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• W4377693896 abstract "Abstract Objective: The aim of this work was to identify the consensus immune subtypes and predict the response to immune checkpoint inhibitor (ICIs) therapy for MDM4 gain/amplification luminal A type breast cancer (BC). Materials and Methods: Luminal A type BC expression data, copy number and corresponding clinical information were downloaded and pre-processed for subsequently analysis from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Furthermore, gene set enrichment analysis (GSEA) was performed to identify transcripts functions between MDM4 gain/amplification and control samples. Subsequently, weighted gene co-expression network analysis (WGCNA) was applied to screen out gene modules related biomarkers for ICIs therapy response in luminal A type BC. We perform an unsupervised consensus clustering in MDM4 gain/amplification luminal A type BC from TCGA BC dataset based immune-related gene signatures (IRGs) and then used luminal A type BC from METABRIC BC as validation datasets. We performed the Tumor Immune Dysfunction and Exclusion (TIDE) analysis to predict ICIs response and explore significant relationship with immune subtype. Results: The results from GSEA indicated that luminal A type BC with MDM4 gain/amplification were significantly enriched in immunological signature gene sets. Significantly, we also identified three gene modules significantly association with immune checkpoint, DNA damage, and immune cell infiltering in luminal A type BC. Luminal A type BC could be categorized into two distinct immune subtypes based on the expression of IRGs. Luminal A type BC in one subtype showed high response to ICIs therapy, characterized by higher immune checkpoint genes score and CD8 + T-cell score compared to tumors in a second subtype. Conclusion: Our findings demonstrated that immune subtype for MDM4 gain/amplification luminal A type BC was beyond the current luminal A/B classification and a subset of luminal A type BC patients may benefit from ICIs therapy." @default.
• W4377693896 created "2023-05-24" @default.
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• W4377693896 date "2023-05-23" @default.
• W4377693896 modified "2023-10-17" @default.
• W4377693896 title "Identification of immune subtypes and response prediction to immune-checkpoint inhibitors for MDM4 gain/amplification luminal A type breast cancer" @default.
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• W4377693896 doi "https://doi.org/10.21203/rs.3.rs-2954307/v1" @default.
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