INHIBITION OF DAPK3, PINPOINTED AS A KEY FACTOR IN THE DEVELOPMENT OF COLITIS-ASSOCIATED DYSPLASIA, INCREASES SEVERITY OF DSS-INDUCED COLITIS VIA HIPPO SIGNALING
Bibliographic record
Abstract
Abstract Introduction Ulcerative colitis (UC) is a progressive disorder that elevates the risk of cancer development through a colitis-dysplasia-carcinoma sequence. Recent evidence demonstrates the necessity of Hippo-YAP/TAZ signaling, interceded by cytoskeletal remodeling, for intestinal regeneration. Death-associated protein kinase 3 (DAPK3) is a regulator of actin-cytoskeleton reorganization that controls proliferation and apoptosis. We first identified DAPK3 as a candidate gene involved in UC progression, and then examined if inhibition of DAPK3 would increase the severity of colitis. Methods Data series GSE47908 [1] comprising microarray expression profile of biopsies from left colon of healthy controls and UC patients with left-sided colitis, pancolitis, or UC-associated dysplasia was retrieved from Gene Expression Omnibus. Differentially expressed genes (DEGs) were analyzed using Ingenuity Pathway Analysis software and topGO R. C57BL/6 mice receiving 2.5% (wt./vol.) DSS or water (7 days) were treated daily s.c. with the DAPK3 pharmacological inhibitor HS38 [2] or vehicle for 12 days (pretreatment: 3 days, recovery: 2 days). Colitis was assessed by disease activity index and histopathology. Intestinal epithelial cell (IEC) proliferation was enumerated via Ki-67 immunohistochemistry (IHC). DAPK3 and YAP abundances were evaluated by immunoblot, and YAP subcellular localization was assessed by IHC. Results topGO analysis showed enrichment of inflammatory processes in pancolitis Π left-side colitis DEGs and enrichment of actin-based processes in pancolitis Π dysplasia DEGs. Pathway analysis revealed trend of Hippo signaling activation as UC progressed from left-side to pancolitis to UC-associated dysplasia. Network analysis implicated DAPK3 as a key factor in colitis-dysplasia progression. Mice treated with DSS showed decreased colonic DAPK3 abundance. Mice co-treated with DSS/HS38 showed significantly increased histological score, and decreased IEC proliferation in comparison with DSS/vehicle controls. Moreover, H2O/HS38 treated mice showed increased colonic YAP abundance versus H2O/vehicle controls while DSS/HS38 co-treatment elicited nuclear accumulation of YAP in IECs localized at the crypt apex. Conclusion DAPK3 is a key factor in intestinal regeneration and UC progression by way of Hippo-YAP signaling. This is potentially arbitrated by DAPK3-dependent reorganization of actin cytoskeleton and focal adhesion dynamics. References: 1. Bjerrum, Jacob T et al. “Transcriptional analysis of left-sided colitis, pancolitis, and ulcerative colitis-associated dysplasia.” Inflamm Bowel Dis vol. 20,12 (2014): 2340–52. [2] Carlson, David A et al. “Fluorescence linked enzyme chemoproteomic strategy for discovery of a potent and selective DAPK1 and ZIPK inhibitor.” ACS Chem Biol vol. 8,12 (2013): 2715–23. Funding Agencies Canadian Institutes of Health Research. Identification of DAPK3 as a potential key factor in UC progression. (A) Networks were constructed for each colitis subtypes based on known molecular interactions of DEGs: Black octagons are networks constructed with dysplasia DEGs, grey hexagons are pancolitis networks, and white rectangles are left-side colitis networks. Shape size represents the relative number of DEGs used to build said network. The networks are connected to one another if there are any overlapping molecules. Line width represent the number of shared molecules. By focusing on networks that had >85% of DEG inputs and keeping edges that involved >5% overlap of common molecules, we arrived at the core network of networks (B) that was heavily leveraged on the edge connecting dysplasia network 1 and pancolitis network 15 (C). One kinase (DAPK3) was identified at this intersection, whose inhibition was test in an animal model of colitis (D).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".