An eight-miRNA signature expression-based risk scoring system for prediction of survival in pancreatic adenocarcinoma

A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis

Researches on the prognosis of pancreatic cancer is of great significance to improve the patient treatment effect and survival. Current researches mainly focus on the prediction of the survival status and the determination of prognostic markers. Each patient has its own characteristics, there is no report about the prediction of survival time. However, accurate prediction of survival time is critical for personalized medicine. In this paper, a hybrid algorithm of Support Vector Regression (SVR) and Recursive Feature Elimination (RFE) was used to construct a quantitative prediction model of Overall Survival (OS) for pancreatic cancer patients, 70 RNAs related to OS were determined, including 33 mRNAs, 28 lncRNAs, and 9 miRNAs. The results of 10-fold cross-validation (R2 is 0.9693) and the generalization ability (R2 is 0.9666) showed that the model has reliable predictive performance and these 70 RNAs are important factors influencing the OS of pancreatic cancer patients. To further study the relationship between RNA-RNA interaction and the survival, competitive endogenous RNA (ceRNA) regulation network was constructed. Degree centrality, betweenness centrality and closeness centrality of nodes in the ceRNA network showed that hsa-mir-570, hsa-mir-944, hsa-mir-6506, hsa-mir-3136, MMP16, PLGLB2, HPGD, FUT1, MFSD2A, SULT1E1, SLC13A5, ZNF488, F2RL2, TNFRSF8, TNFSF11, FHDC1, ISLR2 and THSD7B are hub nodes, which are key RNAs closely determining the OS of pancreatic cancer patients.

Scoring systems for the management of oncological hepato-pancreato-biliary patients

Oncological scoring systems in surgery are used as evidence-based decision aids to best support management through assessing prognosis, effectiveness and recurrence. Currently, the use of scoring systems in the hepato-pancreato-biliary (HPB) field is limited as concerns over precision and applicability prevent their widespread clinical implementation. The aim of this review was to discuss clinically useful oncological scoring systems for surgical management of HPB patients. A narrative review was conducted to appraise oncological HPB scoring systems. Original research articles of established and novel scoring systems were searched using Google Scholar, PubMed, Cochrane, and Ovid Medline. Selected models were determined by authors. This review discusses nine scoring systems in cancers of the liver (CLIP, BCLC, ALBI Grade, RETREAT, Fong's score), pancreas (Genç's score, mGPS), and biliary tract (TMHSS, MEGNA). Eight models used exclusively objective measurements to compute their scores while one used a mixture of both subjective and objective inputs. Seven models evaluated their scoring performance in external populations, with reported discriminatory c-statistic ranging from 0.58 to 0.82. Selection of model variables was most frequently determined using a combination of univariate and multivariate analysis. Calibration, another determinant of model accuracy, was poorly reported amongst nine scoring systems. A diverse range of HPB surgical scoring systems may facilitate evidence-based decisions on patient management and treatment. Future scoring systems need to be developed using heterogenous patient cohorts with improved stratification, with future trends integrating machine learning and genetics to improve outcome prediction.

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

MicroRNA-496 inhibits triple negative breast cancer cell proliferation by targeting Del-1

Del-1 has been linked to the pathogenesis of various cancers, including breast cancer. However, the regulation of Del-1 expression remains unclear. We previously reported the interaction between microRNA-137 (miR-137) and the Del-1 gene. In this study, we investigated miR-496 and miR-137 as regulators of Del-1 expression in triple negative breast cancer (TNBC). Del-1 mRNA and miR-496 were measured by quantitative PCR in breast cancer cells (MDA-MB-231, MCF7, SK-BR3, and T-47D) and tissues from 30 patients with TNBC. The effects of miR-496 on cell proliferation, migration, and invasion were determined with MTT, wound healing, and Matrigel transwell assays, respectively. In MDA-MB-231 cells, miR-496 levels were remarkably low and Del-1 mRNA levels were higher than in other breast cancer cell lines. Luciferase reporter assays revealed that miR-496 binds the 3'-UTR of Del-1 and Del-1 expression is downregulated by miR-496 mimics. Furthermore, miR-496 inhibited the proliferation, migration, and invasion of MDA-MB-231 cells. The effects of miR-496 on cell proliferation were additive with those of miR-137, another miRNA that regulates Del-1 expression. Moreover, in the 30 TNBC specimens, miR-496 was downregulated (P < .005) and the levels of Del-1 in the plasma were significantly elevated as compared with in normal controls (P = .0142). The Cancer Genome Atlas (TCGA) data showed the correlation of miR-496 expression with better overall survival in patients with early TNBC. In in silico and in vitro analyses, we showed that Del-1 is a target of miR-496 in TNBC and thereby affects cancer progression. Our findings suggest that miR-496 and miR-137 additively target Del-1 and act as modulating factors in TNBC. They are potentially new biomarkers for patients with TNBC.

miR-1301-3p promotes the proliferation and migration of lung cancer cells via direct repression of polymerase I and transcript release factor

