NUDT7 Loss Promotes KrasG12D CRC Development
Bibliographic record
Abstract
Studies have suggested that dysregulation of peroxisomal lipid metabolism might play an important role in colorectal cancer (CRC) development. Here, we found that KrasG12D-driven CRC tumors demonstrate dysfunctional peroxisomal β-oxidation and identified Nudt7 (peroxisomal coenzyme A diphosphatase NUDT7) as one of responsible peroxisomal genes. In KrasG12D-driven CRC tumors, the expression level of Nudt7 was significantly decreased. Treatment of azoxymethane/dextran sulfate sodium (AOM/DSS) into Nudt7 knockout (Nudt7−/−) mice significantly induced lipid accumulation and the expression levels of CRC-related genes whereas xenografting of Nudt7-overexpressed LS-174T cells into mice significantly reduced lipid accumulation and the expression levels of CRC-related genes. Ingenuity pathway analysis of microarray using the colon of Nudt7−/− and Nudt7+/+ mice treated with AOM/DSS suggested Wnt signaling as one of activated signaling pathways in Nudt7−/− colons. Upregulated levels of β-catenin were observed in the colons of KrasG12D and AOM/DSS-treated Nudt7−/− mice and downstream targets of β-catenin such as Myc, Ccdn1, and Nos2, were also significantly increased in the colon of Nudt7−/− mice. We observed an increased level of palmitic acid in the colon of Nudt7−/− mice and attachment of palmitic acid-conjugated chitosan patch into the colon of mice induced the expression levels of β-catenin and CRC-related genes. Overall, our data reveal a novel role for peroxisomal NUDT7 in KrasG12D-driven CRC development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".