Person:

Goldman, Aaron

Cancer microenvironment is a remarkably heterogeneous composition of cellular and non-cellular components, regulated by both external and intrinsic physical and chemical stimuli. Physical alterations driven by increased proliferation of neoplastic cells and angiogenesis in the cancer microenvironment result in the exposure of the cancer cells to elevated levels of flow-based shear stress. We developed a dynamic microfluidic cell culture platform utilizing eshopagael cancer cells as model cells to investigate the phenotypic changes of cancer cells upon exposure to fluid shear stress. We report the epithelial to hybrid epithelial/mesenchymal transition as a result of decreasing E-Cadherin and increasing N-Cadherin and vimentin expressions, higher clonogenicity and ALDH positive expression of cancer cells cultured in a dynamic microfluidic chip under laminar flow compared to the static culture condition. We also sought regulation of chemotherapeutics in cancer microenvironment towards phenotypic control of cancer cells. Such in vitro microfluidic system could potentially be used to monitor how the interstitial fluid dynamics affect cancer microenvironment and plasticity on a simple, highly controllable and inexpensive bioengineered platform.

Understanding the emerging models of adaptive resistance is key to overcoming cancer chemotherapy failure. Using human breast cancer explants, in vitro cell lines, mouse in vivo studies and mathematical modelling, here we show that exposure to a taxane induces phenotypic cell state transition towards a favoured transient CD44HiCD24Hi chemotherapy-tolerant state. This state is associated with a clustering of CD44 and CD24 in membrane lipid rafts, leading to the activation of Src Family Kinase (SFK)/hemopoietic cell kinase (Hck) and suppression of apoptosis. The use of pharmacological inhibitors of SFK/Hck in combination with taxanes in a temporally constrained manner, where the kinase inhibitor is administered post taxane treatment, but not when co-administered, markedly sensitizes the chemotolerant cells to the chemotherapy. This approach of harnessing chemotherapy-induced phenotypic cell state transition for improving antitumour outcome could emerge as a translational strategy for the management of cancer.

Metastasis can involve repeated cycles of epithelial-to-mesenchymal transition (EMT) and its reverse mesenchymal-to-epithelial transition. Cells can also undergo partial transitions to attain a hybrid epithelial/mesenchymal (E/M) phenotype that allows the migration of adhering cells to form a cluster of circulating tumour cells. These clusters can be apoptosis-resistant and possess an increased metastatic propensity as compared to the cells that undergo a complete EMT (mesenchymal cells). Hence, identifying the key players that can regulate the formation and maintenance of such clusters may inform anti-metastasis strategies. Here, we devise a mechanism-based theoretical model that links cell–cell communication via Notch-Delta-Jagged signalling with the regulation of EMT. We demonstrate that while both Notch-Delta and Notch-Jagged signalling can induce EMT in a population of cells, only Jagged-dominated Notch signalling, but not Delta-dominated signalling, can lead to the formation of clusters containing hybrid E/M cells. Our results offer possible mechanistic insights into the role of Jagged in tumour progression, and offer a framework to investigate the effects of other microenvironmental signals during metastasis.

Pharmacological concentrations of small molecule natural products, such as ascorbic acid, have exhibited distinct cell killing outcomes between cancer and normal cells whereby cancer cells undergo apoptosis or necrosis while normal cells are not adversely affected. Here, we develop a mathematical model for ascorbic acid that can be utilized as a tool to understand the dynamics of reactive oxygen species (ROS) induced cell death. We determine that not only do endogenous antioxidants such as catalase contribute to ROS-induced cell death, but also cell membrane properties play a critical role in the efficacy of ROS as a cytotoxic mechanism against cancer cells vs. normal cells. Using in vitro assays with breast cancer cells, we have confirmed that cell membrane properties are essential for ROS, in the form of hydrogen peroxide (H2O2), to induce cell death. Interestingly, we did not observe any correlation between intracellular H2O2 and cell survival, suggesting that cell death by H2O2 is triggered by interaction with the cell membrane and not necessarily due to intracellular levels of H2O2. These findings provide a putative mechanistic explanation for the efficacy and selectivity of therapies such as ascorbic acid that rely on ROS-induced cell death for their anti-tumor properties.

Background and purpose Predicting the efficacy of anticancer therapy is the holy grail of drug development and treatment selection in the clinic. To achieve this goal, scientists require pre-clinical models that can reliably screen anticancer agents with robust clinical correlation. However, there is increasing challenge to develop models that can accurately capture the diversity of the tumor ecosystem, and therefore reliably predict how tumors respond or resistant to treatment. Indeed, tumors are made up of a heterogeneous landscape comprising malignant cells, normal and abnormal stroma, immune cells, and dynamic microenvironment containing chemokines, cytokines and growth factors. In this mini-review we present a focused, brief perspective on emerging preclinical models for anticancer therapy that attempt to address the challenge posed by tumor heterogeneity, highlighting biomarkers of response and resistance. Recent findings Starting from 2-dimensional and 3-dimensional in-vitro models, we discuss how organoid co-cultures have led to accelerated efforts in anti-cancer drug screening, and advanced our fundamental understanding for mechanisms of action using high-throughput platforms that interrogate various biomarkers of ‘clinical’ efficacy. Then, mentioning the limitations that exist, we focus on in-vivo and human explant technologies and models, which build-in intrinsic tumor heterogeneity using the native microenvironment as a scaffold. Importantly, we will address how these models can be harnessed to understand cancer immunotherapy, an emerging therapeutic strategy that seeks to recalibrate the body’s own immune system to fight cancer. Conclusion: Over the past several decades, numerous model systems have emerged to address the exploding market of drug development for cancer. While all of the present models have contributed critical information about tumor biology, each one carries limitations. Harnessing pre-clinical models that incorporate cell heterogeneity is beginning to address some of the underlying challenges associated with predicting clinical efficacy of novel anticancer agents.

Purpose of review The vision and strategy for the 21st century treatment of cancer calls for a personalized approach in which therapy selection is designed for each individual patient. While genomics has led the field of personalized cancer medicine over the past several decades by connecting patient-specific DNA mutations with kinase-targeted drugs, the recent discovery that tumors evade immune surveillance has created unique challenges to personalize cancer immunotherapy. In this mini-review we will discuss how personalized medicine has evolved recently to accommodate the emerging era of cancer immunotherapy. Moreover, we will discuss novel platform technologies that have been engineered to address some of the persisting limitations. Recent finding Beginning with early evidence in personalized medicine, we discuss how biomarker-driven approaches to predict clinical success have evolved to account for the heterogeneous tumor ecosystem. In the emerging field of cancer immunotherapy, this challenge requires the use of a novel set of tools, distinct from the classic approach of next-generation genomic sequencing-based strategies. We will introduce new techniques that seek to tailor immunotherapy by re-programming patient-autologous T-cells, and new technologies that are emerging to predict clinical efficacy by mapping infiltration of lymphocytes, and harnessing fully humanized platforms that reconstruct and interrogate immune checkpoint blockade, ex-vivo. Summary While cancer immunotherapy is now leading to durable outcomes in difficult-to-treat cancers, success is highly variable. Developing novel approaches to study cancer immunotherapy, personalize treatment to each patient, and achieve greater outcomes is penultimate to developing sustainable cures in the future. Numerous techniques are now emerging to help guide treatment decisions, which go beyond simple biomarker-driven strategies, and are now we are seeking to interrogate the entirety of the dynamic tumor ecosystem.