Patient-Derived Xenograft Establishment from Human Malignant Pleural Mesothelioma
Bibliographic record
Abstract
Abstract Purpose: Malignant pleural mesothelioma (MPM) is a rare but aggressive disease with few therapeutic options. The tumor–stromal interface is important in MPM, but this is lost in cell lines, the main model used for preclinical studies. We sought to characterize MPM patient-derived xenografts (PDX) to determine their suitability as preclinical models and whether tumors that engraft reflect a more aggressive biological phenotype. Experimental Design: Fresh tumors were harvested from extrapleural pneumonectomy, decortication, or biopsy samples of 50 MPM patients and implanted subcutaneously into immunodeficient mice and serially passaged for up to five generations. We correlated selected mesothelioma biomarkers between PDX and patient tumors, and PDX establishment with the clinical pathologic features of the patients, including their survival. DNA of nine PDXs was profiled using the OncoScan FFPE Express platform. Ten PDXs were treated with cisplatin and pemetrexed. Results: A PDX was formed in 20 of 50 (40%) tumors implanted. Histologically, PDX models closely resembled the parent tumor. PDX models formed despite preoperative chemotherapy and radiotherapy. In multivariable analysis, patients whose tumors formed a PDX had significantly poorer survival when the model was adjusted for preoperative treatment (HR, 2.46; 95% confidence interval, 1.1–5.52; P = 0.028). Among 10 models treated with cisplatin, seven demonstrated growth inhibition. Genomic abnormalities seen in nine PDX models were similar to that previously reported. Conclusions: Patients whose tumors form PDX models have poorer clinical outcomes. MPM PDX tumors closely resemble the genotype and phenotype of parent tumors, making them valuable models for preclinical studies. Clin Cancer Res; 23(4); 1060–7. ©2016 AACR.
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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) | 0.000 | 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) | 0.002 | 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 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".