Abstract A70: Identification of pancreatic cancer neoantigens by exome and RNA sequencing analysis
Authors: Cullinan Darren R. , Goedegebuure S. Peter , Miller Chris A. , Nywening Timothy M. , Kim Samuel , Mardis Elaine R. , Hawkins William G. , Gillanders William E. 
Published: December 2016

Abstract
Introduction: Recent reports suggest that the mutational landscape predicts response to checkpoint blockade therapy in non-small cell lung cancer and colorectal cancer. Neoantigens, identified by exome and RNA sequencing using immune prediction algorithms, have been successfully targeted by dendric cell vaccination in melanoma. The relative abundance of non-malignant cells within the stroma has made Identification of neoantigens in pancreatic cancer (PC) challenging. Here we report successful isolation and high quality sequencing of PC neoplastic ductal cells specifically, resulting in the identification of immunogenic mutations.
Methods: Specimens from freshly resected PC tumors were collected in the operating room and immediately frozen in OCT. Laser microdissection was performed by a pathologist to isolate PC malignant cells from the stromal compartment at &gt;90% purity. DNA and RNA were isolated from the purified tumors with nonsynonymous mutations identified by tumor/normal exome sequencing and expression verified by RNA sequencing. HLA typing was inferred from exome sequencing and verified by standard HLA typing techniques. Candidate neoantigen binding scores were determined via NetMHC. Tumor infiltrating lymphocyte (TIL) culture was carried out over 12-14 days by serial reduction of tumor concentration as the TIL proliferated in the presence of IL-2 containing media (50 units/mL).
Results: Patient #567 was confirmed to express HLA-A3 and HLA-A23. 105 nonsynonymous mutations were identified by tumor/normal exome sequencing, all of which were single nucleotide polymorphisms. Candidate neoantigens were identified and prioritized based on predicted binding of the mutant amino acid sequence to MHC class I. 30 candidate neoantigens were prioritized for further evaluation based on a binding score of &lt; 500 nM, and superior predicted binding associated with the mutant sequence compared to the wildtype sequence. Mutant allele expression was verified by a fragments per kilobase of exon per million fragments mapped (FKPM) &gt;1, with a cut off for RNA variant allele frequency (VAF) greater than 20%. Using this stringent criteria 10 candidate epitopes were identified. Next, we validated this process in 17 consecutive PC patients. DNA and RNA were successfully isolated from 13 patients (76.5%), the remaining four had no viable tumor at pathology. The mean RNA integrity number (RIN) for the isolated samples was 7.6 (Range 5-8.7). Additionally, to test for existing immune response to the predicted epitopes TIL were successfully cultured from 6 of 8 (75%) attempted patients with a mean yield of 3.0x106 (Range 1x105 – 7.2x106).
Conclusion: Obtaining high quality, reliable sequencing data from PC patients is possible using rigorous tumor purification techniques to specifically select malignant cells. Candidate neoantigens can be identified using a combination of epitope prediction algorithms. Expansion of TIL populations in vitro may offer functional studies to further refine the optimal selection of immunogenic neoantigens and optimize personalized vaccination strategies in PC.
Citation Format: Darren R. Cullinan, S. Peter Goedegebuure, Chris A. Miller, Timothy M. Nywening, Samuel Kim, Elaine R. Mardis, William G. Hawkins, William E. Gillanders.{Authors}. Identification of pancreatic cancer neoantigens by exome and RNA sequencing analysis. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr A70.