the pioneer factor FOXA1 to establish a genomic landscape conducive to ERα control. Here, we identify the H3K4 methyltransferase KMT2C as necessary for hormone-driven ERα activity and breast cancer proliferation. KMT2C knockdown suppresses estrogen-dependent gene expression and causes H3K4me1 and H3K27ac loss selectively at ERα enhancers. Correspondingly, KMT2C loss impairs estrogen-driven breast cancer proliferation but has no effect on ER- breast cells. Whereas KMT2C loss disrupts estrogen-driven proliferation, it conversely promotes tumor outgrowth under hormone-depleted conditions. In accordance, KMT2C is one of the most frequently mutated genes in ER-positive breast cancer with KMT2C deletion correlating with significantly shorter progression-free survival on anti-estrogen therapy. From a therapeutic standpoint, KMT2C-depleted cells that develop hormone-independence retain their dependence on ERα, displaying ongoing sensitivity to ERα antagonists. We conclude that KMT2C is a key regulator of ERα activity whose loss uncouples breast cancer proliferation from hormone abundance.

Study Design Comparative cohort study. Objective To compare coronal deformity control, lengthening efficacy, and sagittal alignment between distraction-based growing rod constructs utilizing tandem versus wedding band connectors. Summary of Background Data Different construct designs exist for growing rod treatment of early-onset scoliosis. All use a version of a rod connector, with the two main types being tandem and wedding band. Little data exist to quantify the impact of connector choice on radiographic outcomes of treatment. Methods A multicenter database of prospectively and retrospectively collected data on early-onset scoliosis patients was reviewed. Patients of any thoracic or thoracolumbar coronal plane deformity whose initial growing rod treatment was initiated before age 10 years and underwent at least 3 years of dual growing rod treatment with either tandem or wedding band connectors were included. Preoperative, immediate postoperative, and prefinal radiographs were reviewed and compared in regard to major curve magnitude, T1–T12 and T1–S1 spinal length, length of instrumentation, and sagittal plane measures. Results A total of 209 patients were included. The overall percent change from preoperative to prefinal in all radiographic parameters was not different between the two groups indicating similar efficacy in treatment. After controlling for institutional variation, the improvement of the major coronal Cobb angle from preoperative to prefinal was statistically improved for the tandem group (34° vs. 29°, p = .002) and the difference in T5–T12 kyphosis from preoperative to prefinal was significantly different between the groups (−6° vs. +1.3°, p = .008). Conclusion We identified little difference in the effects of connector type on radiographic outcomes of patients treated with traditional growing rod, which indicates that both wedding band and tandem connectors function similarly. The small differences detected suggest that tandem connectors may improve major Cobb correction, and wedding band connectors may maintain thoracic kyphosis over time. Level of Evidence Level III

Summary: This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smoking and/or human papillomavirus (HPV). SCCs harbor 3q, 5p, and other recurrent chromosomal copy-number alterations (CNAs), DNA mutations, and/or aberrant methylation of genes and microRNAs, which are correlated with the expression of multi-gene programs linked to squamous cell stemness, epithelial-to-mesenchymal differentiation, growth, genomic integrity, oxidative damage, death, and inflammation. Low-CNA SCCs tended to be HPV(+) and display hypermethylation with repression of TET1 demethylase and FANCF, previously linked to predisposition to SCC, or harbor mutations affecting CASP8, RAS-MAPK pathways, chromatin modifiers, and immunoregulatory molecules. We uncovered hypomethylation of the alternative promoter that drives expression of the ΔNp63 oncogene and embedded miR944. Co-expression of immune checkpoint, T-regulatory, and Myeloid suppressor cells signatures may explain reduced efficacy of immune therapy. These findings support possibilities for molecular classification and therapeutic approaches. : Campbell et al. reveal that squamous cell cancers from different tissue sites may be distinguished from other cancers and subclassified molecularly by recurrent alterations in chromosomes, DNA methylation, messenger and microRNA expression, or by mutations. These affect squamous cell pathways and programs that provide candidates for therapy. Keywords: genomics, transcriptomics, proteomics, head and neck squamous cell carcinoma, lung squamous cell carcinoma, esophageal squamous cell carcinoma, cervical squamous cell carcinoma, bladder carcinoma with squamous differentiation, human papillomavirus

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.

