Activity of the Monocarboxylate Transporter 1 Inhibitor AZD3965 in Small Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE: The monocarboxylate transporter 1 (MCT1) inhibitor, AZD3965, is undergoing phase I evaluation in the United Kingdom. AZD3965 is proposed, via lactate transport modulation, to kill tumor cells reliant on glycolysis. We investigated the therapeutic potential of AZD3965 in small cell lung cancer (SCLC) seeking rationale for clinical testing in this disease and putative predictive biomarkers for trial use. EXPERIMENTAL DESIGN: AZD3965 sensitivity was determined for seven SCLC cell lines, in normoxia and hypoxia, and for a tumor xenograft model. Proof of mechanism was sought via changes in intracellular/tumor lactate. Expression of MCT1 and related transporter MCT4 was assessed by Western blot analysis. Drug resistance was investigated via MCT4 siRNAi and overexpression. The expression and clinical significance of MCT1 and MCT4 were explored in a tissue microarray (TMA) from 78 patients with SCLC. RESULTS: AZD3965 sensitivity varied in vitro and was highest in hypoxia. Resistance in hypoxia was associated with increased MCT4 expression. In vivo, AZD3965 reduced tumor growth and increased intratumor lactate. In the TMA, high MCT1 expression was associated with worse prognosis (P = 0.014). MCT1 and hypoxia marker CA IX expression in the absence of MCT4 was observed in 21% of SCLC tumors. CONCLUSIONS: This study provides a rationale to test AZD3965 in patients with SCLC. Our results suggest that patients with tumors expressing MCT1 and lacking in MCT4 are most likely to respond.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".