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The cBioPortal for Cancer Genomics was originally developed at [Memorial Sloan Kettering Cancer Center]( (MSK). The [public cBioPortal site]( is hosted by the [Center for Molecular Oncology]( at MSK. The cBioPortal software is now available under an open source license via [GitHub]( The software is now developed and maintained by a multi-institutional team, consisting of MSK, the Dana Farber Cancer Institute, Princess Margaret Cancer Centre in Toronto, Children's Hospital of Philadelphia, The Hyve in the Netherlands, and Bilkent University in Ankara, Turkey.
## Memorial Sloan Kettering Cancer Center
* Jianjiong Gao
* Benjamin Gross
* S. Onur Sumer
* Yichao Sun
* Hongxin Zhang
* Adam Abeshouse
* Ritika Kundra
* Ino de Bruijn
* Zachary Heins
* Robert Sheridan
* Angelica Ochoa
* Manda Wilson
* Jiaojiao Wang
* Nikolaus Schultz
## Dana-Farber Cancer Institute
* Ethan Cerami
* Ersin Ciftci
* James Lindsay
* Priti Kumari
* Catherine Del Vecchio
* Andy Dufilie
* Chris Sander
## Princess Margaret Cancer Centre, Toronto
* Stuart Watt
* Trevor Pugh
## Children's Hospital of Philadelphia
* Pichai Raman
* Karthik Kalletla
* John Maris
* Adam Resnick
## The Hyve
* Pieter Lukasse
* Fedde Schaeffer
* Sjoerd van Hagen
* Sander de Ridder
* Kees van Bochove
## Bilkent University
* Ugur Dogrusoz
* Istemi Bahceci
* M. Furkan Sahin
## Weill Cornell Medicine
* Alexandros Sigaras
* Ken Eng
* Andrea Sboner
* Olivier Elemento
* Mark Rubin
* Lewis Cantley
## Alumni
* B. Arman Aksoy
* Caitlin Byrne
* Hsiao-Wei Chen
* Fred Criscuolo
* Gideon Dresdner
* Arthur Goldberg
* Michael Heuer
* Anders Jacobsen
* Erik Larsson
* Dong Li
* James Xu
## Funding for the cBioPortal for Cancer Genomics is or has been provided by:
### Current:
* Marie-José and Henry R. Kravis Center for Molecular Oncology at MSK
* Dana Farber Cancer Institute
* Robertson Foundation
* POETIC Consortium
* Prostate Cancer Foundation
* Breast Cancer Research Foundation
* Adenoid Cystic Carcinoma Research Foundation
### Past:
* Stand Up 2 Cancer
* American Association for Cancer Research (AACR) through Project GENIE
* The Ben & Catherine Ivy Foundation
* NCI, as a [TCGA Genome Data Analysis Center (GDAC)]( (NCI-U24CA143840)
* NCRR, as the [National Resource for Network Biology (NRNB)]( Research Resource (RR 031228-02)
* Starr Cancer Consortium
\ No newline at end of file
# Frequently Asked Questions
## General Questions
### What is the cBioPortal for Cancer Genomics?
The cBioPortal for Cancer Genomics is an open-access, open-source resource for interactive exploration of multidimensional cancer genomics data sets. The cBioPortal 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.
### How do I get started?
Check out our [tutorial paper]( to get started.
### What data types are in the portal?
The portal currently stores DNA copy-number data (putative, discrete values per gene, e.g. "deeply deleted" or "amplified", as well as log2 levels), mRNA and microRNA expression data, non-synonymous mutations, protein-level and phosphoprotein level (RPPA) data, DNA methylation data, and limited de-identified clinical data. For a complete breakdown of available data types per cancer study go to the [Data Sets Page](
### What is the process of data curation?
The TCGA provisional datasets are directly from [TCGA data center]( partly via [Broad Firehose]( which are updated regularly.
We are also actively curating datasets from literature. Studies from literature were curated from the data published with the papers. We sometimes reach out to the investigators to additional data such as clinical attributes. All the mutation data (VCF or MAF) were processed through an internal pipeline to annotate the variant effects in a consistent way across studies.