SUMMARY Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes—modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility., In Brief Peng et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to characterize tumor subtypes based on the expression of seven metabolic pathways. They find metabolic expression subtypes are associated with patient survivals and suggest the therapeutic and predictive relevance of subtype-related master regulators.

Purpose Treatment of advanced non–small-cell lung cancer with immune checkpoint inhibitors (ICIs) is characterized by durable responses and improved survival in a subset of patients. Clinically available tools to optimize use of ICIs and understand the molecular determinants of response are needed. Targeted next-generation sequencing (NGS) is increasingly routine, but its role in identifying predictors of response to ICIs is not known. Methods Detailed clinical annotation and response data were collected for patients with advanced non–small-cell lung cancer treated with anti–programmed death-1 or anti–programmed death-ligand 1 [anti-programmed cell death (PD)-1] therapy and profiled by targeted NGS (MSK-IMPACT; n = 240). Efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, and durable clinical benefit (DCB) was defined as partial response/stable disease that lasted > 6 months. Tumor mutation burden (TMB), fraction of copy number–altered genome, and gene alterations were compared among patients with DCB and no durable benefit (NDB). Whole-exome sequencing (WES) was performed for 49 patients to compare quantification of TMB by targeted NGS versus WES. Results Estimates of TMB by targeted NGS correlated well with WES (ρ = 0.86; P < .001). TMB was greater in patients with DCB than with NDB ( P = .006). DCB was more common, and progression-free survival was longer in patients at increasing thresholds above versus below the 50th percentile of TMB (38.6% v 25.1%; P < .001; hazard ratio, 1.38; P = .024). The fraction of copy number–altered genome was highest in those with NDB. Variants in EGFR and STK11 associated with a lack of benefit. TMB and PD-L1 expression were independent variables, and a composite of TMB plus PD-L1 further enriched for benefit to ICIs. Conclusion Targeted NGS accurately estimates TMB and elevated TMB further improved likelihood of benefit to ICIs. TMB did not correlate with PD-L1 expression; both variables had similar predictive capacity. The incorporation of both TMB and PD-L1 expression into multivariable predictive models should result in greater predictive power.

Purpose: KRAS mutations occur in approximately 25% of patients with non–small cell lung cancer (NSCLC). Despite the uniform presence of KRAS mutations, patients with KRAS-mutant NSCLC can have a heterogeneous clinical course. As the pattern of co-occurring mutations may describe different biological subsets of patients with KRAS-mutant lung adenocarcinoma, we explored the effects of co-occurring mutations on patient outcomes and response to therapy.Experimental Design: We identified patients with advanced KRAS-mutant NSCLC and evaluated the most common co-occurring genomic alterations. Multivariate analyses were performed incorporating the most frequent co-mutations and clinical characteristics to evaluate association with overall survival as well as response to platinum–pemetrexed chemotherapy and immune checkpoint inhibitors.Results: Among 330 patients with advanced KRAS-mutant lung cancers, the most frequent co-mutations were found in TP53 (42%), STK11 (29%), and KEAP1/NFE2L2 (27%). In a multivariate analysis, there was a significantly shorter survival in patients with co-mutations in KEAP1/NFE2L2 [HR, 1.96; 95% confidence interval (CI), 1.33–2.92; P ≤ 0.001]. STK11 (HR, 1.3; P = 0.22) and TP53 (HR 1.11, P = 0.58) co-mutation statuses were not associated with survival. Co-mutation in KEAP1/NFE2L2 was also associated with shorter duration of initial chemotherapy (HR, 1.64; 95% CI, 1.04–2.59; P = 0.03) and shorter overall survival from initiation of immune therapy (HR, 3.54; 95% CI, 1.55–8.11; P = 0.003).Conclusions: Among people with KRAS-mutant advanced NSCLC, TP53, STK11, and KEAP1/NFE2L2 are the most commonly co-occurring somatic genomic alterations. Co-mutation of KRAS and KEAP1/ NFE2L2 is an independent prognostic factor, predicting shorter survival, duration of response to initial platinum-based chemotherapy, and survival from the start of immune therapy. Clin Cancer Res; 24(2); 334–40. ©2017 AACR.

