HSP70 and HSP90 are two powerful chaperone machineries involved in survival and proliferation of tumor cells. Residing in various cellular compartments, HSP70 and HSP90 perform specific functions. Concurrently, HSP70 and HSP90 homologs may also translocate from their primary site under various stress conditions. Herein, we address the current literature on the role of HSP70 and HSP90 chaperone networks in cancer. The goal is to provide a comprehensive review on the functions of cytosolic, mitochondrial and endoplasmic reticulum HSP70 and HSP90 homologs in cancer. Given that high expression of HSP70 and HSP90 enhances tumor development and associates with tumor aggressiveness, further understanding of HSP70 and HSP90 chaperone networks may provide clues for the discoveries of novel anti-cancer therapies.
Hepatitis C virus (HCV) infection is one of the main causes of chronic liver disease, with approximately 71 million chronically infected individuals worldwide. 1 Numerous studies have found a high prevalence
Heat shock proteins are molecular chaperones which support tumor development by regulating various cellular processes including unfolded protein response, mitochondrial bioenergetics, apoptosis, autophagy, necroptosis, lipid metabolism, angiogenesis, cancer cell stemness, epithelial-mesenchymal transition and tumor immunity. Apart from their intracellular activities, HSPs have also distinct extracellular functions. However, the role that HSP chaperones play in the regulation of immune responses inside and outside the cell is not yet clear. Herein, we explore the intracellular and extracellular immunologic functions of HSPs in cancer. A broader understanding of how HSPs modulate immune responses may provide critical insights for the development of effective immunotherapies.
Immunotherapy harnessing the host immune system for tumor destruction revolutionized oncology research and advanced treatment strategies for lymphoma patients. Lymphoma is a heterogeneous group of cancer, where the central roles in pathogenesis play immune evasion and dysregulation of multiple signaling pathways. Immunotherapy-based approaches such as engineered T cells (CAR T), immune checkpoint modulators and NK cell-based therapies are now in the frontline of lymphoma research. Even though emerging immunotherapies showed promising results in treating lymphoma patients, low efficacy and on-target/off-tumor toxicity are of a major concern. To address that issue it is suggested to look into the emerging role of heat shock proteins. Heat shock proteins (HSPs) showed to be highly expressed in lymphoma cells. HSPs are known for their abilities to modulate immune responses and inhibit apoptosis, which made their successful entry into cancer clinical trials. Here, we explore the role of HSPs in Hodgkin and Non-Hodgkin lymphoma and their involvement in CAR T therapy, checkpoint blockade and NK cell- based therapies. Understanding the role of HSPs in lymphoma pathogenesis and the ways how HSPs may enhance anti-tumor responses, may help in the development of more effective, specific and safe immunotherapy.
Heat shock proteins (HSPs) are a large family of molecular chaperones, which have shown to be implicated in various hallmarks of cancer such as resistance to apoptosis, invasion, angiogenesis, induction of immune tolerance, and metastasis. Several studies reported aberrant expression of HSPs in liquid biopsies of cancer patients and this has opened new perspectives on the use of HSPs as biomarkers of cancer. However, no specific diagnostic, predictive, or prognostic HSP chaperone-based urine biomarker has been yet discovered. On the other hand, divergent expression of HSPs has also been observed in other pathologies, including neurodegenerative and cardiovascular diseases, suggesting that new approaches should be employed for the discovery of cancer-specific HSP biomarkers. In this study, we propose a new strategy in identifying cancer-specific HSP-based biomarkers, where HSP networks in urine can be used to predict cancer. By analyzing HSPs present in urine, we could predict cancer with approximately 90% precision by machine learning approach. We aim to show that coupling the machine learning approach and the understanding of how HSPs operate, including their functional cycles, collaboration with and within networks, is effective in defining patients with cancer, which may provide the basis for future discoveries of novel HSP-based biomarkers of cancer.
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