AZD2811 plus venetoclax combination in DLBCL. A, Combo Emax versus HSA in 25 B-cell NHL cell lines including 11 DLBCL cell lines. Cell lines with high combination activity (combo Emax > 0.5 and HSA > 0.1) are in red. B, Growth inhibition and HSA excess matrices in DLBCL cell line WSUDLCL2. C, Western blot analysis for cleaved PARP in WSUDLCL2 cells treated with AZD2811 or venetoclax alone or in combination. D, Matrix plots indicating combination activity (measured by growth inhibition) in WSUDLCL2 cells pretreated with pan caspase inhibitor Q-VD-OPH and exposed to AZD2811 combined with venetoclax for 72 hours. Matrix values represent cell viability normalized to day 0 on the scale of 0 to 200 (value < 100 = percentage of growth inhibition, value > 100 = cell death). E, Tumor growth in WSUDLCL2 xenografts treated with AZD2811 or venetoclax alone or in combination for 46 days (n = 6 per group, * 0.05 < P < 0.01, ** 0.01 < P < 0.001). Data are plotted as mean tumor volume ± SEM. PO, orally; QD, every day; QW, every week.
ARTICLE ABSTRACT
Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific “emergent” biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets.
We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of “emergent” combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses.This article is featured in Selected Articles from This Issue, p. 695
