Family history and molecular features of children, adolescents, and young adults with colorectal carcinoma
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer is extremely rare in childhood. Published case series reporting children and adolescents with colorectal cancer have not focused on the underlying genetic aspects of the tumour or genetic susceptibility of the families. AIMS: We examined a cohort of patients with early onset colorectal cancer to determine whether a specific genetic predisposition could be elucidated. In particular, we focused on whether DNA mismatch repair gene deficiency which causes hereditary non-polyposis colorectal cancer (HNPCC) could be elucidated. METHODS: Patients with colorectal cancer </=24 years of age were identified from a database at the Familial Gastrointestinal Cancer Registry at Mount Sinai Hospital, Toronto. Detailed pedigrees were ascertained from the proband or parents. Tumours were tested for microsatellite instability, a hallmark of HNPCC. Germline mismatch repair gene mutations (MSH2 and MLH1) were sought in some cases. Clinical data were obtained by chart audit. RESULTS: Among 1382 probands in our registry, 16 (1%) colorectal cancer patients were 24 years or younger at the time of diagnosis. Microsatellite instability was identified in tumours from eight (73%) of 11 evaluated patients. Germline mutations in mismatch repair genes were identified in six of 12 patients, including MSH2 (n = 3), MLH1 (n = 2), and PMS2 (n = 1). Ten (63%) of 16 families met the Amsterdam criteria for HNPCC. Among these, six were screened for mismatch repair gene mutations and three were found to carry MSH2 or MLH1 germline mutations. Location of the colorectal cancers included rectum/sigmoid (n = 9), splenic flexure (n = 2), hepatic flexure (n = 3), and caecum (n = 2). Forty four per cent (7/16) of these young cases developed additional malignancies (gastrointestinal (n = 8) and extraintestinal (n = 4)) during follow up (mean 12.8 (SD 12.4) years (range 0.08-30)). CONCLUSIONS: Patients with early onset colorectal carcinoma often have an inherited predisposition to the disease. Tumours with high frequency microsatellite instability and germline mutations of mismatch repair genes are sufficiently common in this patient population that they should be considered, even though family histories may not satisfy the stringent Amsterdam criteria for HNPCC. Young colorectal cancer patients are at increased risk of developing second gastrointestinal and extraintestinal malignancies.
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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".