학술논문

Prognostic and Predictive Blood-Based Biomarkers in Patients with Advanced Pancreatic Cancer: Results from CALGB80303 (Alliance)
Document Type
article
Source
Clinical Cancer Research. 19(24)
Subject
Digestive Diseases
Clinical Research
Pancreatic Cancer
Rare Diseases
Cancer
4.1 Discovery and preclinical testing of markers and technologies
Detection
screening and diagnosis
Adult
Aged
Aged
80 and over
Antibodies
Monoclonal
Humanized
Bevacizumab
Biomarkers
Tumor
Chemokine CXCL12
Clinical Trials
Phase III as Topic
Deoxycytidine
Female
Humans
Kaplan-Meier Estimate
Male
Middle Aged
Neoplasm Staging
Pancreatic Neoplasms
Prognosis
Proportional Hazards Models
Vascular Endothelial Growth Factor D
Vesicular Transport Proteins
Gemcitabine
Alliance for Clinical Trials In Oncology
Oncology and Carcinogenesis
Oncology & Carcinogenesis
Language
Abstract
PurposeCALGB80303 was a phase III trial of 602 patients with locally advanced or metastatic pancreatic cancer comparing gemcitabine/bevacizumab versus gemcitabine/placebo. The study found no benefit in any outcome from the addition of bevacizumab to gemcitabine. Blood samples were collected and multiple angiogenic factors were evaluated and then correlated with clinical outcome in general (prognostic markers) and with benefit specifically from bevacizumab treatment (predictive markers).Experimental designPlasma samples were analyzed via a novel multiplex ELISA platform for 31 factors related to tumor growth, angiogenesis, and inflammation. Baseline values for these factors were correlated with overall survival (OS) using univariate Cox proportional hazard regression models and multivariable Cox regression models with leave-one-out cross validation. Predictive markers were identified using a treatment by marker interaction term in the Cox model.ResultsBaseline plasma was available from 328 patients. Univariate prognostic markers for OS were identified including: Ang2, CRP, ICAM-1, IGFBP-1, TSP-2 (all P < 0.001). These prognostic factors were found to be highly significant, even after adjustment for known clinical factors. Additional modeling approaches yielded prognostic signatures from multivariable Cox regression. The gemcitabine/bevacizumab signature consisted of IGFBP-1, interleukin-6, PDGF-AA, PDGF-BB, TSP-2; whereas the gemcitabine/placebo signature consisted of CRP, IGFBP-1, PAI-1, PDGF-AA, P-selectin (both P < 0.0001). Finally, three potential predictive markers of bevacizumab efficacy were identified: VEGF-D (P < 0.01), SDF1 (P < 0.05), and Ang2 (P < 0.05).ConclusionThis study identified strong prognostic markers for pancreatic cancer patients. Predictive marker analysis indicated that plasma levels of VEGF-D, Ang2, and SDF1 significantly predicted for benefit or lack of benefit from bevacizumab in this population.