MMS19 as a potential predictive marker of adjuvant chemotherapy benefit in resected non-small cell lung cancer
Bibliographic record
Abstract
BACKGROUND: Resectable non-small cell lung cancer (NSCLC) treatment options most often consist of surgical resection along with adjuvant chemotherapy (ACT). The benefit of ACT however is modest and is accompanied by important side effects. OBJECTIVE: One central quest in the field is therefore the identification of a predictive marker of the response to ACT. METHODS: We applied an unbiased approach based on high content analysis of expression data generated from a discovery patient cohort. RESULTS: We identified MMS19, a component of the cytoplasmic Iron-Sulfur Assembly (CIA) machinery important for the Nucleotide Excision Repair (NER) pathway as a pivotal gene for cisplatin toxicity. We then confirmed the association between MMS19 expression and the response to Cisplatin treatment in a panel of NSCLC cell lines. Finally we validated these pre-clinical data in a subgroup of JBR.10 trial patients through a hypothesis-driven analysis, and showed that MMS19 levels associated with ACT benefit. CONCLUSIONS: We therefore propose the expression level of MMS19 as a candidate predictive marker of ACT benefit in resected NSCLC 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 | 0.001 |
| 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) | 0.002 | 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".