Significance: The epithelial-to-mesenchymal transition (EMT) is a critical cell biological process that occurs during normal embryonic development and cancer progression. Our study combines single-cell RNA-sequencing analysis and mathematical modeling to identify critical regulators of EMT. Detailed analyses of TGF-β1–induced EMT by single-cell RNA-sequencing data revealed simultaneous activation of EMT signaling pathways. We created mathematical approaches to identify the master regulatory pathway of EMT and key downstream mediators of this process. This study sheds light on the signaling architecture that governs EMT and informs ongoing efforts to delineate drivers of cancer initiation, progression, and metastasis.
Background: The epithelial-mesenchymal transition (EMT) enables dissociation of tumour cells from the primary tumour mass, invasion through the extracellular matrix, intravasation into blood vessels and colonisation of distant organs. Cells that revert to the epithelial state via the mesenchymal-epithelial transition cause metastases, the primary cause of death in cancer patients. EMT also empowers cancer cells with stem-cell properties and induces resistance to chemotherapeutic drugs. Understanding the driving factors of EMT is critical for the development of effective therapeutic interventions. Methods: This manuscript describes the generation of a database containing EMT gene signatures derived from cell lines, patient-derived xenografts and patient studies across cancer types and multiomics data and the creation of a web-based portal to provide a comprehensive analysis resource. Results: EMTome incorporates (i) EMT gene signatures; (ii) EMT-related genes with multiomics features across different cancer types; (iii) interactomes of EMT-related genes (miRNAs, transcription factors, and proteins); (iv) immune profiles identified from The Cancer Genome Atlas (TCGA) cohorts by exploring transcriptomics, epigenomics, and proteomics, and drug sensitivity and (iv) clinical outcomes of cancer cohorts linked to EMT gene signatures. Conclusion: The web-based EMTome portal is a resource for primary and metastatic tumour research publicly available at www.emtome.org.
Cancer Stem cells (CSCs) are a unipotent cell population present within the tumour cell mass. CSCs are known to be highly chemo-resistant, and in recent years, they have gained intense interest as key tumour initiating cells that may also play an integral role in tumour recurrence following chemotherapy. Cancer cells have the ability to alter their metabolism in order to fulfil bio-energetic and biosynthetic requirements. They are largely dependent on aerobic glycolysis for their energy production and also are associated with increased fatty acid synthesis and increased rates of glutamine utilisation. Emerging evidence has shown that therapeutic resistance to cancer treatment may arise due to dysregulation in glucose metabolism, fatty acid synthesis, and glutaminolysis. To propagate their lethal effects and maintain survival, tumour cells alter their metabolic requirements to ensure optimal nutrient use for their survival, evasion from host immune attack, and proliferation. It is now evident that cancer cells metabolise glutamine to grow rapidly because it provides the metabolic stimulus for required energy and precursors for synthesis of proteins, lipids, and nucleic acids. It can also regulate the activities of some of the signalling pathways that control the proliferation of cancer cells. This review describes the key metabolic pathways required by CSCs to maintain a survival advantage and highlights how a combined approach of targeting cellular metabolism in conjunction with the use of chemotherapeutic drugs may provide a promising strategy to overcome therapeutic resistance and therefore aid in cancer therapy.
The epithelial–mesenchymal transition (EMT) often plays a critical role in cancer metastasis and chemoresistance, and decoding its dynamics is crucial to design effective therapeutics. EMT is regulated at multiple levels—transcriptional, translational, protein stability and epigenetics; the mechanisms by which epigenetic regulation can alter the dynamics of EMT remain elusive. Here, to identify the possible effects of epigenetic regulation in EMT, we incorporate a feedback term in our previously proposed model of EMT regulation of the miR-200/ZEB/miR-34/SNAIL circuit. This epigenetic feedback that stabilizes long-term transcriptional activity can alter the relative stability and distribution of states in a given cell population, particularly when incorporated in the inhibitory effect on miR-200 from ZEB. This feedback can stabilize the mesenchymal state, thus making transitions out of that state difficult. Conversely, epigenetic regulation of the self-activation of ZEB has only minor effects. Our model predicts that this effect could be seen in experiments, when epithelial cells are treated with an external EMT-inducing signal for a sufficiently long period of time and then allowed to recover. Our preliminary experimental data indicates that a chronic TGF- β exposure gives rise to irreveversible EMT state; i.e. unable to reverse back to the epithelial state. Thus, this integrated theoretical-experimental approach yields insights into how an epigenetic feedback may alter the dynamics of EMT.
Breast cancer is the most commonly diagnosed cancer in the USA. Although advances in treatment over the past several decades have significantly improved the outlook for this disease, most women who are diagnosed with estrogen receptor positive disease remain at risk of metastatic relapse for the remainder of their life. The cellular source of late relapse in these patients is thought to be disseminated tumor cells that reactivate after a long period of dormancy. The biology of these dormant cells and their natural history over a patient’s lifetime is largely unclear. We posit that research on tumor dormancy has been significantly limited by the lack of clinically relevant models. This review will discuss existing dormancy models, gaps in biological understanding, and propose criteria for future models to enhance their clinical relevance.