What question did this study set out to answer?

The study aims to improve prognostication in pancreatic ductal adenocarcinoma by integrating tumor microenvironment and molecular signatures into a staging system.

April 27, 2026Discover Oncology0 citationsOpen Access

A tumor microenvironment integrated (TMI) staging system for pancreatic ductal adenocarcinoma based on cancer-associated fibroblast and molecular consensus signatures

SYSamuel Jianjie YeoAgency for Science, Technology and Research ISIan Tate Ek Ern SIM HTHui Yi TayNational Cancer Centre Singapore

Key Points

The study aims to improve prognostication in pancreatic ductal adenocarcinoma by integrating tumor microenvironment and molecular signatures into a staging system.
Clustered a discovery cohort (n = 320) into tumor subtypes using molecular signatures.
Used single-cell RNA-seq data to estimate cancer-associated fibroblast fractions and established thresholds for myofibroblastic CAFs.
Compared the newly developed TMI staging system against the AJCC clinical staging system using a validation cohort (n = 156).
TMI staging system demonstrated better prediction of overall survival with Harrell’s C-index of 0.558 versus 0.547 for AJCC in the discovery cohort.
In the validation cohort, TMI outperformed AJCC with C-index values of 0.535 compared to 0.500.
Identified fibronectin 1 (FN1) as a key protein associated with poor prognosis linked to myCAF and tumor cell interactions.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive solid tumor with poor prognosis. Existing prognostication systems rely on clinical staging, but systems of tumor classification through molecular signatures and the association between cancer-associated fibroblast (CAF) subtypes and clinical outcomes suggest that prognostic systems could be improved by integrating these data. We clustered a discovery cohort (n = 320) of PDAC into basal and nonbasal tumor subtypes by applying a molecular signature previously defined by O’Kane et al. We performed deconvolution using data of annotated cells from separate single-cell RNA-seq studies to estimate the fractions of different CAFs in each case in the discovery cohort and further generated a fraction threshold for myofibroblastic CAFs (myCAFs) enrichment delineating poor prognosis. We integrated these molecular classifications and metastasis status to generate a tumor microenvironment integrated (TMI) staging system, which we subsequently compared against the 7th American Joint Committee on Cancer (AJCC) clinical staging system using an external validation cohort (n = 156). We finally explored the signaling pathways within the single-cell dataset to identify key signaling pathways associated with myCAFs. TMI staging outperformed AJCC staging in predicting overall survival within both the discovery cohort (Harrell’s C-index: 0.558 vs. 0.547) and validation cohort (Harrell’s C-index: 0.535 vs. 0.500). In terms of differences, TMI was better able to account for overall survival rate variations, while AJCC staging remained stronger in hazard consistency, a surrogate of the similarity of survival rates within subgroups of each defined stage. We further identified fibronectin 1 (FN1) as a key ECM signaling protein within PDAC tumors, both in myCAF autocrine signaling as well as between myCAFs and ductal epithelial cells (including tumor cells), that are enriched in both basal (TMI-Poor) and nonbasal, myCAF-enriched (TMI-Intermediate) cases, and that delineate a poorer prognosis. The integration of tumor subtyping and stromal myCAF fractions with clinical staging improves prognostication in PDAC. Among the ECM signaling proteins, FN1 shows promise in explaining the relationship between basal subtypes and myCAF-enrichment, with poor prognosis.

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