The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data
Open accessAbstract
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. Cancer Discov; 2(5); 401–4. ©2012 AACR.
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Publicly available gene expression data from a matched cohort of mCRPC was downloaded from cBioportal.
“Publicly available gene expression data from a matched cohort established previously59 or mCRPC was downloaded from cBioportal (20 May 2021)94–96.”
From Genome-scale CRISPR screens identify PTGES3 as a direct modulator of androgen receptor function in advanced prostate cancer (2025) · cites this paper as [95]
IMP2 is genomically altered in over 2% of all cancers, which is above the baseline of random alterations in the average passenger genes.
“IMP2 is genomically altered in over 2% of all cancers, which is above the baseline of random alterations in the average passenger genes (Figure 5A) [77,78,79].”
From IMPlications of IMP2 in RNA Biology and Disease (2025) · cites this paper as [77]
The paper’s description of the portal explains how it records and displays genomic alterations, and its examples report frequencies for other genes in specific cancers. Searches for IMP2 (including IGF2BP2), the over-2% figure, and a passenger-gene baseline found no passage establishing the claimed comparison across all cancers. (LLM, conf=0.76)
Experimental — accuracy not yet measuredGenomic amplifications creating extra copies of IGF2BP2 occur in 9% of lung cancers.
“Genomic amplifications creating extra copies of IGF2BP2 occur in 9% of lung cancers (Figure 5A) [77,78,79].”
From IMPlications of IMP2 in RNA Biology and Disease (2025) · cites this paper as [77]
The paper’s discussion of the cBio Portal describes copy-number amplifications and gives an amplification frequency for C11orf30/EMSY in ovarian cancer, but not for IGF2BP2 in lung cancer. Searches for IGF2BP2, lung cancer, and the claimed 9% frequency found no passage addressing that result; the cited copy does not establish or contradict it. (LLM, conf=0.75)
Experimental — accuracy not yet measuredKRAS mutations are implicated in 25-30% of all human cancers, about 19% of non-small cell lung cancers, about 40% of colorectal cancers, and about 73% of pancreatic ductal adenocarcinoma cases.
“KRAS mutations are implicated in 25–30% of all human cancers, about 19% of non-small cell lung cancers (NSCLCs), about 40% of colorectal cancers (CRCs), and about 73% of pancreatic ductal adenocarcinoma (PDAC) cases (Figure 1) [1,2].”
From KRAS: Biology, Inhibition, and Mechanisms of Inhibitor Resistance (2024) · cites this paper as [1]
The portal-description and Figure 1 passages (page unavailable) discuss genomic alterations in other genes, but do not report KRAS mutation rates. Searches for KRAS and the claimed percentages found no passage in our copy supporting the rates for all cancers, NSCLC, colorectal cancer, or pancreatic ductal adenocarcinoma. (LLM, conf=0.77)
Experimental — accuracy not yet measuredTP53 is deregulated in 22% of glioblastomas, while ARF, MDM2, and MDM4 are deregulated in 61%, 10%, and 10% of glioblastomas, respectively.
“TP53 is deregulated in 22% of GBMs, while ARF, MDM2, and MDM4 are deregulated in 61%, 10%, and 10% of GBMs, respectively (Figure 1) [22,23].”
From The p53 Pathway in Glioblastoma (2018) · cites this paper as [22]
The paper’s Figure 1 description and discussion of TCGA GBM data concern RB-pathway alterations, not the claimed TP53, ARF, MDM2, and MDM4 frequencies. Searches for those genes and for the stated percentages found no passage in our copy that reports them. (LLM, conf=0.76)
Experimental — accuracy not yet measured
The most frequently deregulated component of the p53 pathway is a homozygous deletion of the CDKN2A/ARF locus, occurring in approximately 60% of all glioblastoma cases.
“The most frequently deregulated component of the p53 pathway is a homozygous deletion of the CDKN2A/ARF locus, which occurs in ~60% of all GBM cases (Figure 1) [22,23].”