Item does not contain fulltext STUDY DESIGN: Retrospective study of prospectively collected data. OBJECTIVES: The purpose of this study was to evaluate the relationship between apical vertebral axial rotation and pretreatment patient-reported health-related quality of life (HRQOL), disability, and pain in patients with adult degenerative scoliosis (ADS) using a novel radiographic software tool. SUMMARY OF BACKGROUND DATA: Recent studies have demonstrated that in ADS, sagittal and coronal plane deformity are weakly to moderately associated with HRQOL, disability, and pain. However, as ADS is a three-dimensional spinal deformity, the impact of axial malalignment on HRQOL is yet to be determined. METHODS: A total of 74 ADS patients were enrolled. HRQOL measures included the Short Form-36v2 (SF-36v2) and Scoliosis Research Society questionnaire (SRS-22r). Disability and pain measures included the Oswestry Disability Index (ODI) and numeric rating scale back and leg pain. Radiographic measures included Cobb angle (CA), sagittal spinopelvic parameters, lateral and anteroposterior (AP) translation of the apical vertebra. The amount of apical vertebral axial rotation was measured on digital AP radiograph images using a novel software technology. Subjects were stratified into four clinical groups based on the degree of apical vertebral axial rotation. RESULTS: Apical vertebral axial rotation showed no association with lateral (r = 0.21; p = .15) and AP (r = 0.08, p = .80) translation of the apical vertebra. A significant moderate association was found between apical vertebral axial rotation and Cobb angle (r = 0.57; p < .05). Patients in the group with the highest degree of apical vertebral axial rotation reported significantly worse ODI and SRS-22r Subtotal and Pain scores (p < .05), irrespective of sagittal spinopelvic parameters. CONCLUSIONS: This is the first study that reports on the association between apical vertebral axial rotation and pretreatment HRQOL, disability, and pain in ADS. This study suggests that increased apical vertebral axial rotation is associated with suboptimal pretreatment health status scores. LEVEL OF EVIDENCE: Level III.

The incidence of esophagogastric cancer is rapidly rising, but only a minority of patients derive durable benefit from current therapies. Chemotherapy as well as anti-HER2 and PD-1 antibodies are standard treatments. To identify predictive biomarkers of drug sensitivity and mechanisms of resistance, we implemented prospective tumor sequencing of patients with metastatic esophagogastric cancer. There was no association between homologous recombination deficiency defects and response to platinum-based chemotherapy. Patients with microsatellite instability–high tumors were intrinsically resistant to chemotherapy but more likely to achieve durable responses to immunotherapy. The single Epstein–Barr virus–positive patient achieved a durable, complete response to immunotherapy. The level of ERBB2 amplification as determined by sequencing was predictive of trastuzumab benefit. Selection for a tumor subclone lacking ERBB2 amplification, deletion of ERBB2 exon 16, and comutations in the receptor tyrosine kinase, RAS, and PI3K pathways were associated with intrinsic and/or acquired trastuzumab resistance. Prospective genomic profiling can identify patients most likely to derive durable benefit to immunotherapy and trastuzumab and guide strategies to overcome drug resistance. Significance: Clinical application of multiplex sequencing can identify biomarkers of treatment response to contemporary systemic therapies in metastatic esophagogastric cancer. This large prospective analysis sheds light on the biological complexity and the dynamic nature of therapeutic resistance in metastatic esophagogastric cancers. Cancer Discov; 8(1); 49–58. ©2017 AACR. See related commentary by Sundar and Tan, p. 14. See related article by Pectasides et al., p. 37. This article is highlighted in the In This Issue feature, p. 1

