Evidence map›Paper›PMID 42033556›Full record

ArticleDiscover oncology2026

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

Samuel Jianjie Yeo, Ian Tate Ek Ern Sim, Hui Yi Tay, David Tai, Ruoyu Shi, Jason Yongsheng Chan

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Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Samuel Jianjie YeoLee Kong Chian School of Medicine, Singapore, Singapore.
Ian Tate Ek Ern SimLee Kong Chian School of Medicine, Singapore, Singapore.
Hui Yi TayCancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore.
David TaiDivision of Medical Oncology, National Cancer Centre Singapore, 30 Hospital Blvd, Singapore, 168583, Singapore.
Ruoyu ShiDepartment of Pathology, National University Hospital, Singapore, Singapore.
Jason Yongsheng ChanCancer Discovery Hub, National Cancer Centre Singapore, Singapore, Singapore. jason.chan.y.s@singhealth.com.sg.

Funding

Duke-NUS Medical School and the "Estate of Tan Sri Khoo Teck Puat" Khoo Bridge Funding Award (Duke-NUS-KBrFA/2025/0090)Singapore Ministry of Health's National Medical Research Council Research Transition Award (TA21jun-0005), Clinician Scientist Individual Research Grant (CIRG25jan-0007), Large Collaborative Grant (OFLCG-23May0039), and TETRAD II Collaborative Centre Grant (CG21APR2002)SingHealth Duke-NUS AM/ACP-Designated Philanthropic Fund Grant Award 08/FY2023/EX/27-A65
6 · The paper itself

Abstract

backgroundPancreatic 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.

methodsWe 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.

resultsTMI 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.

conclusionThe 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.

Indexed as

Cancer-associated fibroblastsCellChatClinical proteomic tumor analysis consortiumFibronectin 1PrognosisRNAseqSingle-cell sequencingThe Cancer Atlas Genome

Identifiers

PMID42033556
PMCPMC13247034

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.