<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Thennavan A</submitter><funding>Breast Cancer Research Foundation</funding><funding>Susan G. Komen</funding><funding>National Cancer Institute</funding><funding>NCI NIH HHS</funding><funding>University of North Carolina at Chapel Hill</funding><pagination>100067</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9028992</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>1(3)</volume><pubmed_abstract>Breast cancer is classified into multiple distinct histologic types, and many of the rarer types have limited characterization. Here, we extend The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset with additional histologic type annotations, in a total of 1063 breast cancers. We analyze this extended dataset to define transcriptomic and genomic profiles of six rare special histologic types: cribriform, micropapillary, mucinous, papillary, metaplastic, and invasive carcinoma with medullary pattern. We show the broader applicability of our constructed special histologic type gene signatures in the TCGA Pan-Cancer Atlas dataset with a predictive model that detects mucinous histologic type across cancers of other organ systems. Using a normal mammary cell differentiation score analysis, w</pubmed_abstract><journal>Cell genomics</journal><pubmed_title>Molecular analysis of TCGA breast cancer histologic types.</pubmed_title><pmcid>PMC9028992</pmcid><funding_grant_id>RO1-CA195740</funding_grant_id><funding_grant_id>P50 CA058223</funding_grant_id><funding_grant_id>R01 CA195740</funding_grant_id><funding_grant_id>R01 CA148761</funding_grant_id><funding_grant_id>P50-CA58223</funding_grant_id><funding_grant_id>SAC-160074</funding_grant_id><funding_grant_id>RO1-CA148761</funding_grant_id><pubmed_authors>Xia Y</pubmed_authors><pubmed_authors>Allison K</pubmed_authors><pubmed_authors>Collins LC</pubmed_authors><pubmed_authors>Beck A</pubmed_authors><pubmed_authors>Thennavan A</pubmed_authors><pubmed_authors>Schnitt SJ</pubmed_authors><pubmed_authors>Hoadley KA</pubmed_authors><pubmed_authors>Chen YY</pubmed_authors><pubmed_authors>Beca F</pubmed_authors><pubmed_authors>Tse GM</pubmed_authors><pubmed_authors>Perou CM</pubmed_authors><pubmed_authors>Recio SG</pubmed_authors></additional><is_claimable>false</is_claimable><name>Molecular analysis of TCGA breast cancer histologic types.</name><description>Breast cancer is classified into multiple distinct histologic types, and many of the rarer types have limited characterization. Here, we extend The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset with additional histologic type annotations, in a total of 1063 breast cancers. We analyze this extended dataset to define transcriptomic and genomic profiles of six rare special histologic types: cribriform, micropapillary, mucinous, papillary, metaplastic, and invasive carcinoma with medullary pattern. We show the broader applicability of our constructed special histologic type gene signatures in the TCGA Pan-Cancer Atlas dataset with a predictive model that detects mucinous histologic type across cancers of other organ systems. Using a normal mammary cell differentiation score analysis, w</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 Dec</publication><modification>2026-05-10T01:01:04.383Z</modification><creation>2025-04-07T01:52:44.895Z</creation></dates><accession>S-EPMC9028992</accession><cross_references><pubmed>35465400</pubmed><doi>10.1016/j.xgen.2021.100067</doi></cross_references></HashMap>