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A targetable dependency on nonsense-mediated decay for proteostasis and immune control in small cell lung cancer

Torres Fernandez, L. A.; Boehm, V.; Kaufmann, J.; Ruminska, A.; Becker, J. P.; Garcia Marquez, M.; Bruijn, B.; Muller, C.; Alavinejad, N.; Lovric, L.; Bihler, J.; Weihrauch, K. R.; Kaiser, L.; Schmiel, M.; Maas, L.; Beleggia, F.; Ibruli, O.; Gobel, B.; Sakthivelu, V.; Bosco, G.; Fanyu, L.; Androulidaki, A.; Karstedt, S.; Cartolano, M.; Bragelmann, J.; Valiulis, J.; DRozario, J.; Wobst, N.; Hopker, K.; John, F.; Wolf, J.; Quaas, A.; Knapp, S.; Davoodi, P.; Schollhorn, A.; Gouttefangeas, C.; Rammensee, H.-G.; Riemer, A. B.; Reinhardt, H. C.; Schloer, H. A.; Gehring, N. H.; Peifer, M.; Thomas, R.

2026-04-02 cancer biology
10.64898/2026.03.31.715503 bioRxiv
Show abstract

Small cell lung cancer (SCLC) is among the deadliest cancers with excessive somatic alterations, expectedly resulting in immunogenic epitopes. However, patient benefit from immunotherapy is limited. We found abundant frameshift mutations in SCLC, regarded as highly immunogenic, counterbalanced by a hyperactive nonsense-mediated decay (NMD) pathway, responsible for frameshift-mRNA degradation. NMD activity correlated with tumor mutational burden (TMB) across cancers, suggesting that SCLC depends on NMD for cellular homeostasis and immune evasion. NMD inhibition impaired SCLC proliferation and induced ER stress-dependent apoptosis in a TMB-dependent manner, thereby enabling pharmacological inhibition in vivo which effectively controlled tumor growth. By integrating genome and transcriptome sequencing with MHC-I immunopeptidomics and functional in vitro and in vivo assays, we identified that NMD inhibition boosted neoantigen expression and presentation by tumor cells and increased T cell recognition, thus enhancing overall tumor immunogenicity and further improving immunotherapy efficacy in vivo. Our work shows that SCLC - as a TMBhigh cancer - relies on NMD for survival and immune escape, uncovering a novel TMB-dependent tractable vulnerability for this devastating disease.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.