RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology

Wiesmann, F.; Litchfield, C.; Mayoux, M.; Tumor Profiler Consortium,; Wicki, A.; Becher, B.; Koelzer, V. H.; Moch, H.; Buljan, M.; Tugues, S.; Sobottka, B.

doi:10.1101/2025.09.17.676675

bioRxiv · 10.1101/2025.09.17.676675

RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology

Wiesmann, F.·Litchfield, C.·Mayoux, M.·Tumor Profiler Consortium,·Wicki, A.·Becher, B.·Koelzer, V. H.·Moch, H.·Buljan, M.·Tugues, S.·Sobottka, B.

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Abstract

Clinical implementation of comprehensive genomic profiling, via whole-genome (WGS) or whole-exome sequencing (WES), is constrained by sparse mutation burdens and analytic pipelines reliant on matched transcriptomes. Currently, gene-centric analysis prevails, but overlooks the complex, multigene and pathway perturbations shaping tumor biology. We introduce RIPPLET, a DNA-only framework converting somatic variants into quantitative gene-impact scores and topology-aware pathway-perturbation profiles. By integrating tissue-specific protein-protein interaction networks with cohort-informed reweighting, RIPPLET prioritizes likely functionally relevant alterations. Applied across 33 TCGA cancer types, RIPPLET surpasses four state-of-the-art multi-omic driver-prioritization tools in recovering cancer type-specific drivers. In a cohort of metastatic cutaneous melanomas, it identifies pathway signatures that predict drug response, provide prognostic insight and distinguish immune-infiltration phenotypes without RNA data, independently validated on an in-house cohort. RIPPLET enables DNA-only inference of tumor-specific gene and pathway dysregulation, aligning with clinical sequencing workflows and offering a scalable precision-oncology strategy in transcriptome-limited settings.

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Wiesmann, F., Litchfield, C., Mayoux, M., Tumor Profiler Consortium,, Wicki, A., Becher, B., Koelzer, V. H., Moch, H., Buljan, M., Tugues, S., Sobottka, B.. 2025-09-19. RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology. https://doi.org/10.1101/2025.09.17.676675

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