From The p53 Pathway in Glioblastoma (2018) · cites this paper as [22]
The portal paper’s GBM example discusses CDKN2A as part of an RB-pathway OncoPrint, not as a p53-pathway finding (section labeled Abstract; page unavailable). Searches for p53, CDKN2A homozygous deletion, and the claimed ~60% frequency found no passage in our copy establishing the claim. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn patients with HCC, chromosomal amplifications including PROX1 are associated with increased survival.
“in patients with HCC, high PROX1 expression or chromosomal amplifications including PROX1 were both associated with increased survival25–32”
From Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis (2025) · cites this paper as [26]
The paper’s Figure 1 caption discusses survival in glioblastoma, while its amplification examples concern glioblastoma and ovarian cancer. Searches for PROX1 and for HCC chromosomal amplifications with increased survival found no passage addressing the claimed association in patients with HCC. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn patients with HCC, high PROX1 expression is associated with increased survival.
“in patients with HCC, high PROX1 expression or chromosomal amplifications including PROX1 were both associated with increased survival25–32”
From Active repression of cell fate plasticity by PROX1 safeguards hepatocyte identity and prevents liver tumorigenesis (2025) · cites this paper as [26]
The portal description and Figure 1 discuss survival analysis for RB-pathway alterations in glioblastoma, not PROX1 in HCC (page not provided). Searches for PROX1, HCC, and the claimed expression–survival association found no passage in our copy addressing that association. (LLM, conf=0.75)
Experimental — accuracy not yet measuredSomatic mutation of the STAT3 gene in cancer is rare (1.08%; 54/4980 tumors analyzed to date by whole exome sequencing by The Cancer Genome Atlas).
“The prevalence of STAT3 overactivation in cancer cannot be explained by mutational activation of STAT3 because somatic mutation of the STAT3 gene in cancer is rare (1.08%; 54/4980 tumors analyzed to date by whole exome sequencing by The Cancer Genome Atlas).38”
From Critical analysis of the potential for targeting STAT3 in human malignancy (2013) · cites this paper as [38]
The portal description (section labelled Abstract; page unavailable) says it includes TCGA datasets and mutation data, but does not report STAT3 mutation prevalence. Searches of our copy for STAT3, 54/4980, 1.08%, and the claimed whole-exome tumor count found no passage supporting the figure or the explanation of STAT3 overactivation. (LLM, conf=0.76)
Experimental — accuracy not yet measuredPTEN is an important tumour suppressor gene mutated in 6% of colorectal cancers.
“It is an important tumour suppressor gene mutated in 6% of colorectal cancers (CRCs), and germline variants in PTEN are causative of PTEN hamartoma tumour syndrome (Hobert and Eng, 2009; Cerami et al., 2012).”
From Efficient genetic editing of human intestinal organoids using ribonucleoprotein-based CRISPR (2023) · cites this paper as Cerami et al., 2012
The indexed passage on protein and phosphoprotein analysis (page unavailable) discusses PTEN deletion in ovarian cancer and notes that colorectal cancer data are available, but gives no PTEN mutation frequency for colorectal cancer. Searches for PTEN, colorectal cancer, and 6% found no passage calling PTEN a tumour suppressor or supporting the claimed 6% figure. (LLM, conf=0.76)
Experimental — accuracy not yet measuredCancer samples often carry mutations in BRCA1 residues 758-1064.
“We note that the region of BRCA1 (amino acid residues 758-1064) that harbors the RAD51 interaction domain17 is frequently mutated in cancer (cBioPortal for Cancer Genomic)44,45”
From BRCA1–BARD1 promotes RAD51-mediated homologous DNA pairing (2017) · cites this paper as [44]
KRAS is the oncogenic protein most often altered in solid tumours.
“Despite being the most frequently altered oncogenic protein in solid tumours, KRAS has historically been considered ‘undruggable’”
From The current state of the art and future trends in RAS-targeted cancer therapies (2022) · cites this paper as [17]
About 20% of all malignancies have a RAS abnormality, and about 17% of solid tumours have KRAS mutations, including about 90% of pancreatic, 50% of colon and 25% of lung adenocarcinomas.