Malignant peritoneal mesothelioma (PeM) is a rare and fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM exist. Some immune checkpoint inhibitor studies of mesothelioma have found positivity to be associated with a worse prognosis.To search for novel therapeutic targets for PeM, we performed a comprehensive integrative multi-omics analysis of the genome, transcriptome, and proteome of 19 treatment-naïve PeM, and in particular, we examined BAP1 mutation and copy number status and its relationship to immune checkpoint inhibitor activation.We found that PeM could be divided into tumors with an inflammatory tumor microenvironment and those without and that this distinction correlated with haploinsufficiency of BAP1. To further investigate the role of BAP1, we used our recently developed cancer driver gene prioritization algorithm, HIT'nDRIVE, and observed that PeM with BAP1 haploinsufficiency form a distinct molecular subtype characterized by distinct gene expression patterns of chromatin remodeling, DNA repair pathways, and immune checkpoint receptor activation. We demonstrate that this subtype is correlated with an inflammatory tumor microenvironment and thus is a candidate for immune checkpoint blockade therapies.Our findings reveal BAP1 to be a potential, easily trackable prognostic and predictive biomarker for PeM immunotherapy that refines PeM disease classification. BAP1 stratification may improve drug response rates in ongoing phases I and II clinical trials exploring the use of immune checkpoint blockade therapies in PeM in which BAP1 status is not considered. This integrated molecular characterization provides a comprehensive foundation for improved management of a subset of PeM patients.

Background While electroconvulsive therapy is widely regarded as a lifesaving and safe procedure, evidence regarding its effects on myocardial cell injury is sparse. The objective of this investigation was to determine the incidence and magnitude of new cardiac troponin elevation after electroconvulsive therapy using a novel high-sensitivity cardiac troponin I assay. Methods This was a prospective cohort study in adult patients undergoing electroconvulsive therapy in a single academic center (up to three electroconvulsive therapy treatments per patient). The primary outcome was new high-sensitivity cardiac troponin I elevation after electroconvulsive therapy, defined as an increase of high-sensitivity cardiac troponin I greater than 100% after electroconvulsive therapy compared to baseline with at least one value above the limit of quantification (10 ng/l). Twelve-lead electrocardiogram and high-sensitivity cardiac troponin I values were obtained before and 15 to 30 min after electroconvulsive therapy; in a subset of patients, an additional 2-h high-sensitivity cardiac troponin I value was obtained. Results The final study population was 100 patients and a total of 245 electroconvulsive therapy treatment sessions. Eight patients (8 of 100; 8%) experienced new high-sensitivity cardiac troponin I elevation after electroconvulsive therapy with a cumulative incidence of 3.7% (9 of 245 treatments; one patient had two high-sensitivity cardiac troponin I elevations), two of whom had a non–ST-elevation myocardial infarction (incidence 2 of 245; 0.8%). Median high-sensitivity cardiac troponin I concentrations did not increase significantly after electroconvulsive therapy. Tachycardia and/or elevated systolic blood pressure developed after approximately two thirds of electroconvulsive therapy treatments. Conclusions Electroconvulsive therapy appears safe from a cardiac standpoint in a large majority of patients. A small subset of patients with preexisting cardiovascular risk factors, however, may develop new cardiac troponin elevation after electroconvulsive therapy, the clinical relevance of which is unclear in the absence of signs of myocardial ischemia.

Rectal cancer (RC) is a challenging disease to treat that requires chemotherapy, radiation, and surgery to optimize outcomes for individual patients. No accurate model of RC exists to answer fundamental research questions relevant to patients. We established a biorepository of 65 patient-derived RC organoid cultures (tumoroids) from patients with primary, metastatic, or recurrent disease. RC tumoroids retained molecular features of the tumors from which they were derived, and their ex vivo responses to clinically relevant chemotherapy and radiation treatment correlated with the clinical responses noted in individual patients’ tumors. Upon engraftment into murine rectal mucosa, human RC tumoroids gave rise to invasive RC followed by metastasis to lung and liver. Importantly, engrafted tumors displayed the heterogenous sensitivity to chemotherapy observed clinically. Thus, the biology and drug sensitivity of RC clinical isolates can be efficiently interrogated using an organoid-based, ex vivo platform coupled with in vivo endoluminal propagation in animals.

