Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms in TNBC. The gene expression data of breast cancer patients were obtained from the TCGA and METABRIC databases. Gene set variation analysis (GSVA) revealed specific upregulation or abnormal expression of immunodeficiency pathways in TNBC patients. Multi-omics data showed significant differential expression of Primary Immunodeficiency Genes (PIDGs) in TNBC patients, who are prone to genomic-level variations. Consensus clustering was used in two datasets to classify patients into two distinct molecular subtypes based on PIDGs expression patterns, with each displaying different biological features and immune landscapes. To further explore the prognostic characteristics of PIDGs-regulated molecules, we constructed a four-gene prognostic PIDG score model and a nomogram using least absolute shrinkage and selection operator (LASSO) regression analysis in combination with clinicopathological parameters. The PIDG score was closely associated with the immune therapy and drug sensitivity of TNBC patients, providing potential guidance for clinical treatment. Particularly noteworthy is the close association of this scoring with RNA modifications; patients with different scores also exhibited different mutation landscapes. This study offers new insights for the clinical treatment of TNBC and for identifying novel prognostic markers and therapeutic targets in TNBC.

Backgrounds: C4orf19, a protein encoded by an open reading frame on human chromosome 4, exhibits aberrant expression in various tumors and is linked to patient prognosis, though its role in head and neck squamous cell carcinoma (HNSCC) remains unclear. Methods: TCGA and GEO datasets were analyzed to evaluate the prognostic value of C4orf19 in HNSCC. Functional assays (EdU, immunofluorescence, and CCK-8) were used to assess the effects of C4orf19 knockdown on tumor cell proliferation. Drug sensitivity analyses using the GDSC database and 5-fluorouracil (5-FU) chemosensitization experiments were performed. Bioinformatics approaches (CIBERSORT, ssGSEA, xCell, and maftools) were applied to explore associations between C4orf19 expression, the tumor microenvironment (TME), immune checkpoints, and tumor mutational burden (TMB). Results: C4orf19 was downregulated in HNSCC patients and was associated with a poor prognosis. While C4orf19 knockdown did not affect proliferation of HNSCC cells, it enhanced 5-FU sensitivity. Mechanistically, C4orf19 may influence immunotherapy efficacy by modulating immune checkpoint gene expression, remodeling TME, and regulating TMB. These findings suggest that C4orf19 expression may serve as a predictive biomarker for immunotherapy response in HNSCC patients. Conclusions: C4orf19 expression shows potential as a predictive biomarker for immunotherapy response in HNSCC patients. The study highlights its role in enhancing chemosensitization and predicting immunotherapy efficacy, positioning C4orf19 as a promising prognostic biomarker and therapeutic predictor in HNSCC.