Bioinformatics analysis of the role of lysosome-related genes in breast cancer
This study aimed to investigate the roles of lysosome-related genes in BC prognosis and immunity. Transcriptome data from TCGA and MSigDB, along with lysosome-related gene sets, underwent NMF cluster analysis, resulting in two subtypes. Using lasso regression and univariate/multivariate Cox regressi...
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Zusammenfassung: | This study aimed to investigate the roles of lysosome-related genes in BC prognosis and immunity. Transcriptome data from TCGA and MSigDB, along with lysosome-related gene sets, underwent NMF cluster analysis, resulting in two subtypes. Using lasso regression and univariate/multivariate Cox regression analysis, an 11-gene signature was successfully identified and verified. High- and low-risk populations were dominated by HR+ sample types. There were differences in pathway enrichment, immune cell infiltration, and immune scores. Sensitive drugs targeting model genes were screened using GDSC and CCLE. This study constructed a reliable prognostic model with lysosome-related genes, providing valuable insights for BC clinical immunotherapy. Lysosome-related genes can be used to predict survival outcomes in BRCA patients.Significant differences were showed in the immune status of patient with different prognoses.Immunotherapy may show better therapeutic results in low-risk patients.The most promising targeted drugs in the low-risk group are mainly Lapatinib, Palbociclib and Ribociclib. Lysosome-related genes can be used to predict survival outcomes in BRCA patients. Significant differences were showed in the immune status of patient with different prognoses. Immunotherapy may show better therapeutic results in low-risk patients. The most promising targeted drugs in the low-risk group are mainly Lapatinib, Palbociclib and Ribociclib. |
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DOI: | 10.6084/m9.figshare.26378836 |