Journal Article

Morphological classification of pancreatic ductal adenocarcinoma that predicts molecular subtypes and correlates with clinical outcome

O’Kane, Grainne, Wilson, Gavin W, Chetty, Runjan, Seto, Matthew, Vajpeyi, Rajkumar, N Kalimuthu, Sangeetha, Notta, Faiyaz, Gallinger, Steven, Grant, Robert C

2020

Overview

IntroductionTranscriptional 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.DesignWe 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.ResultsWe 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.ConclusionOur 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.

• Publisher: BMJ Publishing Group Ltd and British Society of Gastroenterology,BMJ Publishing Group LTD
• Subject: Adenocarcinoma / Adult / Aged / basal subtype / Cancer therapies / Carcinoma, Pancreatic Ductal - genetics / Carcinoma, Pancreatic Ductal - pathology / Chemotherapy / classical subtype / Classification / Clinical outcomes / Deep Learning / Female / Gene expression / Gene Expression Regulation, Neoplastic / Glands / Health care networks / Humans / Kaplan-Meier Estimate / Male / Medical prognosis / Middle Aged / Morphology / Observer Variation / Pancreas / Pancreatic cancer / pancreatic ductal adenocarcinoma / Pancreatic Neoplasms / Pancreatic Neoplasms - genetics / Pancreatic Neoplasms - pathology / Patients / pattern-based morphological classification system / Prognosis / Reproducibility of Results / Ribonucleic acid / RNA / Studies / Survival analysis / Transcription / Transcriptome / Tumors