Prognostic Implications of microRNA-155, -133a, -21 and -205 in BreastCancer Patients’ Plasma
Bibliographic record
Abstract
BACKGROUND: Breast cancer, being a heterogenous disease at the intra-tumoral and intertumoral levels, presents challenges in following the progress of the disease. Tumour-secreted aberrantly expressed miRNAs obtained from peripheral blood represent a non-invasive alternative resource for detecting and monitoring the development of the disease. This study evaluates the expression of miR-155, miR-133a, miR-21 and miR-205 as non-invasive, prognostic and follow-up markers for breast cancer. METHODS: Plasma expression levels of miR-155, miR-133a, miR-21 and miR-205 were measured using real-time PCR in breast cancer patients (n=63) at presentation, healthy controls (n=25), and in post-treatment samples of 31 patients. A meta-analysis was performed using 43 studies identified from PubMed, Google Scholar and Scopus databases. Hedge's g values were used to calculate the overall effect size. RESULTS: Plasma miR-21 levels were higher in breast cancer patients at presentation compared to controls, while no difference was observed for miR-155, miR-133a and miR-205. These results were further supported by the meta-analysis. The altered levels of miR-155 during tamoxifen treatment indicated a potential role for miR-155 in monitoring treatment response. Further, high expressions of at least three miRNAs correlated with poor overall survival in the breast cancer patients. CONCLUSION: Plasma levels of miR-155, miR-133a, miR-21 and miR-205 may be useful as prognostic and follow-up markers for breast cancer with further validation in a large cohort of patients.
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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) | 0.001 | 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".