Resistance to chemotherapy is a leading cause of treatment failure. Drug-resistance mechanisms involve mutations in specific proteins or changes in their expression levels. It is commonly understood that resistance mutations happen randomly prior to treatment and are selected during the treatment. However, selection of drug-resistant mutants in culture could be achieved by multiple drug exposures of cloned genetically identical cells, and thus cannot result from selection of pre-existent mutations. Accordingly, adaptation must involve generation of mutations de-novo upon drug treatment. Here we explored the origin of resistance mutations to a widely used Top1 inhibitor irinotecan, which triggers DNA breaks, causing cytotoxicity. Resistance mechanism involved gradual accumulation of recurrent mutations in non-coding regions of DNA at Top1-cleavage sites. Surprisingly, cancer cells had higher number of such sites than reference genome, which may define their increased sensitivity to irinotecan. Homologous recombination repair of DNA double strand breaks at these sites following initial drug exposures gradually reverted cleavage-sensitive “cancer” sequences back to cleavage-resistant “normal” sequences. These mutations reduced generation of DNA breaks upon subsequent exposures, thus gradually increasing the drug resistance. Together, large target size for mutations and their Top1-guided generation lead to their gradual and rapid accumulation, synergistically accelerating development of resistance. Abstract Figure:

Loss of function screens using shRNA (short hairpin RNA) and CRISPR (clustered regularly interspaced short palindromic repeats) are routinely used to identify genes that modulate responses of tumor cells to anti-cancer drugs. Here, by integrating GSEA (Gene Set Enrichment Analysis) and CMAP (Connectivity Map) analyses of multiple published shRNA screens, we identified a core set of pathways that affect responses to multiple drugs with diverse mechanisms of action. This suggests that these pathways represent “weak points” or “Achilles heels”, whose mild disturbance should make cancer cells vulnerable to a variety of treatments. These “weak points” include proteasome, protein synthesis, RNA splicing, RNA synthesis, cell cycle, Akt-mTOR, and tight junction-related pathways. Therefore, inhibitors of these pathways are expected to sensitize cancer cells to a variety of drugs. This hypothesis was tested by analyzing the diversity of drugs that synergize with FDA-approved inhibitors of the proteasome, RNA synthesis, and Akt-mTOR pathways. Indeed, the quantitative evaluation indicates that inhibitors of any of these signaling pathways can synergize with a more diverse set of pharmaceuticals, compared to compounds inhibiting targets distinct from the “weak points” pathways. Our findings described here imply that inhibitors of the “weak points” pathways should be considered as primary candidates in a search for synergistic drug combinations.

Imaging in monitoring metastasis in mouse models have low sensitivity and is not quantitative. Cell DNA barcoding, demonstrating high sensitivity and resolution, allows monitoring effects of drugs on the number of tumor and metastatic clones. However, this technology is not suitable for comparison of sizes of metastatic clones in different animals, e.g. drug treated and untreated, due to high biological and technical variability upon tumor and metastatic growth and isolation of barcodes from tissue DNA. Yet, both numbers of clones and their sizes are critical parameters for analysis of drug effects. Here we developed a modification of the barcoding approach for monitoring drug effects on tumors and metastasis that is quantitative, highly sensitive and highly reproducible. This novel cell double barcoding system allows simultaneously following the fate of two or more cell variants or cell lines in xenograph models in vivo, and also following the fates of individual clones within each of these populations. This system allows comparing effects of drugs on different cell populations, and thus normalizing drug effects by drug-resistant lines, which corrects for both biological and technical variabilities and significantly increases the reproducibility of results. Using this barcoding system, we uncovered that effects of a novel DYRK1B kinase inhibitor FX9847 on primary tumors and metastasis is clone-dependent, while a distinct drug osimertinib demonstrated clone-independent effects on cancer cell populations. Overall cell double barcoding approach can significantly enrich our understanding of drug effects in basic research and preclinical studies. Citation Format: Arkadi Hesin, Santosh Kumar, Valid Gahramanov, Maria Becker, Maria Vilenchik, Ilya Alexandrov, Julia Yaglom, Michael Sherman. A cell double barcoding system for quantitative evaluation of primary tumors & metastasis in animals: Uncovers clonal-specific anti-cancer drug effects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6269.