The cBio Cancer Genomics Portal provides visualization, analysis and download of large-scale cancer genomics data sets.

The portal is developed and maintained by the Computational Biology Center at Memorial Sloan-Kettering Cancer Center.

  • Network of genomic alterations in Serous Ovarian Cancer.

    Network of BRCA1, BRCA2 and all altered neighbors, as identified in the TCGA ovarian cancer data set. Pink shading indicates frequency of alteration across all patients (white = low frequency of alteration; red = high frequency of alteration); Green discs indicate rate of mutation across all patients.

    Data source: TCGA Serous Ovarian Cancer Data Set.
  • OncoPrint of TP53 Pathway Alterations in Glioblastoma.

    Example of TP53, MDM2, and MDM4 in Glioblastoma, visualized as an OncoPrint across all patients.

    Data Source: TCGA Gliobastoma Data Set.
  • EGFR Amplifications in Gliobastoma.

    Example of CNA v. mRNA Plot for EGFR in Glioblastoma Multiforme. CNA amplifications are accompanied by mRNA up-regulation.

    Data Source: TCGA Gliobastoma Data Set.
  • Survival Analysis of BRCA Mutated v. Non-BRCA Mutated in Serous Ovarian Cancer.

    BRCA-mutated cases show significantly better overall survival.

    Data Source: TCGA Serous Ovarian Cancer Data Set.
  • Epigenetic Silencing of BRCA1 in Serous Ovarian Cancer

    Example of Methylation v. mRNA Plot for BRCA1 in Serous Overian Cancer.

    Data Source: TCGA Serous Ovarian Cancer Data Set.
  • Structural view of a PIK3R1 mutation in Glioblastoma

    The D560Y variant of PIK3R1 in glioblastoma is shown on the PIK3R1 protein structure (on the Mutation Assessor website). The mutated residue is shown in red.

    Data Source: TCGA Glioblastoma Data Set.
  • TP53 mutations in ovarian cancer

    TP53 is mutated in 95% of serous ovarian cancer patients. Some of these mutations are truncating, and most of the missense mutations are predicted to have a high functional impact (prediction by Mutation Assessor).

    Data Source: TCGA Serous Ovarian Cancer Data Set.
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Query Download Data
Select Cancer Study:
Select Genomic Profiles:
Select Patient/Case Set:
(Tip: Hover your mouse over a case set to view a description.)
Enter Gene Set:       Advanced: Onco Query Language (OQL)

Or Select from Example Gene Sets:

Optional Arguments:   
Compute Mutual Exclusivity / Co-occurence between all pairs of genes.
     (Not recommended for more than 10 genes.)

Data Sets

The Portal contains data for 5030 tumor samples from 20 cancer studies. [Details.]

Example Queries

RAS/RAF alterations in colorectal cancer

BRCA1 and BRCA2 mutations in ovarian cancer

Protein changes in PTEN-altered ovarian cancer samples

TP53 and MDM2/4 alterations in GBM

PTEN mutations in GBM in text format

What's New

Check out our new network visualization options. Available under the network tab on all result pages.

What People are Saying

  "Whenever bench scientists ask me how they can look at TCGA data, I've never had a good answer for them. Now I do. The cBio Portal meets a critical need--it is the interface that the cancer research community needs to access the wealth of TCGA. Even as a computational biologist, I use it to follow-up on genes of interest. It makes querying the data much less painful."

– Postdoctoral Fellow, Oregon Health & Science University

  "I would like to congratulate you and the team of the cBio portal. It's just an amazing tool to work with, and we at Mass General really appreciate it."

– Research Fellow at Massachusetts General Hospital

  "As a bench biologist with primary aim of determining gene aberrations in GBM, I found your site absolutely fantastic! Thank you! I have to reiterate how awesome and user-friendly your group has made this site - finally accomplishing the goal of having data easily accessible and meaningful."

– Sr. Research Associate at Knight Cancer Institute/OHSU

  "Thank you for your incredible resource that has helped greatly in accessing the TCGA genomics data."

– Postdoctoral Fellow, Johns Hopkins University School of Medicine, Dept Radiation Oncology and Molecular Radiation Sciences

  "I have been enjoying the ease with which TCGA data can be extracted in R using your CGDS package. Very nice work!"

– Sr. Software Engineer, Institute for Systems Biology

  "Thank you for generating such an excellent software. It is very useful for our research."

– Research Fellow, Memorial Sloan-Kettering Cancer Center

  "Thank you very much for providing and maintaining this great resource."

– Scientist, Discovery Bioinformatics, Biotechnology Company

  "I want to thank you for the nice, useful and user-friendly interface you have generated and shared with the community."

– Postdoctoral Fellow, Harvard Medical School, Children's Hospital Boston