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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

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.

SUBMITTER: Berger AC

PROVIDER: S-EPMC5959730 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

Berger Ashton C AC Korkut Anil A Kanchi Rupa S RS Hegde Apurva M AM Lenoir Walter W Liu Wenbin W Liu Yuexin Y Fan Huihui H Shen Hui H Ravikumar Visweswaran V Rao Arvind A Schultz Andre A Li Xubin X Sumazin Pavel P Williams Cecilia C Mestdagh Pieter P Gunaratne Preethi H PH Yau Christina C Bowlby Reanne R Robertson A Gordon AG Tiezzi Daniel G DG Wang Chen C Cherniack Andrew D AD Godwin Andrew K AK Kuderer Nicole M NM Rader Janet S JS Zuna Rosemary E RE Sood Anil K AK Lazar Alexander J AJ Ojesina Akinyemi I AI Adebamowo Clement C Adebamowo Sally N SN Baggerly Keith A KA Chen Ting-Wen TW Chiu Hua-Sheng HS Lefever Steve S Liu Liang L MacKenzie Karen K Orsulic Sandra S Roszik Jason J Shelley Carl Simon CS Song Qianqian Q Vellano Christopher P CP Wentzensen Nicolas N Weinstein John N JN Mills Gordon B GB Levine Douglas A DA Akbani Rehan R

Cancer cell 20180402 4

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 recep ...[more]

PMID: 29622464

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Project description:BackgroundIn recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs).MethodsTo compare consistency and difference, we explored the expression pattern and prognostic value of necroptosis-related genes (NRGs) in pan-GC analysis through Linear regression and Empirical Bayesian, Univariate Cox analysis, and public databases from TCGA and Genotype-Tissue Expression (GTEx), including CESC, OV, UCEC, and UCS. We explored the copy number variation (CNV), methylation level and enrichment pathways of NRGs in the four GCs. Based on LASSO Cox regression analysis or principal component analysis, we established the prognostic NRG-signature or necroptosis-score for the four GCs. In addition, we predicted and compared functional pathways, tumor mutational burden (TMB), somatic mutation features, immunity status, immunotherapy, chemotherapeutic drug sensitivity of the NRG-signature based on NRGs. We also examined the expression level of several NRGs in OV samples that we collected using Quantitative Real-time PCR.ResultsWe confirmed the presence of NRGs in expression, prognosis, CNV, and methylation for four GCs, thus comparing the consistency and difference among the four GCs. The prognosis and independent prognostic value of the risk signatures based on NRGs were determined. Through the results of subclass mapping, we found that GC patients with lower risk score may be more sensitive to PDL1 response and more sensitive to immune checkpoint blockade therapy. Drug susceptibility analysis showed that, 51, 45, 64, and 29 drugs with differences between risk groups were yielded in CESC, OV, UCEC, and UCS respectively. For OV, the expression differences of several NRGs in the tissues we collected were similar to that in TCGA.ConclusionOur comprehensive analysis of NRGs and NRG-signature demonstrated their similarity and difference, as well as their potential roles in prognosis and could guide therapeutic strategies, thus improving the outcome of GC patients.

Dataset Information

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

Publications

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

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