A Novel Biomarker Panel Examining Response to Gemcitabine with or without Erlotinib for Pancreatic Cancer Therapy in NCIC Clinical Trials Group PA.3
Bibliographic record
Abstract
PURPOSE: NCIC Clinical Trials Group PA.3 was a randomized control trial that demonstrated improved overall survival (OS) in patients receiving erlotinib in addition to gemcitabine for locally advanced or metastatic pancreatic cancer. Prior to therapy, patients had plasma samples drawn for future study. We sought to identify biomarkers within these samples. EXPERIMENTAL DESIGN: Using the proximity ligation assay (PLA), a probe panel was built from commercially available antibodies for 35 key proteins selected from a global genetic analysis of pancreatic cancers, and used to quantify protein levels in 20 uL of patient plasma. To determine if any of these proteins levels independently associated with OS, univariate and mulitbaraible Cox models were used. In addition, we examined the associations between biomarker expression and disease stage at diagnosis using Fisher's exact test. The correlation between Erlotinib sensitivity and each biomarkers was assessed using a test of interaction between treatment and biomarker. RESULTS AND CONCLUSION: Of the 569 eligible patients, 480 had samples available for study. Samples were randomly allocated into training (251) and validation sets (229). Among all patients, elevated levels of interleukin-8 (IL-8), carcinoembryonic antigen (CEA), hypoxia-inducible factor 1-alpha (HIF-1 alpha), and interleukin-6 were independently associated with lower OS, while IL-8, CEA, platelet-derived growth factor receptor alpha and mucin-1 were associated with metastatic disease. Patients with elevated levels of receptor tyrosine-protein kinase erbB-2 (HER2) expression had improved OS when treated with erlotinib compared to placebo. In conclusion, PLA is a powerful tool for identifying biomarkers from archived, small volume serum samples. These data may be useful to stratify patient outcomes regardless of therapeutic intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT00040183.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".