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Author

Neerav Shukla

Other affiliations: Cornell University, Philips
Bio: Neerav Shukla is an academic researcher from Memorial Sloan Kettering Cancer Center. The author has contributed to research in topics: Sarcoma & Medicine. The author has an hindex of 24, co-authored 82 publications receiving 5208 citations. Previous affiliations of Neerav Shukla include Cornell University & Philips.
Topics: Sarcoma, Medicine, Leukemia, Cancer, Targeted therapy


Papers
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Journal ArticleDOI
Ahmet Zehir1, Ryma Benayed1, Ronak Shah1, Aijazuddin Syed1, Sumit Middha1, Hyunjae R. Kim1, Preethi Srinivasan1, Jianjiong Gao1, Debyani Chakravarty1, Sean M. Devlin1, Matthew D. Hellmann1, David Barron1, Alison M. Schram1, Meera Hameed1, Snjezana Dogan1, Dara S. Ross1, Jaclyn F. Hechtman1, Deborah DeLair1, Jinjuan Yao1, Diana Mandelker1, Donavan T. Cheng1, Raghu Chandramohan1, Abhinita Mohanty1, Ryan Ptashkin1, Gowtham Jayakumaran1, Meera Prasad1, Mustafa H Syed1, Anoop Balakrishnan Rema1, Zhen Y Liu1, Khedoudja Nafa1, Laetitia Borsu1, Justyna Sadowska1, Jacklyn Casanova1, Ruben Bacares1, Iwona Kiecka1, Anna Razumova1, Julie B Son1, Lisa Stewart1, Tessara Baldi1, Kerry Mullaney1, Hikmat Al-Ahmadie1, Efsevia Vakiani1, Adam Abeshouse1, Alexander V Penson1, Philip Jonsson1, Niedzica Camacho1, Matthew T. Chang1, Helen Won1, Benjamin Gross1, Ritika Kundra1, Zachary J. Heins1, Hsiao-Wei Chen1, Sarah Phillips1, Hongxin Zhang1, Jiaojiao Wang1, Angelica Ochoa1, Jonathan Wills1, Michael H. Eubank1, Stacy B. Thomas1, Stuart Gardos1, Dalicia N. Reales1, Jesse Galle1, Robert Durany1, Roy Cambria1, Wassim Abida1, Andrea Cercek1, Darren R. Feldman1, Mrinal M. Gounder1, A. Ari Hakimi1, James J. Harding1, Gopa Iyer1, Yelena Y. Janjigian1, Emmet Jordan1, Ciara Marie Kelly1, Maeve A. Lowery1, Luc G. T. Morris1, Antonio Omuro1, Nitya Raj1, Pedram Razavi1, Alexander N. Shoushtari1, Neerav Shukla1, Tara Soumerai1, Anna M. Varghese1, Rona Yaeger1, Jonathan A. Coleman1, Bernard H. Bochner1, Gregory J. Riely1, Leonard B. Saltz1, Howard I. Scher1, Paul Sabbatini1, Mark E. Robson1, David S. Klimstra1, Barry S. Taylor1, José Baselga1, Nikolaus Schultz1, David M. Hyman1, Maria E. Arcila1, David B. Solit1, Marc Ladanyi1, Michael F. Berger1 
TL;DR: A large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer are compiled and identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types.
Abstract: 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.

2,330 citations

Journal ArticleDOI
16 May 2017
TL;DR: OncoKB, 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.
Abstract: PurposeWith prospective clinical sequencing of tumors emerging as a mainstay in cancer care, an urgent need exists 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.MethodsOncoKB annotates the biologic and oncogenic effects and 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 on the basis of US Food and Drug Administration labeling, National Comprehensive Cancer Network guidelines, disease-focused expert group recommendations, and scientific literature.ResultsTo date, > 3,000 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 5,98...

1,451 citations

Journal ArticleDOI
TL;DR: An integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes of soft-tissue sarcomas yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.
Abstract: Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.

