Adam Abeshouse

Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients

Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of genomic alterations in genes and pathways that can be targeted therapeutically. The existence of recurrent targetable alterations across distinct histologically defined tumor types, coupled with an expanding portfolio of molecularly targeted therapies, demands flexible and comprehensive approaches to profile clinically relevant genes across the full spectrum of cancers. We established a large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which we have compiled tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer and available pathological and clinical annotations. Using these data, we identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types. Patients were enrolled on genomically matched clinical trials at a rate of 11%. To enable discovery of novel biomarkers and deeper investigation into rare alterations and tumor types, all results are publicly accessible.

Prospective Genomic Profiling of Prostate Cancer Across Disease States Reveals Germline and Somatic Alterations That May Affect Clinical Decision Making

PURPOSE A long natural history and a predominant osseous pattern of metastatic spread are impediments to the adoption of precision medicine in patients with prostate cancer. To establish the feasibility of clinical genomic profiling in the disease, we performed targeted deep sequencing of tumor and normal DNA from patients with locoregional, metastatic non-castrate, and metastatic castration-resistant prostate cancer (CRPC). METHODS Patients consented to genomic analysis of their tumor and germline DNA. A hybridization capture-based clinical assay was employed to identify single nucleotide variations, small insertions and deletions, copy number alterations and structural rearrangements in over 300 cancer-related genes in tumors and matched normal blood. RESULTS We successfully sequenced 504 tumors from 451 patients with prostate cancer. Potentially actionable alterations were identified in DNA damage repair (DDR), PI3K, and MAP kinase pathways. 27% of patients harbored a germline or a somatic alteration in a DDR gene that may predict for response to PARP inhibition. Profiling of matched tumors from individual patients revealed that somatic TP53 and BRCA2 alterations arose early in tumors from patients who eventually developed metastatic disease. In contrast, comparative analysis across disease states revealed that APC alterations were enriched in metastatic tumors, while ATM alterations were specifically enriched in CRPC. CONCLUSION Through genomic profiling of prostate tumors representing the disease clinical spectrum, we identified a high frequency of potentially actionable alterations and possible drivers of disease initiation, metastasis and castration-resistance. Our findings support the routine use of tumor and germline DNA profiling for patients with advanced prostate cancer, for the purpose of guiding enrollment in targeted clinical trials and counseling families at increased risk of malignancy.

Small cell carcinomas of the bladder and lung are characterized by a convergent but distinct pathogenesis

Purpose: Small-cell carcinoma of the bladder (SCCB) is a rare and aggressive neuroendocrine tumor with a dismal prognosis and limited treatment options. As SCCB is histologically indistinguishable from small-cell lung cancer, a shared pathogenesis and cell of origin has been proposed. The aim of this study is to determine whether SCCBs arise from a preexisting urothelial carcinoma or share a molecular pathogenesis in common with small-cell lung cancer. Experimental Design: We performed an integrative analysis of 61 SCCB tumors to identify histology- and organ-specific similarities and differences. Results: SCCB has a high somatic mutational burden driven predominantly by an APOBEC-mediated mutational process. TP53, RB1, and TERT promoter mutations were present in nearly all samples. Although these events appeared to arise early in all affected tumors and likely reflect an evolutionary branch point that may have driven small-cell lineage differentiation, they were unlikely the founding transforming event, as they were often preceded by diverse and less common driver mutations, many of which are common in bladder urothelial cancers, but not small-cell lung tumors. Most patient tumors (72%) also underwent genome doubling (GD). Although arising at different chronologic points in the evolution of the disease, GD was often preceded by biallelic mutations in TP53 with retention of two intact copies. Conclusions: Our findings indicate that small-cell cancers of the bladder and lung have a convergent but distinct pathogenesis, with SCCBs arising from a cell of origin shared with urothelial bladder cancer. Clin Cancer Res; 24(8); 1965–73. ©2017 AACR. See related commentary by Oser and Jänne, p. 1775

Abstract 5277: The cBioPortal for cancer genomics and its application in precision oncology

The cBioPortal for Cancer Genomics provides intuitive visualization and analysis of complex cancer genomics data. The public site (http://cbioportal.org/) is accessed by more than 1,500 researchers per day, and there are now dozens of local instances of the software that host private data sets at cancer centers around the globe. We have recently released the software under an open source license, making it free to use and modify by anybody. The software and detailed documentation are available at https://github.com/cBioPortal/cbioportal. We are now establishing a multi-institutional software development network, which will coordinate and drive the future development of the software and associated data pipelines. This group will focus on four main areas: 1. New analysis and visualization features, including: a. Improved support for cross-cancer queries and cohort comparisons. b. Enhanced clinical decision support for precision oncology, including an improved patient view with knowledge base integration, patient timelines and improved tools for visualizing tumor evolution. 2. New data pipelines, including support for new genomic data types and streamlined pipelines for TCGA and the International Cancer Genome Consortium (ICGC). 3. Software architecture and performance improvements. 4. Community engagement: Documentation, user support, and training. This coordinated effort will help to further establish the cBioPortal as the software of choice in cancer genomics research, both in academia and the pharmaceutical industry. Furthermore, as the sequencing of tumor samples has entered clinical practice, we are expanding the features of the software so that it can be used for precision medicine at cancer centers. In particular, clean, web-accessible, interactive clinical reports integrating multiple sources of genome variation and clinical annotation over time has potential to improve clinical action beyond current text-based molecular reports. By making complex genomic data easily interpretable and linking it to information about drugs and clinical trials, the cBioPortal software has the potential to facilitate the use of genomic data in clinical decision making. Citation Format: Jianjiong Gao, James Lindsay, Stuart Watt, Istemi Bahceci, Pieter Lukasse, Adam Abeshouse, Hsiao-Wei Chen, Ino de Bruijn, Benjamin Gross, Dong Li, Ritika Kundra, Zachary Heins, Jorge Reis-Filho, Onur Sumer, Yichao Sun, Jiaojiao Wang, Qingguo Wang, Hongxin Zhang, Priti Kumari, M. Furkan Sahin, Sander de Ridder, Fedde Schaeffer, Kees van Bochove, Ugur Dogrusoz, Trevor Pugh, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for cancer genomics and its application in precision oncology. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5277.

