Reduced mitochondrial DNA copy number is correlated with tumor progression and prognosis in Chinese breast cancer patients
Bibliographic record
Abstract
Somatic mutations and large-scale depletion in mitochondrial DNA (mtDNA) have been extensively detected in various human cancers. However, it still remains unclear whether the alterations in mtDNA content are related to the clinicopathological parameters and patient prognosis in breast cancer. In the present study, we analyzed the copy number of mtDNA in 59 cases of invasive breast tumors and paired nontumorous tissues using quantitative real-time PCR. Our data showed that the level of mtDNA was significantly decreased in tumor tissues as compared to the adjacent nontumorous counterparts (P = 0.001). The reduced copy number in mtDNA was associated with an older onset age (>or=50 years old, P = 0.035) as well as a higher histological grade (P = 0.012). Survival analysis measured by the Kaplan-Meier curves and the log-rank test indicated that patients with reduced mtDNA content had significantly poorer disease-free survival (DFS, P = 0.0079) and overall survival (OS, P = 0.011) rate. In addition, tumors harboring mutations in displacement (D)-loop region, particularly at the polycytidine stretch (T/N ratio = 64.3 +/- 8.2%) or close to the replication origins of the heavy-strand (T/N ratio = 68.7 +/- 5.5%), had a significantly lower copy number of mtDNA than the ones without D-loop alterations. Together, our results suggested that reduced copy number of mtDNA may be involved in breast neoplastic transformation or progression and mtDNA content might be potentially used as a tool to predict prognosis. Somatic mutation in the D-loop region probably is one of key contributing factors leading to decreased mtDNA level in breast tumors.
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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 | 0.001 |
| 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) | 0.001 | 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".