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Tumor-Intrinsic IL-17 Signaling Correlates with Multimodal Resistance Phenotypes Following Oncolytic Adenovirus Challenge

Saad, E.; Hammad, M.

2026-03-31 cancer biology
10.64898/2026.03.27.714871 bioRxiv
Show abstract

Oncolytic adenovirus (ADV) therapy faces heterogeneous responses, implying tumor-intrinsic resistance. We identify interleukin-17 (IL-17) signaling as a novel potential barrier associated with multi-modal cellular reprogramming. Transcriptomic analysis of ADV-treated 4T1 murine mammary carcinoma cells revealed specific upregulation of Il17rb, Il17rd, and Il17f, indicating viral induction of this inflammatory axis. The IL-17 signature correlates strongly with a cancer stemness phenotype. Metabolically, it associates with increased lipid metabolism and suppressed glycolysis, suggesting a state resistant to viral replication. Furthermore, it broadly negatively correlates with programmed cell death pathways (apoptosis, necrosis) while positively associating with pro-survival autophagy. IL-17 component expression effectively stratifies samples into distinct metastatic risk categories, underscoring its prognostic potential. Our findings reveal a previously unrecognized, tumor-intrinsic role for IL-17 signaling in ADV resistance, associated with enhanced stemness, altered metabolism, and impaired cell death. This nominates the IL-17 pathway as both a predictive biomarker and a therapeutic target for combination strategies. HighlightsO_LIOncolytic adenovirus infection selectively upregulates IL-17 receptor subunits (IL17RB, IL17RD) and IL17F ligand in 4T1 tumor cells C_LIO_LIIL-17 receptor expression strongly correlates with cancer stemness gene signatures, particularly through IL17RB and IL17RD C_LIO_LIThe IL-17 axis associates with broad suppression of lytic cell death pathways (apoptosis, necrosis, necroptosis) while positively correlating with autophagy C_LIO_LIIL-17 pathway activity correlates with metabolic reprogramming favoring lipid turnover over glycolysis C_LIO_LIIL-17 expression levels stratify samples into distinct metastatic risk categories, suggesting biomarker potential C_LI

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