ArticleGut2026
Stromal biomarker-based framework for identifying pMMR/MSS and dMMR/MSI colorectal cancers with poor outcomes and limited benefit from immunotherapy.
Article in Gut, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Biomarkers and future directions for immunotherapy in microsatellite-stable colorectal cancer: a systematic review.Molecular biology reports · 2026Pooled it
- Lactate as a Master Regulator of Immune Suppression: From Metabolic Waste to Epigenetic Checkpoint in Colorectal Cancer.International journal of molecular sciences · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer (CRC) remains a leading cause of cancer mortality worldwide, with clinical progress limited by intratumoural cellular diversity and the absence of robust, informative markers.
objectiveLeveraging the heterogeneity of cancer-associated fibroblasts (CAFs) within the tumour microenvironment, this study aims to identify and evaluate candidate biomarkers to support patient stratification and improve prediction of therapeutic responses.
designWe applied a multiomic approach integrating single-cell RNA sequencing, computational cell deconvolution and protein-level assessment from patient tumours, complemented by in vitro and in vivo preclinical models, to characterise stromal populations linked to CRC progression and treatment resistance.
resultsRetrospective analysis of over 3000 patient samples across multiple cohorts identified a distinct subset of CAFs expressing collagen triple helix repeat containing 1 (CTHRC1). CTHRC1(+) CAFs were associated with increased transforming growth factor-beta (TGF-beta) signalling and poor clinical outcomes in early and advanced disease stages. CTHRC1(+) CAFs enabled stratification of both mismatch repair-deficient/microsatellite instability (dMMR/MSI) and mismatch repair-proficient/microsatellite stability (pMMR/MSS) tumours into immune-inflamed and poorly immunogenic subtypes. Retrospective analysis of several clinical trials revealed that CTHRC1(+) CAFs are linked to resistance to immune checkpoint inhibitors in MSI and MSS tumours, suggesting therapeutic potential for combining TGF-beta blockade with immunotherapy.
conclusionCTHRC1-expressing CAFs represent clinically relevant biomarkers that link molecular profiling with diagnostic pathology. Our findings support the potential incorporation of CTHRC1(+) CAF assessment into routine histopathological workflows, pending prospective validation, and suggest a framework for stroma-informed CRC stratification, particularly in patients with stroma-rich, treatment-resistant tumours and pMMR/MSS with limited therapeutic options.
Indexed as
Identifiers
41980760What OpenQuestion holds
Registered trials
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 OpenQuestion graph.