PILRA serves as a diagnostic and prognostic biomarker and modulates the tumor immune microenvironment and immunotherapy response in breast cancer.
Paired immunoglobulin-like type 2 receptor alpha (PILRA) is a membrane-associated receptor involved in immune regulation and signal transduction. However, its expression and functional role in breast cancer remain largely unknown. This study investigated the expression, mutation, and DNA methylation patterns of PILRA in breast cancer, along with its impact on immune infiltration and associated pathways. We also evaluated its potential as a therapeutic target for predicting prognosis and guiding immunotherapy in breast cancer.
PILRA expression in breast cancer was analyzed using TCGA and GTEx datasets. Protein expression in breast cancer and adjacent normal tissues was evaluated by immunohistochemistry, and expression levels were validated by RT-qPCR in 50 paired tumor and adjacent tissue samples. cBioPortal was used to assess mutation profiles and prognostic relevance. Associations with drug resistance were examined by analyzing relationships to resistance- and sensitivity-related genes. DNA methylation and its prognostic impact were analyzed using MethSurv. The prognostic and diagnostic value of PILRA was evaluated through survival and ROC curve analyses. Single-cell and tissue expression data were obtained from HPA and GTEx, and gene effect score from DepMap. Immune associations were assessed using TISIDB. Gene correlation and protein-protein interaction networks were analyzed via TCGA and STRING, followed by KEGG and GO enrichment.
PILRA expression was upregulated in breast cancer tissues and associated with poor survival and drug resistance. We identified R236M as the dominant mutation site and found that its mutation is linked to improved prognosis. PILRA methylation downregulated its expression and correlated with better prognosis. Survival analysis and ROC curves supported the potential of PILRA as a prognostic biomarker. PILRA was involved in immune infiltration and modulated the abundance of various immune cells and the tumor microenvironment, suggesting a role in immune regulation and tissue maintenance. Correlation and enrichment analyses revealed that PILRA-associated genes were mainly involved in cancer-related processes and pathways, with key hub genes in the PPI network.
We identified PILRA as a diagnostic and prognostic biomarker in breast cancer and analyzed its association with immunotherapy response. The findings provide new insight and potential strategies for breast cancer diagnosis and treatment.
PILRA expression in breast cancer was analyzed using TCGA and GTEx datasets. Protein expression in breast cancer and adjacent normal tissues was evaluated by immunohistochemistry, and expression levels were validated by RT-qPCR in 50 paired tumor and adjacent tissue samples. cBioPortal was used to assess mutation profiles and prognostic relevance. Associations with drug resistance were examined by analyzing relationships to resistance- and sensitivity-related genes. DNA methylation and its prognostic impact were analyzed using MethSurv. The prognostic and diagnostic value of PILRA was evaluated through survival and ROC curve analyses. Single-cell and tissue expression data were obtained from HPA and GTEx, and gene effect score from DepMap. Immune associations were assessed using TISIDB. Gene correlation and protein-protein interaction networks were analyzed via TCGA and STRING, followed by KEGG and GO enrichment.
PILRA expression was upregulated in breast cancer tissues and associated with poor survival and drug resistance. We identified R236M as the dominant mutation site and found that its mutation is linked to improved prognosis. PILRA methylation downregulated its expression and correlated with better prognosis. Survival analysis and ROC curves supported the potential of PILRA as a prognostic biomarker. PILRA was involved in immune infiltration and modulated the abundance of various immune cells and the tumor microenvironment, suggesting a role in immune regulation and tissue maintenance. Correlation and enrichment analyses revealed that PILRA-associated genes were mainly involved in cancer-related processes and pathways, with key hub genes in the PPI network.
We identified PILRA as a diagnostic and prognostic biomarker in breast cancer and analyzed its association with immunotherapy response. The findings provide new insight and potential strategies for breast cancer diagnosis and treatment.