With over 1 million incidence cases and more than 780,000 deaths in 2018, gastric cancer (GC) was ranked as the 5th most common cancer and the 3rd leading cause of cancer deaths worldwide. Though several biomarkers, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4), have been identified, their diagnostic accuracies were modest. Circulating tumor cells (CTCs), cells derived from tumors and present in body fluids, have recently emerged as promising biomarkers, diagnostically and prognostically, of cancers, including GC. In this review, we present the landscape of CTCs from migration, to the presence in circulation, biologic properties, and morphologic heterogeneities. We evaluated clinical implications of CTCs in GC patients, including diagnosis, prognosis, and therapeutic management, as well as their application in immunotherapy. On the one hand, major challenges in using CTCs in GC were analyzed, from the differences of cut-off values of CTC positivity, to techniques used for sampling, storage conditions, and CTC molecular markers, as well as the unavailability of relevant enrichment and detection techniques. On the other hand, we discussed future perspectives of using CTCs in GC management and research, including the use of circulating tumor microembolies; of CTC checkpoint blockade in immunotherapy; and of organoid models. Despite the fact that there are remaining challenges in techniques, CTCs have potential as novel biomarkers and/or a non-invasive method for diagnostics, prognostics, and treatment monitoring of GC, particularly in the era of precision medicine.
In the United States, Prostate Cancer (PCa) is the leading cause of cancer-related mortality in men. PCa resulted in abnormal growth and function of prostate gland such as secretion of high level of gamma-seminoprotein (gama-SM)/Prostate-Specific Antigen (PSA) which could be detected in the blood. Beside gama-SM protein, the levels of heat shock proteins (Hsp70) were also observed significantly high. Therefore, gama-SM and Hsp70 are unique proteins with high potential for PCa therapeutics and diagnostics. High level of Hsp70 suppresses apoptosis, thus allowing PCa cells to exist; however, depletion of Hsp70 induces apoptosis in PCa cells. Gama-SM is the most prominent biomarker for PCa screening; however, its accuracy is still questionable. Thus, a more suitable streamline biomarker for PCa screening is urgently needed. Hsp70 and gama-SM proteins could be used as a revolutionary biomarker for PCa, and could help to identify possible therapeutic target(s). In this review article we will discuss the relationship between the Hsp70 and gama-SM proteins with PCa, their potential as a dual biomarker, and the possibility for both proteins being used as therapeutic targets.
Cellular metabolic dysregulation is a consequence of COVID-19 infection that is a key determinant of disease severity. To understand the mechanisms underlying these cellular changes, we performed high-dimensional immune cell profiling of PBMCs from COVID-19-infected patients, in combination with single cell transcriptomic analysis of COVID-19 BALFs. Hypoxia, a hallmark of COVID-19 ARDS, was found to elicit a global metabolic reprogramming in effector lymphocytes. In response to oxygen and nutrient-deprived microenvironments, these cells shift from aerobic respiration to increase their dependence on anaerobic processes including glycolysis, mitophagy, and glutaminolysis to fulfill their bioenergetic demands. We also demonstrate metabolic dysregulation of ciliated lung epithelial cells is linked to significant increase of proinflammatory cytokine secretion and upregulation of HLA class 1 machinery. Augmented HLA class-1 antigen stimulation by epithelial cells leads to cellular exhaustion of metabolically dysregulated CD8 and NK cells, impairing their memory cell differentiation. Unsupervised clustering techniques revealed multiple distinct, differentially abundant CD8 and NK memory cell states that are marked by high glycolytic flux, mitochondrial dysfunction, and cellular exhaustion, further highlighting the connection between disrupted metabolism and impaired memory cell function in COVID-19. Our findings provide novel insight on how SARS-CoV-2 infection affects host immunometabolism and anti-viral response during COVID-19.
Cellular metabolic dysregulation is a consequence of SARS-CoV-2 infection that is a key determinant of disease severity. However, how metabolic perturbations influence immunological function during COVID-19 remains unclear. Here, using a combination of high-dimensional flow cytometry, cutting-edge single-cell metabolomics, and re-analysis of single-cell transcriptomic data, we demonstrate a global hypoxia-linked metabolic switch from fatty acid oxidation and mitochondrial respiration towards anaerobic, glucose-dependent metabolism in CD8+Tc, NKT, and epithelial cells. Consequently, we found that a strong dysregulation in immunometabolism was tied to increased cellular exhaustion, attenuated effector function, and impaired memory differentiation. Pharmacological inhibition of mitophagy with mdivi-1 reduced excess glucose metabolism, resulting in enhanced generation of SARS-CoV-2- specific CD8+Tc, increased cytokine secretion, and augmented memory cell proliferation. Taken together, our study provides critical insight regarding the cellular mechanisms underlying the effect of SARS-CoV-2 infection on host immune cell metabolism, and highlights immunometabolism as a promising therapeutic target for COVID-19 treatment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.