Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response

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Roelands, Jessica | Hendrickx, Wouter | Zoppoli, Gabriele | Mall, Raghvendra | Saad, Mohamad | Halliwill, Kyle | Curigliano, Giuseppe | Rinchai, Darawan | Decock, Julie | Delogu, Lucia | Turan, Tolga | Samayoa, Josue | Chouchane, Lotfi | Ballestrero, Alberto | Wang, Ena | Finetti, Pascal | Bertucci, François | Miller, Lance | Galon, Jerome | Marincola, Francesco | Kuppen, Peter | Ceccarelli, Michele | Bedognetti, Davide

Edité par CCSD ; BMJ Publishing Group -

International audience. Background An immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown. Methods To explore the contextual prognostic value of cancer immune phenotypes, we applied a multimodal pan-cancer analysis among 31 different histologies (9282 patients), encompassing immune and oncogenic transcriptomic analysis, mutational and neoantigen load and copy number variations. Results We demonstrated that the favorable prognostic connotation conferred by the presence of a Th-1 immune response was abolished in tumors displaying specific tumor-cell intrinsic attributes such as high transforming growth factor-beta (TGF-β) signaling and low proliferation capacity. This observation was independent of mutation rate. We validated this observation in the context of immune checkpoint inhibition. WNT- β catenin, barrier molecules, Notch, hedgehog, mismatch repair, telomerase activity and AMPK signaling were the pathways most coherently associated with an immune silent phenotype together with mutations of driver genes including IDH1/2, FOXA2, HDAC3, PSIP1, MAP3K1, KRAS, NRAS, EGFR, FGFR3, WNT5A and IRF7 . Conclusions This is the first systematic study demonstrating that the prognostic and predictive role of a bona fide favorable intratumoral immune response is dependent on the disposition of specific oncogenic pathways. This information could be used to refine stratification algorithms and prioritize hierarchically relevant targets for combination therapies.

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