Retrospective data support overall survival (OS) advantage to high clonal tumor mutation burden (cTMB), high clonal neoantigen load (cNEO) and low intratumor heterogeneity (ITH) in cancer patients who receive immunotherapy. In order to explore this relationship prospectively with Vigil, a triple function targeted immunotherapy involving ovarian cancer patients in long term follow up of the Phase 2b VITAL trial, we developed an exome sequencing procedure and associated bioinformatics pipeline to determine clonal signal patterns. DNA libraries containing exome sequences tagged with unique molecular identifiers (UMI) were prepared from paired samples and sequenced on Illumina sequencers to high coverage depths of ~ 930X (tumor) and ~ 130X (normal). Raw sequence reads were processed into optimized binary alignment map (BAM) files, using the UMI information. The BAM files were inputted into modules for calling MHC-I alleles, annotating single nucleotide variants (SNVs) and small insertions/deletions (InDels), and for determination of allelic copy number. The outputs were used to predict the sequence of peptide neoantigens and to perform clonality analysis in order to assign each SNV and InDel in a patient tumor sample to a primary clone or subclone. The Clonal Neoantigen pipeline was further assessed using whole exome Illumina sequencing data from three previously published studies. Evaluation of the pipeline using synthetic sequencing data from a sub-clonal deconvolution tool benchmarking study, showed positive predictive value (PPV) and positive percent agreement (PPA) of >
97.5% and >
96.5%, respectively, for SNV and InDel detection with minimum requirements for variant density and allele fraction. Haplotype calls from the Clonal Neoantigen pipeline MHC-I/ MHC-II typing module matched a published benchmark for 91.5% of the calls in a sample of 99 patients. Analysis of exome sequencing data from 14 patients with advanced melanoma revealed a strong correlation between cTMB values determined by the Clonal Neoantigen pipeline as compared to those calculated from the published data (R