Cargando…
Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis
Objective: Liquid-liquid phase separation (LLPS) is a functional unit formed by specific molecules. It lacks a membrane and has been reported to play a crucial role in tumor drug resistance and growth by regulating gene expression and drug distribution. However, whether LLPS could be used to predict...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554098/ https://www.ncbi.nlm.nih.gov/pubmed/36246644 http://dx.doi.org/10.3389/fgene.2022.834471 |
_version_ | 1784806618249035776 |
---|---|
author | Yu-Qing, Huang Peng-Ping, Li Ke, Sun Ke-Xing, Yin Wei-Jun, Zhang Zhen-Yu, Wang |
author_facet | Yu-Qing, Huang Peng-Ping, Li Ke, Sun Ke-Xing, Yin Wei-Jun, Zhang Zhen-Yu, Wang |
author_sort | Yu-Qing, Huang |
collection | PubMed |
description | Objective: Liquid-liquid phase separation (LLPS) is a functional unit formed by specific molecules. It lacks a membrane and has been reported to play a crucial role in tumor drug resistance and growth by regulating gene expression and drug distribution. However, whether LLPS could be used to predict cancer prognosis was not clear. This study aimed to construct a prognostic model for breast cancer based on LLPS-correlated genes (LCGs). Methods: LCGs were identified using the PhaSepDB, gene expression profile and clinical characteristics of breast cancer were obtained from TCGA and cBioportal. The PanCancer Atlas (TCGA) cohort was used as the training cohort to construct the prognostic model, while the Nature 2012 and Nat Commun 2016 (TCGA) cohort and GEO data were used as test cohort to perform external verification. Data analysis was performed with R4.2.0 and SPSS20.0. Results: We identified 140 prognosis-related LCGs (pLCGs) (p< 0.01) in all cohorts, 240 pLCGs (p< 0.01) in the luminal cohort, and 28 pLCGs (p< 0.05) in the triple-negative breast cancer (TNBC) cohort. Twelve genes in all cohorts (training cohort: 5/10-year ROC values were 0.76 and 0.77; verification cohort: 5/10-year ROC values were 0.61 and 0.58), eight genes in the luminal cohort (training cohort: 5/10-year ROC values were 0.79 and 0.75; verification cohort: 5/10-year ROC values were 0.62 and 0.62), and four genes in the TNBC cohort (training cohort: 5/10-year ROC values were 0.73 and 0.79; verification cohort: 5/10-year ROC values were 0.55 and 0.54) were screened out to construct the prognostic prediction model. The 17-gene risk-score was constructed in all cohorts (1/3/5-year ROC values were 0.88, 0.83, and 0.81), and the 11-gene risk-score was constructed in the luminal cohort (1/3/5-year ROC values were 0.67, 0.85 and 0.84), and the six-gene risk-score was constructed in the TNBC cohort (1/3/5-year ROC value were 0.87, 0.88 and 0.81). Finally, the risk-score and clinical factors were applied to construct nomograms in all cohorts (1/3/5-year ROC values were 0.89, 0.79 and 0.75, C-index = 0.784), in the luminal cohort (1/3/5-year ROC values were 0.84, 0.83 and 0.85, C-index = 0.803), and in the TNBC cohort (1/3/5-year ROC values were 0.95, 0.84 and 0.77, C-index = 0.847). Discussion: This study explored the roles of LCGs in the prediction of breast cancer prognosis. |
format | Online Article Text |
id | pubmed-9554098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95540982022-10-13 Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis Yu-Qing, Huang Peng-Ping, Li Ke, Sun Ke-Xing, Yin Wei-Jun, Zhang Zhen-Yu, Wang Front Genet Genetics Objective: Liquid-liquid phase separation (LLPS) is a functional unit formed by specific molecules. It lacks a membrane and has been reported to play a crucial role in tumor drug resistance and growth by regulating gene expression and drug distribution. However, whether LLPS could be used to predict cancer prognosis was not clear. This study aimed to construct a prognostic model for breast cancer based on LLPS-correlated genes (LCGs). Methods: LCGs were identified using the PhaSepDB, gene expression profile and clinical characteristics of breast cancer were obtained from TCGA and cBioportal. The PanCancer Atlas (TCGA) cohort was used as the training cohort to construct the prognostic model, while the Nature 2012 and Nat Commun 2016 (TCGA) cohort and GEO data were used as test cohort to perform external verification. Data analysis was performed with R4.2.0 and SPSS20.0. Results: We identified 140 prognosis-related LCGs (pLCGs) (p< 0.01) in all cohorts, 240 pLCGs (p< 0.01) in the luminal cohort, and 28 pLCGs (p< 0.05) in the triple-negative breast cancer (TNBC) cohort. Twelve genes in all cohorts (training cohort: 5/10-year ROC values were 0.76 and 0.77; verification cohort: 5/10-year ROC values were 0.61 and 0.58), eight genes in the luminal cohort (training cohort: 5/10-year ROC values were 0.79 and 0.75; verification cohort: 5/10-year ROC values were 0.62 and 0.62), and four genes in the TNBC cohort (training cohort: 5/10-year ROC values were 0.73 and 0.79; verification cohort: 5/10-year ROC values were 0.55 and 0.54) were screened out to construct the prognostic prediction model. The 17-gene risk-score was constructed in all cohorts (1/3/5-year ROC values were 0.88, 0.83, and 0.81), and the 11-gene risk-score was constructed in the luminal cohort (1/3/5-year ROC values were 0.67, 0.85 and 0.84), and the six-gene risk-score was constructed in the TNBC cohort (1/3/5-year ROC value were 0.87, 0.88 and 0.81). Finally, the risk-score and clinical factors were applied to construct nomograms in all cohorts (1/3/5-year ROC values were 0.89, 0.79 and 0.75, C-index = 0.784), in the luminal cohort (1/3/5-year ROC values were 0.84, 0.83 and 0.85, C-index = 0.803), and in the TNBC cohort (1/3/5-year ROC values were 0.95, 0.84 and 0.77, C-index = 0.847). Discussion: This study explored the roles of LCGs in the prediction of breast cancer prognosis. Frontiers Media S.A. 2022-09-28 /pmc/articles/PMC9554098/ /pubmed/36246644 http://dx.doi.org/10.3389/fgene.2022.834471 Text en Copyright © 2022 Yu-Qing, Peng-Ping, Ke, Ke-Xing, Wei-Jun and Zhen-Yu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Yu-Qing, Huang Peng-Ping, Li Ke, Sun Ke-Xing, Yin Wei-Jun, Zhang Zhen-Yu, Wang Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title | Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title_full | Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title_fullStr | Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title_full_unstemmed | Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title_short | Comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
title_sort | comprehensive analysis of liquid-liquid phase separation-related genes in prediction of breast cancer prognosis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554098/ https://www.ncbi.nlm.nih.gov/pubmed/36246644 http://dx.doi.org/10.3389/fgene.2022.834471 |
work_keys_str_mv | AT yuqinghuang comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis AT pengpingli comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis AT kesun comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis AT kexingyin comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis AT weijunzhang comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis AT zhenyuwang comprehensiveanalysisofliquidliquidphaseseparationrelatedgenesinpredictionofbreastcancerprognosis |