“each dataset indicates that ~20% of all malignancies have a RAS abnormality. Overall, ~17% of solid tumours have KRAS mutations, including ~90% of pancreatic, ~50% of colon and ~25% of lung adenocarcinomas16,17”
From The current state of the art and future trends in RAS-targeted cancer therapies (2022) · cites this paper as [17]
KRAS mutations account for about 78% of RAS mutations in NSCLC, and activating missense KRAS mutations occur in about 25% of NSCLCs, usually mutually exclusive with other actionable drivers such as EGFR, BRAF and ALK.
“KRAS mutations predominate in NSCLCs, accounting for ~78% of all RAS mutations found in such tumours17. The activating missense KRAS mutations that occur in ~25% of NSCLCs19–23 are typically mutually exclusive with other clinically actionable driver mutations, such as those in EGFR, BRAF and ALK24.”
From The current state of the art and future trends in RAS-targeted cancer therapies (2022) · cites this paper as [17]
About one in seven human cancers carry a KRAS alteration.
“approximately one in seven of all human cancers harbor KRAS (Kirsten rat sarcoma virus) alterations”
From Expanding the Reach of Precision Oncology by Drugging All <i>KRAS</i> Mutants (2022) · cites this paper as [4]
KRAS is among the most frequently mutated oncogenes in human cancer.
“KRAS is the most frequently mutated oncogene”
From Expanding the Reach of Precision Oncology by Drugging All <i>KRAS</i> Mutants (2022) · cites this paper as [4]
Based on non-small cell lung cancer datasets within cBioPortal, the landscape of KRAS G12C mutated tumors includes a complex landscape of co-altered genes.
“Based on non-small cell lung cancer datasets within cBioPortal, the landscape of KRAS G12C mutated tumors includes a complex landscape of co-altered genes (Fig. 3)25,26.”
From Selective KRAS G12C inhibitors in non-small cell lung cancer: chemistry, concurrent pathway alterations, and clinical outcomes (2021) · cites this paper as [25]
Frequently co-altered genes in KRAS G12C mutated NSCLC include TP53, STK11, KEAP1, and CDKN2A.
“Frequently co-altered genes include TP53, STK11, KEAP1, and CDKN2A.”
From Selective KRAS G12C inhibitors in non-small cell lung cancer: chemistry, concurrent pathway alterations, and clinical outcomes (2021) · cites this paper as [25]
Within the KRAS mutant subgroup, lower RNA expression of PTK2 (FAK coding gene) correlates with better survival outcomes.
“Within the KRAS mutant subgroup, lower RNA expression of PTK2 (FAK coding gene) correlates with better survival outcomes”
From Focal Adhesion Kinase (FAK) Inhibition Synergizes with KRAS G12C Inhibitors in Treating Cancer through the Regulation of the FAK–YAP Signaling (2021) · cites this paper as [19]
For the KRAS wild type subgroup, there is no difference between the PTK2 low and high expression groups.
“while for KRAS wild type subgroup, there is no difference between the PTK2 low and high expression groups (Figure 1A,B)”
From Focal Adhesion Kinase (FAK) Inhibition Synergizes with KRAS G12C Inhibitors in Treating Cancer through the Regulation of the FAK–YAP Signaling (2021) · cites this paper as [19]
Analysis of TCGA data shows that a fraction of multiple cancers have overexpressed MDMX concurrently with inactivated p53.
“Analysis of the data in The Cancer Genome Atlas provides further evidence that a certain fraction of multiple cancers have overexpressed MDMX (amplification or mRNA) concurrently with inactivated (mutated or deleted) p53 (Table 1;34,35).”
From Mdmx promotes genomic instability independent of p53 and Mdm2 (2015) · cites this paper as [34]
In TCGA data, squamous cell carcinoma of the lung or head and neck co-inactivated ARF and TP53 in about 20% of tumors.
“For example, we evaluated ARF and TP53 status in the data from The Cancer Genome Atlas (TCGA) and determined that malignancies such as squamous cell carcinoma of the lung or head and neck co-inactivate ARF and TP53 in approximately 20% of these tumors (Table 1; (Cerami, et al., 2012; Gao, et al., 2013).”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
In TCGA data, 5.3% of breast adenocarcinomas had amplified USP7, and 75% of those tumors retained wild-type TP53 allele status.
