Applications of adenine base editors (ABEs) have been constrained by the limited compatibility of the deoxyadenosine deaminase component with Cas homologs other than SpCas9. We evolved the deaminase component of ABE7.10 using phage-assisted non-continuous and continuous evolution (PANCE and PACE), resulting in ABE8e. ABE8e contains eight additional mutations that increase activity (k app ) 590-fold compared with ABE7.10. ABE8e offers substantially improved editing efficiencies when paired with a variety of Cas9 or Cas12 homologs. ABE8e is more processive than ABE7.10, which could benefit screening, disrupting regulatory regions and multiplex base editing applications. A modest increase in Cas9-dependent and -independent DNA off-target editing, and in transcriptome-wide RNA off-target editing can be ameliorated by introducing additional mutations in the TadA-8e domain. Finally, we show that ABE8e can efficiently edit natural mutations in a GATA1 binding site in the BCL11A enhancer or the HBG promoter in human cells, targets which were poorly edited with ABE7.10. ABE8e broadens the effectiveness and applicability of adenine base editing.

Understanding intrinsic and acquired resistance is crucial to overcoming cancer chemotherapy failure. While it is well-established that intratumor, subclonal genetic and phenotypic heterogeneity significantly contribute to resistance, it is not fully understood how tumor sub-clones interact with each other to withstand therapy pressure. Here, we report a previously unrecognized behavior in heterogeneous tumors: cooperative adaptation to therapy (CAT), in which cancer cells induce co-resistant phenotypes in neighboring cancer cells when exposed to cancer therapy. Using a CRISPR/Cas9 toolkit we engineered phenotypically diverse non-small cell lung cancer (NSCLC) cells by conferring mutations in Dicer1, a type III cytoplasmic endoribonuclease involved in small non-coding RNA genesis. We monitored three-dimensional growth dynamics of fluorescently-labeled mutant and/or wild-type cells individually or in co-culture using a substrate-free NanoCulture system under unstimulated or drug pressure conditions. By integrating mathematical modeling with flow cytometry, we characterized the growth patterns of mono- and co-cultures using a mathematical model of intra- and interspecies competition. Leveraging the flow cytometry data, we estimated the model’s parameters to reveal that the combination of WT and mutants in co-cultures allowed for beneficial growth in previously drug sensitive cells despite drug pressure via induction of cell state transitions described by a cooperative game theoretic change in the fitness values. Finally, we used an ex vivo human tumor model that predicts clinical response through drug sensitivity analyses and determined that cellular and morphologic heterogeneity correlates to prognostic failure of multiple clinically-approved and off-label drugs in individual NSCLC patient samples. Together, these findings present a new paradox in drug resistance implicating non-genetic cooperation among tumor cells to thwart drug pressure, suggesting that profiling for druggable targets (i.e. mutations) alone may be insufficient to assign effective therapy.

Metastable phenotypic state transitions in cancer cells can lead to the development of transient adaptive resistance or tolerance to chemotherapy. Here, we report that the acquisition of a phenotype marked by increased abundance of CD44 (CD44Hi) by breast cancer cells as a tolerance response to routinely used cytotoxic drugs, such as taxanes, activated a metabolic switch that conferred tolerance against unrelated standard-of-care chemotherapeutic agents, such as anthracyclines. We characterized the sequence of molecular events that connected the induced CD44Hi phenotype to increased activity of both the glycolytic and oxidative pathways and glucose flux through the pentose phosphate pathway (PPP). When given in a specific order, a combination of taxanes, anthracyclines, and inhibitors of glucose-6-phosphate dehydrogenase (G6PD), an enzyme involved in glucose metabolism, improved survival in mouse models of breast cancer. The same sequence of the three-drug combination reduced the viability of patient breast tumor samples in an explant system. Our findings highlight a convergence between phenotypic and metabolic state transitions that confers a survival advantage to cancer cells against clinically used drug combinations. Pharmacologically targeting this convergence could overcome cross-drug tolerance and could emerge as a new paradigm in the treatment of cancer.

Drug-induced resistance, or tolerance, is an emerging yet poorly understood failure of anticancer therapy. The interplay between drug-tolerant cancer cells and innate immunity within the tumor, the consequence on tumor growth, and therapeutic strategies to address these challenges remain undescribed. Here, we elucidate the role of taxane-induced resistance on natural killer (NK) cell tumor immunity in triple-negative breast cancer (TNBC) and the design of spatiotemporally controlled nanomedicines, which boost therapeutic efficacy and invigorate “disabled” NK cells. Drug tolerance limited NK cell immune surveillance via drug-induced depletion of the NK-activating ligand receptor axis, NK group 2 member D, and MHC class I polypeptide-related sequence A, B. Systems biology supported by empirical evidence revealed the heat shock protein 90 (Hsp90) simultaneously controls immune surveillance and persistence of drug-treated tumor cells. On the basis of this evidence, we engineered a “chimeric” nanotherapeutic tool comprising taxanes and a cholesterol-tethered Hsp90 inhibitor, radicicol, which targets the tumor, reduces tolerance, and optimally reprimes NK cells via prolonged induction of NK-activating ligand receptors via temporal control of drug release in vitro and in vivo. A human ex vivo TNBC model confirmed the importance of NK cells in drug-induced death under pressure of clinically approved agents. These findings highlight a convergence between drug-induced resistance, the tumor immune contexture, and engineered approaches that consider the tumor and microenvironment to improve the success of combinatorial therapy. Significance: This study uncovers a molecular mechanism linking drug-induced resistance and tumor immunity and provides novel engineered solutions that target these mechanisms in the tumor and improve immunity, thus mitigating off-target effects.

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Understanding intrinsic and adaptive resistance is crucial to overcoming multiple myeloma chemotherapy failure. We recently demonstrated that standard chemotherapy can induce cancer cells to phenotypically transition to a transient state of dormancy and drug tolerance. Further, targeting cells precisely during this transition can thwart the emergence of adaptive resistance (Goldman, 2015). However, it is not yet understood how the stromal contexture may contribute to this chemotherapy-induced drug tolerance. We developed a deterministic mathematical model containing a system of differential equations to examine how stromal fibroblasts temporally affect phenotypic switching between active and dormant, bortezomib-tolerant cancer cell states. The equations describe the total growth rate of each cell state population, which is influenced by that population’s count and baseline growth rate, the frequencies of transitions to and from the other cell state, the drug treatment concentration, and the population carrying capacity. The model also establishes that the presence of fibroblasts affects the frequency of transitions between the cell states. This framework is calibrated to in vitro data, and model simulations predict that bortezomib-tolerant myeloma cells may escape more quickly from dormancy and proliferate when they are incubated in the presence of fibroblasts than in their absence. This prediction is supported by preliminary experimental observations. The mathematical model could be adapted to predict how stromal fibroblasts, or the tumor microenvironment generally, may influence phenotypic switching in other cancers. Citation Format: Elliot Eton, Kamran Kaveh, Sachin Khiste, Andrea Fernandes, Ashima Agarwal, Shiladitya Sengupta, Aaron Goldman. Mathematical modeling of stromal fibroblast-mediated adaptive resistance to bortezomib in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 694.

<p>supplemental tables 1-3</p>