Authors' Affiliations: Division of Medical Oncology; Alliance Statistics and Data Center, Duke University Medical Center; Durham, North Carolina; Section of Hematology/Oncology, University of Chicago Cancer Research Center; Chicago, Illinois; Department of Surgery, Brigham and Women's Hospital & Harvard Medical School; Boston, Massachusetts; Department of Internal Medicine, Ohio State University; Columbus, Ohio; and Division of Medical Oncology, University of California, San Francisco, California.
Clin Cancer Res. 2013 Dec 15;19(24):6957-66. doi: 10.1158/1078-0432.CCR-13-0926. Epub 2013 Oct 4.
CALGB80303 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).
Plasma 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.
Baseline 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).
This 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.
CALGB80303 是一项针对 602 例局部晚期或转移性胰腺癌患者的 III 期临床试验，比较了吉西他滨/贝伐单抗与吉西他滨/安慰剂。研究发现，贝伐单抗联合吉西他滨并不能改善任何结局。采集血样并评估了多种血管生成因子，然后将其与总体临床结局（预后标志物）以及贝伐单抗治疗的具体获益（预测标志物）相关联。
通过一种新颖的多指标 ELISA 平台，对与肿瘤生长、血管生成和炎症相关的 31 种因子的血浆样本进行分析。使用单变量 Cox 比例风险回归模型和具有留一交叉验证的多变量 Cox 回归模型，根据无进展生存期（OS）对这些因素的基线值进行相关性分析。使用 Cox 模型中的治疗与标志物相互作用项确定预测标志物。
328 例患者可获得基线血浆。确定了与 OS 相关的单变量预后标志物，包括：Ang2、CRP、ICAM-1、IGFBP-1、TSP-2（均 P < 0.001）。即使在调整了已知临床因素后，这些预后因素仍具有高度显著性。通过多变量 Cox 回归进一步建立了预后模型。吉西他滨/贝伐单抗标志物签名包括 IGFBP-1、白细胞介素 6、PDGF-AA、PDGF-BB、TSP-2；而吉西他滨/安慰剂标志物签名包括 CRP、IGFBP-1、PAI-1、PDGF-AA、P-选择素（均 P < 0.0001）。最后，确定了 3 种贝伐单抗疗效的潜在预测标志物：VEGF-D（P < 0.01）、SDF1（P < 0.05）和 Ang2（P < 0.05）。
本研究确定了胰腺癌患者的强有力的预后标志物。预测标志物分析表明，VEGF-D、Ang2 和 SDF1 的血浆水平显著预测了该人群中贝伐单抗的获益或无获益。
