Serum level of co-expressed hub miRNAs as diagnostic and prognostic biomarkers for pancreatic ductal adenocarcinoma

A comprehensive meta-analysis of transcriptome data to identify signature genes associated with pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 5%. Absence of symptoms at primary tumor stages, as well as high aggressiveness of the tumor can lead to high mortality in cancer patients. Most patients are recognized at the advanced or metastatic stage without surgical symptom, because of the lack of reliable early diagnostic biomarkers. The objective of this work was to identify potential cancer biomarkers by integrating transcriptome data.

METHODS

Several transcriptomic datasets comprising of 11 microarrays were retrieved from the GEO database. After pre-processing, a meta-analysis was applied to identify differentially expressed genes (DEGs) between tumor and nontumor samples for datasets. Next, co-expression analysis, functional enrichment and survival analyses were used to determine the functional properties of DEGs and identify potential prognostic biomarkers. In addition, some regulatory factors involved in PDAC including transcription factors (TFs), protein kinases (PKs), and miRNAs were identified.

RESULTS

After applying meta-analysis, 1074 DEGs including 539 down- and 535 up-regulated genes were identified. Pathway enrichment analyzes using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that DEGs were significantly enriched in the HIF-1 signaling pathway and focal adhesion. The results also showed that some of the DEGs were assigned to TFs that belonged to 23 conserved families. Sixty-four PKs were identified among the DEGs that showed the CAMK family was the most abundant group. Moreover, investigation of corresponding upstream regions of DEGs identified 11 conserved sequence motifs. Furthermore, weighted gene co-expression network analysis (WGCNA) identified 8 modules, more of them were significantly enriched in Ras signaling, p53 signaling, MAPK signaling pathways. In addition, several hubs in modules were identified, including EMP1, EVL, ELP5, DEF8, MTERF4, GLUP1, CAPN1, IGF1R, HSD17B14, TOM1L2 and RAB11FIP3. According to survival analysis, it was identified that the expression levels of two genes, EMP1 and RAB11FIP3 are related to prognosis.

CONCLUSION

We identified several genes critical for PDAC based on meta-analysis and system biology approach. These genes may serve as potential targets for the treatment and prognosis of PDAC.

Identification of formononetin as the active compound of CR-SR in hepatocellular carcinoma treatment: An integrated approach combining network pharmacology and weighted gene co-expression networks

Hepatocellular carcinoma (HCC) is a life-threatening disease for which there is no cure. Traditional Chinese medicine is a treasure trove of Medicinals that has been used for thousands of years. In China, the traditional herb pair, Curcumae Rhizoma and Sparganii Rhizoma (CR-SR) represent a classic herbal combination used for the treatment of HCC. However, the drug targets and pharmacological mechanism of action of CR-SR in the treatment of HCC are unclear. To address this, we screened the active components and drug targets of CR-SR from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and a high-throughput experiment- and reference-guided database of traditional Chinese medicines (HERB database). Combined with the weighted co-expression network analysis of dataset GSE76427, we constructed an active component-target-disease regulatory network. It was found that CR-SR's active components for HCC treatment included trans-gondoic acid, beta-sitosterol, stigmasterol, hederagenin, and formononetin. These compounds specifically targeted the genes Estrogen Receptor 1 (ESR1), Cyclin A2 (CCNA2), Checkpoint Kinase 1 (CHEK1), and Nuclear Receptor Coactivator 2 (NCOA2). ESR1, CCNA2, and CHEK1 genes showed significant differences in survival prognosis, expression levels, and statistical significance during the pathological stage. Moreover, their high affinity for formononetin was determined through molecular docking analysis. Cell assays and high-throughput sequencing were performed to reveal that the inhibitory effect of formononetin on HepG2 cell proliferation was related to hepatocyte metabolism and cell cycle regulation-related pathways. This study provides insights into potential HCC treatments.

Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model

Background

Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications.

Methods

In this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method.

Results

Our analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age.

Conclusion

Our study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.

A Comprehensive Study on Signal Transduction and Therapeutic Role of miR-877 in Human Cancers

MicroRNAs are a group of short non-coding RNAs (miRNAs), which are epigenetically involved in gene expression and other cellular biological processes and can be considered as potential biomarkers for cancer detection and support for treatment management. This review aims to amass the evidence in order to reach the molecular mechanism and clinical significance of miR-877 in different types of cancer. Dysregulation of miR-877 level in various types of malignancies as bladder cancer, cervical cancer, cholangiocarcinoma, colorectal cancer (CRC), gastric cancer, glioblastoma, head and neck squamous cell carcinoma (HNSCC), hepatocellular carcinoma, laryngeal squamous cell carcinoma, melanoma, non-small cell lung cancer (NSCLC), oral squamous cell carcinoma, ovarian cancer (OC), pancreatic ductal adenocarcinoma, and renal cell carcinoma (RCC) have reported, significantly increase or decrease in its level, which can be indicated to its function as oncogene or tumor suppressor. MiR-877 is involved in cell proliferation, migration, and invasion through cell cycle pathways in cancer. MiR-877 could be potential a candidate as a valuable biomarker for prognosis in various cancers. Through this study, we proposed that miR-877 can potentially be a candidate as a prognostic marker for early detection of tumor development, progression, as well as metastasis.

