Four potential microRNAs affect the progression of pancreatic ductal adenocarcinoma by targeting MET via the PI3K/AKT signaling pathway

A Machine Learning Method for a Blood Diagnostic Model of Pancreatic Cancer Based on microRNA Signatures

This study aimed to construct a blood diagnostic model for pancreatic cancer (PC) using miRNA signatures by a combination of machine learning and biological experimental verification. Gene expression profiles of patients with PC and transcriptome normalization data were obtained from the Gene Expression Omnibus (GEO) database. Using random forest algorithm, lasso regression algorithm, and multivariate cox regression analyses, the classifier of differentially expressed miRNAs was identified based on algorithms and functional properties. Next, the ROC curve analysis was used to evaluate the predictive performance of the diagnostic model. Finally, we analyzed the expression of two specific miRNAs in Capan-1, PANC-1, and MIA PaCa-2 pancreatic cells using qRT-PCR. Integrated microarray analysis revealed that 33 common miRNAs exhibited significant differences in expression profiles between tumor and normal groups (P value < 0.05 and |logFC| > 0.3). Pathway analysis showed that differentially expressed miRNAs were related to P00059 p53 pathway, hsa04062 chemokine signaling pathway, and cancer-related pathways including PC. In ENCORI database, the hsa-miR-4486 and hsa-miR-6075 were identified by random forest algorithm and lasso regression algorithm and introduced as major miRNA markers in PC diagnosis. Further, the receiver operating characteristic curve analysis achieved the area under curve score > 80%, showing good sensitivity and specificity of the two-miRNA signature model in PC diagnosis. Additionally, hsa-miR-4486 and hsa-miR-6075 genes expressions in three pancreatic cells were all up-regulated by qRT-PCR. In summary, these findings suggest that the two miRNAs, hsa-miR-4486 and hsa-miR-6075, could serve as valuable prognostic markers for PC.

Effect of miR-27b on the proliferation and apoptosis of diffuse large b-cell lymphoma cells by targeting the regulation of MET/PI3K/AKT pathway

BACKGROUND

This study aimed to explore the regulation of miR-27b expression on MET/PI3K/AKT pathway, and to explain its effect on biological functions of DLBCL cells.

METHODS

The expressions of miR-27b and MET gene in DLBCL cells and normal human B cell lines were determined by qRT-PCR. miR-27b expression in DLBCL cell line Toledo was over-expressed with the cell transfection method. The proliferation of DLBCL cells was determined by MTT. And the invasiveness of DLBCL cells was determined by Transwell. The level of apoptosis in DLBCL cells was determined by ELISA. miR-27b targeting of MET was verified by dual- luciferase reporter assay. The activation of MET/PI3K/AKT pathway and the expression of downstream related proteins were determined by Western blot.

RESULTS

The results showed that miR-27b was poorly expressed in DLBCL cell lines compared with normal human B cell lines, and was associated with its high proliferation, high invasiveness and low apoptosis level. High miR-27b expression can reduce the proliferation and increase the apoptosis level in DLBCL cells. By examining the effect of miR-27b over-expression on the MET/PI3K/AKT pathway, it was found that miR-27b can inhibit the proliferation and invasiveness and promote the apoptosis of DLBCL cells by targeting the inhibition of MET expression and the activation of PI3K/AKT pathway.

CONCLUSION

miR-27b can inhibit the proliferation and invasiveness of DLBCL cells and promote the apoptosis of the cells by targeting MET/PI3K/AKT pathway.

Circulating Nucleic Acids as Novel Biomarkers for Pancreatic Ductal Adenocarcinoma

Despite considerable advancements in the clinical management of PDAC it remains a significant cause of mortality. PDAC is often diagnosed at advanced stages due to vague symptoms associated with early-stage disease and a lack of reliable diagnostic biomarkers. Late diagnosis results in a high proportion of cases being ineligible for surgical resection, the only potentially curative therapy for PDAC. Furthermore, a lack of prognostic biomarkers impedes clinician's ability to properly assess the efficacy of therapeutic interventions. Advances in our ability to detect circulating nucleic acids allows for the advent of novel biomarkers for PDAC. Tumor derived circulating and exosomal nucleic acids allow for the detection of PDAC-specific mutations through a non-invasive blood sample. Such biomarkers could expand upon the currently limited repertoire of tests available. This review outlines recent developments in the use of molecular techniques for the detection of these nucleic acids and their potential roles, alongside current techniques, in the diagnosis, prognosis and therapeutic governance of PDAC.

Biomarkers for early detection of pancreatic cancer - miRNAs as a potential diagnostic and therapeutic tool?

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies, with poor prognosis resulting mostly from late diagnosis. Surgery remains the most effective treatment and early detection significantly increases the overall survival. Biomarkers used for diagnosis and to monitor the response to treatment, such as carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA), are not adequate as early detection markers of PDAC, partly due to low sensitivity/specificity. Therefore, new biomarkers for PDAC are critically needed. This review aims at recent advancements in the identification and characterization of new biomarkers, microRNAs, which might prove useful in the early detection of PDAC.