Please [contact us]( to suggest public datasets to curate.
### How do I get updates on new portal developments and new data sets?
Please subscribe to our low-traffic [news mailing list]( or follow us on [Twitter](
### Does the portal work on all browsers and operating systems?
We support and test on the following web browsers: Internet Explorer 11.0 and above, Firefox 3.0 and above, Safari and Google Chrome. If you notice any other incompatibilities, please let us know.
### How do I cite the cBioPortal?
You can cite the following portal papers:
* Cerami et al. The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data. _Cancer Discovery_. May 2012 2; 401. [Abstract](
* Gao et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. _Sci. Signal._ 6, pl1 (2013). [Reprint](
### Can I use figures from the cBioPortal in my publications or presentations?
Yes, you are free to use any of the figures from the portal in your publications or presentations (many are available as PDFs for easier scaling and editing). When you do, please cite Cerami et al., Cancer Discov. 2012 and Gao et al. Sci. Signal. 2013.
When using TCGA data in your publications, please adhere to the [TCGA publication guidelines](
### How is the cBioPortal for Cancer Genomics different from the TCGA Data Portal?
The cBio portal is an exploratory analysis tool for exploring large-scale cancer genomic data sets. You can quickly view genomic alterations across a set of patients, across a set of cancer types, perform survival analysis and perform network analysis. By contrast, the [TCGA Data Portal]( aims to be the definitive place for full-download and access to all data generated by TCGA. If you want to explore a pathway of interest in one or more cancer types, the cBio portal is probably where you want to start. However, if you want to download raw mRNA expression files or full segmented copy number files, the TCGA Data Portal is probably where you want to start.
### Does the cBioPortal provide a Web Service API? R interface? MATLAB interface?
Yes, the cBioPortal provides a [Web API](, and [R/MATLAB interfaces](
### Can I create a local instance of cBioPortal to host my own data?
Yes, the cBioPortal is open-source, and available on [GitHub]( Our [Wiki pages]( provide complete download and installation instructions.
### I'd like to contribute code to the cBioPortal. How do I get started?
Great! We would love to have your contributions. To get started, head over to our GitHub repository and check out our page on [how to contribute](
## Data-Specific Questions
### Does the cBioPortal contain synonymous mutation data?
No, the cBioPortal does not currently support synonymous mutations. This may change in the future, but we have no plans yet to add this feature.
### Why do some cancer studies have mutation data and others do not?
We store mutation data for published cancer studies. We do not, however store mutation data for provisional cancer data sets generated by TCGA. This is because provisional studies contain preliminary somatic mutations, which per NCI guidelines cannot be redistributed until they have been validated. As each cancer study is published and finalized by the TCGA, we will import the corresponding mutation data.
### Does the portal contain cancer study X?
Check out the [Data Sets Page]( for the complete set of cancer studies currently stored in the portal. If you do not see your specific cancer study of interest, please contact us directly, and we will let you know if it's in the queue.
### What kind of clinical data is stored in the portal?
The portal currently stores overall and disease-free survival data, plus limited de-identified clinical data, such as gender, age, stage and tumor grade, when available.
### Does the portal store raw or probe-level data?
No, the portal only contains gene-level data. Data for different isoforms of a given gene are merged. Raw and probe-level data for all date sets is available via NCBI GEO or through the TCGA Data Portal. See the cancer type description on the main query page for links to the raw data.
### Which methylation probe is used for genes with multiple probes?
For genes with multiple probes, we only include methylation data from the probe with the strongest negative correlation between the methylation signal and the gene's expression.
### How can I query phosphoprotein levels in the portal?
You need to input special IDs for each phosphoprotein/phopshosite such as _AKT_pS473_ (which means AKT protein phosphorylated at serine residue at position 473). You could also input aliases such as _phosphoAKT1_ or _phosphoprotein_, and the portal will ask you to select the phosphoprotein/phosphosite of your interest.
