MicroRNAs as biomarkers and perspectives in the therapy of pancreatic cancer

Calix[6]arene dismantles extracellular vesicle biogenesis and metalloproteinases that support pancreatic cancer hallmarks

Many challenges are faced in pancreatic cancer treatment due to late diagnosis and poor prognosis because of high recurrence and metastasis. Extracellular vesicles (EVs) and matrix metalloproteinases (MMPs), besides acting in intercellular communication, are key players in the cancer cell plasticity responsible for initiating metastasis. Therefore, these entities provide valuable targets for the development of better treatments. In this context, this study aimed to evaluate the potential of calix[6]arene to disturb the release of EVs and the activity of MMPs in pancreatic cancer cells. We found a correlation between the endocytic-associated mediators and the prognosis of pancreatic cancer patients. We observed a more active EV machinery in the pancreatic cancer cell line PANC-1, which was reduced three-fold by treatment with calix[6]arene at subtoxic concentration (5 μM; p 〈0,001). We observed the modulation of 186 microRNAs (164 miRNAs upregulated and 22 miRNAs downregulated) upon calix[6]arene treatment. Interestingly, some of them as miR-4443 and miR-3909, regulates genes HIF1A e KIF13A that are well known to play a role in transport of vesicles. Furthermore, Calix[6]arene downmodulated matrix metalloproteinases (MMPs) -2 and - 9 and disturbed the viability of pancreatic organoids which recapitulate the cellular heterogeneity, structure, and functions of primary tissues. Our findings shed new insights on calix[6]arene's antitumor mechanism, including its intracellular effects on vesicle production and trafficking, as well as MMP activity, which may harm the tumor microenvironment and contribute to a reduction in cancer cell dissemination, which is one of the challenges associated with high mortality in pancreatic cancer.

Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9, and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.

microRNAs (miRNAs) in Glioblastoma Multiforme (GBM)-Recent Literature Review

Glioblastoma multiforme (GBM) is the most common, malignant, poorly promising primary brain tumor. GBM is characterized by an infiltrating growth nature, abundant vascularization, and a rapid and aggressive clinical course. For many years, the standard treatment of gliomas has invariably been surgical treatment supported by radio- and chemotherapy. Due to the location and significant resistance of gliomas to conventional therapies, the prognosis of glioblastoma patients is very poor and the cure rate is low. The search for new therapy targets and effective therapeutic tools for cancer treatment is a current challenge for medicine and science. microRNAs (miRNAs) play a key role in many cellular processes, such as growth, differentiation, cell division, apoptosis, and cell signaling. Their discovery was a breakthrough in the diagnosis and prognosis of many diseases. Understanding the structure of miRNAs may contribute to the understanding of the mechanisms of cellular regulation dependent on miRNA and the pathogenesis of diseases underlying these short non-coding RNAs, including glial brain tumors. This paper provides a detailed review of the latest reports on the relationship between changes in the expression of individual microRNAs and the formation and development of gliomas. The use of miRNAs in the treatment of this cancer is also discussed.

Selective and sensitive detection of miRNA-198 using single polymeric microfiber waveguide platform with heterogeneous CHA amplification strategy

Pancreatic cancer (PC), which has a high fatality rate, is a kind of cancer with poor diagnosis and poor prognosis. Development of selective and sensitive detection platform to diagnose and prognostic of PC has attracted considerable attention. The miRNA-198 has been reported a potential prognostic and early diagnostic marker signature of PC. Herein, we report a novel sensitive detection of miRNA-198 in buffer and serum based on one dimensional chitosan/fluorescein isothiocyanate (CS/FITC) fluorescent microfiber waveguide system combined with the catalytic hairpin assembly amplification strategy. By combination with condensing enrichment effect, the proposed detection platform exhibited high specificity and sensitivity to miRNA-198 target, giving a detection limit as low as 2 fM. More importantly, the proposed detection platform can be applied directly to distinguish the expression of miRNA-198 in clinical serum, affording the ability to distinguish pancreatic cancer patients from those of healthy human beings, and quantify the expression variation of miRNA-198 for the pancreatic cancer patients before and after resection, which may pave the way to develop novel clinical diagnostic equipment for cancer diagnosis and therapeutic evaluation.

Exosomal miR-19a decreases insulin production by targeting Neurod1 in pancreatic cancer associated diabetes

BACKGROUND

New onset diabetes mellitus demonstrates a roughly correlation with pancreatic cancer (PaC), which is unique in PaC and was named as PaC-induced DM, but the inner mechanism remains unclear. Exosomes mediate intercellular communication and bearing microRNAs might be direct constituent of effect in target cells.

METHODS AND RESULTS

The isolated exosomes from PaC cells were used to treat pancreatic β cells or the primary mice islets, and the glucose stimulated insulin secretions were measured. We validated the exosomal miR-19a from PaC cells to be an important mediator in the down regulation of insulin secretion by targeting Neurod1, the validated gene involved in insulin secretion, by using the quantitative real-time PCR, western blot, and promoter luciferase activity. The relative insulin, cAMP and Ca²⁺ expressions were also assayed to verify the inverse correlation between cancerous miR-19a and pancreatic islets Neurod1.

CONCLUSIONS

Our study indicated that signal changes between cancer cells and β cells via exosomes might be important in the pathogenesis of PaC-induced DM and supplemented the pathogenesis of PaC-induced DM and provide a possible access of PaC screening strategy.

Humoral Predictors of Malignancy in IPMN: A Review of the Literature

Pancreatic cystic lesions are increasingly detected in cross-sectional imaging. Intraductal papillary mucinous neoplasm (IPMN) is a mucin-producing subtype of the pancreatic cyst lesions arising from the pancreatic duct system. IPMN is a potential precursor of pancreatic cancer. The transformation of IPMN in pancreatic cancer is progressive and requires the occurrence of low-grade dysplasia, high-grade dysplasia, and ultimately invasive cancer. Jaundice, enhancing mural nodule >5 mm, main pancreatic duct diameter >10 mm, and positive cytology for high-grade dysplasia are considered high-risk stigmata of malignancy. While increased levels of carbohydrate antigen 19-9 (CA 19-9) (>37 U/mL), main pancreatic duct diameter 5-9.9 mm, cyst diameter >40 mm, enhancing mural nodules <5 mm, IPMN-induced acute pancreatitis, new onset of diabetes, cyst grow-rate >5 mm/year are considered worrisome features of malignancy. However, cross-sectional imaging is often inadequate in the prediction of high-grade dysplasia and invasive cancer. Several studies evaluated the role of humoral and intra-cystic biomarkers in the prediction of malignancy in IPMN. Carcinoembryonic antigen (CEA), CA 19-9, intra-cystic CEA, intra-cystic glucose, and cystic fluid cytology are widely used in clinical practice to distinguish between mucinous and non-mucinous cysts and to predict the presence of invasive cancer. Other biomarkers such as cystic fluid DNA sequencing, microRNA (mi-RNA), circulating microvesicles, and liquid biopsy are the new options for the mini-invasive diagnosis of degenerated IPMN. The aim of this study is to review the literature to assess the role of humoral and intracystic biomarkers in the prediction of advanced IPMN with high-grade dysplasia or invasive carcinoma.