Characterization of Pancreatic Cancer with Ultra-low Tumor Mutational Burden

Author:

Imamura Taisuke1,Ashida Ryo1,Ohshima Keiichi2,Uesaka Katsuhiko1,Sugiura Teiichi1,Ohgi Katsuhisa1,Yamada Mihoko1,Otsuka Shimpei1,Hatakeyama Keiichi2,Nagashima Takeshi3,Sugino Takashi1,Urakami Kenichi2,Akiyama Yasuto2,Yamaguchi Ken3

Affiliation:

1. Shizuoka Cancer Center

2. Shizuoka Cancer Center Research Institute

3. Shizuoka Cancer Center Hospital and Research Institute

Abstract

Abstract In pancreatic cancer (PC), Tumor mutation burden (TMB) has been reported to be lower than in other cancers, with its clinical significance remaining unclear. We analyzed the dataset of whole-exome sequencing and gene expression profiling of 93 resected PC cases. The median TMB was 0.24. The TMB was classified as High (≥ 5.0), Low (< 5.0, ≥ 1.0), or Ultra-low (< 1.0). Nineteen samples (20%) were classified as TMB-low, and 74 (80%) were classified as TMB-ultra-low; no samples were TMB-high. TMB-ultra-low PC had significantly fewer borderline resectable lesions (P = 0.028) and fewer adenosquamous carcinomas (P = 0.003) than TBM-low PC. Furthermore, the TMB-ultra-low PC showed significantly lower detection rates of driver mutations and copy number variations. Microsatellite instability was not significantly correlated with the TMB status. The TMB-ultra-low PC had a significantly better prognosis than TBM-low PC (P = 0.023). A multivariate analysis identified TMB-ultra-low PC as an independent favorable prognostic factor (hazard ratio, 2.11; P = 0.019). A gene expression analysis showed that TMB-ultra-low PC was associated with reduced TP53 inactivation (P = 0.003) and reduced chromosomal instability (P = 0.001) compared to TBM-low PC. TMB-ultra-low PC had specific gene expression signatures and a better prognosis than TMB-low PC.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3