Expression pattern of miR-16-2-3p and its prognostic values on pediatric acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is a debilitating illness that easily occurs in adolescents. microRNAs (miRNAs) are potential biomarkers for multiple diseases. This paper was to elaborate on the expression of miR-16-2-3p in childhood ALL and its clinical values on ALL diagnosis and prognosis. First, serum miR-16-2-3p expression in ALL children and healthy volunteers was measured using RT-qPCR. Next, diagnostic potential and prognostic values of miR-16-2-3p on ALL were analyzed through receiver operating characteristic (ROC) curve, Kaplan-Meier survival curve, and multivariate Cox regression analysis, respectively. No significant difference was observed in the clinical baseline data between ALL patients and healthy children. ALL patients showed downregulated serum miR-16-2-3p (0.65 ± 0.27) (p < .01), whose area under the ROC curve was 0.837 with a cut-off value of 0.745 (67.92% sensitivity, 96.94% specificity). ALL patients with higher miR-16-2-3p expression had higher survival rates than those with lower miR-16-2-3p expression. Low miR-16-2-3p expression predicted poor prognosis of ALL patients. After adjusting LDH and lymphomyelocyte proportion (p = 0.003, HR = 0.003, 95%CI = 0.000-0.145), miR-16-2-3p was recognized as an independent prognostic factor for ALL patient survival. Briefly, low serum miR-16-2-3p expression in ALL children could aid ALL diagnosis and predict poor prognosis.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

MiR-3201 as a Prognostic Blood Biomarker for Curative Treatments in Hepatocellular Carcinoma

Background: Hepatic resection, radiofrequency ablation (RF), and liver transplantation (LT) represent the only available curative treatments for early stage hepatocellular carcinoma (HCC). Various studies showed that the 5-year overall survival (OS) rate reaches ∼70% after resection and ∼60% after RF. Objective: To improve the success rate of curative therapies and consequently the OS, an improvement in patients' selection and management should be pursued. In this regard, microRNAs (miRNAs) can be helpful prognostic biomarkers. Materials and Methods: In this retrospective study, a miRNA array profiling was performed on 34 HCC blood samples which is collected before therapy (T0), 1 month (T1), and 6 months (T2) after curative treatments (resection and RF) to identify noninvasive biomarker candidates for therapy response and OS. MiRNAs were validated in 80 blood HCC samples using quantitative real-time PCR (qRT-PCR). Patients were divided into complete responder (CR) and partial responder and progressive disease (PRPD). Results: Among the selected miRNAs, miR-3201 is significantly associated with treatment response in the validation phase, showing a 23% reduction (P = .026) in CR compared to PRPD. MiR-3201 was able to distinguish CR from PRPD (area under the curve [AUC] = 0.69, 71% sensitivity, 70% specificity, P = .0036). Furthermore, lower levels of miR-3201 were associated with longer OS (hazard ratio [HR] = 2.61, P = .0006). Conclusions: Blood miR-3201 could be used as a prognostic biomarker for curative therapy response and OS in HCC.

The implication of liquid biopsies to predict chemoresistance in pancreatic cancer

Pancreatic cancer is one of the most aggressive diseases among solid tumors. Most patients are diagnosed with advanced or metastatic disease and are characterized by poor chemosensitivity. Therefore, earlier diagnosis and novel therapeutic possibilities for pancreatic cancer patients are urgently needed. Liquid biopsy is an emerging technology that allows the noninvasive sampling of tumor material. Nowadays, liquid biopsy has shown promising results as diagnostic, prognostic and predictive biomarkers, but it has not yet been universally adopted into regular use by clinicians. In this review, we describe different components of liquid biopsy, especially circulating tumor cells, circulating tumor DNA and exosomes and their potential clinical utility for pancreatic cancer patients.

MiR-877 suppresses gastric cancer progression by downregulating AQP3

OBJECTIVES

Gastric cancer (GC) is the leading cause of cancer-related deaths worldwide; however, the underlying molecular mechanisms of GC remain unclear. This study investigated the role of the miR-877-AQP3 axis in GC tumorigenesis.

METHODS

The levels of miR-877 expression were measured in GC tissues and cell lines by qRT-PCR. Functional assays were performed to elucidate the role of miR-877 in GC development.

