Abstract Background: B-cell lymphomas display heterogeneous responses to kinase inhibitors, reflecting underlying variability in kinase activity and signaling network states. Understanding how baseline kinase activity and broader signaling network patterns relate to drug sensitivity could improve therapeutic stratification and uncover mechanisms of drug response. Methods: Drug sensitivity data (IC50 values) for B-cell lymphoma cell lines were retrieved from the CancerRxGene database (Genomics of Drug Sensitivity in Cancer) and response variability for small-molecule inhibitors targeting serine/threonine kinase (STK) families was quantified using the standard deviation of its LN(IC50) values across cell lines. For 11 B-cell lymphoma cell lines, kinase activity profiling was performed using KinomePro platform (PamGene International B.V.) and Upstream Kinase Analysis was used to predict kinases from the phosphorylation signatures. We conducted Multi-Omics Factor Analysis (MOFA) to integrate phosphorylation signatures and drug sensitivity data, identifying latent factors that capture correlations between kinases and drug responses. Results: Drug responses showed substantial heterogeneity across cell lines: 7% of drugs were homogeneous (LN(IC50) SD 0.5), 41% moderately heterogeneous (SD 0.5-1), and 52% heterogeneous (SD 1). In cell lines where drug sensitivity was observed, only 10-30% showed elevated activity of the drug target kinase, and this correlation was not statistically significant. Correlation analysis (MOFA) identified latent factors that mapped kinase activity to drug sensitivity and revealed two distinct sensitivity clusters: one comprising PI3K/AKT/mTOR, central to cell growth, survival, metabolism, and proliferation; and a second cluster including CDK, ATM/ATR, Wee1, AURKA, and MAPK, central to DNA damage response, cell cycle regulation and checkpoint signaling. Upstream Kinase Analysis validated that cell lines sensitive to AKT/PI3K/mTOR inhibitors exhibited relatively high AKT and RSK signaling activity, whereas cell lines sensitive to inhibitors targeting cell cycle pathway showed higher baseline CDK and MAPK family kinases. Conclusions: Our integrative analysis of drug sensitivity and kinase-activity data demonstrates that B-cell lymphoma response is shaped not only by individual kinase activities but also by the architecture of signaling networks. The strong concordance between baseline kinase activity signatures and drug sensitivity highlights network-level determinants of response. Signal-network signatures associated with sensitivity may serve as biomarkers for stratification and provide mechanistic insight into heterogeneous drug responses. These findings lay a foundation for functional validation and the development of combination therapies guided by network-level dependencies. Citation Format: Simar Pal Singh, Laken Woods, Robin Keijzers, Gitanjali Dharmadhikari, Dóra Schuller, Rik de Wijn. Network-level kinase activity associate with differential drug sensitivity in B-Cell lymphoma cell lines abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5766.
Singh et al. (Fri,) studied this question.