ArticleScientific reports2022
Transcriptional dynamics of colorectal cancer risk associated variation at 11q23.1 correlate with tuft cell abundance and marker expression in silico.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Review
- Association between methylation quantitative trait loci and colorectal cancer risk, survival and cancer recurrence.British journal of cancer · 2025Article
- Article
- Integrative Multiomics in the Lung Reveals a Protective Role of Asporin in Pulmonary Arterial Hypertension.Circulation · 2024Article
- Colonic Tuft Cells: The Less-Recognized Therapeutic Targets in Inflammatory Bowel Disease and Colorectal Cancer.International journal of molecular sciences · 2024Review
- Genetic mapping revealsScience immunology · 2023Article
- The critical roles and therapeutic implications of tuft cells in cancer.Frontiers in pharmacology · 2022Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
Colorectal cancer (CRC) is characterised by heritable risk that is not well understood. Heritable, genetic variation at 11q23.1 is associated with increased colorectal cancer (CRC) risk, demonstrating eQTL effects on 3 cis- and 23 trans-eQTL targets. We sought to determine the relationship between 11q23.1 cis- and trans-eQTL target expression and test for potential cell-specificity. scRNAseq from 32,361 healthy colonic epithelial cells was aggregated and subject to weighted gene co-expression network analysis (WGCNA). One module (blue) included 19 trans-eQTL targets and was correlated with POU2AF2 expression only. Following unsupervised clustering of single cells, the expression of 19 trans-eQTL targets was greatest and most variable in cluster number 11, which transcriptionally resembled tuft cells. 14 trans-eQTL targets were found to demarcate this cluster, 11 of which were corroborated in a second dataset. Intra-cluster WGCNA and module preservation analysis then identified twelve 11q23.1 trans-eQTL targets to comprise a network that was specific to cluster 11. Finally, linear modelling and differential abundance testing showed 11q23.1 trans-eQTL target expression was predictive of cluster 11 abundance. Our findings suggest 11q23.1 trans-eQTL targets comprise a POU2AF2-related network that is likely tuft cell-specific and reduced expression of these genes correlates with reduced tuft cell abundance in silico.
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Registered trials
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