RESULTS

Our results showed that miR-877 levels were lower in GC tissues and cell lines compared with the corresponding controls. Additionally, reduced miR-877 levels were associated with unfavorable prognoses. Increased miR-877 expression suppressed proliferation, invasion, and epithelial-mesenchymal transition, while promoting apoptosis in GC cells. Luciferase reporter assays showed that aquaporin 3 (AQP3) was a direct downstream target of miR-877. Overexpression of AQP3 partially rescued the tumor suppressive effects of miR-877 in GC cells. Moreover, miR-877 was negatively correlated with AQP3 mRNA expression in GC tissues.

CONCLUSIONS

This study demonstrated that miR-877 plays a suppressive role in GC tumorigenesis by regulating AQP3.

Understanding the Molecular Mechanism of miR-877-3p Could Provide Potential Biomarkers and Therapeutic Targets in Squamous Cell Carcinoma of the Cervix

No therapeutic targets and molecular biomarkers are available in cervical cancer (CC) management. In other cancer types, micro-RNA-877-3p (miR-877-3p) has been associated with events relevant for CC development. Thus, we aimed to determine miR-877-3p role in CC. miR-877-3p levels were examined by quantitative-PCR in 117 cervical lesions and tumors. Effects on CC cell proliferation, migration, and invasion were evaluated upon anti-miR-877-3p transfection. miR-877-3p dependent molecular mechanism was comprehensively explored by proteomics, dual-luciferase reporter assay, western blot, and immunohistochemistry. Cervical tumors expressed higher miR-877-3p levels than benign lesions. miR-877-3p promoted CC cell migration and invasion, at least partly by modulating cytoskeletal protein folding through the chaperonin-containing T-complex protein 1 complex. Notably, miR-877-3p silencing synergized with paclitaxel. Interestingly, miR-877-3p downregulated the levels of an in silico-predicted target, ZNF177, whose expression and subcellular location significantly distinguished high-grade squamous intraepithelial lesions (HSILs) and squamous cell carcinomas of the cervix (SCCCs). Cytoplasmic ZNF177 was significantly associated with worse progression-free survival in SCCC. Our results suggest that: (i) miR-877-3p is a potential therapeutic target whose inhibition improves paclitaxel effects; (ii) the expression and location of its target ZNF177 could be diagnostic biomarkers between HSIL and SCCC; and (iii) cytoplasmic ZNF177 is a poor-prognosis biomarker in SCCC.

Identification of novel candidate biomarkers for pancreatic adenocarcinoma based on TCGA cohort

Pancreatic adenocarcinoma (PAAD) is the most serious solid tumor type throughout the world. The present study aimed to identify novel biomarkers and potential efficacious small drugs in PAAD using integrated bioinformatics analyses. A total of 4777 differentially expressed genes (DEGs) were filtered, 2536 upregulated DEGs and 2241 downregulated DEGs. Weighted gene co-expression network analysis was then used and identified 12 modules, of which, blue module with the most significant enrichment result was selected. KEGG and GO enrichment analyses showed that all DEGs of blue module were enriched in EMT and PI3K/Akt pathway. Three hub genes (ITGB1, ITGB5, and OSMR) were determined as key genes with higher expression levels, significant prognostic value and excellent diagnostic efficiency for PAAD. Additionally, some small molecule drugs that possess the potential to treat PAAD were screened out, including thapsigargin (TG). Functional in vitro experiments revealed that TG repressed cell viability via inactivating the PI3K/Akt pathway in PAAD cells. Totally, our findings identified three key genes implicated in PAAD and screened out several potential small drugs to treat PAAD.

Identification of key modules and hub genes in glioblastoma multiforme based on co-expression network analysis

Glioblastoma multiforme (GBM) is the most malignant primary tumour in the central nervous system, but the molecular mechanisms underlying its pathogenesis remain unclear. In this study, data set GSE50161 was used to construct a co‐expression network for weighted gene co‐expression network analysis. Two modules (dubbed brown and turquoise) were found to have the strongest correlation with GBM. Functional enrichment analysis indicated that the brown module was involved in the cell cycle, DNA replication, and pyrimidine metabolism. The turquoise module was primarily related to circadian rhythm entrainment, glutamatergic synapses, and axonal guidance. Hub genes were screened by survival analysis using The Cancer Genome Atlas and Human Protein Atlas databases and further tested using the GSE4290 and Gene Expression Profiling Interactive Analysis databases. The eight hub genes (NUSAP1, SHCBP1, KNL1, SULT4A1, SLC12A5, NUF2, NAPB, and GARNL3) were verified at both the transcriptional and translational levels, and these gene expression levels were significant based on the World Health Organization classification system. These hub genes may be potential biomarkers and therapeutic targets for the accurate diagnosis and management of GBM.

