Common mitochondrial polymorphisms as risk factor for endometrial cancer
Bibliographic record
Abstract
Endometrial carcinoma is the most commonly diagnosed gynaecological cancer in developed countries. Although the molecular genetics of this disease has been in the focus of many research laboratories for the last 20 years, relevant prognostic and diagnostic markers are still missing. At the same time mitochondrial DNA mutations have been reported in many types of cancer during the last two decades. It is therefore very likely that the mitochondrial genotype is one of the cancer susceptibility factors. To investigate the presence of mtDNA somatic mutations and distribution of inherited polymorphisms in endometrial adenocarcinoma patients we analyzed the D-loop sequence of cancer samples and their corresponding normal tissues and moreover performed mitochondrial haplogroup analysis. We detected 2 somatic mutation and increased incidence of mtDNA polymorphisms, in particular 16223C (80% patients, p = 0.005), 16126C (23%, p = 0.025) and 207A (19%, p = 0.027). Subsequent statistical analysis revealed that endometrial carcinoma population haplogroup distribution differs from the Polish population and that haplogroup H (with its defining polymorphism - C7028T) is strongly underrepresented (p = 0.003), therefore might be a cancer-protective factor. Our report supports the notion that mtDNA polymorphisms establish a specific genetic background for endometrial adenocarcinoma development and that mtDNA analysis may result in the development of new molecular tool for cancer detection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".