Dual role of <i>TGFBR1 </i>as a modifier of colorectal cancer risk.
Bibliographic record
Abstract
600 Background: Experimental and clinical evidence suggests that constitutively decreased Transforming Growth Factor Beta type I receptor (TGFBR1) signaling predisposes to colorectal cancer (CRC) development. However, associations between TGFBR1 variants and CRC risk in case-control studies have been inconsistent. Methods: We utilized 1,043 CRC cases and their 1,627 unaffected sibling controls obtained from the Colon Cancer Family Registry (C-CFR). Individuals were genotyped for twelve TGFBR1 haplotype tagging SNPs. SNPs associated with CRC risk were validated in 261 CRC cases and 531 controls of African American ancestry and 990 CRC cases and 3,427 controls of Han Chinese ancestry. Validated SNPs were functionally characterized with respect to TGFBR1 expression and TGF-β signaling. Results: The TGFBR1 rs7034462-TT genotype was associated with CRC risk in C-CFR participants (OR 3.80[1.46-9.85]) and African Americans (OR 8.16[2.07-32.08]) (see Table). The TT genotype was associated with stage III and stage IV at diagnosis in C-CFR participants (OR 2.99[1.15-7.81] and OR 9.38[1.54-57.28]) and African Americans (OR 5.89[1.15-30.02] and OR 12.75[1.88-86.33]), respectively. The rs7034462-CT genotype was associated with decreased risk for CRC in African Americans (OR 0.55[0.31-0.99]) and Han Chinese (OR 0.67[0.48-0.95]) (see table). Cells carrying the rs7034462-TT genotype exhibited decreased constitutive TGFBR1 expression, increased SMAD7 expression, and decreased TGF-β signaling. Conclusions: The TGFBR1 rs7034462-T allele has dual, opposite roles with respect to CRC risk. The rare rs7034462-TT genotype is a moderate penetrance genotype associated with risk for CRC and advanced stage disease at diagnosis. In contrast, the common rs7034462-CT genotype is associated with decreased CRC risk. [Table: see text]
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".