Exploring biomarker predictors of response to nintedanib and bevacizumab combination therapy in advanced cancer patients: Correlative studies from Phase 1b study

Background: Bevacizumab and other VEGF inhibitors provide clinical benefit across multiple cancers but are limited by resistance driven largely by revascularization through alternate pro-angiogenic pathways, including PDGFR and FGFR. Nintedanib, a triple kinase inhibitor targeting VEGFR, PDGFR, and FGFR, may overcome these escape mechanisms. The safety and efficacy of nintedanib plus bevacizumab was previously explored in our phase 1B study and published. We are presenting correlative biomarker studies on the plasma samples acquired at prespecified endpoints. Methods: Plasma samples were obtained from patients enrolled in a phase 1 dose-escalation study evaluating nintedanib in combination with bevacizumab for advanced solid tumors (lung n=9, colon n=8, cervical n=1). Baseline plasma biomarkers-including IL-8, ICAM-1, Angiopoietin-2, KDR/VEGFR2, E-selectin, VEGF, and SDF-1alpha-were analyzed and correlated with clinical outcomes. Biomarker quantification was performed using multiplex bead-based immunoassays (Luminex), with select analytes validated by ELISA. Results: Nintedanib 200 mg twice daily was well tolerated with no dose-limiting toxicities. . Among bevacizumab-pretreated patients, 55% achieved durable disease control, including one complete response and four stable diseases. Higher baseline levels of KDR/VEGFR2 and E-selectin and lower SDF-1alpha were associated with improved outcomes. ANOVA identified several biomarkers significantly linked to disease control, including KDR/VEGFR2 (p=0.004), PDGF-AA (p=0.037), and Endoglin (p=0.020). Conclusion: Nintedanib combined with bevacizumab was safe, well tolerated, and demonstrated meaningful clinical activity in heavily pretreated patients. Baseline KDR/VEGFR2, E-selectin, and SDF-1alpha emerged as potential predictive biomarkers. These data support further validation in larger cohort as a strategy to refine biomarker-driven patient selection for treatments in lung and colorectal cancers.