Abstract P3-05-13: The neo-epitope landscape of breast cancer: Implications for immunotherapy
Authors: P Narang, M Chen, AA Sharma, KS Anderson, MA Wilson Sayres
Journal: Cancer Research (2018)

Abstract Introduction: Immune checkpoint blockade is an effective immunotherapy for multiple cancers, including a subset of TNBCs. The clinical response to checkpoint blockade correlates with high tumor mutational burden. Cancer-induced mutations are predicted to generate new HLA-binding epitopes (neo-epitopes), which are potential targets of T cells. To determine the neo-epitope load in breast cancer, we developed a rapid bioinformatics pipeline and filtering strategy, EpitopeHunter, to identify and prioritize clinically relevant neo-epitopes from the landscape of somatic mutations. Here, we determined the specificity and frequency of neo-epitopes from the TCGA dataset of invasive breast cancers. Methods: We analyzed 842 tumor and normal breast cancer exome sequencing from the TCGA dataset. Subgroup analysis was performed based on the IHC status of ER, PR and HER2: (i) TNBC (n=98); (ii) ER and/or PR(+), Her2(-) (n=604); and (iii) ER and PR(+/-), Her-2(+) (n=140). Cancer specific mutations were called uniformly for the aligned tumor and normal pairs using VarScan2. For each annotated non-synonymous mutation, we generated all possible neo-epitopes (up to 11-mers) including the mutant amino acid. HLA typing of A, B and C MHC class I genes of each patient was determined using the POLYSOLVER algorithm. We selected high affinity binding epitopes using the IEDB prediction algorithm based on the known epitopes to identify likely binding of each neo-epitope within the suite of patient-specific HLA alleles (IEDB score &amp;lt; 500). We then filtered the epitopes based on tumor transcript abundance using RNAseq expression for 837/842 patients. An expression value of FPKM &amp;gt; 2 was used as a cut-off for the expressed neo-epitopes. Results: Total mutational burden was highest for TNBC (median=53, range: 2-1162); followed by ER and PR(+/-), Her-2(+) (median=40, range: 6-4983); and lowest for ER and/or PR (+), Her-2(-) (median=30, range: 0-5515). About 15% of the nonsynonymous mutations led to the generation of neo-epitopes. The neo-epitope load (high affinity neo-epitopes with IEDB score &amp;lt;500) is highly correlated with the mutational burden (R2= 0.8-0.9). Number of patients with at least one neo-epitope expressed in each category was: TNBC (n= 79/97, 81%); ER and/or PR(+), Her2(-) (n=478/600, 79%); and ER and PR(+/-), Her-2(+) (n=115/140, 82%). Overall, 672/837 patients have at least one predicted high affinity neo-epitope expressed, with an average of 14.7 (1-525) neo-epitopes expressed per patient. Conclusions: We have developed a rapid bioinformatics pipeline, EpitopeHunter, for the identification of neo-epitopes from tumor sequencing data. Eighty percent of breast cancer patients have at least one expressed neo-epitope, which may serve as candidates for targeted immunotherapy. Citation Format: Narang P, Chen M, Sharma AA, Anderson KS, Wilson Sayres MA. The neo-epitope landscape of breast cancer: Implications for immunotherapy [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-05-13.