Harnessing function of EMT in cancer drug resistance: a metastasis regulator determines chemotherapy response.

Epithelial-mesenchymal transition (EMT) is a complicated molecular process that governs cellular shape and function changes throughout tissue development and embryogenesis. In addition, EMT contributes to the development and spread of tumors. Expanding and degrading the surrounding microenvironment, cells undergoing EMT move away from the main location. On the basis of the expression of fibroblast-specific protein-1 (FSP1), fibroblast growth factor (FGF), collagen, and smooth muscle actin (-SMA), the mesenchymal phenotype exhibited in fibroblasts is crucial for promoting EMT. While EMT is not entirely reliant on its regulators like ZEB1/2, Twist, and Snail proteins, investigation of upstream signaling (like EGF, TGF-ß, Wnt) is required to get a more thorough understanding of tumor EMT. Throughout numerous cancers, connections between tumor epithelial and fibroblast cells that influence tumor growth have been found. The significance of cellular crosstalk stems from the fact that these events affect therapeutic response and disease prognosis. This study examines how classical EMT signals emanating from various cancer cells interfere to tumor metastasis, treatment resistance, and tumor recurrence.

Nano-scale delivery systems for siRNA delivery in cancer therapy: New era of gene therapy empowered by nanotechnology.

RNA interference (RNAi) is a unique treatment approach used to decrease a disease's excessive gene expression, including cancer. SiRNAs may find and destroy homologous mRNA sequences within the cell thanks to RNAi processes. However, difficulties such poor cellular uptake, off-target effects, and susceptibility to destruction by serum nucleases in the bloodstream restrict the therapeutic potential of siRNAs. Since some years ago, siRNA-based therapies have been in the process of being translated into the clinic. Therefore, the primary emphasis of this work is on sophisticated nanocarriers that aid in the transport of siRNA payloads, their administration in combination with anticancer medications, and their use in the treatment of cancer. The research looks into molecular manifestations, difficulties with siRNA transport, the design and development of siRNA-based delivery methods, and the benefits and drawbacks of various nanocarriers. The trapping of siRNA in endosomes is a challenge for the majority of delivery methods, which affects the therapeutic effectiveness. Numerous techniques for siRNA release, including as pH-responsive release, membrane fusion, the proton sponge effect, and photochemical disruption, have been studied to overcome this problem. The present state of siRNA treatments in clinical trials is also looked at in order to give a thorough and systematic evaluation of siRNA-based medicines for efficient cancer therapy.

The endocannabinoid system, a new gatekeeper in the pharmacology of human hepatocellular carcinoma.

Despite numerous prevention methodologies and treatment options, hepatocellular carcinoma (HCC) still remains as the third leading life-threatening cancer. It is thus pertinent to develop new treatment modality to fight this devastating carcinoma. Ample recent studies have shown the anti-inflammatory and antitumor roles of the endocannabinoid system in various forms of cancers. Preclinical studies have also confirmed that cannabinoid therapy can be an optimal regimen for cancer treatments. The endocannabinoid system is involved in many cancer-related processes, including induction of endoplasmic reticulum (ER) stress-dependent apoptosis, autophagy, PITRK and ERK signaling pathways, cell invasion, epithelial-mesenchymal transition (EMT), and cancer stem cell (CSC) phenotypes. Moreover, changes in signaling transduction of the endocannabinoid system can be a potential diagnostic and prognostic biomarker for HCC. Due to its pivotal role in lipid metabolism, the endocannabinoid system affects metabolic reprogramming as well as lipid content of exosomes. In addition, due to the importance of non-coding RNAs (ncRNAs), several studies have examined the relationship between microRNAs and the endocannabinoid system in HCC. However, HCC is a pathological condition with high heterogeneity, and therefore using the endocannabinoid system for treatment has faced many controversies. While some studies favored a role of the endocannabinoid system in carcinogenesis and tumor induction, others exhibited the anticancer potential of endocannabinoids in HCC. In this review, specific studies delineating the relationship between endocannabinoids and HCC are examined. Based on collected findings, detailed studies of the molecular mechanism of endocannabinoids as well as preclinical studies for investigating therapeutic or carcinogenic impacts in HCC cancer are strongly suggested.

