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A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed i...

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Autores principales: Zhou, Yang, Lei, Dengliang, Hu, Gangli, Luo, Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995863/
https://www.ncbi.nlm.nih.gov/pubmed/35419294
http://dx.doi.org/10.3389/fonc.2022.760190
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author Zhou, Yang
Lei, Dengliang
Hu, Gangli
Luo, Fang
author_facet Zhou, Yang
Lei, Dengliang
Hu, Gangli
Luo, Fang
author_sort Zhou, Yang
collection PubMed
description We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed in HCCs relative to normal peritumoral tissues were extracted through statistical analysis. The CCS was constructed by Cox regression analyses. Predictive capacity and clinical practicality of the signature were evaluated and validated. The expression of the function-unknown genes in the CCS was determined by RT-qPCR. Candidate gene TICRR was selected for subsequent validation through functional experiments. A cell cycle-related 13-mRNA signature was generated from the exploratory cohort [The Cancer Genome Atlas (TCGA), n = 371)]. HCC cases were classified as high- vs. low-risk groups per overall survival (OS) [hazard ratio (HR) = 2.699]. Significantly, the CCS exhibited great predictive value for prognosis in three independent cohorts, particularly in GSE76427 cohort [area under the curve (AUC) = 0.835/0.822/0.808/0.821/0.826 at 1/2/3/4/5 years]. The nomogram constructed by integrating clinicopathological features with the CCS indicated high accuracy and practicability. Significant enrichment of tumorigenesis-associated pathways was observed in the high-risk patients by Gene Set Enrichment Analysis (GSEA). RT-qPCR revealed that TICRR was overexpressed in HCC samples. Increased TICRR expression implied poor prognosis in HCC patients. Furthermore, depletion of TICRR in HCC cells decreased cell proliferation and the G1/S transition. In conclusion, the established 13-CCS had efficacy in prognostic prediction of HCC patients. Additionally, TICRR was demonstrated as a tumor-driver gene for this deadly disease.
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spelling pubmed-89958632022-04-12 A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma Zhou, Yang Lei, Dengliang Hu, Gangli Luo, Fang Front Oncol Oncology We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed in HCCs relative to normal peritumoral tissues were extracted through statistical analysis. The CCS was constructed by Cox regression analyses. Predictive capacity and clinical practicality of the signature were evaluated and validated. The expression of the function-unknown genes in the CCS was determined by RT-qPCR. Candidate gene TICRR was selected for subsequent validation through functional experiments. A cell cycle-related 13-mRNA signature was generated from the exploratory cohort [The Cancer Genome Atlas (TCGA), n = 371)]. HCC cases were classified as high- vs. low-risk groups per overall survival (OS) [hazard ratio (HR) = 2.699]. Significantly, the CCS exhibited great predictive value for prognosis in three independent cohorts, particularly in GSE76427 cohort [area under the curve (AUC) = 0.835/0.822/0.808/0.821/0.826 at 1/2/3/4/5 years]. The nomogram constructed by integrating clinicopathological features with the CCS indicated high accuracy and practicability. Significant enrichment of tumorigenesis-associated pathways was observed in the high-risk patients by Gene Set Enrichment Analysis (GSEA). RT-qPCR revealed that TICRR was overexpressed in HCC samples. Increased TICRR expression implied poor prognosis in HCC patients. Furthermore, depletion of TICRR in HCC cells decreased cell proliferation and the G1/S transition. In conclusion, the established 13-CCS had efficacy in prognostic prediction of HCC patients. Additionally, TICRR was demonstrated as a tumor-driver gene for this deadly disease. Frontiers Media S.A. 2022-03-28 /pmc/articles/PMC8995863/ /pubmed/35419294 http://dx.doi.org/10.3389/fonc.2022.760190 Text en Copyright © 2022 Zhou, Lei, Hu and Luo 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
Zhou, Yang
Lei, Dengliang
Hu, Gangli
Luo, Fang
A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title_full A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title_fullStr A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title_full_unstemmed A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title_short A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma
title_sort cell cycle-related 13-mrna signature to predict prognosis in hepatocellular carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995863/
https://www.ncbi.nlm.nih.gov/pubmed/35419294
http://dx.doi.org/10.3389/fonc.2022.760190
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