A new 7-gene survival score assay for pancreatic cancer patient prognosis prediction

Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS). Then, according to the optimal value of the cross-validation curve (lambda = 0.031), 7 non-zero coefficients (ARNTL2, DSG3, PTPRR, ANLN, S100A14, ANKRD22, and TSPAN7) were selected to establish a prognostic prediction model of PDAC patients. We further confirmed the expression level of 7 genes using RT-PCR, western blot, and immunohistochemistry staining in PDAC patients' tissues. Our results showed that the ROC curve of the 7-mRNA model indicated good predictive ability for 1- and 2-year OS in three datasets (TCGA: 0.71, 0.69; ICGC: 0.8, 0.74; GEO batch: 0.61, 0.7, respectively). The hazard ratio (HR) of the low-risk group had a similar significant result (TCGA: HR = 0.3723; ICGC: HR = 0.2813; GEO batch: HR = 0.4999; all P < 0.001). Furthermore, Log-rank test results in three cohorts showed that the 7-mRNA assay excellently predicted the prognosis and metastasis, especially in TNM stage I&II subgroups of PDAC. In conclusion, the strong validation of our 7-mRNA signature indicates the promising effectiveness of its clinical application, especially in patients with TNM stages I&II.

The Emerging Role of miRNAs for the Radiation Treatment of Pancreatic Cancer

Simple Summary

Pancreatic cancer is an aggressive disease with a high mortality rate. Radiotherapy is one treatment option within a multimodal therapy approach for patients with locally advanced, non-resectable pancreatic tumors. However, radiotherapy is only effective in about one-third of the patients. Therefore, biomarkers that can predict the response to radiotherapy are of utmost importance. Recently, microRNAs, small non-coding RNAs regulating gene expression, have come into focus as there is growing evidence that microRNAs could serve as diagnostic, predictive and prognostic biomarkers in various cancer entities, including pancreatic cancer. Moreover, their high stability in body fluids such as serum and plasma render them attractive candidates for non-invasive biomarkers. This article describes the role of microRNAs as suitable blood biomarkers and outlines an overview of radiation-induced microRNAs changes and the association with radioresistance in pancreatic cancer.

Abstract

Today, pancreatic cancer is the seventh leading cause of cancer-related deaths worldwide with a five-year overall survival rate of less than 7%. Only 15–20% of patients are eligible for curative intent surgery at the time of diagnosis. Therefore, neoadjuvant treatment regimens have been introduced in order to downsize the tumor by chemotherapy and radiotherapy. To further increase the efficacy of radiotherapy, novel molecular biomarkers are urgently needed to define the subgroup of pancreatic cancer patients who would benefit most from radiotherapy. MicroRNAs (miRNAs) could have the potential to serve as novel predictive and prognostic biomarkers in patients with pancreatic cancer. In the present article, the role of miRNAs as blood biomarkers, which are associated with either radioresistance or radiation-induced changes of miRNAs in pancreatic cancer, is discussed. Furthermore, the manuscript provides own data of miRNAs identified in a pancreatic cancer mouse model as well as radiation-induced miRNA changes in the plasma of tumor-bearing mice.

Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients

The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum samples from 20 patients with hepatocellular carcinoma (HCC) were profiled through miRNA 3.0 gene array and miRNAs biomarker candidates were identified through WGCNA. Results were validated by qRT-PCR in 102 HCC serum samples collected at diagnosis. WGCNA identified 16 miRNA modules, nine of them were significantly associated with the clinical characteristics of the patient. The Red module had a significant negative correlation with patients Survival (− 0.59, p = 0.007) and albumin (− 0.52, p = 0.02), and a positive correlation with PCR (0.61, p = 0.004) and alpha-fetoprotein (0.51, p = 0.02). In the red module, 16 circulating miRNAs were significantly associated with patient survival. MiR-3185 and miR-4507 were identified as predictors of patient survival after the validation phase. At diagnosis, high expression of circulating miR-3185 and miR-4507 identifies patients with longer survival (HR 2.02, 95% CI 1.10–3.73, p = 0.0086, and HR of 1.75, 95% CI 1.02–3.02, p = 0.037, respectively). Thought a WGCNA we identified miR-3185 and miR-4507 as promising candidate biomarkers predicting a longer survival in HCC patients.

