Assessment of colorectal cancer molecular features along bowel subsites challenges the conception of distinct dichotomy of proximal versus distal colorectum
Bibliographic record
Abstract
OBJECTIVE: Colorectal cancer is typically classified into proximal colon, distal colon and rectal cancer. Tumour genetic and epigenetic features differ by tumour location. Considering a possible role of bowel contents (including microbiome) in carcinogenesis, this study hypothesised that tumour molecular features might gradually change along bowel subsites, rather than change abruptly at splenic flexure. DESIGN: Utilising 1443 colorectal cancers in two US nationwide prospective cohort studies, the frequencies of molecular features (CpG island methylator phenotype (CIMP), microsatellite instability (MSI), LINE-1 methylation and BRAF, KRAS and PIK3CA mutations) were examined along bowel subsites (rectum, rectosigmoid junction, sigmoid, descending colon, splenic flexure, transverse colon, hepatic flexure, ascending colon and caecum). The linearity and non-linearity of molecular relations along subsites were statistically tested by multivariate logistic or linear regression analysis. RESULTS: The frequencies of CIMP-high, MSI-high and BRAF mutations gradually increased from the rectum (<2.3%) to ascending colon (36-40%), followed by falls in the caecum (12-22%). By linearity tests, these molecular relations were significantly linear from rectum to ascending colon (p<0.0001), and there was little evidence of non-linearity (p>0.09). Caecal cancers exhibited the highest frequency of KRAS mutations (52% vs 27-35% in other sites; p<0.0001). CONCLUSIONS: The frequencies of CIMP-high, MSI-high and BRAF mutations in cancer increased gradually along colorectum subsites from the rectum to ascending colon. These novel data challenge the common conception of discrete molecular features of proximal versus distal colorectal cancers, and have a substantial impact on clinical, translational and epidemiology research, which has typically been performed with the dichotomous classification of proximal versus distal tumours.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".