The functional genetic variant Arg324Gly of frizzled-related protein is associated with colorectal cancer risk
Bibliographic record
Abstract
The Wnt-beta-catenin pathway plays a central role in colorectal tumorigenesis. Frizzled-related protein (FRZB, also termed secreted frizzled-related protein 3, sFRP3) antagonizes the signaling of wingless (Wnt) ligands through the frizzled membrane-bound receptors, resulting in beta-catenin destabilization thereby suppressing the expression of target genes. Recently, the FRZB Gly324 variant has been shown to have an attenuated ability to antagonize Wnt signaling and to be associated with an increased osteoarthritis risk. Here, we investigated, for the first time, the role of Arg324Gly (970C>G) along with Arg200Trp (598C>T) on colorectal cancer (CRC) risk by analyzing 659 patients and 607 control individuals drawn from the German DACHS (Darmkrebs: Chancen der Verhütung durch Screening) study. Although Arg200Trp showed no effect on CRC risk, we found homozygous carriers of Gly324 more frequent in cases than in controls, leading to a significantly increased risk for CRC [odds ratio (OR) = 5.1, 95% confidence interval (95% CI) = 1.74-14.71, P < 0.001]. The association was stronger in rectal cancer (OR = 7.52, 95% CI = 2.40-23.25, P < 0.0001) than in colon cancer (OR = 3.66, 95% CI = 1.14-11.76, P < 0.05). Since modified Wnt signaling and down-regulation of frizzled-related proteins have been observed in many human cancers, this variant may also affect the susceptibility to other cancers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| 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".