Montero, M.-P. | bioRxiv Science

bioRxiv2022

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

Synergistic drug combinations are an attractive anticancer strategy but prove challenging to identify. Here we present a stepwise approach consisting in revealing core cancer vulnerabilities and exploiting them through drug combination screen to uncover synergistic treatments for glioblastoma patients. MethodsWe established an innovative method, based on high-throughput screening, target deconvolution and functional genomics, to reveal core vulnerabilities in glioblastoma. Combination drug screen targeting these vulnerabilities was then designed to unveil synergistic associations. The therapeutic potential of the top drug combination was validated in two different clinically-relevant models: an organotypic ex vivo model and a syngeneic orthotopic mouse model of glioblastoma. ResultsLarge-scale monotherapy drug screening identified 83 potent anti-glioblastoma compounds. Target deconvolution using public chemoinformatic databases uncovered 1,100 targets and interactors of the hit compounds. Screening of a focused siRNA library targeting the top 292 drug interactors revealed 22 targetable vulnerabilities, 9 of which were confirmed as core glioblastoma vulnerabilities by mining the CRISPR screen cohort data from the online Cancer Dependency Map portal. Six selective inhibitors of the core vulnerabilities were then screened in combination with a custom-made library of 88 compounds and synergies amongst the 528 tested pairwise combinations were predicted. The combinations of CHK1 / MEK and AURKA / BET inhibitors were highlighted and validated in 3D tumor spheroids. Using an organotypic ex vivo model and a syngeneic orthotopic mouse model, we definitively ascertained the efficacy of dual AURKA / BET inhibition in glioblastoma. ConclusionsCollectively, we uncovered that dual inhibition of BET proteins and aurora kinase A is highly synergistic against GBM. Moreover, our study indicates that our approach to exploit drug poly-pharmacology for the rational design of drug combination screens represent a valuable strategy to discover synergistic treatments against refractory cancers.

pharmacology and toxicology↗

bioRxiv2021

Metronomic therapy prevents emergence of drug resistance by maintaining the dynamic of intratumor heterogeneity.

Despite recent advances in deciphering cancer drug resistance mechanisms, relapse is a widely observed phenomenon in advanced cancers, mainly due to intratumor clonal heterogeneity. How tumor clones progress and impact each other remains elusive. By better understanding clone dynamics, we could reveal valuable biological insights and unveil vulnerabilities that could be therapeutically exploited. In this study, we developed 2D and 3D non-small cell lung cancer co-culture systems and defined a phenomenological mathematical model. Our results demonstrated a dominant role of the drug-sensitive clones over the drug-resistant ones under untreated conditions. Model predictions and their experimental in vitro and in vivo validations indicated that metronomic schedule leads to a better regulation of tumor cell heterogeneity over time than maximum-tolerated dose schedule, while achieving control of global tumor progression. We finally showed that drug-sensitive clones exert a suppressive effect on the proliferation of the drug-resistant ones through a paracrine mechanism way, which is linked to metabolic cell clone activity. Altogether, these computational and experimental approaches allow assessment of drug schedules controlling drug-sensitive and -resistant clone balance and highlight the potential of targeting cell metabolism to manage intratumor heterogeneity. SignificanceCombined computational and experimental models reveal how drug-sensitive tumor cells exert their dominance over drug-resistant cells and how it impacts optimal chemotherapy scheduling.

cancer biology↗