Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.

TRP channel expression correlates with the epithelial–mesenchymal transition and high-risk endometrial carcinoma

Transient receptor potential (TRP) channels excel in cellular sensing as they allow rapid ion influx across the plasma membrane in response to a variety of extracellular cues. Recently, a distinct TRP mRNA expression signature was observed in stromal cells (ESC) and epithelial cells (EEC) of the endometrium, a tissue in which cell phenotypic plasticity is essential for normal functioning. However, it is unknown whether TRP channel mRNA expression is subject to the phenotypic switching that occurs during epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET), and whether TRP channel mRNA expression is associated with aggressive phenotypes in endometrial cancer (EC). Here, we induced EMT and MET in vitro using in primary EEC and ESC, respectively, and analyzed expression and functionality of TRP channels using RT-qPCR and intracellular Ca2+ imaging. The outcome of these experiments showed a strong association between TRPV2 and TRPC1 mRNA expression and the mesenchymal phenotype, whereas TRPM4 mRNA expression correlated with the epithelial phenotype. In line herewith, increased TRPV2 and TRPC1 mRNA expression levels were observed in both primary and metastatic EC biopsies and in primary EC cells with a high EMT status, indicating an association with an aggressive tumor phenotype. Remarkably, TRPV2 mRNA expression in primary EC biopsies was associated with tumor invasiveness and cancer stage. In contrast, increased TRPM4 mRNA expression was observed in EC biopsies with a low EMT status and less aggressive tumor phenotypes. Taken together, this dataset proved for the first time that TRP channel mRNA expression is strongly linked to cellular phenotypes of the endometrium, and that phenotypic transitions caused by either experimental manipulation or malignancy could alter this expression in a predictable manner. These results implicate that TRP channels are viable biomarkers to identify high-risk EC, and potential targets for EC treatment.

Dynamic Phenotypic Switching and Group Behavior Help Non-Small Cell Lung Cancer Cells Evade Chemotherapy

Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a ‘persister-like’ behavior and are attenuated by sensitive cells; they also appear to ‘educate’ sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer.

Stabilization of Microbial Communities by Responsive Phenotypic Switching

Clonal microbes can switch between different phenotypes and recent theoretical work has shown that stochastic switching between these subpopulations can stabilize microbial communities. This phenotypic switching need not be stochastic, however, but can also be in response to environmental factors, both biotic and abiotic. Here, motivated by the bacterial persistence phenotype, we explore the ecological effects of such responsive switching by analyzing phenotypic switching in response to competing species. We show how the stability of microbial communities with responsive switching differs generically from that of communities with stochastic switching only. To understand this effect, we go on to analyse simple two-species models. Combining exact results and numerical simulations, we extend the classical stability results for models of two competing species without phenotypic variation to the case where one of the two species switches, stochastically and responsively, between two phenotypes. In particular, we show that responsive switching can stabilize coexistence even when stochastic switching on its own does not affect the stability of the community.

Phenotypic Switching and Filamentation in Candida haemulonii, an Emerging Opportunistic Pathogen of Humans

The capacity to switch between distinct cell types, known as phenotypic switching, is a common strategy adopted by Candida species to adapt to diverse environments. Despite considerable studies on phenotypic plasticity of various Candida species, Candida haemulonii is considered to be incapable of phenotypic switching or filamentous growth.

Lnc-C2orf63-4-1 Confers VSMC Homeostasis and Prevents Aortic Dissection Formation via STAT3 Interaction

Emerging evidence indicates that long non-coding RNAs (lncRNAs) serve as a critical molecular regulator in various cardiovascular diseases. Here, we aimed to identify and functionally characterize lncRNAs as potential mediators in the development of thoracic aortic dissection (TAD). We identified that a novel lncRNA, lnc-C2orf63-4-1, was lowly expressed in aortic samples of TAD patients and angiotensin II (Ang II)-challenged vascular smooth muscle cells (VSMCs), which was correlated with clinically aortic expansion. Besides, overexpression of lnc-C2orf63-4-1 significantly attenuated Ang II-induced apoptosis, phenotypic switching of VSMCs and degradation of extracellular matrix both in vitro and in vivo. A customized transcription factor array identified that signal transducer and activator of transcription 3 (STAT3) functioned as the main downstream effector. Mechanistically, dual-luciferase report analysis and RNA antisense purification (RAP) assay indicated that lnc-C2orf63-4-1 directly decreased the expression of STAT3, which was depend on the reduced stabilization of STAT3 mRNA. Importantly, up-regulation of STAT3 efficiently reversed the protective role of lnc-C2orf63-4-1 against Ang II-mediated vascular remodeling. Therefore, lnc-C2orf63-4-1 negatively regulated the expression of STAT3 and prevented the development of aortic dissection. Our study revealed that lnc-C2orf63-4-1 played a critical role in vascular homeostasis, and its dysfunction exacerbated Ang II-induced pathological vascular remodeling.

Population Dynamics of Hybrid State during Adaptive Therapy in Cancer

Drug resistance emerges due to drug-induced phenotypic switching of drug-sensitive to drug-resistant subpopulations in cancer during therapy. Existing models indicate the competitive advantage of sensitive over resistant population to regulate tumor and reducing the treatment cost with increased time to progression of tumor ultimately benefiting the patient in a clinical setting. Here, we present a Lotka Volterra (LV) based population dynamics (PD) model of the drug-sensitive, drug-resistant, and transient drug-hybrid state along with phenotypic switching during adaptive therapy based on a simple cancer biomarker (CB) to decide the adaptive therapy dosage to regulate cancer. We identified that the strength of intra-competition along with phenotypic switching parameters is crucial to mediate the effectiveness of adaptive therapy and also investigated the significance of the initial fraction of subpopulations on AT. We hypothesize and predict the dynamics of drug-induced transient hybrid state playing a key role in the cancer cells undergoing metastasis.

Responses of White Blood Cells to Killed Candida albicans as a Preventive Strategy

C. albicans is by far the most common Candida species causing infection in humans which include superficial and a life- threatening systemic infections. Despite the public health significance of candida infections, phenotypic switching of C. albicans, slow mycological diagnosis, limitation of use of antifungal agents due to toxicity, high cost and emergence of resistance have impeded effective treatment. Therefore, a need for safe and potent strategy to prevent this disease is necessary. This chapter discusses the roles of white blood cells as the first line defense mechanism against inactivated C. albicans.