### How can I query microRNAs in the portal?
You can input either precusor or mature miRNA IDs. Since one precusor ID may correspond to multiple mature IDs and vise versa, the portal creates one internal ID for each pair of precursor ID and mature ID mapping. For example, an internal ID of MIR-29B-1/29B stands for precursor microRNA hsa-mir-29b-1 and mature microRNA hsa-miR-29b. After entering a precusor or mature ID, you will be asked to select one internal ID for query and that internal ID will also be displayed in the Oncoprint.
### What are mRNA and microRNA Z-Scores?
For mRNA and microRNA expression data, we typically compute the relative expression of an individual gene and tumor to the gene's expression distribution in a reference population. That reference population is all samples that are diploid for the gene in question (by default for mRNA), or normal samples (when specified), or all profiled samples . The returned value indicates the number of standard deviations away from the mean of expression in the reference population (Z-score). This measure is useful to determine whether a gene is up- or down-regulated relative to the normal samples or all other tumor samples.
### Are there any normal samples available through cBioPortal?
No, we currently do not store any normal data in our system.
### What is GISTIC? What is RAE?
Copy number data sets within the portal are generated by [GISTIC]( or [RAE]( algorithms. Both algorithms attempt to identify significantly altered regions of amplification or deletion across sets of patients. Both algorithms also generate putative gene/patient copy number specific calls, which are then input into the portal.
For TCGA studies, the table in all_thresholded.by_genes.txt (which is the part of the GISTIC output that is used to determine the copy-number status of each gene in each sample in cBioPortal) is obtained by applying both low- and high-level thresholds to to the gene copy levels of all the samples. The entries with value +/- 2 exceed the high-level thresholds for amps/dels, and those with +/- 1 exceed the low-level thresholds but not the high-level thresholds. The low-level thresholds are just the 'amp_thresh' and 'del_thresh' noise threshold input values to GISTIC (typically 0.1 or 0.3) and are the same for every thresholds.
By contrast, the high-level thresholds are calculated on a sample-by-sample basis and are based on the maximum (or minimum) median arm-level amplification (or deletion) copy number found in the sample. The idea, for deletions anyway, is that this level is a good approximation for hemizygous given the purity and ploidy of the sample. The actual cutoffs used for each sample can be found in a table in the output file sample_cutoffs.txt. All GISTIC output files for TCGA are available at:
### What do "-2", "-1", "0", "1", and "2" mean in the copy-number data?
These levels are derived from the copy-number analysis algorithms GISTIC or RAE, and indicate the copy-number level per gene. "-2" is a deep loss, possibly a homozygous deletion, "-1" is a shallow loss (possibly heterozygous deletion), "0" is diploid, "1" indicates a low-level gain, and "2" is a high-level amplification. Note that these calls are putative.
### What are the sources of biological network data?
The biological network data were retrieved from [Pathway Commons](
### How does cBioPortal handle duplicate samples or sample IDs across different studies?
The cBioPortal assumes that samples or patients that have the same ID are actually the same. This is important for cross-cancer queries, where each sample should only be counted once. If a sample is part of multiple cancer cohorts, its alterations are only counted once in cross-cancer summaries: while it is listed multiple times in cross-cancer mutation tables, it is only counted once in summary statistics (e.g., alteration frequencies) and in mutation diagrams. To avoid any confusion and miscounts, all sample IDs in cBioPortal of samples that are different should be unique, and identical samples in different cohorts should use the same ID.
## OncoPrint-Specific Questons
### What are OncoPrints?
OncoPrints are compact means of visualizing distinct genomic alterations, including somatic mutations, copy number alterations, and mRNA expression changes across a set of cases. They are extremely useful for visualizing gene set and pathway alterations across a set of cases, and for visually identifying trends, such as trends in mutual exclusivity or co-occurence between gene pairs within a gene set. Individual genes are represented as rows, and individual cases or patients are represented as columns.
![Example OncoPrint](images/previews/gbm_oncoprint.png)
### Can I change the order of genes in the OncoPrint?
The order of genes in the OncoPrint is determined by the order entered into the initial query field. Simply change the initial gene order, resubmit your query, and the change will be reflected in the OncoPrint.
