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bioRxiv · 10.64898/2026.06.08.730822

Predicting Immunotherapy Response Through Chemotherapy-Induced Tumor Microenvironment Remodeling

Angel, A.·Lin, Z.·Brunwesser, M.·Aran, D.
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Abstract

BackgroundChemotherapy before immunotherapy improves outcomes in multiple cancers, but the benefit is heterogeneous: only some tumors undergo the immune remodeling that makes subsequent immunotherapy effective, and no biomarker identifies these patients prospectively, leading to uniform use of chemo-immunotherapy and avoidable toxicity. MethodsA random forest model of tumor-microenvironment (TME) favorability, trained on 1,936 immunotherapy-treated patients, was applied to 334 paired pre-/post-chemotherapy biopsies across 19 studies to identify TME "converters," from which a 50-gene baseline signature was derived. The signature was tested in IMvigor210 (the only cohort containing both treatment arms) and in five independent chemo-immunotherapy validation cohorts, and for specificity against 22 immunotherapy-only cohorts. ResultsOf 209 paired-biopsy patients with unfavorable baseline TME, 61 (29%) converted to a favorable state after chemotherapy; converters were indistinguishable from non-converters at baseline by cell composition, motivating a gene-level signature. In IMvigor210, the signature discriminated responders among chemotherapy-primed patients with unfavorable baseline TME (AUC = 0.80, 95% CI: 0.67-0.94) but showed no signal in the trials immunotherapy-only arm (interaction OR = 4.42, p = 0.006). Across five independent chemo-immunotherapy cohorts, responders consistently scored higher than non-responders, yielding a significant pooled effect by meta-analysis (pooled g = 0.59, 95% CI: 0.11-1.08, p = 0.017) and individual significance in two (LUD2015-005, p = 0.009; GSE165252, p = 0.02). A meta-analysis of 22 immunotherapy-only cohorts constrained any effect there to a small magnitude (Hedges g = 0.08, 95% CI: -0.08 to 0.23), and five established immune signatures did not reproduce this treatment-context specificity. Converter tumors harbored coordinated baseline programs of proliferative stress, innate and adaptive immune readiness, and functional vasculature. ConclusionsA baseline transcriptomic signature predicts immunotherapy response specifically in chemotherapy-primed patients, a treatment-context specificity not shown by established immune biomarkers. These findings support prospective validation of the signature to guide chemotherapy- immunotherapy sequencing. SignificanceChemotherapy is now added to immunotherapy across a growing list of cancers, yet every eligible patient receives it even though only some tumors need it, and current biomarkers (PD-L1, tumor mutational burden, microsatellite instability) cannot identify which. We report the first biomarker to predict benefit from the chemotherapy component itself: a baseline gene-expression signature that flags likely responders in chemotherapy-primed settings while remaining silent under immunotherapy alone. This treatment-context specificity shifts the biomarker question from "who responds to immunotherapy" to "who needs the chemotherapy," pointing toward a way to spare patients unnecessary toxicity and rationally sequence chemo-immunotherapy.

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Angel, A., Lin, Z., Brunwesser, M., Aran, D.. 2026-06-11. Predicting Immunotherapy Response Through Chemotherapy-Induced Tumor Microenvironment Remodeling. https://doi.org/10.64898/2026.06.08.730822

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