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A comprehensive pan-cancer molecular study of gynecologic and breast cancers
| File | Description | Size | Format | |
|---|---|---|---|---|
 1-s2.0-S1535610818301193-main.pdf | Published version | 7.74 MB | Adobe PDF | View/Open |
| Title: | A comprehensive pan-cancer molecular study of gynecologic and breast cancers |
| 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 Robertson, AG 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, CS Song, Q Vellano, CP Wentzensen, N Weinstein, JN Mills, GB Levine, DA Akbani, R |
| Item Type: | Journal Article |
| Abstract: | 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. |
| Issue Date: | 9-Apr-2018 |
| Date of Acceptance: | 12-Mar-2018 |
| URI: | http://hdl.handle.net/10044/1/71239 |
| DOI: | https://doi.org/10.1016/j.ccell.2018.03.014 |
| ISSN: | 1535-6108 |
| Publisher: | Elsevier |
| Start Page: | 690 |
| End Page: | 705.e9 |
| Journal / Book Title: | Cancer Cell |
| Volume: | 33 |
| Issue: | 4 |
| Copyright Statement: | © 2018 Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Sponsor/Funder: | SAIC-F-Frederick, Inc Leidos Biomedical Research, Inc. |
| Funder's Grant Number: | TCGA Pilot Program 15Y011ST |
| Keywords: | Science & Technology Life Sciences & Biomedicine Oncology Cell Biology MUTATIONAL SIGNATURES CLASS DISCOVERY ACCURATE MICROARRAY GENERATION LANDSCAPE REVEALS PFKFB3 QUANTIFICATION IDENTIFICATION TCGA The Cancer Genome Atlas breast cancer cervical cancer gynecologic cancer omics ovarian cancer pan-gynecologic uterine cancer uterine carcinosarcoma Breast Neoplasms DNA Copy Number Variations Databases, Genetic Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genetic Predisposition to Disease Genital Neoplasms, Female Humans Mutation Organ Specificity Prognosis RNA, Long Noncoding Receptors, Estrogen Cancer Genome Atlas Research Network Humans Breast Neoplasms Genital Neoplasms, Female Genetic Predisposition to Disease Receptors, Estrogen Prognosis Gene Expression Profiling Organ Specificity Gene Expression Regulation, Neoplastic Mutation Databases, Genetic Female Gene Regulatory Networks DNA Copy Number Variations RNA, Long Noncoding Science & Technology Life Sciences & Biomedicine Oncology Cell Biology MUTATIONAL SIGNATURES CLASS DISCOVERY ACCURATE MICROARRAY GENERATION LANDSCAPE REVEALS PFKFB3 QUANTIFICATION IDENTIFICATION Oncology & Carcinogenesis 1112 Oncology and Carcinogenesis 1109 Neurosciences |
| Publication Status: | Published |
| Open Access location: | https://www.cell.com/cancer-cell/fulltext/S1535-6108(18)30119-3 |
| Online Publication Date: | 2018-04-02 |
| Appears in Collections: | Department of Surgery and Cancer |