Abstract 3832: A tissue injury-like state in mouse with BMP signaling impaired Foxl1+ telocytes leads to abnormal ECM biodynamics and neoplasia initiation
Bibliographic record
Abstract
Abstract "Tumors are wounds that do not heal" is an accepted concept where the tumor stroma composition bears a resemblance to the granulation tissue of healing wounds. Most of the solid cancers can be associated with a reorganization of the extracellular matrix (ECM) within the tumor leading to fibrosis and increased tissue stiffness, contributing to disease malignancy. Colorectal cancer (CRC) makes no exception to this microenvironment reorganization. The colon stroma is home to multiple cell types involved in ECM biodynamics such as the FoxL1+ Telocytes (TCFoxL1+) which form a network underneath the epithelium, contributing to the microenvironment that supports epithelial and immune cell homeostasis. Our group already showed, in a mouse model of CRC, that BMPR1A signaling deletion in TCFoxL1+ influences the microenvironment via stromagenesis, immune infiltration and colonic dysplasia. However, the precise biomolecular and biomechanical events that contributes to the onset of this state have yet to be identified. We aimed to identify the early-onset dysplastic modulations in ECM biodynamics induced by BmpR1a-deficient TCFoxL1+ (BmpR1aΔFoxL1+) in mouse colonic mucosa. Matrisomics analysis was thus performed to determine the inventory of ECM proteins expressed solely in the GI stroma following tissue deconstruction of control and BmpR1aΔFoxL1+ mice colons. Characterization of the collagen network and matrisome-associated modulations was evaluated by histological and biochemical methods. Presence of bacteria invading the mucosa was studied by Fluorescence In Situ Hybridization (FISH). Matrisome proteins that were differentially regulated indicate an enrichment for proteins involved in collagen network regulation, wound repair homeostasis and immune response. Increased deposition of collagen, presence of thicker fibers realigned into linear patterns were observed in BmpR1aΔFoxL1+ mouse colon, leading to change in tissue stiffness and biomechanics. Abnormal presence of unfolded collagen with a concomitant increase in a collagen-folding chaperone was also observed. Validations of proteins involved in fibrin clot formation as well as immune response mediators such as S100A9 indicate that BmpR1aΔFoxL1+ mice deal with tissue micro-injuries and inflammation that is unresolved, creating an unfavorable microenvironment for tissue homeostasis leading to neoplasia initiation. Taken together, these results suggest that Bmp-signaling deficient TCFoxL1+ significantly contribute to the collagen network biodynamics through increased collagen deposition, fiber alignment reorganization and regulation of the triple-helix assembly. Other matrisome modulations suggest a state of unresolved wound healing due to tissue injury, that could be the etiology of GI pathology such as CRC and lead to more severe conditions upon various environmental triggers. Citation Format: Veronique Pomerleau, Vilcy Reyes Nicolas, Carla-Marie Jurkovic, François-Michel Boisvert, Nathalie Perreault. A tissue injury-like state in mouse with BMP signaling impaired Foxl1+ telocytes leads to abnormal ECM biodynamics and neoplasia initiation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3832.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".