Four genes relevant to pathological grade and prognosis in ovarian cancer

BACKGROUND: Ovarian cancer is the common tumor in female, the prognostic of which is influenced by a series of factors. In this study, 4 genes relevant to pathological grade in ovarian cancer were screened out by the construction of weighted gene co-expression network analysis. METHODS: GSE9891 with 298 ovarian cancer cases had been used to construct co-expression networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses was used to analyze the possible mechanism of genes involved in the malignant process of ovarian cancer. Hub genes were validated in other independent datasets, such as GSE63885, GSE26193 and GSE30161. Survival analysis based on the hub genes was performed by website of Kaplan Meier-plotter. RESULTS: The result based on weighted gene co-expression network analysis indicated that turquoise module has the highest association with pathological grade. Gene Ontology enrichment analysis revealed that the genes in turquoise module main enrichment in inflammatory response and immune response. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the genes in turquoise module main enrichment in cytokine-cytokine receptor interaction and chemokine signaling pathway. In turquoise module, a total of 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were identified. Then, 4 hub genes were effectively verified in the test datasets (GSE63885, GSE26193 and GSE30161) and tissue samples from Shengjing Hospital of China Medical University. Survival analysis indicated that the 4 hub genes were associated with poor progression-free survival of ovarian cancer. CONCLUSIONS: In conclusion, 4 hub genes (MS4A4A, CD163, CPR65, MS4A6A) were verified associated with pathological grade of ovarian cancer. Moreover, MS4A4A, CD163, MS4A6A may serve as a surface marker for M2 macrophages. Targeting the 4 hub genes may can improve the prognosis of ovarian cancer.

Prognostic value of microRNAs in pancreatic cancer: a meta-analysis

BACKGROUND

The prognostic impact of microRNA (miRNA) expression levels in pancreatic cancer (PC) has been estimated for years, but the outcomes are controversial and heterogeneous. Therefore, we comprehensively reviewed the evidence collected on miRNA expression in PC to determine this effect.

RESULTS

PC patients with high miR-21 (HR=2.61, 95%CI=1.68-4.04), miR-451a (HR=2.23, 95%CI=1.23-4.04) or miR-1290 (HR=1.43, 95%CI=1.04-1.95) levels in blood had significantly poorer OS (P<0.05). Furthermore, PC patients with high miR-10b (HR=1.73, 95%CI=1.09-2.76), miR-17-5p (HR=1.91, 95%CI=1.30-2.80), miR-21 (HR=1.90, 95%CI=1.61-2.25), miR-23a (HR=2.18, 95%CI=1.52-3.13), miR-155 (HR=2.22, 95%CI=1.27-3.88), miR-203 (HR=1.65, 95%CI=1.14-2.40), miR-221 (HR=1.72, 95%CI=1.08-2.74), miR-222 levels (HR=1.72, 95%CI=1.02-2.91) or low miR-29c (HR=1.39, 95%CI=1.08-1.79), miR-126 (HR=1.55, 95%CI=1.23-1.95), miR-218 (HR=2.62, 95%CI=1.41-4.88) levels in tissues had significantly shorter OS (P<0.05).

CONCLUSIONS

In summary, blood miR-21, miR-451a, miR-1290 and tissue miR-10b, miR-17-5p, miR-21, miR-23a, miR-29c, miR-126, miR-155, miR-203, miR-218, miR-221, miR-222 had significant prognostic value.

METHODS

We searched PubMed, EMBASE, Web of Science and Cochrane Database of Systematic Reviews to recognize eligible studies, and 57 studies comprising 5445 PC patients and 15 miRNAs were included to evaluate the associations between miRNA expression levels and overall survival (OS) up to June 1, 2019. Summary hazard ratios (HR) with 95% confidence intervals (CI) were calculated to assess the effect.

Effects of Cardiac Sympathetic Neurodegeneration and PPARγ Activation on Rhesus Macaque Whole Blood miRNA and mRNA Expression Profiles

Degeneration of sympathetic innervation of the heart occurs in numerous diseases, including diabetes, idiopathic REM sleep disorder, and Parkinson's disease (PD). In PD, cardiac sympathetic denervation occurs in 80-90% of patients and can begin before the onset of motor symptoms. Today, there are no disease-modifying therapies for cardiac sympathetic neurodegeneration, and biomarkers are limited to radioimaging techniques. Analysis of expression levels of coding mRNA and noncoding RNAs, such as microRNAs (miRNAs), can uncover pathways involved in disease, leading to the discovery of biomarkers, pathological mechanisms, and potential drug targets. Whole blood in particular is a clinically relevant source of biomarkers, as blood sampling is inexpensive and simple to perform. Our research group has previously developed a nonhuman primate model of cardiac sympathetic denervation by intravenous administration of the catecholaminergic neurotoxin 6-hydroxydopamine (6-OHDA). In this rhesus macaque (Macaca mulatta) model, imaging with positron emission tomography showed that oral administration of the peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone (n = 5; 5 mg/kg daily) significantly decreased cardiac inflammation and oxidative stress compared to placebo (n = 5). Here, we report our analysis of miRNA and mRNA expression levels over time in the whole blood of these monkeys. Differential expression of three miRNAs was induced by 6-OHDA (mml-miR-16-2-3p, mml-miR-133d-3p, and mml-miR-1262-5p) and two miRNAs by pioglitazone (mml-miR-204-5p and mml-miR-146b-5p) at 12 weeks posttoxin, while expression of mRNAs involved in inflammatory cytokines and receptors was not significantly affected. Overall, this study contributes to the characterization of rhesus coding and noncoding RNA profiles in normal and disease-like conditions, which may facilitate the identification and clinical translation of biomarkers of cardiac neurodegeneration and neuroprotection.