### Can I visualize my own data within an OncoPrint?
Yes, check out the OncoPrinter tool on our [tools page](
## What if I have other questions or comments?
Please contact us at []( Previous discussions about cBioPortal are available on the [user discussion mailing list](
# March 28, 2017
* **New features**:
* Per-sample mutation spectra are now available in OncoPrints -- see [example](,NO_CONTEXT_MUTATION_SIGNATURE,%23%20mutations&)
* mRNA heat map clustering is now supported in OncoPrints
* MDACC Next-Generation Clustered Heat Maps are now available in the patient view
* cBioPortal web site style change
# Feburary 2, 2017
* **New features**:
* 3D hotspot mutation annotations are now available from
* **New data**:
* CPTAC proteomics data have been integrated for TCGA breast, ovarian, and colorectal provisional studies
# December 23, 2016
* **New features**:
* Heat map visualization of gene expression data in the OncoPrint
![OncoPrint Heatmap](
* Heat map visualization of gene expression data in the Study View page connecting to MDACC's TCGA Next-Generation Clustered Heat Map Compendium
# October 7, 2016
* **New features**:
* All data sets can now be downloaded as flat files from the new [Data Hub](
* Annotation of putative driver missense mutations in OncoPrints, based on [OncoKB](, mutation hotspots, and recurrence in cBioPortal and COSMIC
* Copy number segments visualization directly in the browser in a new *CN Segments* tab via [IGV.js](
* **Improvements**:
* Improved cancer study view page (bug fixes and increased performance)
# July 24, 2016
* **Added data** of 4,375 samples from 21 published studies:
* [Adenoid Cystic Carcinoma (MDA, Clin Cancer Res 2015)]( *102 samples*
* [Adenoid Cystic Carcinoma (FMI, Am J Surg Pathl. 2014)]( *28 samples*
* [Adenoid Cystic Carcinoma (Sanger/MDA, JCI 2013)]( *24 samples*
* [Adenoid Cystic Carcinoma of the Breast (MSKCC, J Pathol. 2015)]( *12 samples*
* [Bladder Cancer, Plasmacytoid Variant (MSKCC, Nat Genet 2016)]( *34 samples*
* [Breast Cancer (METABRIC, Nat Commun 2016)]( *1980 samples*
* [Chronic Lymphocytic Leukemia (Broad, Cell 2013)]( *160 samples*
* [Chronic Lymphocytic Leukemia (IUOPA, Nature 2015)]( *506 samples*
* [Colorectal Adenocarcinoma (DFCI, Cell Reports 2016)]( *619 samples*
* [Cutaneous T Cell Lymphoma (Columbia U, Nat Genet 2015)]( *42 samples*
* [Diffuse Large B-Cell Lymphoma (Broad, PNAS 2012)]( *58 samples*
* [Hepatocellular Adenoma (Inserm, Cancer Cell 2014)]( *46 samples*
* [Hypodiploid Acute Lymphoid Leukemia (St Jude, Nat Genet 2013)]( *44 samples*
* [Insulinoma (Shanghai, Nat Commun 2013)]( *10 samples*
* [Malignant Pleural Mesothelioma (NYU, Cancer Res 2015)]( *22 samples*
* [Mantle Cell Lymphoma (IDIBIPS, PNAS 2013)]( *29 samples*
* [Myelodysplasia (Tokyo, Nature 2011)]( *29 samples*
* [Neuroblastoma (Broad, Nat Genet 2013)]( *56 samples*
* [Oral Squamous Cell Carcinoma (MD Anderson, Cancer Discov 2013)]( *40 samples*
* [Pancreatic Adenocarcinoma (QCMG, Nature 2016)]( *383 samples*
* [Recurrent and Metastatic Head & Neck Cancer (JAMA Oncology, 2016)]( *151 samples*
* **New TCGA study**:
* [Pan-Lung Cancer (TCGA, Nat Genet 2016)]( *1144 samples*
* Updated **TCGA provisional studies**
* updated to the Firehose run of January 28, 2016
* RPPA data updated with the latest data from MD Anderson
* [OncoTree]( codes assigned per sample
# June 6, 2016
* **New features**:
* Annotation of mutation effect and drug sensitivity on the Mutations tab and the patient view pages (via [OncoKB](
* **Improvements**:
* Improved OncoPrint visualization using WebGL: faster, more zooming flexibility, visualization of recurrent variants
* Improved Network tab with SBGN view for a single interaction
* Performance improvement of tables in the study view page