Tumor-derived exosomal non-coding RNAs as diagnostic biomarkers in cancer.

Almost all clinical oncologists agree that the discovery of reliable, accessible, and non-invasive biomarkers is necessary to decrease cancer mortality. It is possible to employ reliable biomarkers to diagnose cancer in the early stages, predict the patient prognosis, follow up the response to treatment, and estimate the risk of disease recurrence with high sensitivity and specificity. Extracellular vesicles (EVs), especially exosomes, have been the focus of translational research to develop such biomarkers over the past decade. The abundance and distribution of exosomes in bodily fluids, including serum, saliva, and urine, as well as their ability to transport various biomolecules (nucleic acids, proteins, and lipids) derived from their parent cells, make exosomes reliable, accessible, and potent biomarkers for diagnosis and follow-up of solid and hematopoietic tumors. In addition, exosomes play a vital role in various cellular processes, including tumor progression, by participating in intercellular communication. Although these advantages underline the high potential of tumor-derived exosomes as diagnostic biomarkers, the lack of standardized effective methods for their isolation, identification, and precise characterization makes their application challenging in clinical settings. We discuss the importance of non-coding RNAs (ncRNAs) in cellular processes, and the role of tumor-derived exosomes containing ncRNAs as potential biomarkers in several types of cancer. In addition, the advantages and challenges of these studies for translation into clinical applications are covered.

Preoperative and postoperative MRI-based models versus clinical staging systems for predicting early recurrence in hepatocellular carcinoma.

BACKGROUND: To predict the early recurrence of HCC patients who received radical resection using preoperative variables based on Gd-EOB-DTPA enhanced MRI, followed by the comparison with the postoperative model and clinical staging systems. METHODS: One hundred and twenty-nine HCC patients who received radical resection were categorized into the early recurrence group (n = 48) and the early recurrence-free group (n = 81). Through COX regression analysis, statistically significant variables of laboratory, pathologic, and Gd-EOB-DTPA enhanced MRI results were identified. The preoperative and postoperative models were established to predict early recurrence, and the prognostic performances and differences were compared between the two models and clinical staging systems. RESULTS: Six variables were incorporated into the preoperative model, including alpha-fetoprotein (AFP) level, aspartate aminotransferase/platelet ratio index (APRI), rim arterial phase hyperenhancement (rim APHE), peritumoral hypointensity on hepatobiliary phase (HBP), CERHBP (tumor-to-liver SI ratio on hepatobiliary phase imaging), and ADC value. Moreover, the postoperative model was developed by adding microvascular invasion (MVI) and histological grade. The C-index of the preoperative model and postoperative model were 0.889 and 0.901 (p = 0.211) respectively. Using receiver operating characteristic curve analysis (ROC) and decision curve analysis (DCA), it was determined that the innovative models we developed had superior predictive capabilities for early recurrence in comparison to current clinical staging systems. HCC patients who received radical resection were stratified into low-, medium-, and high-risk groups on the basis of the preoperative and postoperative models. CONCLUSION: The preoperative and postoperative MRI-based models built in this study were more competent compared with clinical staging systems to predict the early recurrence in hepatocellular carcinoma.

Approaches for the integration of big data in translational medicine: single-cell and computational methods.

Translational medicine describes a bench-to-bedside approach that eventually converts findings from basic scientific studies into real-world clinical research. It encompasses new treatments, advanced equipment, medical procedures, preventive and diagnostic approaches creating a bridge between basic studies and clinical research. Despite considerable investment in basic science, improvements in technology, and increased knowledge of the biology of human disease, translation of laboratory findings into substantial therapeutic progress has been slower than expected, and the return on investment has been limited in terms of clinical efficacy. In this review, we provide a fresh perspective on some experimental and computational approaches for translational medicine. We cover the analysis, visualization, and modeling of high-dimensional data, with a focus on single-cell technologies, sequence, and structure analysis. Current challenges, limitations, and future directions, with examples from cancer and fibrotic disease, will be discussed.