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Tumor infiltrating neutrophils and gland formation predict overall survival and molecular subgroups in pancreatic ductal adenocarcinoma

Authors :
Julia R. Naso
James T. Topham
Joanna M. Karasinska
Michael K.C. Lee
Steve E. Kalloger
Hui‐li Wong
Jessica Nelson
Richard A. Moore
Andrew J. Mungall
Steven J.M. Jones
Janessa Laskin
Marco A. Marra
Daniel J. Renouf
David F. Schaeffer
Source :
Cancer Medicine, Vol 10, Iss 3, Pp 1155-1165 (2021)
Publication Year :
2021
Publisher :
Wiley, 2021.

Abstract

ABSTRACT Background RNA‐sequencing‐based classifiers can stratify pancreatic ductal adenocarcinoma (PDAC) into prognostically significant subgroups but are not practical for use in clinical workflows. Here, we assess whether histomorphological features may be used as surrogate markers for predicting molecular subgroup and overall survival in PDAC. Methods Ninety‐six tissue samples from 50 patients with non‐resectable PDAC were scored for gland formation, stromal maturity, mucin, necrosis, and neutrophil infiltration. Prognostic PDAC gene expression classifiers were run on all tumors using whole transcriptome sequencing data from the POG trial (NCT02155621). Findings were validated using digital TCGA slides (n = 50). Survival analysis used multivariate Cox proportional‐hazards tests and log‐rank tests. Results The combination of low gland formation and low neutrophil infiltration was significantly associated with the poor prognosis PDAC molecular subgroup (basal‐like or squamous) and was an independent predictor of shorter overall survival, in both frozen section (n = 47) and formalin‐fixed paraffin‐embedded (n = 49) tissue samples from POG patients, and in the TCGA samples. This finding held true in the subgroup analysis of primary (n = 17) and metastatic samples (n = 79). The combination of high gland formation and high neutrophils had low sensitivity but high specificity for favorable prognosis subgroups. Conclusions The assessment of gland formation and neutrophil infiltration on routine histological sections can aid in prognostication and allow inferences to be made about molecular subtype, which may help guide patient management decisions and contribute to our understanding of heterogeneity in treatment response.

Details

Language :
English
ISSN :
20457634
Volume :
10
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.9eff83f544e44f7a8c96d5e8aef3b2f
Document Type :
article
Full Text :
https://doi.org/10.1002/cam4.3695