* Mutation type summary on the Mutations tab
# March 31, 2016
* **New features**:
* Visualization of "Enrichments Analysis" results via volcano plots
* Improved performance of the cross cancer expression view by switching to graphs
* Improvements to the "Clinical Data" tab on the study view page
* More customization options for the cross-cancer histograms
* Performance improvements in the study view and query result tabs
* **Added data** of 1235 samples from 3 published studies:
* [Merged Cohort of LGG and GBM (TCGA, 2016)](
* [Lung Adenocarcinoma (MSKCC, 2015)](
* [Poorly-Differentiated and Anaplastic Thyroid Cancers (MSKCC, JCI 2016)](
# January 12, 2016
* **New features**:
* Visualization of multiple samples in a patient
* Visualization of timeline data of a patient ([example](<br/>
* All **TCGA data** updated to the latest Firehose run of August 21, 2015
* **New TCGA studies**:
* [Cholangiocarcinoma (TCGA, Provisional)](
* [Mesothelioma (TCGA, Provisional)](
* [Testicular Germ Cell Cancer (TCGA, Provisional)](
* [Thymoma (TCGA, Provisional)](
* **Added data** of 650 samples from 10 published studies:
* [Neuroblastoma (AMC Amsterdam, Nature 2012)](
* [Clear Cell Renal Cell Carcinoma (U Tokyo, Nat Genet 2013)](
* [Multiregion Sequencing of Clear Cell Renal Cell Carcinoma (IRC, Nat Genet 2014)](
* [Bladder Urothelial Carcinoma (Dana Farber & MSKCC, Cancer Discovery 2014)](
* [Low-Grade Gliomas (UCSF, Science 2014) ](
* [Esophageal Squamous Cell Carcinoma (UCLA, Nat Genet 2014)](
* [Acinar Cell Carcinoma of the Pancreas (Johns Hopkins, J Pathol 2014)](
* [Gastric Adenocarcinoma (TMUCIH, PNAS 2015)](
* [Primary Central Nervous System Lymphoma (Mayo Clinic, Clin Cancer Res 2015)](
* [Desmoplastic Melanoma (Broad Institute, Nat Genet 2015)](
* All mutation data mapped to [UniProt canonical isoforms](
# December 23, 2015
* **New features**:
* Visualization of RNA-seq expression levels across TCGA studies (cross-cancer queries)<br/>
![cross cancer expression](
* Selection of genes in the study view to initiate queries<br/>
![query gene in study view](
* **Improvement**:
* 3-D structures in the "Mutations" tab are now rendered by 3Dmol.js (previously JSmol)
* Improved performance by code optimization and compressing large data by gzip
# December 1, 2015
* **New feature**: Annotated statistically recurrent hotspots, via new algorithm by [Chang et al. 2015](</br>
![Annotate recurrent hotspots](
# November 9, 2015
* **New features**:
* Links to for mutations<br/>
![Link to](
* Improved display of selection samples on the study view page
* **Improvements**:
* "Enrichments" analysis is now run across all genes
* The "Network" tab is now using Cytoscape.js (Adobe Flash is no longer required)
# October 6, 2015
* **New TCGA data**:
* [Breast Invasive Carcinoma (TCGA, Cell 2015)](
* [Prostate Adenocarcinoma (TCGA, in press)](
* [Uveal Melanoma (TCGA, Provisional)](
* **Added data** of 763 samples from 12 published studies:
* [Small Cell Lung Cancer (U Cologne, Nature 2015)](
* [Uterine Carcinosarcoma (JHU, Nat Commun 2014)](
* [Microdissected Pancreatic Cancer Whole Exome Sequencing (UTSW, Nat Commun 2015)](
* [Pancreatic Neuroendocrine Tumors (JHU, Science 2011)](
* [Renal Non-Clear Cell Carcinoma (Genentech, Nat Genet 2014)](
* [Infant MLL-Rearranged Acute Lymphoblastic Leukemia (St Jude, Nat Genet 2015)](
* [Rhabdomyosarcoma (NIH, Cancer Discov 2014)](
* [Thymic epithelial tumors (NCI, Nat Genet 2014)](
* [Pediatric Ewing Sarcoma (DFCI, Cancer Discov 2014)](
* [Ewing Sarcoma (Institut Cuire, Cancer Discov 2014)](
* [Cutaneous squamous cell carcinoma (DFCI, Clin Cancer Res 2015)](
* [Gallbladder Carcinoma (Shanghai, Nat Genet 2014)](
# August 21, 2015
* All **TCGA data** updated to the Firehose run of April 16, 2015.
