Differences in telomerase activity between colon and rectal cancer
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer is one of the most common cancers and the third leading cause of cancer death in both sexes. The disease progresses as a multistep process and is associated with genetic alterations. One of the characteristic features of cancer is telomerase activation. We sought to evaluate the differences in telomerase activity between colon cancer and adjacent normal tissue and to correlate the differences in telomerase activity between different locations with clinicopathological factors and survival. METHODS: Matched colon tumour samples and adjacent normal mucosa samples 10 cm away from the tumour were collected during colectomy. We assessed telomerase activity using real time polymerase chain reaction. Several pathological characteristics of tumours, including p53, Ki-67, p21, bcl2 and MLH1 expression were also studied. RESULTS: We collected samples from 49 patients. There was a significantly higher telomerase activity in colon cancer tissue than normal tissue. Adenocarcinomas of the right colon express significantly higher telomerase than left-side cancers. Colon cancers and their adjacent normal tissue had significantly more telomerase and were more positive to MLH1 than rectal cancers. The expression of p53 negatively correlated to telomerase activity and was linked to better patient survival. CONCLUSION: Colon and rectal cancers seem to have different telomerase and MLH1 profiles, and this could be another factor for their different biologic and clinical behaviour and progression. These results support the idea that the large bowel cannot be considered a uniform organ, at least in the biology of cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".