Abstract P2-06-26: nf-hlamajority: a Nextflow pipeline for consensus MHC class I typing and its application to neoantigen identification in breast cancer stromal cells

Abstract Introduction: Cancer-associated fibroblasts (CAFs) are a heterogeneous cell type found in the tumour microenvironment (TME). CAFs can support tumour growth and metastasis and contribute to therapeutic resistance. They can also impact immune infiltration and immune responses in the TME. Therefore, therapeutic targeting of CAFs is potentially a viable strategy to treat cancer. Here, we aim to identify somatic mutations in CAFs, that may give rise to neoantigens. HLA genotyping is an important step for neoantigen prediction. This can be carried out in silico using DNA sequencing data, with numerous tools available for this purpose. Claeys et al. (PMID: 37161318) benchmarked several HLA typing tools, finding that a majority voting approach using a combination of four tools resulted in superior performance for each HLA gene. No end-to-end pipeline currently exists to apply this majority voting approach, making it difficult for non-informaticians to implement. The objectives of this work were to: 1) develop a Nextflow bioinformatics pipeline implementing majority voting for MHC class I typing from DNA sequencing data, and 2) use HLA calls from this pipeline to identify potential neoantigens in cancer-associated fibroblasts.Materials and Methods: CAFs and corresponding tumour-associated normal fibroblasts (TANs) were cultured from tissue of 12 breast cancer patients (11 Luminal A and one triple-negative). Bulk RNA-sequencing was carried out on all samples and whole-exome sequencing (WES) was carried out on CAFs and TANs from eleven patients. The Nextflow pipeline developed, nf-hlamajority, was used to determine HLA genotypes using WES from each breast cancer patient and 12 NCI-60 Human Tumor Cell lines. nf-hlamajority takes FASTQ files and performs HLA typing using Optitype, Polysolver, HLA-LA and Kourami. For each HLA gene, it then assigns the HLA genotype called by the highest number of tools. In the case of a tie, the HLA genotype called by the tool with the highest accuracy for that HLA gene, as determined by Claeys et al., is assigned to the sample. HLA calls made by nf-hlamajority in the samples from breast cancer patients were used as input to Landscape of Effective Neoantigens Software (LENS) to identify CAF-specific neoantigens (PMID:37184881).Results and Discussion: In the NCI-60 dataset, 68/70 (97%) nf-hlamajority HLA calls matched the ground-truth PCR genotyping call, demonstrating the high accuracy of the pipeline. nf-hlamajority was then used for the automated high-confidence HLA typing of all breast cancer patients. Using HLA alleles called using nf-hlamajority, LENS identified a number of potential neoantigens resulting from missense mutations, all of which were private to each patient. Interestingly, genes with these mutations included CAF markers and genes implicated in lipid metabolic pathways. CAFs contribute to lipid metabolism within the TME, thus impacting cancer progression and tumour immunogenicity.In this study, we have developed an automated pipeline for consensus HLA typing which we envisage will be useful to the research community. nf-hlamajority has helped us identify candidate neoantigens in breast cancer CAFs. Future work will focus on validation using T-cell immunogenicity assays, improving our understanding of the potential of targeting CAF neoantigens to enhance the efficacy of anti-cancer therapy. Citation Format: Kevin Ryan, Domhnall O’Connor, Barry Digby, Laura Barkley, Pilib Ó Broin. nf-hlamajority: a Nextflow pipeline for consensus MHC class I typing and its application to neoantigen identification in breast cancer stromal cells [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P2-06-26.