* **New feature**: Enrichments Analysis finds alterations that are enriched in either altered or unaltered samples.
* **Improvement**: improved OncoPrint with better performance.
# June 3, 2015
* **Improvements**:
* Allowed downloading data in each chart/table in study summary page.
* Added log-rank test _p_-values to the survival plots in study summary page.
* Improved visualization of patient clinical data in patient-centric view.
* Added option to merge multiple samples for the same patient in OncoPrint.
# April 28, 2015
* **New features**:
* Redesigned query interface to allow selecting multiple cancer studies
* Redesigned **Plots** tab
# January 20, 2015
* All **TCGA data** updated to the Firehose run of October 17, 2014
* **COSMIC data** updated to V71
* **New features**:
* Query page: better search functions to find cancer studies
* OncoPrints now support color coding of different mutation types
* OncoPrints now support multiple clinical annotation tracks
* [**OncoPrinter tool**]( now supports mRNA expression changes
![Oncoprint with multiple clinical tracks](images/previews/multi-clinical-track-oncoprint.png)
# January 6, 2015
* **New feature**: You can now view **frequencies of mutations and copy-number alterations** in the study view. These tables are updated dynamically when selecting subsets of samples.
![Alterations in heavily copy-number altered endometrial cancer cases](images/previews/study_view_alt_frequencies.png)
# December 9, 2014
* **New TCGA data**:
* Added complete and up-to-date **clinical data** for all **TCGA** provisional studies
* All TCGA data updated to the Firehose run of July 15, 2014
* New TCGA provisional studies: Esophageal cancer, Pheochromocytoma and Paraganglioma (PCPG)
* New published TCGA studies: [Thyroid Cancer]( and [Kidney Chromophobe](
* **Added data** of 172 samples from 4 published studies:
* [Cholangiocarcinoma (National University of Singapore, Nature Genetics 2012)](
* [Cholangiocarcinoma (National Cancer Centre of Singapore, Nature Genetics 2013)](
* [Intrahepatic Cholangiocarcinoma (Johns Hopkins University, Nature Genetics 2013)](
* [Bladder Cancer (MSKCC, Eur Urol 2014)](
* **New features**:
* Redesigned **Mutual Exclusivity** tab
* Added **correlation scores** for scatter plots on the Plots tab
* Download links to [**GenomeSpace**](
# October 24, 2014
* Added data of 885 samples from 11 published studies:
* [Colorectal Adenocarcinoma Triplets (MSKCC, Genome Biology 2014)](
* [Esophageal Squamous Cell Carcinoma (ICGC, Nature 2014)](
* [Malignant Peripheral Nerve Sheath Tumor (MSKCC, Nature Genetics 2014)](
* [Melanoma (Broad/Dana Farber, Nature 2012)](
* [Nasopharyngeal Carcinoma (National University Singapore, Nature Genetics 2014)](
* [Prostate Adenocarcinoma CNA study (MSKCC, PNAS 2014)](
* [Prostate Adenocarcinoma Organoids (MSKCC, Cell 2014)](
* [Stomach Adenocarcinoma (TCGA, Nature 2014)](
* [Stomach Adenocarcinoma (Pfizer and University of Hong Kong, Nature Genetics 2014)](
* [Stomach Adenocarcinoma (University of Hong Kong, Nature Genetics 2011)](
* [Stomach Adenocarcinoma (University of Tokyo, Nature Genetics 2014)](
# August 8, 2014
* Released two new tools
* [Oncoprinter]( lets you create Oncoprints from your own, custom data
* [MutationMapper]( draws mutation diagrams (lollipop plots) from your custom data
# May 21, 2014
* All TCGA data updated to the Firehose run of April 16, 2014
# May 12, 2014
* Improved study summary page including survival analysis based on clinical attributes
