Preprints

• Dual inhibition of the nonsense mediated mRNA decay enhances tumour immunogenicity, drives immunoediting, and potentiates checkpoint blockade. I Zadra, D Orsolic, D Kounis [...] F Supek*, A Janic* (2025) biorxiv. 

Immune checkpoint blockade has transformed cancer therapy, but current biomarkers such as tumour mutation burden often fail to reliably predict clinical benefit. One proposed reason for this discrepancy is the activity of nonsense-mediated mRNA decay (NMD), a cellular quality-control pathway that degrades mutant transcripts, potentially reducing the presentation of neoantigens that would otherwise stimulate anti-tumour immunity. To address this, we identified publicly available small-molecule inhibitors targeting the NMD factors SMG5 and SMG7 (NMDi), which we have prioritise as the NMD components most strongly associated with NMD efficiency across TCGA tumours, and evaluated their therapeutic potential in vivo. In a syngeneic, DNA repair deficient mouse model of lung adenocarcinoma, NMDi treatment alone substantially reduced tumour burden, and its combination with anti–PD-1 therapy led to additive benefit either treatment alone. These effects were immune-dependent and specifically required CD8□ T cells. Transcriptomic and single-cell analyses revealed that NMDi reprograms the tumour immune microenvironment, enriching for clonally expanded, cytotoxic CD8□ T cells and altering macrophage states toward those associated with tumour regression. Whole-genome sequencing of tumours revealed that NMDi also promotes immunoediting, leading to negative selection against immunogenic mutations and coding indels, with selective pressure comparable to or greater than that induced by anti–PD-1 treatment. Guided by these results, we generated a new protein language model trained on tumour mutations that can identify neopeptides with immunogenic properties, revealing that the NMDi tumour landscape provides a rich genomic and immunopeptidomic setting for exposing neoantigens that evade immunoediting. Together, these pre-clinical and integrative genomic-transcriptomic insights position NMD inhibition as a promising immunostimulatory strategy that can potentiate immune checkpoint blockade efficacy in tumours.

• The DiffInvex evolutionary model for conditional somatic selection identifies chemotherapy resistance genes in 10,000 cancer genomes. A Khalil, F Supek (2021) bioRxiv. 

Tumors often show an initial response to chemotherapy, but then develop resistance, leading to relapse and poor prognosis. We hypothesized that a genomic comparison of mutations in pre-treated versus treatment-naive tumors would serve to identify genes that confer resistance. A challenge in such an analysis is that therapy alters mutation burdens and signatures, confounding association studies and complicating identifying causal, selected mutations. We developed DiffInvex, a framework for identifying changes in selection acting on individual genes in somatic genomes. Crucially, DiffInvex draws on a mutation rate baseline that accounts for these shifts in neutral mutagenesis during cancer evolution. We applied DiffInvex to 9,953 cancer whole-genomes from 29 cancer types from 8 studies, containing both WGS of treatment-naive tumors and tumors pre-treated by various drugs, identifying genes where point mutations are under conditional positive or negative selection for a certain chemotherapeutic, suggesting resistance mechanisms occurring via point mutation. DiffInvex confirmed well-known chemoresistance-driver mutations in EGFR, ESR1, KIT and AR genes as being under conditional positive selection, with additional cancer types identified for EGFR and KIT. Additionally, DiffInvex identified 11 genes with treatment-associated selection for different classes of therapeutics. In most cases, these genes were common cancer genes including PIK3CA, APC, MAP2K4 and MAP3K1. This suggests that tumor resistance to therapy via mutation often occurs via selective advantages conferred by known driver genes, rather than via mutations in specialized resistance genes. Various gene-chemotherapy associations were further supported in tests for functional impact of mutations, again implemented in a conditional selection setting, as well as replicating in independent panel or exome sequencing data. In addition to nominating drug resistance genes that could be targeted by future therapeutics, DiffInvex can also be applied to diverse analysis in cancer evolution, such as comparing normal and tumoral tissues, or analyzing subclonal evolution, identifying changes in selection over time.

• Copy number-independent allelic imbalance in mRNA is selected in cancer and has prognostic relevance.
  G Palou*, P Pericot*, F Supek (2025) bioRxiv.

Allelic imbalance (AI) in levels of mRNAs in cancer is widely appreciated to result from somatic copy number alterations (CNA) affecting one allele. Apart from CNA, other mechanisms could lead to imbalanced mRNA expression of the alleles, and similarly drive cancer evolution by epistatic interactions with the somatic mutations. By integrating genomic and transcriptomic pan-cancer data, we show that mRNA allelic imbalance favoring the mutant allele in driver genes is subject to positive selection, generating second-hit events often independently of somatic CNA. In some cases, the somatic coding mutations could induce allele-specific expression directly, e.g. with splicing-altering exonic mutations, which can be selected in various cancer genes. However, in the majority of cases, these and related somatic mutation effects (which might in principle alter transcription output via impacting promoters or intragenic enhancers) do not explain the CNA-independent mRNA-level AI, suggesting prevalent epigenetic alterations affecting alleles differently in tumors. Importantly, the mRNA AI events associate with worse overall survival across all cancer types, outperforming various other predictive markers. Our study suggests that mRNA allelic imbalances can occur independently of CNA but similarly function as second-hit events to somatic mutations, driving tumorigenesis, and so represent valuable prognostic biomarkers for cancer patient stratification.