Optimization of Circulating Biomarkers of Obatoclax-Induced Cell Death in Patients with Small Cell Lung Cancer
Bibliographic record
Abstract
Small cell lung cancer (SCLC) is an aggressive disease in which, after initial sensitivity to platinum/etoposide chemotherapy, patients frequently relapse with drug-resistant disease. Deregulation of the Bcl-2 pathway is implicated in the pathogenesis of SCLC, and early phase studies of Bcl-2 inhibitors have been initiated in SCLC. Obatoclax is a small-molecule drug designed to target the antiapoptotic Bcl-2 family members to a proapoptotic effect. Preclinical studies were conducted to clarify the kinetics of obatoclax-induced apoptosis in a panel of SCLC cell lines to assist with the interpretation of biomarker data generated during early phase clinical trials. In vitro, obatoclax was synergistic with cisplatin and etoposide, and "priming" cells with obatoclax before the cytotoxics maximized tumor cell death. Peak levels of apoptosis, reflected by cleaved cytokeratin 18 (CK18) levels (M30 ELISA) and caspase activity (SR-DEVD-FMK), occurred 24 hours after obatoclax treatment. A phase 1b-2 trial of obatoclax administered using two infusion regimens in combination with carboplatin and etoposide has been completed in previously untreated patients with extensive-stage SCLC. Circulating pharmacodynamic biomarkers of cell death, full-length and/or cleaved CK18, and oligonucleosomal DNA were studied in the phase 1b trial. All SCLC patients classified as "responders" after two cycles of treatment showed significantly increased levels of full-length and cleaved CK18 (M65 ELISA) on day 3 of study. However, the preclinical data and the absence of a peak in circulating caspase-cleaved CK18 in trial patients suggest suboptimal timing of blood sampling, which will need refinement in future trials incorporating obatoclax.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".