e.g. [TCGA Endometrial Cancer cohort](
![Study view](images/previews/study_view.png)
# March 27, 2014
* New features:
* Visualizing of mutations mapped on 3D structures (individual or multiple mutations, directly in the browser)
* Gene expression correlation analysis (find all genes with expression correlation to your query genes)
* The Patient-Centric View now displays mutation frequencies across all cohorts in cBioPortal for each mutation
* The Mutation Details Tab and the Patient-Centric View now display the copy-number status of each mutation
![3D viewer & Co-expression](images/previews/news_3d_coexp.png)
# March 18, 2014
* All TCGA data updated to the Firehose run of January 15, 2014
* Updated to the latest COSMIC data (v68)
* Added two new provisional TCGA studies:
* Adrenocortical Carcinoma
* Uterine Carcinosarcoma
* Added mutation data of 898 samples from 11 published studies:
* Hepatocellular Carcinoma (RIKEN, Nature Genetics 2012)
* Hepatocellular Carcinoma (AMC, Hepatology in press)
* Medulloblastoma (Broad, Nature 2012)
* Medulloblastoma (ICGC, Nature 2012)
* Medulloblastoma (PCGP, Nature 2012)
* Multiple Myeloma (Broad, Cancer Cell 2014)
* Pancreatic Adenocarcinoma (ICGC, Nature 2012)
* Small Cell Carcinoma of the Ovary (MSKCC, Nature Genetics in press)
* Small Cell Lung Cancer (CLCGP, Nature Genetics 2012)
* Small Cell Lung Cancer (Johns Hopkins, Nature Genetics 2012)
* NCI-60 Cell Lines (NCI, Cancer Res. 2012)
# December 9, 2013
* Added mutation data of 99 bladder cancer samples (BGI, Nature Genetics 2013)
# December 6, 2013
* Data sets matching four recently submitted or published TCGA studies are now available
* Glioblastoma (Cell 2013)
* Bladder carcinoma (Nature, in press)
* Head & neck squamous cell carcinoma (submitted)
* Lung adenocarcinoma (submitted)
# November 8, 2013
* All TCGA data updated to the Firehose run of September 23, 2013.
* Updated to the latest COSMIC data (v67).
* Added mutation data of 792 samples from 9 published cancer studies:
* Esophageal Adenocarcinoma (Broad, Nature Genetics 2013)
* Head and Neck Squamous Cell Carcinoma (Broad, Science 2011)
* Head and Neck Squamous Cell Carcinoma (Johns Hopkins, Science 2011)
* Kidney Renal Clear Cell Carcinoma (BGI, Nature Genetics 2012)
* Prostate Adenocarcinoma, Metastatic (Michigan, Nature 2012)
* Prostate Adenocarcinoma (Broad/Cornell, Nature Genetics 2012)
* Prostate Adenocarcinoma (Broad/Cornell, Cell 2013)
* Skin Cutaneous Melanoma (Yale, Nature Genetics 2012)
* Skin Cutaneous Melanoma (Broad, Cell 2012)
# October 21, 2013
* Improved interface for survival plots, including information on individual samples via mouse-over
* New fusion glyph in OncoPrints [![FGFR3 fusions in head and neck carcinoma](images/previews/fusion-in-oncoprint.png)](
* Improved cross-cancer query: new alteration frequency histogram (example below - query gene: CDKN2A) and mutation diagram
<center>![Cross Cancer Query](images/previews/cross_cancer.png)</center>
# September 9, 2013
* Updated COSMIC data (v66 Release)
* Improved / interactive visualization on the "Protein changes" tab
* Enhanced mutation diagrams: color-coding by mutation time and syncing with table filters
* Addition of DNA cytoband information in the patient view of copy-number changes
* OncoPrints now allow the display of an optional track with clinical annotation (Endometrial cancer example below)
<center>![Oncoprint with clinical track](images/previews/oncoprint_clinical_track.png)</center>
# July 25, 2013
* Multi-gene correlation plots.
