Inactivation of Interferon Regulatory Factor 1 Causes Susceptibility to Colitis-Associated Colorectal Cancer
Bibliographic record
Abstract
Abstract The mechanisms linking chronic inflammation of the gut (IBD) and increased colorectal cancer susceptibility are poorly understood. IBD risk is influenced by genetic factors, including the IBD5 locus (human 5q31), that harbors the IRF1 gene. A cause-to-effect relationship between chronic inflammation and colorectal cancer, and a possible role of IRF1 were studied in Irf1-/- mice in a model of colitis-associated colorectal cancer (CA-CRC) induced by azoxymethane and dextran sulfate. Loss of Irf1 causes hyper-susceptibility to CA-CRC, with early onset and increased number of tumors leading to rapid lethality. Transcript profiling (RNA-seq) and immunostaining of colons shows heightened inflammation and enhanced enterocyte proliferation in Irf1−/− mutants, prior to appearance of tumors. Considerable infiltration of leukocytes is seen in Irf1−/− colons at this early stage, and is composed primarily of proinflammatory Gr1+ Cd11b+ myeloid cells and other granulocytes, as well as CD4+ lymphoid cells. Differential susceptibility to CA-CRC of Irf1−/− vs. B6 controls is fully transferable through hematopoietic cells as observed in bone marrow chimera studies. Transcript signatures seen in Irf1−/− mice in response to AOM/DSS are enriched in clinical specimens from patients with IBD and with colorectal cancer. In addition, IRF1 expression in the colon is significantly decreased in late stage colorectal cancer (stages 3, 4) and is associated with poorer prognosis. This suggests that partial or complete loss of IRF1 expression alters the type, number, and function of immune cells in situ during chronic inflammation, possibly via the creation of a tumor-promoting environment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".