“However, 5.3% (40 of 760) of breast adenocarcinomas contained amplified USP7 and of those, 75% maintained wild-type TP53 allele status, which implies that USP7 may have other functions related to oncogenesis.”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
In the authors' TCGA evaluation, USP7 was rarely amplified in human cancer.
“Our evaluation of TCGA data revealed that USP7 is rarely amplified in human cancer (Cerami, et al., 2012; Gao, et al., 2013).”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
Only a small fraction of analyzed tumors, 0.84% (18 of 2148), carried p21 deletions or mutations.
“0.84% (18 of 2148) tumors analyzed had p21 deletions or mutations (Cerami, et al., 2012; Gao, et al., 2013).”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
In the authors' TCGA analysis, up to 6% of specific human malignancies had amplified MDM2 or MDM4 together with TP53 mutations.
“Our analysis of TCGA data showed that up to 6% of specific human malignancies have amplified MDM2 or MDM4 (and even more have increased MDM2 or MDM4 mRNA expression) with concomitant TP53 mutations”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
More than 6% of specific human malignancies had increased MDM2 or MDM4 mRNA expression together with TP53 mutations.
“even more have increased MDM2 or MDM4 mRNA expression”
From The Mdm network and its regulation of p53 activities: a rheostat of cancer risk (2014) · cites this paper as Cerami, et al., 2012
Cellosaurus and cBioPortal do not provide cell model functional information, while PharmacoDB does not contain genomic annotation of the cell models and has limited sample/model information.
“First, Cellosaurus and cBioPortal do not provide cell model functional information, while PharmacoDB does not contain genomic annotation of the cell models and has limited sample/model information.”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [36]
cBioPortal and COSMIC are primarily focused on patient tumour genomic data.
“Second, cBioPortal and COSMIC are primarily focused on patient tumour genomic data.”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [36]
Neither cBioPortal, PharmacoDB nor COSMIC curate samples to map unique identifiers or link samples and models from the same patient, which can be important for identifying mis-identified or cross-contaminated samples.
“Third, neither cBioPortal, PharmacoDB nor COSMIC curate samples to map unique identifiers or link samples and models from the same patient, which can be important for identifying mis-identified or cross-contaminated samples.”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [36]
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- Authors
- Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., Antipin, Y., Reva, B., Goldberg, A. P., Sander, C., & Schultz, N.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Authors' Affiliations: 1Computational Biology Center, Memorial Sloan-Kettering Cancer Center, 2Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York; and 3Computer Engineering Department, Bilkent University, Ankara, Turkey
- Corresponding author
- Cerami, Ethan
- ORCID
- Venue
- Cancer Discovery
- Published
- 2012-05-01
- Volume
- 2
- Issue
- 5
- Pages
- 401-404
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC3956037
- OpenAlex
- W2149441684
- Semantic Scholar
- b8d2639696825d163188eb5cea5582c350987b70
- Cited by
- 17,455
- References
- 17
- Citations by year
- 2026: 945 · 2025: 1525 · 2024: 1764 · 2023: 2020 · 2022: 2020 · 2021: 2136 · 2020: 1836 · 2019: 1393 · 2018: 1048 · 2017: 906 · 2016: 764 · 2015: 583 · 2014: 324 · 2013: 159 · 2012: 15
- FWCI
- 114.79
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Bilkent University Institutional Repository (Bilkent University) (submittedVersion, other-oa)
- Bilkent University Institutional Repository (Bilkent University) (submittedVersion)
- Funders
- Memorial Sloan-Kettering Cancer Center
- University of Toronto
- Bilkent Üniversitesi
- National Institutes of Health
- University of Texas MD Anderson Cancer Center
- Stand Up To Cancer (SU2C‐AACR‐DT0209)
- National Cancer Institute (SU2C-AACR-DT0209, R01CA132744, U24CA143840, NCI-U24CA143840, NCI-R21CA135870, R21CA135870)
- National Institute of General Medical Sciences (GM 103504, P41GM103504)
- National Center for Research Resources (RR031228, P41RR031228)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- cancer genomics data, interactive data exploration, tumor molecular profiles, clinical features, cancer research resources
- MeSH terms
- Database Management Systems, Humans, Neoplasms, Databases, Factual, Internet, Genomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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