Emergence of Anti-Cancer Drug Resistance: Exploring the Importance of the Microenvironmental Niche via a Spatial Model

Practically, all chemotherapeutic agents lead to drug resistance. Clinically, it is a challenge to determine whether resistance arises prior to, or as a result of, cancer therapy. Further, a number of different intracellular and microenvironmental factors have been correlated with the emergence of drug resistance. With the goal of better understanding drug resistance and its connection with the tumor microenvironment, we have developed a hybrid discrete-continuous mathematical model. In this model, cancer cells described through a particle-spring approach respond to dynamically changing oxygen and DNA damaging drug concentrations described through partial differential equations. We thoroughly explored the behavior of our self-calibrated model under the following common conditions: a fixed layout of the vasculature, an identical initial configuration of cancer cells, the same mechanism of drug action, and one mechanism of cellular response to the drug. We considered one set of simulations in which drug resistance existed prior to the start of treatment, and another set in which drug resistance is acquired in response to treatment. This allows us to compare how both kinds of resistance influence the spatial and temporal dynamics of the developing tumor, and its clonal diversity. We show that both pre-existing and acquired resistance can give rise to three biologically distinct parameter regimes: successful tumor eradication, reduced effectiveness of drug during the course of treatment (resistance), and complete treatment failure

Overcoming the challenges of cancer drug resistance through bacterial-mediated therapy.

Despite tremendous efforts to fight cancer, it remains a major public health problem and a leading cause of death worldwide. With increased knowledge of cancer pathways and improved technological platforms, precision therapeutics that specifically target aberrant cancer pathways have improved patient outcomes. Nevertheless, a primary cause of unsuccessful cancer therapy remains cancer drug resistance. In this review, we summarize the broad classes of resistance to cancer therapy, particularly pharmacokinetics, the tumor microenvironment, and drug resistance mechanisms. Furthermore, we describe how bacterial-mediated cancer therapy, a bygone mode of treatment, has been revitalized by synthetic biology and is uniquely suited to address the primary resistance mechanisms that confound traditional therapies. Through genetic engineering, we discuss how bacteria can be potent anticancer agents given their tumor targeting potential, anti-tumor activity, safety, and coordinated delivery of anti-cancer drugs

Selinexor overcomes hypoxia-induced drug resistance in multiple myeloma

Increased levels of the nuclear export protein, exportin 1 (XPO1), were demonstrated in multiple myeloma (MM) patients. Targeting XPO1 with selinexor (the selective inhibitor of nuclear export; SINE compound KPT-330) demonstrates broad antitumor activity also in patient cells resistant to bortezomib; hence, it is a promising target in MM patients. Hypoxia is known to mediate tumor progression and drug resistance (including bortezomib resistance) in MM cells. In this study, we tested the effects of selinexor alone or in combination with bortezomib in normoxia and hypoxia on MM cell survival and apoptosis in vitro and in vivo. In vitro, selinexor alone decreased survival and increased apoptosis, resensitizing MM cells to bortezomib. In vivo, we examined the effects of selinexor alone on tumor initiation and tumor progression, as well as selinexor in combination with bortezomib, on tumor growth in a bortezomib-resistant MM xenograft mouse model. Selinexor, used as a single agent, delayed tumor initiation and tumor progression, prolonging mice survival. In bortezomib-resistant xenografts, selinexor overcame drug resistance, significantly decreasing tumor burden and extending mice survival when combined with bortezomib

Exploiting the synergy between carboplatin and ABT-737 in the treatment of ovarian carcinomas

Platinum drug-resistance in ovarian cancers is a major factor contributing to chemotherapeutic resistance of recurrent disease. Members of the Bcl-2 family such as the anti-apoptotic protein Bcl-XL have been shown to play a role in this resistance. Consequently, concurrent inhibition of Bcl-XL in combination with standard chemotherapy may improve treatment outcomes for ovarian cancer patients. Here, we develop a mathematical model to investigate the potential of combination therapy with ABT-737, a small molecule inhibitor of Bcl-XL, and carboplatin, a platinum-based drug, on a simulated tumor xenograft. The model is calibrated against in vivo\ud experimental data, wherein tumor xenografts were established in mice and treated with ABT-737 and carboplatin on a fixed periodic schedule, alone or in combination, and tumor sizes recorded regularly. We show that the validated model can be used to predict the minimum drug load that will achieve a predetermined level of tumor growth inhibition, thereby maximizing the synergy between the two drugs. Our simulations suggest that the time of infusion of each carboplatin dose is a critical parameter, with an 8-hour infusion of carboplatin administered each week combined with a daily bolus dose of ABT-737 predicted to minimize residual disease. We also investigate the potential of ABT-737 co-therapy with carboplatin to prevent or delay the onset of carboplatin-resistance under two scenarios. When resistance is acquired as a result of aberrant DNA-damage repair in cells treated with carboplatin, the model is used to identify drug delivery schedules that induce tumor remission with even low doses of combination therapy. When resistance is intrinsic, due to a pre-existing cohort of resistant cells, tumor remission is no longer feasible, but our model can be used to identify dosing strategies that extend disease-free survival periods. These results underscore the potential of our model to accelerate the development of novel therapeutics such as ABT-737, by predicting optimal treatment strategies when these drugs are given in combination with currently approved cancer medications

Transcriptomic-metabolomic reprogramming in EGFR-mutant NSCLC early adaptive drug escape linking TGFβ2-bioenergetics-mitochondrial priming.