Introduction and Objectives: The main objective is to analyze the impact of incorporating a mobile application to the process of smoking cessation in terms of efficacy after one-year follow-up. Methods: The trial takes place within the SmokeFreenBrain European project, financed by the H2020 program under GA No 681120 and registered in Clinicaltrials.govNCT03553173, performed from October 2017 to October 2018. 240 patients from the Smoking Cessation Office were recruited. Randomized open trial with 4 parallel groups (2 control groups - bupropion or varenicline - and 2 intervention groups - bupropion + app or varenicline + app). Data were collected regarding epidemiology, clinical features, Fagerstrom test, Richmond test, EuroQoL-5D-5L quality of life test, co-oximetry and cotinine test. Results: 97 out of 240 patients recruited completed the 12-month follow-up. The sample was made up of 49 men and 46 women, with a mean (±SD) age of 50.3 ± 9.08. Out of 97 patients, 46.5% were assigned to the control group and 53.7% to the intervention group. Fagerstrom test showed a nicotine dependence of 5.2 ± 2.1 and 5.1 ± 1.8 in the control group and the intervention group, respectively. Richmond test assessed the motivation to quit smoking, measuring 9.4 ± 0.8 in the control group and 9.4 ± 0.8 in the intervention group. Efficacy (abstinence after a 12-month follow-up) was of 64.7% in the intervention group and of 40.9% in the control group (p=0.002), leaving aside the pharmacological treatment prescribed. Conclusions: Using a motivational mobile phone App together with pharmacological treatment is significantly more effective in achieving smoking cessation after a 12-month follow-up, compared to pharmacological treatment alone.

Previous studies suggest that a meaningful and easily understood measure of treatment outcome may be the proportion of patients who are in a “patient acceptable symptom state” (PASS). We sought to quantify the score equivalent to PASS for different outcome instruments, in patients with adult spinal deformity (ASD). We analysed the following 12-month questionnaire data from the European Spine Study Group (ESSG): Oswestry Disability Index (ODI; 0–100); Numeric Rating Scales (NRS; 0–10) for back/leg pain; Scoliosis Research Society (SRS) questionnaire; and an item “if you had to spend the rest of your life with the symptoms you have now, how would you feel about it?” (5-point scale, dichotomised with top 2 responses “somewhat satisfied/very satisfied” being considered PASS+, everything else PASS−). Receiver operating characteristics (ROC) analyses indicated the cut-off scores equivalent to PASS+. Out of 1043 patients (599 operative, 444 non-operative; 51 ± 19 years; 84% women), 42% reported being PASS+ at 12 months’ follow-up. The ROC areas under the curve were 0.71–0.84 (highest for SRS subscore), suggesting the questionnaire scores discriminated well between PASS+ and PASS−. The scores corresponding to PASS+ were > 3.5 for the SRS subscore (> 3.3–3.8 for SRS subdomains); ≤ 18 for ODI; and ≤ 3 for NRS pain. There were slight differences in cut-offs for subgroups of age, treatment type, aetiology, baseline symptoms, and sex. Most interventions for ASD improve patients’ complaints but do not totally eliminate them. Reporting the percentage achieving a score equivalent to an “acceptable state” may represent a more stringent and discerning target for denoting treatment success in ASD. These slides can be retrieved under Electronic Supplementary Material.

While genomic sequencing routinely identifies oncogenic alterations for the majority of cancers, many tumors harbor no discernable driver lesion. Here, we describe the exceptional molecular phenotype of a genomically quiet kidney tumor, clear cell papillary renal cell carcinoma (CCPAP). In spite of a largely wild-type nuclear genome, CCPAP tumors exhibit severe depletion of mitochondrial DNA (mtDNA) and RNA and high levels of oxidative stress, reflecting a shift away from respiratory metabolism. Moreover, CCPAP tumors exhibit a distinct metabolic phenotype uniquely characterized by accumulation of the sugar alcohol sorbitol. Immunohistochemical staining of primary CCPAP tumor specimens recapitulates both the depletion of mtDNA-encoded proteins and a lipid-depleted metabolic phenotype, suggesting that the cytoplasmic clarity in CCPAP is primarily related to the presence of glycogen. These results argue for non-genetic profiling as a tool for the study of cancers of unknown driver.

