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Treatment scheduling effects on the evolution of drug resistance in heterogeneous cancer cell populations.

ABSTRACT: The effect of scheduling of targeted therapy combinations on drug resistance is underexplored in triple-negative breast cancer (TNBC). TNBC constitutes heterogeneous cancer cell populations the composition of which can change dynamically during treatment resulting in the selection of resistant clones with a fitness advantage. We evaluated crizotinib (ALK/MET inhibitor) and navitoclax (ABT-263; Bcl-2/Bcl-xL inhibitor) combinations in a large design consisting of 696 two-cycle sequential and concomitant treatment regimens with varying treatment dose, duration, and drug holiday length over a 26-day period in MDA-MB-231 TNBC cells and found that patterns of resistance depend on the schedule and sequence in which the drugs are given. Further, we tracked the clonal dynamics and mechanisms of resistance using DNA-integrated barcodes and single-cell RNA sequencing. Our study suggests that longer formats of treatment schedules in vitro screening assays are required to understand the effects of resistance and guide more realistically in vivo and clinical studies.

SUBMITTER: Patwardhan GA

PROVIDER: S-EPMC8154902 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Treatment scheduling effects on the evolution of drug resistance in heterogeneous cancer cell populations.

Patwardhan Gauri A GA Marczyk Michal M Wali Vikram B VB Stern David F DF Pusztai Lajos L Hatzis Christos C

NPJ breast cancer 20210526 1

The effect of scheduling of targeted therapy combinations on drug resistance is underexplored in triple-negative breast cancer (TNBC). TNBC constitutes heterogeneous cancer cell populations the composition of which can change dynamically during treatment resulting in the selection of resistant clones with a fitness advantage. We evaluated crizotinib (ALK/MET inhibitor) and navitoclax (ABT-263; Bcl-2/Bcl-xL inhibitor) combinations in a large design consisting of 696 two-cycle sequential and conco ...[more]

PMID: 34040000

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Project description:Mass drug administration (MDA) with antimalarials has been shown to reduce prevalence and interrupt transmission in small populations, in populations with reliable access to antimalarial drugs, and in populations where sustained improvements in diagnosis and treatment are possible. In addition, when MDA is effective it eliminates both drug-resistant parasites and drug-sensitive parasites, which has the long-term benefit of extending the useful therapeutic life of first-line therapies for all populations, not just the focal population where MDA was carried out. However, in order to plan elimination measures effectively, it is necessary to characterize the conditions under which failed MDA could exacerbate resistance. We use an individual-based stochastic model of Plasmodium falciparum transmission to evaluate this risk for MDA using dihydroartemisinin-piperaquine (DHA-PPQ), in populations where access to antimalarial treatments may not be uniformly high and where re-importation of drug-resistant parasites may be common. We find that artemisinin-resistance evolution at the kelch13 locus can be accelerated by MDA when all three of the following conditions are met: (1) strong genetic bottlenecking that falls short of elimination, (2) re-importation of artemisinin-resistant genotypes, and (3) continued selection pressure during routine case management post-MDA. Accelerated resistance levels are not immediate but follow the rebound of malaria cases post-MDA, if this is allowed to occur. Crucially, resistance is driven by the selection pressure during routine case management post-MDA and not the selection pressure exerted during the MDA itself. Second, we find that increasing treatment coverage post-MDA increases the probability of local elimination in low-transmission regions (prevalence < 2%) in scenarios with both low and high levels of drug-resistance importation. This emphasizes the importance of planning for and supporting high coverage of diagnosis and treatment post-MDA.

Project description:Combinations of metabolic blockers (incl. fenofibrate) with chemotherapeutic drugs interfere with the drug-resistance of prostate cancer cells. However, their effect on cancer stem cells-dependent microevolution of prostate cancer malignancy remains unaddressed. Here, we hypothesize that the combined docetaxel/fenofibrate treatment prompts the selective expansion of cancer stem cells that affects the microevolution of their progenies. Accordingly, we adapted a combined in vitro/in vivo approach to identify biological and therapeutic consequences of this process. Minute subpopulations of docetaxel-resistant CD133high and/or CD44high cancer stem cell-like (SCL) cells were found in prostate cancer DU145 and PC3 cell populations. When pretreated with docetaxel, they readily differentiated into docetaxel-resistant CD44negative "bulk" cells, thus accounting for the microevolution of drug-resistant cell lineages. Combined docetaxel/fenofibrate treatment induced the generation of poly(morpho)nuclear giant cells and drug-resistant CD44high SCL cells. However, the CD44negative offspring of docetaxel- and docetaxel/fenofibrate-treated SCLs remained relatively sensitive to the combined treatment, while retaining enhanced resistance to docetaxel. Long-term propagation of drug-resistant SCL-derived lineages in the absence of docetaxel/fenofibrate resulted in their reverse microevolution toward the drug-sensitivity and invasive phenotype. Consequently, prostate tumors were able to recover from the combined docetaxel/fenofibrate stress after the initial arrest of their expansion in vivo. In conclusion, we have confirmed the potential of fenofibrate for the metronomic treatment of drug-resistant prostate tumors. However, docetaxel/fenofibrate-induced selective expansion of hyper-resistant CD44high SCL prostate cells and their "bulk" progenies prompts the microevolution of prostate tumor drug-resistance. This process can limit the implementation of metabolic chemotherapy in prostate cancer treatment.

Dataset Information

Treatment scheduling effects on the evolution of drug resistance in heterogeneous cancer cell populations.

Publications

Treatment scheduling effects on the evolution of drug resistance in heterogeneous cancer cell populations.

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