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Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma

Background: Hepatocellular Carcinoma (HCC) is a highly heterogeneous malignant tumor, and its prognostic prediction is extremely challenging. Ferroptosis is a cell mechanism dependent on iron, which is very significant for HCC development. Long non-coding RNA (lncRNA) is also linked to HCC progressi...

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Autores principales: Yang, Xin, Mei, Minhui, Yang, Jingze, Guo, Jinlu, Du, Fan, Liu, Shi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9134948/
https://www.ncbi.nlm.nih.gov/pubmed/35550563
http://dx.doi.org/10.18632/aging.204073
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author Yang, Xin
Mei, Minhui
Yang, Jingze
Guo, Jinlu
Du, Fan
Liu, Shi
author_facet Yang, Xin
Mei, Minhui
Yang, Jingze
Guo, Jinlu
Du, Fan
Liu, Shi
author_sort Yang, Xin
collection PubMed
description Background: Hepatocellular Carcinoma (HCC) is a highly heterogeneous malignant tumor, and its prognostic prediction is extremely challenging. Ferroptosis is a cell mechanism dependent on iron, which is very significant for HCC development. Long non-coding RNA (lncRNA) is also linked to HCC progression. This work aimed to establish a prognosis risk model for HCC and to discover a possible biomarker and therapeutic target. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq transcriptome data and clinic information of HCC patients. Firstly, univariate Cox was utilized to identify 66 prognostic ferroptosis-related lncRNAs. Then, the identified lncRNAs were further included in the multivariate Cox analysis to construct the prognostic model. Eventually, we performed quantitative polymerase chain reaction (q-PCR) to validate the risk model. Results: We established a prognostic seventeen-ferroptosis-related lncRNA signature model. The signature could categorize patients into two risk subgroups, with the low-risk subgroup associated with a better prognosis. Additionally, the area under the curve (AUC) of the lncRNAs signature was 0.801, indicating their reliability in forecasting HCC prognosis. Risk score was an independent prognostic factor by regression analyses. Gene set enrichment analysis (GSEA) analyses demonstrated a remarkable enrichment of cancer-related and immune-related pathways in the high-risk group. Besides, the immune status was decreased in the high-risk group. Eventually, three prognostic lncRNAs were validated in human HCCLM3 cell lines. Conclusions: The risk model based on seventeen-ferroptosis-related lncRNA has significant prognostic value for HCC and may be therapeutic targets associated with ferroptosis in clinical ways.
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spelling pubmed-91349482022-06-01 Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma Yang, Xin Mei, Minhui Yang, Jingze Guo, Jinlu Du, Fan Liu, Shi Aging (Albany NY) Research Paper Background: Hepatocellular Carcinoma (HCC) is a highly heterogeneous malignant tumor, and its prognostic prediction is extremely challenging. Ferroptosis is a cell mechanism dependent on iron, which is very significant for HCC development. Long non-coding RNA (lncRNA) is also linked to HCC progression. This work aimed to establish a prognosis risk model for HCC and to discover a possible biomarker and therapeutic target. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq transcriptome data and clinic information of HCC patients. Firstly, univariate Cox was utilized to identify 66 prognostic ferroptosis-related lncRNAs. Then, the identified lncRNAs were further included in the multivariate Cox analysis to construct the prognostic model. Eventually, we performed quantitative polymerase chain reaction (q-PCR) to validate the risk model. Results: We established a prognostic seventeen-ferroptosis-related lncRNA signature model. The signature could categorize patients into two risk subgroups, with the low-risk subgroup associated with a better prognosis. Additionally, the area under the curve (AUC) of the lncRNAs signature was 0.801, indicating their reliability in forecasting HCC prognosis. Risk score was an independent prognostic factor by regression analyses. Gene set enrichment analysis (GSEA) analyses demonstrated a remarkable enrichment of cancer-related and immune-related pathways in the high-risk group. Besides, the immune status was decreased in the high-risk group. Eventually, three prognostic lncRNAs were validated in human HCCLM3 cell lines. Conclusions: The risk model based on seventeen-ferroptosis-related lncRNA has significant prognostic value for HCC and may be therapeutic targets associated with ferroptosis in clinical ways. Impact Journals 2022-05-12 /pmc/articles/PMC9134948/ /pubmed/35550563 http://dx.doi.org/10.18632/aging.204073 Text en Copyright: © 2022 Yang et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Yang, Xin
Mei, Minhui
Yang, Jingze
Guo, Jinlu
Du, Fan
Liu, Shi
Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title_full Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title_fullStr Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title_full_unstemmed Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title_short Ferroptosis-related long non-coding RNA signature predicts the prognosis of hepatocellular carcinoma
title_sort ferroptosis-related long non-coding rna signature predicts the prognosis of hepatocellular carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9134948/
https://www.ncbi.nlm.nih.gov/pubmed/35550563
http://dx.doi.org/10.18632/aging.204073
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