MiR-193b-3p and miR-132-3p as prognostic biomarkers of survival in pleural mesothelioma patients treated with first-line bevacizumab plus pemetrexed-platinum chemotherapy in the IFCT-0701 MAPS phase 3 trial
Bibliographic record
Abstract
We investigated whether angiogenesis-related microRNAs (miRNAs) predict survival in patients with pleural mesothelioma (PM) treated with bevacizumab plus pemetrexed-platinum chemotherapy in the Mesothelioma Avastin Cisplatin Pemetrexed Study ('MAPS', NCT00651456) phase 3 trial phase III trial (NCT00651456). Twelve miRNAs were measured in FFPE samples from 236 of the 448 MAPS trial patients (50.8 %), normalized to RNU48. Overall survival (OS) and progression-free survival (PFS) were analyzed by miRNA expression using univariate and multivariate models adjusted for clinical covariates. Internal validation was performed by bootstrapping. Interaction tests assessed the predictive value of each miRNA with respect to treatment arm. Low miR-193b-3p expression was associated with longer OS in PM patients, as shown in both univariate and multivariate analyses (adjusted HR = 0.87 [0.81-0.93], p < 0.001; bootstrap inclusion fraction [BIF]: 81.3 %), with both treatment arms analyzed together. It also predicted longer PFS (adjusted HR = 0.91 [0.85-0.97], p = 0.0042). Interaction tests revealed that for four miRNAs (miR-155-5p, miR-29c-5p, miR-132-3p, and miR-100-5p), lower expression levels were associated with greater efficacy of the bevacizumab/cisplatin/pemetrexed combination. Notably, the interaction between treatment arms and miR-132-3p expression was statistically significant (p = 0.004). In the IFCT-GFPC-0701 MAPS trial, low miR-193b-3p expression demonstrated significant independent prognostic value, being associated with longer OS and PFS. Additionally, low expression of miR-155-5p, miR-29c-5p, miR-132-3p, and miR-100-5p showed independent predictive value for improved survival in the bevacizumab plus chemotherapy arm. Thus, a simple qRT-PCR assay of these four miRNAs may help identifying PM patients most likely to benefit from bevacizumab.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".