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Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation

BACKGROUND: As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear. METHODS: Multi-dimensional d...

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Autores principales: Liu, Peng, Deng, Xinpei, Zhou, Huamao, Xie, Jindong, Kong, Yanan, Zou, Yutian, Yang, Anli, Li, Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644223/
https://www.ncbi.nlm.nih.gov/pubmed/38022619
http://dx.doi.org/10.3389/fimmu.2023.1297180
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author Liu, Peng
Deng, Xinpei
Zhou, Huamao
Xie, Jindong
Kong, Yanan
Zou, Yutian
Yang, Anli
Li, Xing
author_facet Liu, Peng
Deng, Xinpei
Zhou, Huamao
Xie, Jindong
Kong, Yanan
Zou, Yutian
Yang, Anli
Li, Xing
author_sort Liu, Peng
collection PubMed
description BACKGROUND: As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear. METHODS: Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the DDR-related features of BC. We collected 276 DDR-related genes based on the Molecular Signature Database (MSigDB) database and previous studies. We acquired public datasets included the SCAN-B dataset (GEO: GSE96058), METABRIC database, and TCGA-BRCA database. Corresponding repositories such as transcriptomics, genomics, and clinical information were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE161529, and GSE158724. Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462, GSE20181, and GSE130788 were extracted for independent analyses. RESULTS: The DDR classification was constructed in the SCAN-B dataset (GEO: GSE96058) and METABRIC database, Among BC patients, there were two clusters with distinct clinical and molecular characteristics: the DDR-suppressed cluster and the DDR-active cluster. A superior survival rate is found for tumors in the DDR-suppressed cluster, while those with the DDR-activated cluster tend to have inferior prognoses and clinically aggressive behavior. The DDR classification was validated in the TCGA-BRCA cohort and shown similar results. We also found that two clusters have different pathway activities at the genomic level. Based on the intersection of the different expressed genes among these cohorts, we found that PRAME might play a vital role in DDR. The DDR classification was then enabled by establishing a DDR score, which was verified through multilayer cohort analysis. Furthermore, our results revealed that malignant cells contributed more to the DDR score at the single-cell level than nonmalignant cells. Particularly, immune cells with immunosuppressive properties (such as FOXP3+ CD4+ T cells) displayed higher DDR scores among those with distinguishable characteristics. CONCLUSION: Collectively, this study performs general analyses of DDR heterogeneity in BC and provides insight into the understanding of individualized molecular and clinicopathological mechanisms underlying unique DDR profiles.
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spelling pubmed-106442232023-01-01 Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation Liu, Peng Deng, Xinpei Zhou, Huamao Xie, Jindong Kong, Yanan Zou, Yutian Yang, Anli Li, Xing Front Immunol Immunology BACKGROUND: As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear. METHODS: Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the DDR-related features of BC. We collected 276 DDR-related genes based on the Molecular Signature Database (MSigDB) database and previous studies. We acquired public datasets included the SCAN-B dataset (GEO: GSE96058), METABRIC database, and TCGA-BRCA database. Corresponding repositories such as transcriptomics, genomics, and clinical information were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE161529, and GSE158724. Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462, GSE20181, and GSE130788 were extracted for independent analyses. RESULTS: The DDR classification was constructed in the SCAN-B dataset (GEO: GSE96058) and METABRIC database, Among BC patients, there were two clusters with distinct clinical and molecular characteristics: the DDR-suppressed cluster and the DDR-active cluster. A superior survival rate is found for tumors in the DDR-suppressed cluster, while those with the DDR-activated cluster tend to have inferior prognoses and clinically aggressive behavior. The DDR classification was validated in the TCGA-BRCA cohort and shown similar results. We also found that two clusters have different pathway activities at the genomic level. Based on the intersection of the different expressed genes among these cohorts, we found that PRAME might play a vital role in DDR. The DDR classification was then enabled by establishing a DDR score, which was verified through multilayer cohort analysis. Furthermore, our results revealed that malignant cells contributed more to the DDR score at the single-cell level than nonmalignant cells. Particularly, immune cells with immunosuppressive properties (such as FOXP3+ CD4+ T cells) displayed higher DDR scores among those with distinguishable characteristics. CONCLUSION: Collectively, this study performs general analyses of DDR heterogeneity in BC and provides insight into the understanding of individualized molecular and clinicopathological mechanisms underlying unique DDR profiles. Frontiers Media S.A. 2023-10-31 /pmc/articles/PMC10644223/ /pubmed/38022619 http://dx.doi.org/10.3389/fimmu.2023.1297180 Text en Copyright © 2023 Liu, Deng, Zhou, Xie, Kong, Zou, Yang and Li 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 Immunology
Liu, Peng
Deng, Xinpei
Zhou, Huamao
Xie, Jindong
Kong, Yanan
Zou, Yutian
Yang, Anli
Li, Xing
Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title_full Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title_fullStr Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title_full_unstemmed Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title_short Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation
title_sort multi-omics analyses unravel dna damage repair-related clusters in breast cancer with experimental validation
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10644223/
https://www.ncbi.nlm.nih.gov/pubmed/38022619
http://dx.doi.org/10.3389/fimmu.2023.1297180
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