|Title||A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Berger, AC, Korkut, A, Kanchi, RS, Hegde, AM, Lenoir, W, Liu, W, Liu, Y, Fan, H, Shen, H, Ravikumar, V, Rao, A, Schultz, A, Li, X, Sumazin, P, Williams, C, Mestdagh, P, Gunaratne, PH, Yau, C, Bowlby, R, A Robertson, G, Tiezzi, DG, Wang, C, Cherniack, AD, Godwin, AK, Kuderer, NM, Rader, JS, Zuna, RE, Sood, AK, Lazar, AJ, Ojesina, AI, Adebamowo, C, Adebamowo, SN, Baggerly, KA, Chen, T-W, Chiu, H-S, Lefever, S, Liu, L, MacKenzie, K, Orsulic, S, Roszik, J, Shelley, CSimon, Song, Q, Vellano, CP, Wentzensen, N, Weinstein, JN, Mills, GB, Levine, DA, Akbani, R|
|Corporate Authors||Cancer Genome Atlas Research Network|
|Date Published||2018 Apr 09|
We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.
|Alternate Journal||Cancer Cell|