A pyrimidine metabolism-related gene signature for prognosis prediction and immune microenvironment description of breast cancer

嘧啶代谢相关基因特征用于乳腺癌预后预测和免疫微环境描述

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Abstract

BACKGROUND: Metabolic reprogramming is a hallmark in cancer. Pyrimidine metabolism (PM), a part of nucleotide metabolism, has been shown to be associated with the progression of various cancers, and the prognostic predictive ability of pyrimidine metabolism-related genes (PMG) in breast cancer has not been elucidated. This paper was designed to identify pyrimidine metabolism-related prognostic marker of breast cancer and potential targeted therapeutic options. METHODS: The cohort in the TCGA-BRCA dataset was used for patient information, and 108 pyrimidine metabolism-related genes were identified from the MSigDB KEGG pathways. We identified PM clusters in breast cancer and established a PM risk score model based on 10 pyrimidine metabolism-related genes. The status of immune infiltration was assessed in different groups. Further we identified the relevant hub gene and analyzed its significance for breast cancer metastasis and explored patterns of combination therapy. RESULTS: We identified three types of PM clusters in breast cancer and clarified that PM cluster C with inferior prognosis possessed activation of tumor proliferation-associated pathways. The high-risk group in PM risk score model was found to be characterized by an immunosuppressive microenvironment. The hub gene POLR2C (RNA polymerase II subunit C) was further identified and verified as a potential prognostic marker. Furthermore, targeting POLR2C in combination with anti-PD-1 and anti-angiogenic therapies demonstrated a promising tumor suppression effect, suggesting a potential therapeutic direction. CONCLUSIONS: These findings provide additional insights into the link between breast cancer and PMG, offering potential strategies for breast cancer management and treatment.

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