Abstract PO092: Multi-region sequencing analysis of metastatic solid tumors to inform targeting of personalized cancer immunotherapies

Abstract

Abstract Personalized cancer immunotherapies (pCIT) rely on targeting of somatic cancer mutations, which in their translated peptide form are known as neoantigens. Each tumor has a unique set of mutations, and thus, the vast majority of cancer neoantigens targeted by these personalized therapies are private to an individual's tumor. We sought to understand whether a single strategy for targeting private neoantigens—prioritizing clonal neoantigens over subclonal ones—could apply equally well across primary and metastatic lesions in patients with advanced metastatic solid tumors, and across different cancer indications. Previous studies of largely primary tumors in non-metastatic settings have suggested that indications such as melanoma and NSCLC consistently have low mutational heterogeneity and a preponderance of clonal neoantigens, whereas other indications such as CRC, RCC, and breast cancer often have a higher degree of mutational heterogeneity and fewer clonal neoantigens. It remains unclear whether standard clonality metrics (e.g., cancer cell fraction or "CCF") can accurately predict global mutation clonality across tumor lesions and whether CCF could offer any predictive benefit over simple variant allele frequencies. By multi-region sequencing analysis of five metastatic solid tumors across four indications (CRC, NSCLC, RCC, UBC), with all lesions sampled at the same time point, we characterized neoantigen heterogeneity and whether the clonality and expression level of mutations would influence the likely immunogenicity of neoantigen candidates selected for pCIT. We show that the ability to target cancer neoantigens effectively depends on the type of lesion sampled and on indication. In NSCLC and UBC, where most mutations were shared across tumor lesions, effective targeting could be accomplished by sampling either the primary or certain metastatic lesions. However, CRC and RCC tumors had more complex, branching mutational phylogenies, leading to non-overlapping sets of mutations across different tumor lesions. On average, across the five metastatic cases, a given tumor sample’s predictive value for global mutation clonality varied from 20% (RCC) to 70% (NSCLC). Enrichment of clonal neoantigens could be accomplished by prioritizing mutations with higher variant allele frequency (VAF), as expected, but using CCF for mutation prioritization led to poorer enrichment of clonal neoantigens. In one case (UBC), we observed truncal neoantigen reduction via down-regulation of mutant allele expression, suggesting that early immune recognition of tumors is an important factor in pCIT targeting. Our data suggest that indication-specific neoantigen targeting strategies, which consider mutation presence and expression across multiple tumor lesions, may be necessary for pCIT to be broadly effective. Citation Format: Amy Lo, Andrew Wallace, Daniel Oreper, Nicolas Lounsbury, Charles Havnar, Carmina Espiritu, Ximo Pechuan-Jorge, Richard Bourgon, Ryan Jones, Katrina Krogh, Guang-Yu Yang, Oliver Zill. Multi-region sequencing analysis of metastatic solid tumors to inform targeting of personalized cancer immunotherapies [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PO092.