Cyclin dependent kinase 4/6 (CDK4/6) inhibitors (CDK4/6i) are effective in breast cancer; however, drug resistance is frequently encountered and poorly understood. We conducted a genomic analysis of 348 estrogen receptor-positive (ER+) breast cancers treated with CDK4/6i and identified loss-of-function mutations affecting FAT1 and RB1 linked to drug resistance. FAT1 loss led to marked elevations in CDK6, the suppression of which restored sensitivity to CDK4/6i. The induction of CDK6 was mediated by the Hippo pathway with accumulation of YAP and TAZ transcription factors on the CDK6 promoter. Genomic alterations in other Hippo pathway components were also found to promote CDK4/6i resistance. These findings uncover a tumor suppressor function of Hippo signaling in ER+ breast cancer and establish FAT1 loss as a mechanism of resistance to CDK4/6i.

Introduction: The finite element method has been extensively used to analyze the mechanical behavior of endodontic rotary files under bending and torsional conditions. This methodology requires elevated computer-aided design skills to reproduce the geometry of the endodontic file, and also mathematical knowledge to perform the finite element analysis. In this study, an automated procedure is proposed for the computerized generation and finite element analysis of endodontic rotary files under bending and torsional conditions. Methods: An endodontic rotary file with a 25mm total length, 0.25mm at the tip, 1.20mm at 16mm from the tip, 2mm pitch and squared cross section was generated using the proposed procedure and submitted for analysis under bending and torsional conditions by clamping the last 3mm of the endodontic rotary file and applying a transverse load of 0.1N and a torsional moment of 0.3N·cm. Results: The results of the finite element analyses showed a maximum von Mises stress of 398MPa resulting from the bending analysis and a maximum von Mises stress of 843MPa resulting from the torsional analysis, both of which are next to the encastre point. Conclusions: The automated procedure allows an accurate description of the geometry of the endodontic file to be obtained based on its design parameters as well as a finite element model of the endodontic file from the previously generated geometry.

Introduction and Objectives As of January 2021, over 88 million people have been infected with COVID-19. Almost two million people have died of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A high SOFA score and a D-Dimer >1 µg/mL identifies patients with high risk of mortality. High lactate dehydrogenase (LDH) levels on admission are associated with severity and mortality. Different degrees of alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST) abnormalities have been reported in these patients, its association with a mortality risk remains controversial. The aim of this study was to explore the correlation between LDH and in-hospital mortality in Mexican patients admitted with COVID-19. Materials & Methods We performed a retrospective multi-centre cohort study with 377 hospitalized patients with confirmed SARS-CoV-2 in three centres in Mexico City, Mexico, who were ≥18 years old and died or were discharged between April 1 and May 31, 2020. Results A total of 377 patients were evaluated, 298 (79.1%) patients were discharged, and 79 (20.9%) patients died during hospitalization. Non-survivors were older, with a median age of 46.7 ± 25.7 years old, most patients were male. An ALT > 61 U/l (OR 3.45, 95% CI 1.27−9.37; p = 0.015), C-reactive protein (CRP) > 231 mg/l (OR 4.71, 95% CI 2.35−9.46; p = 0.000), LDH > 561 U/l (OR 3.03, 95% CI 1.40−6.55; p = 0.005) were associated with higher odds for in-hospital death. Conclusions Our results indicate that higher levels of LDH, CRP, and ALT are associated with higher in-hospital mortality risk in Mexican patients admitted with COVID-19.

Carmen Peral,1 Francisco Sánchez-Ballester,2 José M García-Mediero,3 Jaime Ramos,1 Javier Rejas1 1Health Economics & Outcomes Research Department, Pfizer, Alcobendas (Madrid), 2Department of Urology, Hospital General Universitario de Valencia, Valencia, 3Department of Urology, Hospital MD Anderson Cancer Center Madrid, Madrid, Spain Objective: To carry out cost-effectiveness analysis from the Spanish National Health System perspective, of treating overactive bladder (OAB), in newly diagnosed patients with two flexible doses of fesoterodine in routine clinical practice.Patients and methods: Economic evaluation of flexible-dose fesoterodine in newly diagnosed patients, including two treatment groups: standard escalating from 4 to 8 mg or fast escalating to 8 mg. Costs were estimated from health care resources utilization related to OAB, and were expressed in 2015 Euros. Quality-adjusted life-years (QALYs) were obtained from overactive bladder questionnaire-short form. Univariate and probabilistic sensitivity analyses were carried out.Results: Three hundred and ninety symptomatic OAB patients treated with fesoterodine and newly diagnosed (141 in fast escalating group and 249 in standard escalating) were analyzed. Adjusted health care total costs were not statistically different; difference−€4.1 (confidence interval: −153.3; 25.1) P=0.842. QALYs were higher in fast escalating to high dose vs standard escalating group, resulting in a cost of−€16,020/QALY gained for fast escalating vs standard escalating group.Conclusion: When the cost-effectiveness threshold is set at a maximum value of €30,000/QALY gained, fesoterodine fast escalating group was cost-effective vs standard escalating group 67.6% of the time. The treatment with fesoterodine, in female patients newly diagnosed, fast escalating to 8 mg was a cost-effective option relative to escalating traditionally from 4 to 8mg, in the management of OAB in routine clinical practice, from the Spanish National Health System perspective. Keywords: antimuscarinic, fesoterodine, flexible dose, overactive bladder, cost-effectiveness