The elevation of S100B and downregulation of circulating miR-602 in the sera of ischemic stroke (IS) patients: the emergence of novel diagnostic and prognostic markers

Ischemic stroke (IS) is a major cause of mortality and disability. However, no reliable prognostic or diagnostic biomarker has been utilized to date. Here, we have evaluated the serum S100B concentration and miR-602 expression as potential biomarkers for IS. Fifty-two IS patients and 52 age- and sex-matched healthy volunteers were enrolled. Blood samples were collected from all patients at the time of admission, 24 and 48 h later, at the time of discharge, and 3 months later. Real-time (RT) PCR was used to measure the serum level of miR602. We also measured the serum concentration of S100B using ELISA. As compared with healthy subjects, IS patients had a higher level of serum S100B and lower serum miR-602. ROC curve analyses revealed that miR-602 (AUC = 0.8168; P < 0.0001) and S100B (AUC = 0.8699; P < 0.0001) had acceptable ability to differentiate between IS patients from healthy subjects. Furthermore, serum S100B was a reliable predictor of the survival outcome at 3 months (P = 0.021). The expression of miR-602 was significantly higher in patients with bigger NIHSS scores. The lower levels of miR-602 and higher concentration of S100B in the sera of IS patients could be associated with clinically significant diagnostic utilities. S100B could be also introduced as a reliable prognostic marker for stroke and implemented in future research.

miR-939-5p Contributes to the Migration and Invasion of Pancreatic Cancer by Targeting ARHGAP4

OBJECTIVE

Rho GTPase-activating protein 4 (ARHGAP4) is a GTPase-activating protein for the small GTPases of the Rho family that is involved in tumorigenesis. We recently reported that ARHGAP4 can mediate Warburg effect and malignant phenotype of pancreatic cancer. However, the regulation of ARHGAP4 remains unclear.

METHODS

ARHGAP4 and miR-939-5p expressions in pancreatic cancer tissues and cell lines were measured by real-time PCR or Western blotting. Pancreatic cancer cells were transfected with miR-939-5p inhibitor, miR-939-5p mimic and/or lentivirus expressing ARHGAP4, and the cell viability, invasion and migration were measured by CCK-8 and Transwell assay, respectively. The suppression of ARHGAP4 expression by miR-939-5p was revealed by luciferase reporter assay, real-time PCR or Western blotting.

RESULTS

ARHGAP4 expression was decreased, while miR-939-5p was increased in pancreatic cancer tissues compared with adjacent-normal pancreatic tissues. Higher miR-939-5p expression was correlated with advanced pathological stages and poor prognosis of pancreatic cancer patients. miR-939-5p directly targeted ARHGAP4. Either miR-939-5p down-regulation or ARHGAP4 overexpression inhibited viability, invasion and migration of pancreatic cancer cells. However, ARHGAP4 overexpression markedly inhibited the increased viability, migration, and invasion induced by miR-939-5p up-regulation in pancreatic cancer cells.

CONCLUSION

These observations suggested that miR-939-5p regulates the malignant phenotype of pancreatic cancer cells by targeting ARHGAP4, establishing miR-939-5p as a novel regulator of ARHGAP4 with a critical role in tumorigenesis in pancreatic cancer.

Serum miR-1290 and miR-1246 as Potential Diagnostic Biomarkers of Human Pancreatic Cancer

Background: Pancreatic cancer (PC) is a highly malignant tumor with no effective early diagnostic biomarkers. This study was performed to screen and identify serum microRNAs (miRNAs) as noninvasive biomarkers for PC diagnosis.

Methods: Two upregulated miRNAs were selected by integrated analysis of three independent GEO datasets. Then, the expressions of two miRNAs in serum were determined by quantitative reverse-transcription PCR among 120 PC patients, 40 benign disease controls and 40 healthy controls. The correlation between serum miRNAs and clinical characteristics was analyzed. The diagnostic utility of miRNAs was compared to CA19-9 using receiver operating characteristic curve analysis.

Results: We discovered miR-1290 and miR-1246 were upregulated in PC patients through GEO datasets analysis. Serum miR-1290 and miR-1246 expression levels were elevated in PC patients compared to all controls and dramatically decreased after tumor resection (all P<0.001). The area under the curve (AUC) for miR-1290 was larger than miR-1246 and CA19-9 (miR-1290: 0.91; miR-1246: 0.81; CA19-9: 0.82). The combined diagnosis of individual or both miRNAs with CA19-9 was more effective for discriminating PC from all controls than the single CA19-9 assay (miR-1290+CA19-9: 0.96, miR-1246+CA19-9: 0.93, miR-1290+miR-1246+CA19-9: 0.97). The abundance of serum miR-1290 and miR-1246 was associated with tumor stage and size respectively and logistic modeling proved that both of them were independent risk factors for PC.

