Integrated bioinformatics analysis of EXOSC family genes in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is a major subtype of non-small cell lung cancer with limited biomarker-guided therapeutic options. The exosome complex (EXOSC) family regulates RNA processing and degradation, but its family-wide clinical and biological relevance in LUSC remains unclear. This study aimed to systematically characterize the expression pattern, prognostic value, immune relevance, pathway associations and therapeutic implications of EXOSC family genes in LUSC. Transcriptomic, proteomic and clinicopathological data were obtained from TCGA, CPTAC, UALCAN, GEPIA2, Human Protein Atlas, cBioPortal, GeneMANIA, TIMER2.0, MSigDB, CTRP and CTD. Expression differences, survival associations, diagnostic performance, genomic alterations, intergene correlations, protein-protein interaction networks, RNA modification-related correlations, immune infiltration, gene set enrichment, co-expression networks, drug sensitivity and prognostic modelling were analysed using integrated bioinformatics approaches. All ten EXOSC family members were significantly upregulated at the mRNA and protein levels in LUSC tissues compared with normal lung tissues. Immunohistochemical analyses further supported increased expression of most EXOSC proteins in tumor samples. EXOSC5 was significantly associated with overall survival, while EXOSC3, EXOSC4, and EXOSC5 demonstrated strong diagnostic performance. Genomic alterations in EXOSC genes were detected in 16.63% of LUSC cases, with EXOSC4 showing the highest alteration frequency. Most EXOSC genes exhibited positive correlations with each other and with regulators involved in m1A, m5C, and m6A RNA modification. Immune infiltration analyses revealed broad inverse associations between EXOSC expression and multiple immune-cell populations, suggesting potential involvement of EXOSC genes in tumor immune microenvironment remodeling. Enrichment and co-expression analyses linked EXOSC dysregulation to extracellular matrix organization, RNA surveillance, DNA replication, spliceosome activity, cell-cycle regulation, and nucleocytoplasmic transport. Drug sensitivity analyses suggested potential pharmacological associations. An EXOSC-based ten-gene prognostic model stratified patients into distinct overall survival groups, although its discriminative performance was modest, indicating that it may serve as a supplementary prognostic tool rather than a standalone clinical predictor. EXOSC family genes are broadly dysregulated in LUSC and are associated with RNA surveillance, immune microenvironment features, tumor-related pathways, drug sensitivity patterns, and patient prognosis. The EXOSC-based prognostic model may provide additional prognostic information; however, further independent validation and clinical investigation are required before its potential clinical application. These findings suggest that EXOSC genes represent candidate biomarkers and provide a foundation for future mechanistic and translational studies in LUSC.