Breast cancer (BC) is a highly heterogeneous malignancy with a complex pathogenesis involving multiple molecular pathways and cellular interactions. The tumor microenvironment (TME) plays a crucial role in this process, but the functions of immune and stromal components within the TME remain to be further elucidated. This study aims to identify core genes associated with differential expression and prognosis in BC, providing new theoretical foundations for BC diagnosis and prognosis assessment. By integrating datasets from GEO and the TCGA database, genes that are differentially expressed and related to prognosis in BC and normal breast tissues were screened. Using various machine learning methods, seven characteristic genes were further identified, and PAMR1 was selected as the main research target. Bioinformatics analysis revealed that PAMR1 is significantly downregulated in BC and is closely related to clinical stage, tumor size, lymph node metastasis, and distant metastasis. Moreover, low levels of PAMR1 expression are significantly associated with poor prognosis. Functional analysis indicated that PAMR1 is associated with multiple immune pathways and may influence BC progression through immune cells. Experimental validation showed that PAMR1 overexpression significantly inhibited breast cancer cell proliferation, migration, and invasion. Furthermore, PAMR1 exerts an important role in predicting drug responses, suggesting that PAMR1 may serve as a potential diagnostic and prognostic biomarker for BC and warrants further investigation.
Wang et al. (Sat,) studied this question.
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