Conclusion: Serum miR-1290 and miR-1246 might be promising biomarkers for PC diagnosis and the combined detection of CA19-9, together with miR-1290 or miR-1246, could improve the diagnostic accuracy of PC.

Cell-Free DNA Methylation: The New Frontiers of Pancreatic Cancer Biomarkers' Discovery

Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancer types world-wide. Its high mortality is related to the difficulty in the diagnosis, which often occurs when the disease is already advanced. As of today, no early diagnostic tests are available, while only a limited number of prognostic tests have reached clinical practice. The main reason is the lack of reliable biomarkers that are able to capture the early development or the progression of the disease. Hence, the discovery of biomarkers for early diagnosis or prognosis of PDAC remains, de facto, an unmet need. An increasing number of studies has shown that cell-free DNA (cfDNA) methylation analysis represents a promising non-invasive approach for the discovery of biomarkers with diagnostic or prognostic potential. In particular, cfDNA methylation could be utilized for the identification of disease-specific signatures in pre-neoplastic lesions or chronic pancreatitis (CP), representing a sensitive and non-invasive method of early diagnosis of PDAC. In this review, we will discuss the advantages and pitfalls of cfDNA methylation studies. Further, we will present the current advances in the discovery of pancreatic cancer biomarkers with early diagnostic or prognostic potential, focusing on pancreas-specific (e.g., CUX2 or REG1A) or abnormal (e.g., ADAMTS1 or BNC1) cfDNA methylation signatures in high risk pre-neoplastic conditions and PDAC.

Systems biology-based investigation of cooperating microRNAs as monotherapy or adjuvant therapy in cancer

MicroRNAs (miRNAs) are short, noncoding RNAs that regulate gene expression by suppressing mRNA translation and reducing mRNA stability. A miRNA can potentially bind many mRNAs, thereby affecting the expression of oncogenes and tumor suppressor genes as well as the activity of whole pathways. The promise of miRNA therapeutics in cancer is to harness this evolutionarily conserved mechanism for the coordinated regulation of gene expression, and thus restoring a normal cell phenotype. However, the promiscuous binding of miRNAs can provoke unwanted off-target effects, which are usually caused by high-dose single-miRNA treatments. Thus, it is desirable to develop miRNA therapeutics with increased specificity and efficacy. To achieve that, we propose the concept of miRNA cooperativity in order to exert synergistic repression on target genes, thus lowering the required total amount of miRNAs. We first review miRNA therapies in clinical application. Next, we summarize the knowledge on the molecular mechanism and biological function of miRNA cooperativity and discuss its application in cancer therapies. We then propose and discuss a systems biology approach to investigate miRNA cooperativity for the clinical setting. Altogether, we point out the potential of miRNA cooperativity to reduce off-target effects and to complement conventional, targeted, or immune-based therapies for cancer.

Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is a class of the commonest malignant carcinomas. The present study aimed to elucidate the potential biomarker and prognostic targets in PDAC. The array data of GSE41368, GSE43795, GSE55643, and GSE41369 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and differentially expressed microRNAs (DEmiRNAs) in PDAC were obtained by using GEO2R, and overlapped DEGs were acquired with Venn Diagrams. Functional enrichment analysis of overlapped DEGs and DEmiRNAs was conducted with Metascape and FunRich, respectively. The protein-protein interaction (PPI) network of overlapped DEGs was constructed by STRING and visualized with Cytoscape. Overall survival (OS) of DEmiRNAs and hub genes were investigated by Kaplan-Meier (KM) plotter (KM plotter). Transcriptional data and correlation analyses among hub genes were verified through GEPIA and Human Protein Atlas (HPA). Additionally, miRNA targets were searched using miRTarBase, then miRNA-DEG regulatory network was visualized with Cytoscape. A total of 32 DEmiRNAs and 150 overlapped DEGs were identified, and Metascape showed that DEGs were significantly enriched in cellular chemical homeostasis and pathways in cancer, while DEmiRNAs were mainly enriched in signal transduction and Glypican pathway. Moreover, seven hub genes with a high degree, namely, V-myc avian myelocytomatosis viral oncogene homolog (MYC), solute carrier family 2 member 1 (SLC2A1), PKM, plasminogen activator, urokinase (PLAU), peroxisome proliferator activated receptor γ (PPARG), MET proto-oncogene, receptor tyrosine kinase (MET), and integrin subunit α 3 (ITGA3), were identified and found to be up-regulated between PDAC and normal tissues. miR-135b, miR-221, miR-21, miR-27a, miR-199b-5p, miR-143, miR-196a, miR-655, miR-455-3p, miR-744 and hub genes predicted poor OS of PDAC. An integrative bioinformatics analysis identified several hub genes that may serve as potential biomarkers or targets for early diagnosis and precision target treatment of PDAC.

