Comprehensive molecular profiling to predict clinical outcomes in pancreatic cancer

利用全面的分子谱分析预测胰腺癌的临床结果

阅读:1
作者:Jung Yong Hong ,Hee Jin Cho ,Seung Tae Kim ,Young Suk Park ,Sang Hyun Shin ,In Woong Han ,Jeeyun Lee ,Jin Seok Heo ,Joon Oh Park

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis among common cancers. The genomic landscape of PDAC is defined by four mutational pathways: kirsten rat sarcoma virus (KRAS), cellular tumor antigen p53 (TP53), cyclin dependent kinase inhibitor 2A (CDKN2A), and SMAD family member 4 (SMAD4). However, there is a paucity of data on the molecular features associated with clinical outcomes after surgery or chemotherapy. Methods: We performed comprehensive molecular characterization of tumor specimens from 83 patients with PDAC who received surgery, using whole-exome sequencing and ribonucleic acid sequencing on tumor and matched normal tissues derived from patients. We also systematically performed integrative analysis, combining genomic, transcriptomic, and clinical features to identify biomarkers and possible therapeutic targets. Results: KRAS (75%), TP53 (67%), CDKN2A (12%), SMAD4 (20%), and ring finger protein 43 (RNF43) (13%) were identified as significantly mutated genes. The tumor-specific transcriptome was classified into two clusters (tumor S1 and tumor S2), which resembled the Moffitt tumor classification. Tumor S1 displayed two distinct subclusters (S1-1 and S1-2). The transcriptome of tumor S1-1 overlapped with the exocrine-like (Collisson)/ADEX (Bailey) subtype, while tumor S1-2 mostly consisted of the classical (Collisson)/progenitor (Bailey) subtype. In the analysis of combinatorial gene alterations, concomitant mutations of KRAS with low-density lipoprotein receptor related protein 1B (LRP1B) were associated with significantly worse disease-free survival after surgery (p = 0.034). One patient (1.2%) was an ultrahypermutant with microsatellite instability. We also identified high protein kinase C lota (PRKCI) expression as an overlapping, poor prognostic marker between our dataset and the TCGA dataset. Conclusion: We identified potential prognostic biomarkers and therapeutic targets of patients with PDAC. Understanding these molecular aberrations that determine patient outcomes after surgery and chemotherapy has the potential to improve the treatment outcomes of PDAC patients. Keywords: KRAS; LRP1B; PRKCI; landscape; pancreatic cancer.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。