Boudjadi, S. | bioRxiv Science

bioRxiv2026

APOBEC3-driven neoantigen-rich cancers co-opt 1q23.3 amplification for tumor-intrinsic immune cloaking

Hypermutational processes, including those driven by the APOBEC3 family of cytidine deaminases, generate abundant neoantigens yet give rise to tumors that evade immune recognition. Here, using multi-omics analyses followed by functional validation, we identified a tumor-intrinsic immune-cloaking mechanism in neoantigen-rich epithelial cancers, characterized by coordinated suppression of antigen presentation, immune-recruiting cytokines and immune-checkpoint programs. In bladder cancer, genome-wide copy-number analysis identified recurrent 1q23.3 amplification as a genomic feature of a neoantigen-high/CD8-low tumor state. Within this locus, NECTIN4 emerged as the dominant candidate effector, outperforming extrachromosomal DNA status as a predictor of immune-neoantigen discordance. Similar associations were observed across breast and lung cancers. Functional studies demonstrated that NECTIN4 was sufficient to establish a T-cell-poor tumor microenvironment and confer resistance to PD-1 blockade in immunocompetent mice. Mechanistically, NECTIN4 engaged a DDR1-SHP2 axis that suppressed STAT1 phosphorylation, silencing tumor-cell immune-engagement programs. NECTIN4 blockade restored STAT1 activity and reduced tumor growth, indicating that the cloaked state is pharmacologically reversible. Mutational signature, breakpoint motif, timing and clonality analyses, together with APOBEC3B expression and germline genetic evidence, linked APOBEC3-mediated mutagenesis to recurrent 1q23.3 amplification encompassing NECTIN4. These findings reveal how neoantigen-generating mutational processes can be coupled to structural genome evolution to enable tumor-intrinsic immune cloaking through a therapeutically targetable NECTIN4-DDR1-SHP2 axis.

cancer biology↗

bioRxiv2025

Pan-cancer prediction of tumor immune activation and response to immune checkpoint blockade from tumor transcriptomics and histopathology

Accurately predicting which patients will respond to immune checkpoint blockade (ICB) remains a major challenge. Here, we present TIME_ACT, an unsupervised 66-gene transcriptomic signature of tumor immune activation derived from TCGA (The Cancer Genome Atlas) melanoma data. First, we demonstrate that TIME_ACT scores accurately identify tumors with activated immune microenvironments across different cancer types. Further, analysis of spatial features reveals that tumor microenvironment regions with dense lymphocyte infiltration near tumor cells have high TIME_ACT scores, successfully marking localized immune activation. Second, across 25 transcriptomic ICB cohorts encompassing nine cancer types, TIME_ACT achieves a mean AUC of 0.76 and a mean odds ratio of 5.77, significantly outperforming 30 established transcriptomic signatures and prediction methods for ICB response, including a recently developed foundation model for immunotherapy response prediction. Third, we show that TIME_ACT scores can be accurately inferred from routine tumor histopathology slides and that slide-inferred TIME_ACT scores predict ICB response across nine new independent patient cohorts spanning eight cancer types, achieving a mean AUC of 0.72 and a mean odds ratio of 4.99. These findings establish TIME_ACT as a robust, pan-cancer biomarker that enables accurate, low-cost, and clinically scalable prediction of ICB response from routine histopathology.

cancer biology↗