Integration and analysis of CPTAC proteomics data in the context of cancer genomics in the cBioPortal

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced extensive mass spectrometry based proteomics data for selected breast, colon and ovarian tumors from The Cancer Genome Atlas (TCGA). We have incorporated the CPTAC proteomics data into the cBioPotal to support easy exploration and integrative analysis of these proteomic datasets in the context of the clinical and genomics data from the same tumors. cBioPortal is an open source platform for exploring, visualizing, and analyzing multi-dimensional cancer genomics and clinical data. The public instance of the cBioPortal (http://cbioportal.org/) hosts more than 100 cancer genomics studies including all of the data from TCGA. Its biologist-friendly interface provides many rich analysis features, including a graphical summary of gene-level data across multiple platforms, correlation analysis between genes or other data types, survival analysis, and network visualization. Here, we present the integration of the CPTAC mass spectrometry based proteomics data into the cBioPortal, consisting of 77 breast, 95 colorectal, and 174 ovarian tumors that already have been profiled by TCGA for mutations, copy number alterations, gene expression, and DNA methylation. As a result, the CPTAC data can now be easily explored and analyzed in the cBioPortal in the context of clinical and genomics data. By integrating CPTAC data into cBioPortal, limitations of TCGA proteomics array data can be overcome while also providing a user-friendly web interface, a web API and an R client to query the mass spectrometry data together with genomic, epigenomic, and clinical data.

Abstract 2607: The cBioPortal for Cancer Genomics: an open source platform for accessing and interpreting complex cancer genomics data in the era of precision medicine

The cBioPortal for Cancer Genomics is an open-access portal (http://cbioportal.org) that enables interactive, exploratory analysis of large-scale cancer genomics data. It integrates genomic and clinical data, and provides a suite of visualization and analysis options, including cohort and patient-level visualization, mutation visualization, survival analysis, enrichment analysis, and network analysis. The user interface is user-friendly, responsive, and makes genomic data easily accessible to translational scientists, biologists, and clinicians. The cBioPortal is a fully open source platform. All code is available on GitHub (https://github.com/cBioPortal/) under GNU Affero GPL license. The code base is maintained by multiple groups, including Memorial Sloan Kettering Cancer Center, Dana-Farber Cancer Institute, Children’s Hospital of Philadelphia, Princess Margaret Cancer Centre, and The Hyve, an open source bioinformatics company based in the Netherlands. More than 30 academic centers as well as multiple pharmaceutical and biotech companies maintain private instances of the cBioPortal. This includes the recently launched cBioPortal instance at the NCI Genomic Data Commons (https://cbioportal.gdc.nci.nih.gov/), and two large cBioPortal instances hosting genomic and clinical data at MSK and DFCI, supporting the MSK-IMPACT and DFCI Profile projects, two of the largest clinical sequencing efforts in the world. Our multi-institutional software team has accelerated the progress of evolving the core architectural technologies and developing new features to keep pace with the rapidly advancing fields of cancer genomics and precision cancer medicine. For example, we have integrated multi-platform genomics data with extensive clinical data including patient demographics, treatment history, and survival data. We have also developed a patient-centric view that visualizes both clinical and genomic data with annotation from OncoKB knowledge base. In the next few years, the development team will focus on the following areas: (1) Implementing major architectural changes to ensure future scalability and performance. (2) New features to support precision medicine, including (i) improved integration of knowledge base annotation, (ii) enhanced visualization of patient timeline, drug response, and tumor evolution, (iii) new patient similarity metrics, (iv) improved support for immunogenomics and immunotherapy, and (v) new visualization and analysis features for understanding response to therapy. (3) New analysis and target discovery features for large cohorts, including (i) supporting user-defined virtual cohort by selecting samples from multiple studies, and (ii) comparison of genomic or clinical characteristics of two or more selected cohorts. (4) Expanding community outreach, user support and training, and documentation. Citation Format: Jianjiong Gao, Ersin Ciftci, Pichai Raman, Pieter Lukasse, Istemi Bahceci, Adam Abeshouse, Hsiao-Wei Chen, Ino de Bruijn, Benjamin Gross, Zachary Heins, Ritika Kundra, Aaron Lisman, Angelica Ochoa, Robert Sheridan, Onur Sumer, Yichao Sun, Jiaojiao Wang, Manda Wilson, Hongxin Zhang, James Xu, Andy Dufilie, Priti Kumari, James Lindsay, Anthony Cros, Karthik Kalletla, Fedde Schaeffer, Sander Tan, Sjoerd van Hagen, Jorge Reis-Filho, Kees van Bochove, Ugur Dogrusoz, Trevor Pugh, Adam Resnick, Chris Sander, Ethan Cerami, Nikolaus Schultz. The cBioPortal for Cancer Genomics: an open source platform for accessing and interpreting complex cancer genomics data in the era of precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2607. doi:10.1158/1538-7445.AM2017-2607