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pmid:38022619

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

Peng Liu · Xinpei Deng · Huamao Zhou · Jindong Xie · Yanan Kong · Yutian Zou · Anli Yang · Xing Li

Frontiers in immunology · 2023 doi:10.3389/fimmu.2023.1297180

Paper

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Experiment

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Data

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Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation.
doi
10.3389/fimmu.2023.1297180
pmid
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Peng Liu
[1]
Xinpei Deng
[2]
Huamao Zhou
[3]
Jindong Xie
[4]
Yanan Kong
[5]
Yutian Zou
[6]
Anli Yang
[7]
Xing Li
journal
Frontiers in immunology
year
2023
abstract
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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Complete file
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The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear.\nMethods: 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. 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Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462,", "5), GSE161529 (26), and GSE158724 (27). Bulk RNA-seq data from GEO: GSE176078 (24), GSE18728 (28)", "unclear. Methods: Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome pro", "f transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the"], "order_basis": "paper_text_order:374", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["nformation were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE1615", "nformation were also downloaded. 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