587 citations

Journal ArticleDOI
19 Aug 2011-Science
TL;DR: Studying a near-diploid human cell line with a stable karyotype, it is found that targeted inactivation of STAG2 led to chromatid cohesion defects and aneuploidy, whereas in two aneuPLoid human glioblastoma cell lines, targeted correction of the endogenous mutant alleles of STAE led to enhanced chromosomal stability.
Abstract: Most cancer cells are characterized by aneuploidy, an abnormal number of chromosomes. We have identified a clue to the mechanistic origins of aneuploidy through integrative genomic analyses of human tumors. A diverse range of tumor types were found to harbor deletions or inactivating mutations of STAG2, a gene encoding a subunit of the cohesin complex, which regulates the separation of sister chromatids during cell division. Because STAG2 is on the X chromosome, its inactivation requires only a single mutational event. Studying a near-diploid human cell line with a stable karyotype, we found that targeted inactivation of STAG2 led to chromatid cohesion defects and aneuploidy, whereas in two aneuploid human glioblastoma cell lines, targeted correction of the endogenous mutant alleles of STAG2 led to enhanced chromosomal stability. Thus, genetic disruption of cohesin is a cause of aneuploidy in human cancer.

439 citations

Journal ArticleDOI
TL;DR: Arant transcriptional up-regulation of MET by oncogenic TFE3 fusion proteins represents another mechanism by which certain cancers become dependent on MET signaling, which is a potential therapeutic target in these cancers.
Abstract: Specific chromosomal translocations encoding chimeric transcription factors are considered to play crucial oncogenic roles in a variety of human cancers but the fusion proteins themselves seldom represent suitable therapeutic targets. Oncogenic TFE3 fusion proteins define a subset of pediatric renal adenocarcinomas and one fusion (ASPL-TFE3) is also characteristic of alveolar soft part sarcoma (ASPS). By expression profiling, we identified the MET receptor tyrosine kinase gene as significantly overexpressed in ASPS relative to four other types of primitive sarcomas. We therefore examined MET as a direct transcriptional target of ASPL-TFE3. ASPL-TFE3 binds to the MET promoter and strongly activates it. Likewise, PSF-TFE3 and NONO-TFE3 also bind this promoter. Induction of MET by ASPL-TFE3 results in strong MET autophosphorylation and activation of downstream signaling in the presence of hepatocyte growth factor (HGF). In cancer cell lines containing endogenous TFE3 fusion proteins, inhibiting MET by RNA interference or by the inhibitor PHA665752 abolishes HGF-dependent MET activation, causing decreased cell growth and loss of HGF-dependent phenotypes. MET is thus a potential therapeutic target in these cancers. Aberrant transcriptional up-regulation of MET by oncogenic TFE3 fusion proteins represents another mechanism by which certain cancers become dependent on MET signaling. The identification of kinase signaling pathways transcriptionally up-regulated by oncogenic fusion proteins may reveal more accessible therapeutic targets in this class of human cancers.

264 citations


Cited by
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28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
Abstract: The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.

11,912 citations

Journal ArticleDOI
TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

10,947 citations

Journal ArticleDOI
Robert M. Samstein1, Chung-Han Lee1, Chung-Han Lee2, Alexander N. Shoushtari1, Alexander N. Shoushtari2, Matthew D. Hellmann2, Matthew D. Hellmann1, Ronglai Shen1, Yelena Y. Janjigian1, Yelena Y. Janjigian2, David Barron1, Ahmet Zehir1, Emmet Jordan1, Antonio Omuro1, Thomas Kaley1, Sviatoslav M. Kendall1, Robert J. Motzer1, Robert J. Motzer2, A. Ari Hakimi1, Martin H. Voss2, Martin H. Voss1, Paul Russo1, Jonathan E. Rosenberg2, Jonathan E. Rosenberg1, Gopa Iyer2, Gopa Iyer1, Bernard H. Bochner1, Dean F. Bajorin2, Dean F. Bajorin1, Hikmat Al-Ahmadie1, Jamie E. Chaft1, Jamie E. Chaft2, Charles M. Rudin2, Charles M. Rudin1, Gregory J. Riely1, Gregory J. Riely2, Shrujal S. Baxi1, Shrujal S. Baxi2, Alan L. Ho2, Alan L. Ho1, Richard J. Wong1, David G. Pfister2, David G. Pfister1, Jedd D. Wolchok1, Jedd D. Wolchok2, Christopher A. Barker1, Philip H. Gutin1, Cameron Brennan1, Viviane Tabar1, Ingo K. Mellinghoff1, Lisa M. DeAngelis1, Charlotte E. Ariyan1, Nancy Y. Lee1, William D. Tap2, William D. Tap1, Mrinal M. Gounder1, Mrinal M. Gounder2, Sandra P. D'Angelo2, Sandra P. D'Angelo1, Leonard B. Saltz1, Leonard B. Saltz2, Zsofia K. Stadler2, Zsofia K. Stadler1, Howard I. Scher2, Howard I. Scher1, José Baselga2, José Baselga1, Pedram Razavi2, Pedram Razavi1, Christopher A. Klebanoff2, Christopher A. Klebanoff1, Rona Yaeger1, Rona Yaeger2, Neil H. Segal2, Neil H. Segal1, Geoffrey Y. Ku2, Geoffrey Y. Ku1, Ronald P. DeMatteo1, Marc Ladanyi1, Naiyer A. Rizvi3, Michael F. Berger1, Nadeem Riaz1, David B. Solit1, Timothy A. Chan1, Luc G. T. Morris1 
TL;DR: Analysis of advanced cancer patients treated with immune-checkpoint inhibitors shows that tumor mutational burden, as assessed by targeted next-generation sequencing, predicts survival after immunotherapy across multiple cancer types.
Abstract: Immune checkpoint inhibitor (ICI) treatments benefit some patients with metastatic cancers, but predictive biomarkers are needed. Findings in selected cancer types suggest that tumor mutational burden (TMB) may predict clinical response to ICI. To examine this association more broadly, we analyzed the clinical and genomic data of 1,662 advanced cancer patients treated with ICI, and 5,371 non-ICI-treated patients, whose tumors underwent targeted next-generation sequencing (MSK-IMPACT). Among all patients, higher somatic TMB (highest 20% in each histology) was associated with better overall survival. For most cancer histologies, an association between higher TMB and improved survival was observed. The TMB cutpoints associated with improved survival varied markedly between cancer types. These data indicate that TMB is associated with improved survival in patients receiving ICI across a wide variety of cancer types, but that there may not be one universal definition of high TMB.

