Summary
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The TCGA Breast Phenotype Research Group is part of the CIP TCGA Radiology Initiative focused on analyzing images from the TCGA-BRCA collection. The group began with a research project aimed at creating an ad hoc multi-institutional research team dedicated to discovering the value of applying controlled terminology to the MR imaging features of patients with breast cancer. These images correlate to the Breast Invasive Carcinoma (BRCA) data in the TCGA Data Portal. |
Starting or Joining a Research Project
Using the data from the TCGA Data Portal researchers have:
- Described new integrated insights into the four standard molecular subtypes of breast cancer: HER2-enriched, Luminal A, Luminal B, and Basal-like
- Also, identified mutated genes that are specific to each subtype
- Found that the Basal-like subtype shares many genetic features with high-grade serous ovarian cancer suggesting that the cancers have a common molecular origin and may share therapeutic opportunities
- Performed computational analyses that suggest that Basal-like breast cancer and serous ovarian cancer might both be susceptible to two types of cancer treatment
- A drug that inhibits blood vessel growth, cutting off the blood supply to the tumor
- Bioreductive drugs, which are inactive drugs that become toxic to cancer cells under low oxygen conditions
Research and Publications
Per TCGA and TCIA Guidelines formal permission requests are still required to submit publications using TCGA-BRCA data. Please see the following links for more information about the freedom-to-publish criteria for these data sets:
Data Source | Status |
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No restrictions; all data available without limitations | |
Publication limitations in place until 10/16/2013 |
We are currently hosting calls in support of TCGA-BRCA research projects on Wednesdays at 4pm Eastern. Please contact us at cancerimagingarchive@mail.nih.gov if you have any questions about these policies, or would like to inquire about setting up a new research project, discuss potential collaborations with existing groups or be otherwise join our public mailing list and be kept in the loop about new data releases and other related news as this effort moves forward.
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This is a listing of ongoing projects. If you are working with the
TCGA-BRCA
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Marker Paper and Image Source Sites (ISS)
Imaging Source Site (ISS) Groups will be populated and governed by participants from institutions that have provided imaging data to the archive for a given cancer type. Modeled after TCGA analysis groups, these groups are given the opportunity to publish a marker paper for a given cancer type per the aforementioned publication policy. It is hoped that this will generate increased participation in the building of these multi-institutional data sets that become an open community resource. Current TCGA-BRCA source sites include:
- Mayo Clinic
- Roswell Park Cancer Institute
- Memorial Sloan-Kettering Cancer Center
- University of Pittsburgh / UPMC
References
The
- Breast Image Feature Scoring Project - This project is in the preliminary stages and is being collaborated on by group members from MSKCC, MDACC, Roswell Park, and UPMC. Multiple readers are evaluating each subject's imaging features using a BIRADS inspired Breast Feature Key and then investigating potential correlations with the TCGA genomic and clinical data. This project is being led by Liz Morris of MSKCC.
- Mapping of Multi-modality Breast Image-based Phenotypes to Histopathology and Genomics – This project seeks to advance and relate quantitative, computer-extracted tumor and parenchymal characteristics from multi-modality breast images (e.g, mammography, ultrasound, and MRI) to clinical outcomes (diagnosis, staging, and response to therapy), histopathology, and genomics. This project being led by Maryellen Giger, Nancy Cox, and Robert Grossman at the University of Chicago. The quantitative output from this project also feeds other projects such as the Breast Image Feature Scoring Project.
- Correlating computer-extracted MRI features with clinical and genomic data - In this project, features are extracted from breast MR images using computer vision algorithms. These features are then correlated with clinical and genomic information. This project is being led by Maciej Mazurowski from Duke University.
- Clustering (supervised & unsupervised) of BRCA Data - Cases are clustered into semantically-distinct categories using image-derived features, followed by examination of genomic correlates from the obtained clusters. This project is being led by Arvind Rao and Gary Whitman of MDACC.
Publications
There are currently no imaging based publications for TCGA-BRCA. However, the following links contain publications from the main TCGA project, as well as their posted publication guidelines.