Inhibitor of apoptosis protein-1 promotes tumor cell survival in mesothelioma
Bibliographic record
Abstract
Malignant pleural mesothelioma (MPM) is a highly lethal pleural neoplasm that is often resistant to chemotherapeutic drugs, including cisplatin, and for which little is known regarding carcinogenic pathways. We used differential display to compare gene expression patterns in mesothelioma, normal pleura and normal lung, in order to better understand MPM pathobiology, and to search for genes that may facilitate drug resistance in this cancer. The human inhibitor of apoptosis protein-1 gene (IAP-1/MIHC/cIAP2) was discovered to be highly expressed in MPM. We confirmed overexpression of IAP-1 mRNA and protein in 39 additional human MPM tumor specimens and 3/5 (60%) MPM cell lines by multiple methods, including real time quantitative reverse transcription-PCR and western blot analysis. Using an antisense targeting approach, we found that attenuation of IAP-1 mRNA levels decreases baseline cell viability and increases the sensitivity of MPM cell lines to cisplatin by nearly 20-fold. Reduced IAP-1 gene expression also results in a concordant increase of the pro-apoptotic cleavage product of caspase 9 and a reduction in the number of viable tumor cells. Our observations strongly suggest that IAP-1 is at least partly responsible for promoting carcinogenesis and mediating resistance to cisplatin in many MPM tumors and that further study of this apoptotic pathway is warranted.
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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".