Characterizing the Prevalence of Chromosome Instability in Interval Colorectal Cancer
Bibliographic record
Abstract
A substantial proportion of colorectal cancers (CRCs) are interval CRCs (I-CRCs; i.e., CRCs diagnosed soon after a colonoscopy). Chromosomal instability (CIN) is defined as an increase in the rate of which whole chromosomes/large chromosomal fragments are gained or lost and is observed in 85% of non-hereditary CRCs. The contribution of CIN to the etiology of I-CRCs remains unknown. We established a fluorescence in situ hybridization (FISH) approach to characterize CIN by enumerating specific chromosomes and determined the prevalence of numerical CIN in a population-based cohort of I-CRCs and control (sporadic) CRCs. Using the population-based Manitoba Health administrative databases and Manitoba Cancer Registry, we identified an age, sex, and colonic site of CRC matched cohort of I-CRCs and controls and retrieved their archived paraffin-embedded tumor samples. FISH chromosome enumeration probes specifically recognizing the pericentric regions of chromosomes 8, 11, and 17 were first used on cell lines and then CRC tissue microarrays to detect aneusomy, which was then used to calculate a CIN score (CS). The 15th percentile CS for control CRC was used to define CIN phenotype. Mean CSs were similar in the control CRCs and I-CRCs; 82% of I-CRCs exhibited a CIN phenotype, which was similar to that in the control CRCs. This study suggests that CIN is the most prevalent contributor to genomic instability in I-CRCs. Further studies should evaluate CIN and microsatellite instability (MSI) in the same cohort of I-CRCs to corroborate our findings and to further assess concomitant contribution of CIN and MSI to I-CRCs.
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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".