Abstract 2484: Development of a gene expression database of pancreatic ductal adenocarcinoma cases by NGS-combined HiCEP to identify tumor markers

Abstract

Abstract Objectives: High coverage expression profiling (HiCEP) is an AFLP-based comprehensive gene expression analysis invented in Japan. There are two advantages of HiCEP compared with existing methods, such as DNA microarrays and RNA sequencing. First, it can efficiently detect an especially low amount of mRNA with high sensitivity and reliability, and second, it enables us to analyze mRNA expression much more quantitatively and reproducibly. On the other hand, it requires complicated processes, including TA cloning of isolated transcripts, to obtain the sequence information of the detected peaks. In order to solve this problem, we established the gene expression database of human cancers by combining the next-generation sequencing (NGS) with HiCEP method. Materials and methods: We applied the NGS-combined HiCEP method to analyze pancreatic ductal adenocarcinoma(PDAC) cases in this study, and tried to establish the gene expression database of PDAC to identify effective tumor markers. We collected samples of both the cancerous and macroscopically non-cancerous tissues from 49 patients diagnosed with PDAC who underwent surgical resection at our institute. Among them, four cases were analyzed by HiCEP. Total RNA was extracted from the cancerous and normal tissues of the four PDAC cases, and transcribed to cDNA. The cDNA was synthesized and subjected to digestion with the restriction enzymes, MspI and MseI, followed by adapter ligation. Selective PCR by 256 kinds of primer pairs was used to amplify the HiCEP fragments, and products with fluorescently-labeled primer were then analyzed by capillary electrophoresis. HiCEP fragments were sequenced by the next-generation sequencer (ion PGM, Thermo Fisher Scientific). Furthermore, we compared the expression levels of HiCEP peaks in cancerous tissues with those in normal tissues. Results: We detected multiple HiCEP peaks that showed higher expression in cancerous tissues than in normal tissues in all four cases, and also found out different peaks showing higher expression in cancerous tissues of cases which had a recurrence of cancer after surgery than in cancerous tissues of cases without recurrences. We determined the sequences of the HiCEP fragments by NGS, and developed the first ever HiCEP fragment database for PDAC. Conclusion: We successfully established a PDAC gene expression database by NGS-combined HiCEP method. We are now performing replication analyses with the other PDAC cases, and further analyses of blood samples from the same PDAC cases, aiming to identify diagnostic and prognostic markers of PDAC. Citation Format: Mikiya Takao, Hirotaka Matsuo, Ryoko Araki, Seiko Shimizu, Makoto Kawaguchi, Akiyoshi Nakayama, Yosuke Kitamura, Yusuke Kawamura, Kazuki Maehara, Masumi Abe, Keiichi Ito, Mayumi Hoshikawa, Junji Yamamoto, Yoji Kishi, Nariyoshi Shinomiya. Development of a gene expression database of pancreatic ductal adenocarcinoma cases by NGS-combined HiCEP to identify tumor markers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2484.