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Jianjiong Gao

BGI Group (China)

ORCID: 0000-0002-5739-1781

Publishes on Cancer Genomics and Diagnostics, Lung Cancer Treatments and Mutations, Bioinformatics and Genomic Networks. 342 papers and 106.9k citations.

342Publications
106.9kTotal Citations

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Top publicationsby citations

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data
Ethan Cerami, Jianjiong Gao, Uğur Doğrusöz et al.|Cancer Discovery|2012
Cited by 18.3kOpen Access

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.

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Jianjiong Gao, Bülent Arman Aksoy, Uğur Doğrusöz et al.|Science Signaling|2013
Cited by 15.9kOpen Access

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.

Comprehensive molecular characterization of gastric adenocarcinoma
Cited by 6.5kOpen Access

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies. The Cancer Genome Atlas reports on molecular evaluation of 295 primary gastric adenocarcinomas and proposes a new classification of gastric cancers into 4 subtypes, which should help with clinical assessment and trials of targeted therapies. This contribution from The Cancer Genome Atlas (TCGA) project describes the molecular evaluation of 295 primary gastric adenocarcinomas. Based on the results, the authors propose a novel classification separating gastric cancers into four subtypes according to: Epstein–Barr virus positive status, microsatellite instability, chromosomal instability or genomic stability. Given the histologic and etiologic heterogeneity of gastric cancer identification of these subtypes, using a schema that can readily be applied to patient samples should help with patient stratification and trials of targeted therapies.