* Variant allele frequency distribution plots for individual tumor samples.
* Tissue images for TCGA samples in the patient view, via [Digital Slide Archive]( [Example](
# July 16, 2013
* All TCGA data updated to the May Firehose run (May 23, 2013).
* TCGA Pancreatic Cancer study (provisional) added.
# July 4, 2013
* Improved rendering of mutation diagrams, including ability to download in PDF format.
* Improved home page: Searchable cancer study & gene set selectors, data sets selector.
# June 17, 2013
* Improved interface for correlation plots, including information on individual samples via mouse-over.
* Gene Details from Biogene are now available in the Network view.
* Added mutation and copy number data from a new adenoid cystic carcinoma study: Ho et al., Nature Genetics 2013.
* Added mutation data from 6 cancer studies.
* Breast Invasive Carcinoma (Shah et al., Nature 2012)
* Breast Invasive Carcinoma (Banerji et al., Nature 2012)
* Breast Invasive Carcinoma (Stephens et al., Nature 2012)
* Lung Adenocarcinoma (Imielinksi et al., Cell 2012)
* Lung Adenocarcinoma (Ding et al., Nature 2008)
* Colorectal Cancer (Seshagiri et al., Nature 2012)
# June 4, 2013
* All TCGA data updated to the April Firehose run (April 21, 2012).
# May 14, 2013
* Added a published TCGA study: Acute Myeloid Leukemia (TCGA, NEJM 2013).
# April 28, 2013
* All TCGA data updated to the March Firehose run (March 26, 2012).
* mRNA percentiles for altered genes shown in patient view.
# April 2, 2013
* All TCGA data updated to the February Firehose run (February 22, 2012).
# March 28, 2013
* All TCGA data updated to the January Firehose run (January 16, 2012).
* Data from a new bladder cancer study from MSKCC has been added (97 samples, Iyer et al., JCO in press).
# February 16, 2013
* The cBio Portal now contains mutation data from all provisional TCGA projects. Please adhere to [the TCGA publication guidelines]( when using these and any TCGA data in your publications.
* All data updated to the October Firehose run (October 24, 2012).
* **Sequencing read counts and frequencies** are now shown in the Mutation Details table when available.
* Improved OncoPrints, resulting in performance improvements.
# November 21, 2012
* Major new feature: Users can now visualize **genomic alterations and clinical data of individual tumors**, including:
* Summary of **mutations** and **copy-number alterations** of interest
* **Clinical trial** information
* TCGA **Pathology Reports**
* New **cancer summary view** (Example [Endometrial Cancer](
* **Updated drug data** from KEGG DRUG and NCI Cancer Drugs (aggregated by [PiHelper](
# October 22, 2012
* All data updated to the **Broad Firehose** run from July 25, 2012.
* **COSMIC data** added to Mutation Details (via Oncotator).
* All predicted functional impact scores are updated to **Mutation Assessor 2.0**.
* Users can now base queries on genes in recurrent regions of copy-number alteration (from **GISTIC** via Firehose).
* The [Onco Query Language (OQL)]( now supports queries for specific mutations or mutation types.
* Data sets added that match the data of all TCGA publications (GBM, ovarian, colorectal, and lung squamous).
# July 18, 2012
* Mutation data for the TCGA lung squamous cell carcinoma and breast cancer projects (manuscripts in press at Nature).
* All data updated to the **latest Broad Firehose run** (May 25, 2012).
* **Drug information** added to the network view (via Drugbank).
* **Improved cross-cancer** queries: Option to select data types, export of summary graphs.
* Users can now base queries on frequently mutated genes (from **MutSig** via Firehose).
# May 16, 2012
* All data updated to the **latest Broad Firehose run** (March 21, 2012).