2,343 citations

Journal ArticleDOI
Ahmet Zehir1, Ryma Benayed1, Ronak Shah1, Aijazuddin Syed1, Sumit Middha1, Hyunjae R. Kim1, Preethi Srinivasan1, Jianjiong Gao1, Debyani Chakravarty1, Sean M. Devlin1, Matthew D. Hellmann1, David Barron1, Alison M. Schram1, Meera Hameed1, Snjezana Dogan1, Dara S. Ross1, Jaclyn F. Hechtman1, Deborah DeLair1, Jinjuan Yao1, Diana Mandelker1, Donavan T. Cheng1, Raghu Chandramohan1, Abhinita Mohanty1, Ryan Ptashkin1, Gowtham Jayakumaran1, Meera Prasad1, Mustafa H Syed1, Anoop Balakrishnan Rema1, Zhen Y Liu1, Khedoudja Nafa1, Laetitia Borsu1, Justyna Sadowska1, Jacklyn Casanova1, Ruben Bacares1, Iwona Kiecka1, Anna Razumova1, Julie B Son1, Lisa Stewart1, Tessara Baldi1, Kerry Mullaney1, Hikmat Al-Ahmadie1, Efsevia Vakiani1, Adam Abeshouse1, Alexander V Penson1, Philip Jonsson1, Niedzica Camacho1, Matthew T. Chang1, Helen Won1, Benjamin Gross1, Ritika Kundra1, Zachary J. Heins1, Hsiao-Wei Chen1, Sarah Phillips1, Hongxin Zhang1, Jiaojiao Wang1, Angelica Ochoa1, Jonathan Wills1, Michael H. Eubank1, Stacy B. Thomas1, Stuart Gardos1, Dalicia N. Reales1, Jesse Galle1, Robert Durany1, Roy Cambria1, Wassim Abida1, Andrea Cercek1, Darren R. Feldman1, Mrinal M. Gounder1, A. Ari Hakimi1, James J. Harding1, Gopa Iyer1, Yelena Y. Janjigian1, Emmet Jordan1, Ciara Marie Kelly1, Maeve A. Lowery1, Luc G. T. Morris1, Antonio Omuro1, Nitya Raj1, Pedram Razavi1, Alexander N. Shoushtari1, Neerav Shukla1, Tara Soumerai1, Anna M. Varghese1, Rona Yaeger1, Jonathan A. Coleman1, Bernard H. Bochner1, Gregory J. Riely1, Leonard B. Saltz1, Howard I. Scher1, Paul Sabbatini1, Mark E. Robson1, David S. Klimstra1, Barry S. Taylor1, José Baselga1, Nikolaus Schultz1, David M. Hyman1, Maria E. Arcila1, David B. Solit1, Marc Ladanyi1, Michael F. Berger1 
TL;DR: A large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer are compiled and identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types.
Abstract: 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.

2,330 citations