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Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer

BACKGROUND: To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be id...

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Autores principales: Liu, Yang, Sun, Hefen, Li, Xuan, Liu, Qiqi, Zhao, Yuanyuan, Li, Liangdong, Xu, Baojin, Hou, Yifeng, Jin, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311660/
https://www.ncbi.nlm.nih.gov/pubmed/34322380
http://dx.doi.org/10.3389/fonc.2021.663556
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author Liu, Yang
Sun, Hefen
Li, Xuan
Liu, Qiqi
Zhao, Yuanyuan
Li, Liangdong
Xu, Baojin
Hou, Yifeng
Jin, Wei
author_facet Liu, Yang
Sun, Hefen
Li, Xuan
Liu, Qiqi
Zhao, Yuanyuan
Li, Liangdong
Xu, Baojin
Hou, Yifeng
Jin, Wei
author_sort Liu, Yang
collection PubMed
description BACKGROUND: To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be identified for supporting the development of precision medicine in breast cancer. METHODS: Based on the TCGA-BRCA and METABRIC databases, the differently expressed RNA binding proteins (RBPs) between tumor and normal tissues were investigated. In this study, we focused on the communal differently expressed RBPs in four subtypes of breast cancer. Lasso-penalized Cox analysis, Stepwise-multivariate Cox analysis and Kaplan–Meier survival curve were performed to identify the hub RBP-coding genes in predicting prognosis of breast cancer, and a prognostic model was established. The efficiency of this model was further validated in other independent GSE20685, GSE4922 and FUSCC-TNBC cohorts by calculating the risk score and performing survival analysis, ROC and nomogram. Moreover, pathologic functions of the candidate RBPs in breast cancer were explored using some routine experiments in vitro, and the potential compounds targeting these RBPs were predicted by reviewing the Comparative Toxicogenomics Database. RESULTS: Here, we identified 62 RBPs which were differently expressed between the tumor and normal tissues. Thereinto, three RBPs (MRPL12, MRPL13 and POP1) acted as independent risk factors, and their expression pattern also correlated with poor prognosis of patients. A prognostic model, built with these 3-RBPs, possessed statistical significance to predict the survival probability of patients with breast cancer. Furthermore, experimental validations showed that down-regulating the expression of endogenous MRPL12, MRPL13 or POP1 could dramatically suppress the cellular viability and migration of breast cancer cells in vitro. Besides, some compounds (such as the Acetaminophen, Urethane and Tunicamycin) were predicted for curing breast cancer via targeting MRPL12, MRPL13 and POP1 simultaneously. CONCLUSION: This study identified and established a 3-RBPs-based signature and nomogram for predicting the survival probability of patients with breast cancer. MRPL12, MRPL13 and POP1 might act as oncogenes in maintaining cellular viability and accelerating metastasis of breast cancer cells, implying the possibility of which to be designed as biomarkers and/or therapeutic targets for breast cancer.
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spelling pubmed-83116602021-07-27 Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer Liu, Yang Sun, Hefen Li, Xuan Liu, Qiqi Zhao, Yuanyuan Li, Liangdong Xu, Baojin Hou, Yifeng Jin, Wei Front Oncol Oncology BACKGROUND: To date, breast cancer remains the primary cause of tumor-related death among women, even though some leap-type developments of oncology have been done to slash the mortality. Considering the tumor heterogeneity and individual variation, the more reliable biomarkers are required to be identified for supporting the development of precision medicine in breast cancer. METHODS: Based on the TCGA-BRCA and METABRIC databases, the differently expressed RNA binding proteins (RBPs) between tumor and normal tissues were investigated. In this study, we focused on the communal differently expressed RBPs in four subtypes of breast cancer. Lasso-penalized Cox analysis, Stepwise-multivariate Cox analysis and Kaplan–Meier survival curve were performed to identify the hub RBP-coding genes in predicting prognosis of breast cancer, and a prognostic model was established. The efficiency of this model was further validated in other independent GSE20685, GSE4922 and FUSCC-TNBC cohorts by calculating the risk score and performing survival analysis, ROC and nomogram. Moreover, pathologic functions of the candidate RBPs in breast cancer were explored using some routine experiments in vitro, and the potential compounds targeting these RBPs were predicted by reviewing the Comparative Toxicogenomics Database. RESULTS: Here, we identified 62 RBPs which were differently expressed between the tumor and normal tissues. Thereinto, three RBPs (MRPL12, MRPL13 and POP1) acted as independent risk factors, and their expression pattern also correlated with poor prognosis of patients. A prognostic model, built with these 3-RBPs, possessed statistical significance to predict the survival probability of patients with breast cancer. Furthermore, experimental validations showed that down-regulating the expression of endogenous MRPL12, MRPL13 or POP1 could dramatically suppress the cellular viability and migration of breast cancer cells in vitro. Besides, some compounds (such as the Acetaminophen, Urethane and Tunicamycin) were predicted for curing breast cancer via targeting MRPL12, MRPL13 and POP1 simultaneously. CONCLUSION: This study identified and established a 3-RBPs-based signature and nomogram for predicting the survival probability of patients with breast cancer. MRPL12, MRPL13 and POP1 might act as oncogenes in maintaining cellular viability and accelerating metastasis of breast cancer cells, implying the possibility of which to be designed as biomarkers and/or therapeutic targets for breast cancer. Frontiers Media S.A. 2021-07-12 /pmc/articles/PMC8311660/ /pubmed/34322380 http://dx.doi.org/10.3389/fonc.2021.663556 Text en Copyright © 2021 Liu, Sun, Li, Liu, Zhao, Li, Xu, Hou and Jin 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 Oncology
Liu, Yang
Sun, Hefen
Li, Xuan
Liu, Qiqi
Zhao, Yuanyuan
Li, Liangdong
Xu, Baojin
Hou, Yifeng
Jin, Wei
Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title_full Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title_fullStr Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title_full_unstemmed Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title_short Identification of a Three-RNA Binding Proteins (RBPs) Signature Predicting Prognosis for Breast Cancer
title_sort identification of a three-rna binding proteins (rbps) signature predicting prognosis for breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311660/
https://www.ncbi.nlm.nih.gov/pubmed/34322380
http://dx.doi.org/10.3389/fonc.2021.663556
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