The Clinical Potential of Oligonucleotide Therapeutics against Pancreatic Cancer

Although many diagnostic and therapeutic modalities for pancreatic cancer have been proposed, an urgent need for improved therapeutic strategies remains. Oligonucleotide therapeutics, such as those based on antisense RNAs, small interfering RNA (siRNA), microRNA (miRNA), aptamers, and decoys, are promising agents against pancreatic cancer, because they can identify a specific mRNA fragment of a given sequence or protein, and interfere with gene expression as molecular-targeted agents. Within the past 25 years, the diversity and feasibility of these drugs as diagnostic or therapeutic tools have dramatically increased. Several clinical and preclinical studies of oligonucleotides have been conducted for patients with pancreatic cancer. To support the discovery of effective diagnostic or therapeutic options using oligonucleotide-based strategies, in the absence of satisfactory therapies for long-term survival and the increasing trend of diseases, we summarize the current clinical trials of oligonucleotide therapeutics for pancreatic cancer patients, with underlying preclinical and scientific data, and focus on the possibility of oligonucleotides for targeting pancreatic cancer in clinical implications.

MiR-890 inhibits proliferation and invasion and induces apoptosis in triple-negative breast cancer cells by targeting CD147

Background

Triple-negative breast cancer (TNBC) is a type of breast cancer with a high degree of malignancy. Because of the remarkable biological characteristics of high invasion, metastasis and recurrence, TNBC is often accompanied by a poor prognosis. As a molecular characteristic of TNBC, high expression of CD147 has been confirmed by a large number of studies. However, the mechanism of CD147 expression regulation in TNBC remains elusive. In this study, we investigated the roles of miR-890 in inhibiting CD147.

Methods

Quantitative Reverse Transcription-Polymerase Chain Reaction (qRT-PCR) was used to detect CD147 mRNA and miR-890 level, and western blotting was used to detect CD147 protein. Bioinformatics screening and 3′-Untranslated Region (3′-UTR) luciferase assays were used to analyze the microRNAs (miRNA) binding site. Cell proliferation, apoptosis and invasion were assessed by using CCK-8, flow cytometry and transwell assays.

Results

The upregulation of miR-890 inhibited cell proliferation and invasion, induced apoptosis in MDA-MB-231 and HCC-70 TNBC cells by negatively regulating its target gene, CD147, and the upregulation of CD147 rescued the inhibitory effects of miR-890. miR-890 targeted CD147 by binding to its 3′-UTR. Further results showed that the upregulation of miR-890 also inhibited the expression of MMPs, the downstream genes of CD147, and promoted the cleavage of Caspase-3. The CD147 recovery experiment was further confirmed by the activity changes in the downstream MMPs of CD147. In addition, it was confirmed that the effect of CD147 in promoting TNBC cell proliferation and invasion, inhibiting apoptosis was related to the change in caspase-3 activity.

Conclusion

The downregulation of miR-890 is the potential cause of high CD147 expression in TNBC, which can promote the malignant transformation of TNBC.

Molecular profiling of mucinous epithelial ovarian cancer by weighted gene co-expression network analysis

PURPOSE

In order to identify the molecular characteristics and improve the efficacy of early diagnosis of mucinous epithelial ovarian cancer (mEOC), here, the transcriptome profiling by weighted gene co-expression network analysis (WGCNA) has been proposed as an effective method.

METHODS

The gene expression dataset GSE26193 was reanalyzed with a systematical approach, WGCNA. mEOC-related gene co-expression modules were detected and the functional enrichments of these modules were performed at GO and KEGG terms. Ten hub genes in the mEOC-related modules were validated using two independent datasets GSE44104 and GSE30274.

RESULTS

11 co-expressed gene modules were identified by WGCNA based on 4917 genes and 99 epithelial ovarian cancer samples. The turquoise module was found to be significantly associated with the subtype of mEOC. KEGG pathway enrichment analysis showed genes in the turquoise module significantly enriched in metabolism of xenobiotics by cytochrome P450 and steroid hormone biosynthesis. Ten hub genes (LIPH, BCAS1, FUT3, ZG16B, PTPRH, SLC4A4, MUC13, TFF1, HNF4G and TFF2) in the turquoise module were validated to be highly expressed in mEOC using two independent gene expression datasets GSE44104 and GSE30274.

CONCLUSION

Our work proposed an applicable framework of molecular characteristics for patients with mEOC, which may help us to obtain a precise and comprehensive understanding on the molecular complexities of mEOC. The hub genes identified in our study, as potential specific biomarkers of mEOC, may be applied in the early diagnosis of mEOC in the future.