The fitness of TP53 mutations can be modeled by mutational signatures, oncogenic activity, and immunogenicity.

  • Major Finding: The fitness of TP53 mutations can be modeled by mutational signatures, oncogenic activity, and immunogenicity.

  • Concept: There is a cancer-specific trade-off between degree of oncogenic potential and immune recognition.

  • Impact: This model improves the understanding of mechanisms driving tumor evolution and can inform precision medicine.

Referred to as hotspot mutations, alterations in oncogenic driver genes commonly cluster at specific sites unique to each gene, and distinct mechanisms have been proposed to explain the distribution of these hotspots, including background mutation patterns, alterations in function, and evasion of the immune system. However, the relative contributions of these processes to the landscape of driver gene mutations has remained poorly explored. Surveying the mutation frequencies of commonly mutated oncogenes and tumor suppressor genes across The Cancer Genome Atlas (TCGA) and the Catalogue of Somatic Mutations in Cancer (COSMIC) databases, Hoyos, Zappasodi, and colleagues demonstrated that hotspots in multiple driver genes, including in TP53PTEN, and NRAS, are highly conserved and predicted to confer suboptimal neoantigen presentation. A mathematical model of mutant free fitness focused on TP53 was developed, based in part on the probability for each mutant to acquire pro-oncogenic potential (positive fitness) or become immunogenic (negative fitness), which successfully predicted the distribution of hotspot TP53 mutations, highlighting that these hotspots displayed an optimal trade-off between oncogenic function and immunogenicity. These predictions of differential immunogenic potential between mutant p53 variants were validated by evaluating specific T-cell reactivity in peripheral blood mononuclear cell samples from patients with cancers harboring these mutations as well as from healthy donors. In addition, the mutant p53 fitness model not only significantly separated early versus late tumor onset for patients with Li-Fraumeni syndrome—which is caused by germline TP53 mutations—but also anticipated survival of patients in TCGA as well as an independent cohort of immunotherapy-treated patients with non–small cell lung cancer. Notably, TP53 hotspot frequencies differed between cancerous and noncancerous tissue, suggesting that the trade-off between oncogenic function and immunogenicity changes over time as the tumor develops, potentially revealing the activity of cancer immunoediting. In summary, this work develops a model that allows the quantification of driver mutation fitness to shed light on tumor evolution and new therapeutic opportunities to target mutant TP53 and potentially other driver genes with immune-based therapies. 

Hoyos D, Zappasodi R, Schulze I, Sethna Z, de Andrade KC, Bajorin DF, et al. Fundamental immune–oncogenicity trade-offs define driver mutation fitness. Nature 2022 May 11 [Epub ahead of print].

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