Study Design Retrospective review. Objective To evaluate which distal anchors in growing rod (GR) constructs optimally correct major curve, pelvic obliquity, sagittal alignment, T1–S1 length, thoracic kyphosis, and lumbar lordosis with the fewest complications at 4 or more years' postoperative follow-up. Summary of Background Data Pelvic fixation to the ilium and/or sacrum in GR constructs is used to treat patients with early-onset scoliosis. No studies have evaluated radiographical outcomes and complications in these patients at 4 or more years' follow-up. Methods Included were 38 patients from a multicenter early-onset-scoliosis database with dual GRs anchored to the pelvis. Radiographic data included major curve, T1–S1 length, T5–T12 kyphosis, lordosis, sagittal alignment, and pelvic obliquity at preoperative and latest follow-up time points. Complications were evaluated for all anchor subtypes. Results Mean follow-up time was 5.3 ± 0.1 years. GRs with distal anchors to the ilium significantly improved major curve (49%, p = .013) and pelvic obliquity (78%, p = .035) compared with constructs anchored to the sacrum only. Constructs with iliac fixation with S1 screws provided greater correction of lumbar kyphosis than constructs with iliac fixation and no S1 screws (p = .023). Constructs with a single caudal crosslink had a greater T1–S1 length at latest follow-up than constructs with combined cephalad and caudal crosslinks (p = .027). There were no significant differences in the rates of infection or instrumentation failure between iliac and sacral fixation groups. GR constructs with distal anchors that used a posterior superior iliac spine start point had a higher infection rate (60%) than those inserted via a sacral-alar-iliac technique (7%) (p = .002). Conclusions GR constructs anchored to the ilium provide significant improvements in the major curve and pelvic obliquity at a minimum of 4 years of follow-up versus constructs anchored to the sacrum alone. Level of Evidence Level III, retrospective cohort study.

Aim: To explore in daily clinical practice the evolution in time of the fesoterodine and solifenacin dose pattern and assess the therapeutic benefit provided by the highest dose of these anti-muscarinics. Patients and Methods: This was a post-hoc analysis of data from an observational, cross-sectional, retrospective and multicenter study. Adult patients diagnosed with over active bladder (OAB) who initiated fesoterodine or solifenacin treatment were included. Data on the prescribed treatment and dose, change of dose, reasons for switching and treatment benefit were recorded. Results: A total of 828 subjects were analyzed (262 receiving solifenacin and 566 fesoterodine). Most subjects were women with a mean time since diagnosis of more than one year and aged around 60 years old. The majority of patients initiated the OAB treatment with the lowest available dose (64% fesoterodine vs. 77% solifenacin). At the follow-up visit 54% of the fesoterodine group and 66% of the solifenacin opted for dose escalation. At the study visit, 70.1% fesoterodine vs. 43.3% solifenacin remained on the highest dose. A significantly greater proportion of subjects receiving fesoterodine 8 mg, reported higher improvement in terms of both patient-reported-treatment benefit and clinical global impression compared with solifenacin 10 mg (p < 0.05). Conclusion: In routine clinical practice more than half of the patients opted for the higher dose and remained on it over time, suggesting a desire for greater efficacy. Fesoterodine 8 mg seems to provide greater benefits from the physician’s and the patient’s point of view compared with those provided by solifenacin 10 mg.