The impact of EGFR-mutant NSCLC precision therapy is limited by acquired resistance despite initial excellent response. Classic studies of EGFR-mutant clinical resistance to precision therapy were based on tumor rebiopsies late during clinical tumor progression on therapy. Here, we characterized a novel non-mutational early adaptive drug-escape in EGFR-mutant lung tumor cells only days after therapy initiation, that is MET-independent. The drug-escape cell states were analyzed by integrated transcriptomic and metabolomics profiling uncovering a central role for autocrine TGFβ2 in mediating cellular plasticity through profound cellular adaptive Omics reprogramming, with common mechanistic link to prosurvival mitochondrial priming. Cells undergoing early adaptive drug escape are in proliferative-metabolic quiescent, with enhanced EMT-ness and stem cell signaling, exhibiting global bioenergetics suppression including reverse Warburg, and are susceptible to glutamine deprivation and TGFβ2 inhibition. Our study further supports a preemptive therapeutic targeting of bioenergetics and mitochondrial priming to impact early drug-escape emergence using EGFR precision inhibitor combined with broad BH3-mimetic to interrupt BCL-2/BCL-xL together, but not BCL-2 alone

Relationship between chronological aging and acquired resistance to cisplatin in the yeast saccharomyces cerevisiae

The Sir2 gene is associated with an increase in longevity in yeasts, worms, flies and rodents. The human homolog, Sirt1, is also involved in longevity, by inhibiting cellular senescence. Studies carry out in tumor cells of neuroblastoma, osteosarcoma, breast and ovary, resistant and sensitive to antineoplastic drugs, suggest that the increase of Sirt1 expression may represent a general phenomenon associated with resistance to chemotherapy, independent of cell type or drug used to induce resistance. Thus, after analyzing tumor biopsies after treating patients with chemotherapy, high amounts of Sirt1 have been observed. The aim of this work is to study the relationship between chronological aging and acquired resistance to Cisplatin in the yeast Saccharomyces cerevisiae.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Emerging Insights of Tumor Heterogeneity and Drug Resistance Mechanisms in Lung Cancer Targeted Therapy

Abstract The biggest hurdle to targeted cancer therapy is the inevitable emergence of drug resistance. Tumor cells employ different mechanisms to resist the targeting agent. Most commonly in EGFR-mutant non-small cell lung cancer, secondary resistance mutations on the target kinase domain emerge to diminish the binding affinity of first- and second-generation inhibitors. Other alternative resistance mechanisms include activating complementary bypass pathways and phenotypic transformation. Sequential monotherapies promise to temporarily address the problem of acquired drug resistance, but evidently are limited by the tumor cells’ ability to adapt and evolve new resistance mechanisms to persist in the drug environment. Recent studies have nominated a model of drug resistance and tumor progression under targeted therapy as a result of a small subpopulation of cells being able to endure the drug (minimal residual disease cells) and eventually develop further mutations that allow them to regrow and become the dominant population in the therapy-resistant tumor. This subpopulation of cells appears to have developed through a subclonal event, resulting in driver mutations different from the driver mutation that is tumor-initiating in the most common ancestor. As such, an understanding of intratumoral heterogeneity—the driving force behind minimal residual disease—is vital for the identification of resistance drivers that results from branching evolution. Currently available methods allow for a more comprehensive and holistic analysis of tumor heterogeneity in that issues associated with spatial and temporal heterogeneity can now be properly addressed. This review provides some background regarding intratumoral heterogeneity and how it leads to incomplete molecular response to targeted therapies, and proposes the use of single-cell methods, sequential liquid biopsy, and multiregion sequencing to discover the link between intratumoral heterogeneity and early adaptive drug resistance. In summary, minimal residual disease as a result of intratumoral heterogeneity is the earliest form of acquired drug resistance. Emerging technologies such as liquid biopsy and single-cell methods allow for studying targetable drivers of minimal residual disease and contribute to preemptive combinatorial targeting of both drivers of the tumor and its minimal residual disease cells

Challenges of drug resistance in the management of pancreatic cancer

The current treatment of choice for metastatic pancreatic cancer involves single agent gemcitabine or combination of gemcitabine with capecitabine and erlotinib (tyrosine kinase inhibitor). Only 25-30% of patients respond to this treatment and patients who do respond initially ultimately exhibit disease progression. Median survival for pancreatic cancer patients has reached a plateau due to inherent and acquired resistance to these agents. Key molecular factors implicated in this resistance include: deficiencies in drug uptake, alteration of drug targets, activations of DNA repair pathways, resistance to apoptosis, and the contribution of the tumor microenvironment. Moreover, for newer agents including tyrosine kinase inhibitors, over expression of signaling proteins, mutations in kinase domains, activation of alternative pathways, mutations of genes downstream of the target, and/or amplification of the target represent key challenges for treatment efficacy. Here we will review the contribution of known mechanisms and markers of resistance to key pancreatic cancer drug treatments