Anatomical Pathology, Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada.
Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
Gut. 2020 Feb;69(2):317-328. doi: 10.1136/gutjnl-2019-318217. Epub 2019 Jun 14.
Transcriptional analyses have identified several distinct molecular subtypes in pancreatic ductal adenocarcinoma (PDAC) that have prognostic and potential therapeutic significance. However, to date, an indepth, clinicomorphological correlation of these molecular subtypes has not been performed. We sought to identify specific morphological patterns to compare with known molecular subtypes, interrogate their biological significance, and furthermore reappraise the current grading system in PDAC.
We first assessed 86 primary, chemotherapy-naive PDAC resection specimens with matched RNA-Seq data for specific, reproducible morphological patterns. Differential expression was applied to the gene expression data using the morphological features. We next compared the differentially expressed gene signatures with previously published molecular subtypes. Overall survival (OS) was correlated with the morphological and molecular subtypes.
We identified four morphological patterns that segregated into two components ('gland forming' and 'non-gland forming') based on the presence/absence of well-formed glands. A morphological cut-off (≥40% 'non-gland forming') was established using RNA-Seq data, which identified two groups (A and B) with gene signatures that correlated with known molecular subtypes. There was a significant difference in OS between the groups. The morphological groups remained significantly prognostic within cancers that were moderately differentiated and classified as 'classical' using RNA-Seq.
Our study has demonstrated that PDACs can be morphologically classified into distinct and biologically relevant categories which predict known molecular subtypes. These results provide the basis for an improved taxonomy of PDAC, which may lend itself to future treatment strategies and the development of deep learning models.
转录分析已经确定了胰腺导管腺癌(PDAC)中的几个不同的分子亚型,这些亚型具有预后和潜在的治疗意义。然而,迄今为止,这些分子亚型与深入的临床形态学相关性尚未得到研究。我们试图确定与已知分子亚型相匹配的特定形态模式,探讨其生物学意义,并重新评估 PDAC 的现行分级系统。
我们首先评估了 86 例原发性、未经化疗的 PDAC 切除标本,这些标本均具有匹配的 RNA-Seq 数据,用于特定的、可重复的形态模式。使用形态特征对基因表达数据进行差异表达分析。然后,我们将差异表达基因特征与先前发表的分子亚型进行比较。将总生存期(OS)与形态和分子亚型相关联。
我们确定了四种形态模式,这些模式根据是否存在成型腺体分为两个成分(“腺体形成”和“非腺体形成”)。使用 RNA-Seq 数据建立了一个形态学截断值(≥40%“非腺体形成”),该值确定了两个具有与已知分子亚型相关的基因特征的组(A 和 B)。两组之间的 OS 存在显著差异。在使用 RNA-Seq 分类为“经典”的中分化和中度分化的癌症中,形态组仍然具有显著的预后意义。
我们的研究表明,PDAC 可以在形态上分为不同的、具有生物学相关性的类别,这些类别可以预测已知的分子亚型。这些结果为 PDAC 的改进分类学提供了基础,这可能有助于未来的治疗策略和深度学习模型的发展。