Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York, USA.
Department of Medicine, Division of Digestiveand Liver Diseases, Columbia University Medical Center, New York, New York, USA.
Gut. 2019 Jun;68(6):1034-1043. doi: 10.1136/gutjnl-2018-317706. Epub 2019 Jan 18.
Pancreatic ductal adenocarcinoma (PDA) has among the highest stromal fractions of any cancer and this has attempts at expression-based molecular classification. The goal of this work is to profile purified samples of human PDA epithelium and stroma and examine their respective contributions to gene expression in bulk PDA samples.
We used laser capture microdissection (LCM) and RNA sequencing to profile the expression of 60 matched pairs of human PDA malignant epithelium and stroma samples. We then used these data to train a computational model that allowed us to infer tissue composition and generate virtual compartment-specific expression profiles from bulk gene expression cohorts.
Our analysis found significant variation in the tissue composition of pancreatic tumours from different public cohorts. Computational removal of stromal gene expression resulted in the reclassification of some tumours, reconciling functional differences between different cohorts. Furthermore, we established a novel classification signature from a total of 110 purified human PDA stroma samples, finding two groups that differ in the extracellular matrix-associated and immune-associated processes. Lastly, a systematic evaluation of cross-compartment subtypes spanning four patient cohorts indicated partial dependence between epithelial and stromal molecular subtypes.
Our findings add clarity to the nature and number of molecular subtypes in PDA, expand our understanding of global transcriptional programmes in the stroma and harmonise the results of molecular subtyping efforts across independent cohorts.
胰腺导管腺癌(PDA)的基质成分比例在所有癌症中是最高的,这使得人们尝试基于表达谱的分子分类。这项工作的目的是分析纯化的人 PDA 上皮和基质样本,并研究它们各自对大量 PDA 样本中基因表达的贡献。
我们使用激光捕获显微切割(LCM)和 RNA 测序技术,对 60 对匹配的人 PDA 恶性上皮和基质样本进行了表达谱分析。然后,我们利用这些数据训练了一个计算模型,该模型允许我们推断组织成分,并从大量基因表达队列中生成虚拟的特定于隔室的表达谱。
我们的分析发现,来自不同公共队列的胰腺肿瘤在组织成分上存在显著差异。通过计算去除基质基因表达,导致一些肿瘤的重新分类,协调了不同队列之间的功能差异。此外,我们从总共 110 个纯化的人 PDA 基质样本中建立了一个新的分类特征,发现了两组在细胞外基质相关和免疫相关过程中存在差异。最后,对跨越四个患者队列的跨隔室亚型进行系统评估表明,上皮和基质分子亚型之间存在部分依赖性。
我们的研究结果增加了对 PDA 中分子亚型的性质和数量的认识,扩展了我们对基质中全局转录程序的理解,并协调了跨独立队列的分子分型研究结果。