Mitochondrial D310 mutations in the early development of breast cancer
Bibliographic record
Abstract
BACKGROUND: The role of mitochondrial DNA (mtDNA) mutations in the development of breast cancer is largely unknown. In this study, we investigated the frequency and pattern of mutations in the D310 region, the most commonly mutated region in mtDNA, in a series of breast lesions. METHODS: Using capillary electrophoresis, we genotyped the D310 sequence of neoplastic epithelial cells from 23 patients with synchronous ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), 26 patients with IDC only and 29 patients with DCIS only. RESULTS: A majority of DCIS (68.4%) and IDC (71.4%) lesions harbour different D310 sequences compared with their matched normal control. Specific D310 sequences were more frequently identified in tumour samples (77.1% of DCIS and 75.5% of IDC) compared with normal tissues (35.3% of normal; P<0.0001). No difference was identified between DCIS lesions with synchronous IDC and those from pure DCIS cases. In five cases, histologically normal tissue adjacent to tumour was found to share D310 sequences with the tumour, while normal tissue taken further away did not. CONCLUSION: Although D310 alterations do not seem to be related to DCIS progression, they were found in histologically normal cells adjacent to tumour. This suggests a field of genetically altered cells, thus D310 mutations could represent a potential marker for the clonal expansion of premalignant breast cancer cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".