Hongxin Zhang
Memorial Sloan Kettering Cancer Center
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Publication
Featured researches published by Hongxin Zhang.
Nature Medicine | 2017
Ahmet Zehir; Ryma Benayed; Ronak Shah; Aijazuddin Syed; Sumit Middha; Hyunjae R. Kim; Preethi Srinivasan; Jianjiong Gao; Debyani Chakravarty; Sean M. Devlin; Matthew D. Hellmann; David Barron; Alison M. Schram; Meera Hameed; Snjezana Dogan; Dara S. Ross; Jaclyn F. Hechtman; Deborah DeLair; Jinjuan Yao; Diana Mandelker; Donavan T. Cheng; Raghu Chandramohan; Abhinita Mohanty; Ryan Ptashkin; Gowtham Jayakumaran; Meera Prasad; Mustafa H Syed; Anoop Balakrishnan Rema; Zhen Y Liu; Khedoudja Nafa
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.
JCO Precision Oncology | 2017
Debyani Chakravarty; Jianjiong Gao; Sarah Phillips; Ritika Kundra; Hongxin Zhang; Jiaojiao Wang; Julia E. Rudolph; Rona Yaeger; Tara Soumerai; Moriah H. Nissan; Matthew T. Chang; Sarat Chandarlapaty; Tiffany A. Traina; Paul K. Paik; Alan L. Ho; Feras M. Hantash; Andrew Grupe; Shrujal S. Baxi; Margaret K. Callahan; Alexandra Snyder; Ping Chi; Daniel C. Danila; Mrinal M. Gounder; James J. Harding; Matthew D. Hellmann; Gopa Iyer; Yelena Y. Janjigian; Thomas Kaley; Douglas A. Levine; Maeve Aine Lowery
PURPOSEnWith prospective clinical sequencing of tumors emerging as a mainstay in cancer care, there is an urgent need for a clinical support tool that distills the clinical implications associated with specific mutation events into a standardized and easily interpretable format. To this end, we developed OncoKB, an expert-guided precision oncology knowledge base.nnnMETHODSnOncoKB annotates the biological and oncogenic effect and the prognostic and predictive significance of somatic molecular alterations. Potential treatment implications are stratified by the level of evidence that a specific molecular alteration is predictive of drug response based on US Food and Drug Administration (FDA) labeling, National Comprehensive Cancer Network (NCCN) guidelines, disease-focused expert group recommendations and the scientific literature.nnnRESULTSnTo date, over 3000 unique mutations, fusions, and copy number alterations in 418 cancer-associated genes have been annotated. To test the utility of OncoKB, we annotated all genomic events in 5983 primary tumor samples in 19 cancer types. Forty-one percent of samples harbored at least one potentially actionable alteration, of which 7.5% were predictive of clinical benefit from a standard treatment. OncoKB annotations are available through a public web resource (http://oncokb.org/) and are also incorporated into the cBioPortal for Cancer Genomics to facilitate the interpretation of genomic alterations by physicians and researchers.nnnCONCLUSIONnOncoKB, a comprehensive and curated precision oncology knowledge base, offers oncologists detailed, evidence-based information about individual somatic mutations and structural alterations present in patient tumors with the goal of supporting optimal treatment decisions.
Genome Medicine | 2017
Jianjiong Gao; Matthew T. Chang; Hannah Johnsen; Sizhi Paul Gao; Brooke E. Sylvester; Selcuk Onur Sumer; Hongxin Zhang; David B. Solit; Barry S. Taylor; Nikolaus Schultz; Chris Sander
Many mutations in cancer are of unknown functional significance. Standard methods use statistically significant recurrence of mutations in tumor samples as an indicator of functional impact. We extend such analyses into the long tail of rare mutations by considering recurrence of mutations in clusters of spatially close residues in protein structures. Analyzing 10,000 tumor exomes, we identify more than 3000 rarely mutated residues in proteins as potentially functional and experimentally validate several in RAC1 and MAP2K1. These potential driver mutations (web resources: 3dhotspots.org and cBioPortal.org) can extend the scope of genomically informed clinical trials and of personalized choice of therapy.
Cancer Research | 2016
Jianjiong Gao; James Lindsay; Stuart Watt; Istemi Bahceci; Pieter Lukasse; Adam Abeshouse; Hsiao-Wei Chen; Ino de Bruijn; Benjamin E. Gross; Dong Li; Ritika Kundra; Zachary J. Heins; Jorge S. 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 J. Pugh; Chris Sander; Ethan Cerami; Nikolaus Schultz
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.
Cancer Research | 2017
Jianjiong Gao; Ersin Ciftci; Pichai Raman; Pieter Lukasse; Istemi Bahceci; Adam Abeshouse; Hsiao-Wei Chen; Ino de Bruijn; Benjamin E. Gross; Zachary J. Heins; Ritika Kundra; Aaron Lisman; Angelica Ochoa; Robert L. 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 S. Reis-Filho; Kees van Bochove
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
Journal of Clinical Oncology | 2016
Debyani Chakravarty; Sarah Phillips; Jianjiong Gao; Ritika Kundra; Hongxin Zhang; Julia E. Rudolph; Rona Yaeger; Tara Soumerai; Moriah H. Nissan; Sarat Chandarlapaty; Tiffany A. Traina; Paul K. Paik; Alan Loh Ho; Feras M. Hantash; Andrew Grupe; Ederlinda Paraiso; Marc Ladanyi; David B. Solit; Paul Sabbatini; Nikolaus Schultz
Cancer Research | 2018
Francisco Sanchez-Vega; Marco Mina; Joshua Armenia; Walid K. Chatila; Augustin Luna; Konnor La; Sofia Dimitriadoy; David Liu; Havish S. Kantheti; Zachary J. Heins; Angelica Ochoa; Benjamin E. Gross; Jianjiong Gao; Hongxin Zhang; Ritika Kundra; Cyriac Kandoth; Istemi Bahceci; Leonard Dervishi; Ugur Dogrusoz; Wanding Zhou; Hui Shen; Peter W. Laird; Alice H. Berger; Trever G. Bivona; Alexander J. Lazar; Gary D. Hammer; Thomas J. Giordano; Lawrence Kwong; Grant A. McArthur; Chenfei Huang
Cancer Research | 2018
Jianjiong Gao; Tali Mazor; Ersin Ciftci; Pichai Raman; Pieter Lukasse; Istemi Bahceci; Adam Abeshouse; Ino de Bruijn; Benjamin E. Gross; Ritika Kundra; Aaron Lisman; Angelica Ochoa; Robert L. Sheridan; Jing Su; Selcuk Onur Sumer; Yichao Sun; Avery Wang; Jiaojiao Wang; Manda Wilson; Hongxin Zhang; Priti Kumari; James Lindsay; Karthik Kalletla; Kelsey Zhu; Oleguer Plantalech; Fedde Schaeffer; Sander Tan; Dionne Zaal; Sjoerd van Hagen; Kees van Bochove
Archive | 2017
Jianjiong Gao; Matthew T. Chang; Hannah Johnsen; Sizhi Gao; Brooke E. Sylvester; Selcuk Onur Sumer; Hongxin Zhang; David B. Solit; Barry S. Taylor; Nikolaus Schultz; Chris Sander