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Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis

Background: In order to reveal the functions of ferroptosis in prostate cancer (PCa), a ferroptosis potential index (FPI) was built. This study researched the influence of ferroptosis on gene mutations, various cellular signaling pathways, biochemical recurrence (BCR), and drug resistance in both FP...

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Autores principales: Wo, Qijun, Liu, Zhenghong, Hu, Linyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289098/
https://www.ncbi.nlm.nih.gov/pubmed/35860472
http://dx.doi.org/10.3389/fgene.2022.852565
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author Wo, Qijun
Liu, Zhenghong
Hu, Linyi
author_facet Wo, Qijun
Liu, Zhenghong
Hu, Linyi
author_sort Wo, Qijun
collection PubMed
description Background: In order to reveal the functions of ferroptosis in prostate cancer (PCa), a ferroptosis potential index (FPI) was built. This study researched the influence of ferroptosis on gene mutations, various cellular signaling pathways, biochemical recurrence (BCR), and drug resistance in both FPI-high and FPI-low groups. Methods: RNA-seq, somatic mutation data, and clinical data were obtained from The Cancer Genome Atlas (TCGA). FPI values were calculated. All samples were divided into FPI-high and FPI-low groups. The BCR-free survival rate, tumor mutation burden (TMB) value, cellular signaling pathway, differentially expressed genes (DEGs), and drug resistance in the two FPI groups were identified. Human PCa cells, LNCaP, were treated with ferroptosis inducer erastin or inhibitor ferrostatin-1. The expression of hub genes was detected by qRT-PCR and Western blot. Results: A high FPI level was significantly related to poor BCR-free survival. Also, higher TMB value was found in the FPI-high group, and FPI was shown to be associated with gene mutations. Then, genes in both groups were revealed to be enriched in different pathways. A total of 310 DEGs were identified to be involved in muscle system processes and neuroactive ligand–receptor interactions. A total of 101 genes were found to be related to BCR-free survival, and a protein–protein interaction (PPI) network was constructed. Two sub-modules were identified by MCODE, and eight hub genes were screened out, among which SYT4 had higher expression levels and poorer BCR-free survival in the FPI-high group, while the remaining hub genes had lower expression levels and poorer BCR-free survival. Drug sensitivity was revealed to be different in the two groups by study on the IC(50) data of different molecules and ferroptosis regulator gene (FRG) expressions. Finally, erastin increased the expression of SYT4 in LNCaP and decreased the expression of the other four genes (ACTC1, ACTA1, ACTN2, and MYH6), while ferrostatin-1 led to the opposite results. The molecular experimental results were consistent with those of bioinformatics analysis, except TNNI1, TNNC2, and NRAP. Conclusion: The current research depicted the ferroptosis level and FRGs in PCa. Ferroptosis was related to TMB value, BCR-free survival, and drug resistance. This study will be beneficial to further research studies on ferroptosis-related molecular mechanisms.
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spelling pubmed-92890982022-07-19 Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis Wo, Qijun Liu, Zhenghong Hu, Linyi Front Genet Genetics Background: In order to reveal the functions of ferroptosis in prostate cancer (PCa), a ferroptosis potential index (FPI) was built. This study researched the influence of ferroptosis on gene mutations, various cellular signaling pathways, biochemical recurrence (BCR), and drug resistance in both FPI-high and FPI-low groups. Methods: RNA-seq, somatic mutation data, and clinical data were obtained from The Cancer Genome Atlas (TCGA). FPI values were calculated. All samples were divided into FPI-high and FPI-low groups. The BCR-free survival rate, tumor mutation burden (TMB) value, cellular signaling pathway, differentially expressed genes (DEGs), and drug resistance in the two FPI groups were identified. Human PCa cells, LNCaP, were treated with ferroptosis inducer erastin or inhibitor ferrostatin-1. The expression of hub genes was detected by qRT-PCR and Western blot. Results: A high FPI level was significantly related to poor BCR-free survival. Also, higher TMB value was found in the FPI-high group, and FPI was shown to be associated with gene mutations. Then, genes in both groups were revealed to be enriched in different pathways. A total of 310 DEGs were identified to be involved in muscle system processes and neuroactive ligand–receptor interactions. A total of 101 genes were found to be related to BCR-free survival, and a protein–protein interaction (PPI) network was constructed. Two sub-modules were identified by MCODE, and eight hub genes were screened out, among which SYT4 had higher expression levels and poorer BCR-free survival in the FPI-high group, while the remaining hub genes had lower expression levels and poorer BCR-free survival. Drug sensitivity was revealed to be different in the two groups by study on the IC(50) data of different molecules and ferroptosis regulator gene (FRG) expressions. Finally, erastin increased the expression of SYT4 in LNCaP and decreased the expression of the other four genes (ACTC1, ACTA1, ACTN2, and MYH6), while ferrostatin-1 led to the opposite results. The molecular experimental results were consistent with those of bioinformatics analysis, except TNNI1, TNNC2, and NRAP. Conclusion: The current research depicted the ferroptosis level and FRGs in PCa. Ferroptosis was related to TMB value, BCR-free survival, and drug resistance. This study will be beneficial to further research studies on ferroptosis-related molecular mechanisms. Frontiers Media S.A. 2022-07-04 /pmc/articles/PMC9289098/ /pubmed/35860472 http://dx.doi.org/10.3389/fgene.2022.852565 Text en Copyright © 2022 Wo, Liu and Hu. 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
Wo, Qijun
Liu, Zhenghong
Hu, Linyi
Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title_full Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title_fullStr Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title_full_unstemmed Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title_short Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis
title_sort identification of ferroptosis-associated genes in prostate cancer by bioinformatics analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9289098/
https://www.ncbi.nlm.nih.gov/pubmed/35860472
http://dx.doi.org/10.3389/fgene.2022.852565
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