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- Title
Clustering cancers by shared transcriptional risk reveals novel targets for cancer therapy.
- Authors
Gao, Hua; Baylis, Richard A.; Luo, Lingfeng; Kojima, Yoko; Bell, Caitlin F.; Ross, Elsie G.; Wang, Fudi; Leeper, Nicholas J.
- Abstract
A. Dimensional reduction and clustering of cancer types (full names provided in Table S1) based on transcriptional hallmark pathway expression and correlation with patient survival identifies three cancer subpopulations. To perform these studies, tumor tissue mRNA-Seq data, patients' demographic information, and survival status for 27 individual cancer types from the TCGA [[2]] (updated through May 2021) were used to compute a survival analysis for each gene and each cancer type.
- Subjects
CANCER treatment; RENAL cell carcinoma; HEAD &; neck cancer; SQUAMOUS cell carcinoma; MEDICAL care
- Publication
Molecular Cancer, 2022, Vol 21, Issue 1, p1
- ISSN
1476-4598
- Publication type
Article
- DOI
10.1186/s12943-022-01592-y