Background Anti-PD-1 therapy has significantly improved clinical outcomes in patients with advanced cutaneous squamous cell carcinoma (cSCC); however, approximately half of patients fail to respond. This study aimed to investigate molecular mechanisms underlying therapeutic resistance and to identify predictive biomarkers. Methods Whole transcriptome profiling was performed using HTG EdgeSeq technology on pre-treatment cSCC samples. Clinical data and treatment outcomes were correlated with gene expression profiles, and differentially expressed genes (DEGs) were analyzed in relation to response. Moreover, promising targets were further analyzed at the protein level via immunofluorescence and immunohistochemistry. Results Tumors from patients achieving disease control showed a distinct immune-active transcriptional profile characterized by interferon-associated signaling, enhanced antigen presentation pathways, and cytotoxic immune activity. Consistently, IFN-γ and cytolytic activity signatures were higher in patients with favorable clinical outcomes. CIBERSORTx-based deconvolution demonstrated marked interpatient heterogeneity, with T cells, macrophages, and NK cells representing major components of the immune infiltrate, but no major differences in overall immune cell composition between patients with early and late/no progression. Histopathological assessment revealed a tendency toward higher immune cell infiltration in patients achieving disease control. Notably, elevated gene expression of SLC7A5 and SOX2 was associated with poor response and early progression. Also, at protein level, higher SLC7A5 expression was associated with early progression, whereas SOX2 showed a more heterogeneous pattern, with particularly high expression in a subset of progressive tumors. Conclusion Our data provide hypothesis-generating evidence that a combination of immune-related and tumor-intrinsic novel molecular markers is associated with response to anti-PD-1 therapy in advanced cSCC, thereby identifying promising candidate biomarkers, which require validation in larger independent cohorts.
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DeTemple et al. (2026) studied this question.
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