Cargando…

Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer

BACKGROUND: Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Jili, Jiang, Shaoqin, Gu, Di, Zhang, Wenhui, Shen, Xianqi, Qu, Min, Yang, Chenghua, Wang, Yan, Gao, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185853/
https://www.ncbi.nlm.nih.gov/pubmed/37205181
http://dx.doi.org/10.3389/fonc.2023.1162653
_version_ 1785042448218587136
author Zhang, Jili
Jiang, Shaoqin
Gu, Di
Zhang, Wenhui
Shen, Xianqi
Qu, Min
Yang, Chenghua
Wang, Yan
Gao, Xu
author_facet Zhang, Jili
Jiang, Shaoqin
Gu, Di
Zhang, Wenhui
Shen, Xianqi
Qu, Min
Yang, Chenghua
Wang, Yan
Gao, Xu
author_sort Zhang, Jili
collection PubMed
description BACKGROUND: Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and clinical decision-making in PCa. METHODS: Cuproptosis-related molecular subtypes were identified by consensus clustering analysis. A prognostic signature was constructed with LASSO cox regression analyses with 10-fold cross-validation. It was further validated in the internal validation cohort and eight external validation cohorts. The tumor microenvironment between the two risk groups was compared using the ssGSEA and ESTIMATE algorithms. Finally, qRT-PCR was used to explore the expression and regulation of these model genes at the cellular level. Furthermore, 4D Label-Free LC-MS/MS and RNAseq were used to investigate the changes in CRGs at protein and RNA levels after the knockdown of the key model gene B4GALNT4. RESULTS: Two cuproptosis-related molecular subtypes with significant differences in prognoses, clinical features, and the immune microenvironment were identified. Immunosuppressive microenvironments were associated with poor prognosis. A prognostic signature comprised of five genes (B4GALNT4, FAM83D, COL1A, CHRM3, and MYBPC1) was constructed. The performance and generalizability of the signature were validated in eight completely independent datasets from multiple centers. Patients in the high-risk group had a poorer prognosis, more immune cell infiltration, more active immune-related functions, higher expression of human leukocyte antigen and immune checkpoint molecules, and higher immune scores. In addition, anti-PDL-1 immunotherapy prediction, somatic mutation, chemotherapy response prediction, and potential drug prediction were also analyzed based on the risk signature. The validation of five model genes' expression and regulation in qPCR was consistent with the results of bioinformatics analysis. Transcriptomics and proteomics analyses revealed that the key model gene B4GALNT4 might regulate CRGs through protein modification after transcription. CONCLUSION: The cuproptosis-related molecular subtypes and the prognostic signature identified in this study could be used to predict the prognosis and contribute to the clinical decision-making of PCa. Furthermore, we identified a potential cuproptosis-related oncogene B4GALNT4 in PCa, which could be used as a target to treat PCa in combination with cuproptosis.
format Online
Article
Text
id pubmed-10185853
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-101858532023-05-17 Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer Zhang, Jili Jiang, Shaoqin Gu, Di Zhang, Wenhui Shen, Xianqi Qu, Min Yang, Chenghua Wang, Yan Gao, Xu Front Oncol Oncology BACKGROUND: Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and clinical decision-making in PCa. METHODS: Cuproptosis-related molecular subtypes were identified by consensus clustering analysis. A prognostic signature was constructed with LASSO cox regression analyses with 10-fold cross-validation. It was further validated in the internal validation cohort and eight external validation cohorts. The tumor microenvironment between the two risk groups was compared using the ssGSEA and ESTIMATE algorithms. Finally, qRT-PCR was used to explore the expression and regulation of these model genes at the cellular level. Furthermore, 4D Label-Free LC-MS/MS and RNAseq were used to investigate the changes in CRGs at protein and RNA levels after the knockdown of the key model gene B4GALNT4. RESULTS: Two cuproptosis-related molecular subtypes with significant differences in prognoses, clinical features, and the immune microenvironment were identified. Immunosuppressive microenvironments were associated with poor prognosis. A prognostic signature comprised of five genes (B4GALNT4, FAM83D, COL1A, CHRM3, and MYBPC1) was constructed. The performance and generalizability of the signature were validated in eight completely independent datasets from multiple centers. Patients in the high-risk group had a poorer prognosis, more immune cell infiltration, more active immune-related functions, higher expression of human leukocyte antigen and immune checkpoint molecules, and higher immune scores. In addition, anti-PDL-1 immunotherapy prediction, somatic mutation, chemotherapy response prediction, and potential drug prediction were also analyzed based on the risk signature. The validation of five model genes' expression and regulation in qPCR was consistent with the results of bioinformatics analysis. Transcriptomics and proteomics analyses revealed that the key model gene B4GALNT4 might regulate CRGs through protein modification after transcription. CONCLUSION: The cuproptosis-related molecular subtypes and the prognostic signature identified in this study could be used to predict the prognosis and contribute to the clinical decision-making of PCa. Furthermore, we identified a potential cuproptosis-related oncogene B4GALNT4 in PCa, which could be used as a target to treat PCa in combination with cuproptosis. Frontiers Media S.A. 2023-05-02 /pmc/articles/PMC10185853/ /pubmed/37205181 http://dx.doi.org/10.3389/fonc.2023.1162653 Text en Copyright © 2023 Zhang, Jiang, Gu, Zhang, Shen, Qu, Yang, Wang and Gao 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
Zhang, Jili
Jiang, Shaoqin
Gu, Di
Zhang, Wenhui
Shen, Xianqi
Qu, Min
Yang, Chenghua
Wang, Yan
Gao, Xu
Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title_full Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title_fullStr Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title_full_unstemmed Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title_short Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
title_sort identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185853/
https://www.ncbi.nlm.nih.gov/pubmed/37205181
http://dx.doi.org/10.3389/fonc.2023.1162653
work_keys_str_mv AT zhangjili identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT jiangshaoqin identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT gudi identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT zhangwenhui identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT shenxianqi identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT qumin identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT yangchenghua identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT wangyan identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer
AT gaoxu identificationofnovelmolecularsubtypesandasignaturetopredictprognosisandtherapeuticresponsebasedoncuproptosisrelatedgenesinprostatecancer