Transcriptomic Analysis of Laser Capture Microdissected Tumors Reveals Cancer- and Stromal-Specific Molecular Subtypes of Pancreatic Ductal Adenocarcinoma

激光捕获显微切割肿瘤的转录组分析揭示了胰腺导管腺癌的癌细胞和间质特异性分子亚型

阅读:1

Abstract

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) lethality is multifactorial; although studies have identified transcriptional and genetic subsets of tumors with different prognostic significance, there is limited understanding of features associated with the minority of patients who have durable remission after surgical resection. In this study, we performed laser capture microdissection (LCM) of PDAC samples to define their cancer- and stroma-specific molecular subtypes and identify a prognostic gene expression signature for short-term and long-term survival. EXPERIMENTAL DESIGN: LCM and RNA sequencing (RNA-seq) analysis of cancer and adjacent stroma of 19 treatment-naïve PDAC tumors was performed. Gene expression signatures were tested for their robustness in a large independent validation set. An RNA-ISH assay with pooled probes for genes associated with disease-free survival (DFS) was developed to probe 111 PDAC tumor samples. RESULTS: Gene expression profiling identified four subtypes of cancer cells (C1-C4) and three subtypes of cancer-adjacent stroma (S1-S3). These stroma-specific subtypes were associated with DFS (P = 5.55E-07), with S1 associated with better prognoses when paired with C1 and C2. Thirteen genes were found to be predominantly expressed in cancer cells and corresponded with DFS in a validation using existing RNA-seq datasets. A second validation on an independent cohort of patients using RNA-ISH probes to six of these prognostic genes demonstrated significant association with overall survival (median 17 vs. 25 months; P < 0.02). CONCLUSIONS: Our results identified specific signatures from the epithelial and the stroma components of PDAC, which add clarity to the nature of PDAC molecular subtypes and may help predict survival.

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。