Aberrant expression of microRNAs (miRNAs or miRs) is associated with a number of human diseases, including lung cancer. Although numerous differentially expressed miRNAs have been identified in lung cancer via microarray and sequencing methods, to the best of our knowledge, only a small portion of these miRNAs have been experimentally verified. In the present study, miR-1301-3p expression levels in lung tumor tissues and lung cancer cells were measured by reverse transcription-quantitative PCR (RT-qPCR) and by analyzing previously published data. Cell Counting Kit-8 and Transwell assays were used to analyze the function of miR-1301-3p in lung cancer tissues and cells. Bioinformatics analysis, RT-qPCR, western blotting and a dual-luciferase reporter assay were performed to investigate the mechanism of miR-1301-3p in lung cancer cells. It was identified that miR-1301-3p is an upregulated miRNA in lung cancer via analyzing previously published microarray and The Cancer Genome Atlas-lung squamous cell carcinoma project data, and the upregulation of miR-1301-3p was confirmed in collected clinical samples and cells. Inhibition of miR-1301-3p suppressed lung cancer cell proliferation and migration. In addition, miR-1301-3p inhibition upregulated E-cadherin, an epithelial cell maker, and downregulated vimentin, a mesenchymal cell marker. Using bioinformatics analysis, it was revealed that polymerase I and transcript release factor (PTRF) is a target of miR-1301-3p. RT-qPCR, western blotting and dual-luciferase reporter assays demonstrated that PTRF is targeted by miR-1301-3p in lung cancer cells. The rescue experiments indicated that silencing PTRF could attenuate the inhibition of cell proliferation and migration induced by miR-1301-3p inhibitor in lung cancer cells. Furthermore, a strong negative correlation between miR-1301-3p and PTRF mRNA was identified in clinical samples. In summary, the present data highlight the involvement of miR-1301-3p in the proliferation and migration of lung cancer cells, indicating that miR-1301-3p may be a promising biomarker for lung cancer.

Transportome Malfunctions and the Hallmarks of Pancreatic Cancer

Ion channels and transporters (ICT) play important roles in almost all basic cellular processes. During last decades, abundant evidences have been provided that ICT (e.g., Ca²⁺ and K⁺ channels) are notable for regulating physiological pancreatic duct cellular function and deregulation of ICT is closely associated with the widely accepted hallmarks of pancreatic ductal adenocarcinoma (PDAC) such as proliferation, apoptosis resistance, invasion, and metastasis. Hence this review focuses on the role of ICT malfunctions in context with the hallmarks of PDAC. After briefly introducing epidemiology and history of molecular oncology of PDAC and summarizing the recent studies on molecular classification systems, we focus then on the exocrine pancreas as a very active secretory gland which considerably impacts the changes in the ion transport system (the transportome) upon malignant transformation. We highlight multiplicity of ICT members (H⁺ transporters, Ca²⁺, K⁺, Na⁺ and Cl^- channels) and their functional impact in PDAC. We also present some selective therapeutic options to interfere with transportome functions and thereby with key mechanisms of malignant progression. This will hopefully contribute to a better clinical outcome based on improved therapeutic strategies for this still extremely deadly disease.

Clinical significance of miR-1180-3p in hepatocellular carcinoma: a study based on bioinformatics analysis and RT-qPCR validation

miRNAs play an indispensable role in human carcinogenesis. Dysregulated miR-1180-3p has been observed in several types of cancer, including hepatocellular carcinoma (HCC). This study intends to correlate the expression level of miR-1180-3p with clinical features and overall survival in HCC patients. The expression and clinical significance of miR-1180-3p, selected from GEO and TCGA databases, were verified using an RT-qPCR method. The target genes of miR-1180-3p were obtained using 3 miRNA target gene prediction databases, and their functions were analyzed using the online tool WebGestalt. miR-1180-3p expression was significantly upregulated in 88 HCC tissues compared with non-tumor liver tissues (0.004 ± 0.009 vs. 0.002 ± 0.002, t = − 2.099, P = 0.038). Additionally, we found that the expression levels of miR-1180-3p were significantly correlated with tumor number (χ² = 9.157, P = 0.006) and MVI (χ² = 11.354, P = 0.003). Based on Kaplan–Meier analysis, patients with high miR-1180 expression had a shorter overall survival than those with low miR-1180-3p expression (P = 0.002). Furthermore, multivariate Cox analyses indicated that miR-1180-3p expression was an independent prognostic factor for overall survival (HR = 13.36, 95% CI 1.16, 153.69, P = 0.038). In addition, a total of 733 target genes of miR-1180-3p were found from three prediction databases. The GO analyses demonstrated that the target genes were closely related to the proliferation and malignancy of tumors. The KEGG analysis showed that target genes were enriched in several key cancer-related signaling pathways, including the Pathways in cancer, the Ras signaling pathway, and the MAPK signaling pathway. In conclusion, we demonstrate that miR-1180-3p is upregulated in HCC and is associated with a poor prognosis. Thus, miR-1180-3p might be useful as a prognostic marker for HCC.

The extensive role of miR-155 in malignant and non-malignant diseases

MicroRNAs (miRNAs) have rapidly emerged as key molecules in cancer initiation and development, showing the capability to regulate pivotal oncogenic pathways. MiR-155 has gathered an increased attention especially in oncology, but also in non-malignanat pathologies. Nowadays, this noncoding RNA is one of the most important miRNAs in cancer, due to the extensive signaling network associated with it, implication in immune system regulation and also deregulation in disease states. Therefore, numerous research protocols are focused on preclinical modulation of miR-155 for therapeutic purposes, or investigation of its dynamic expression for diagnostic/prognostic assessments, with the final intention of bringing this miRNA into the clinical setting. This review comprehensively presents the extended role of miR-155 in cancer and other pathologies, where its expression is dysregulated. Finally, we assess the future steps toward miR-155 based therapeutics.

A seven-miRNA expression-based prognostic signature and its corresponding potential competing endogenous RNA network in early pancreatic cancer

The present study aimed to establish a microRNA (miRNA/miR) signature to predict the prognosis of patients with pancreatic cancer (PC) at the early stage and to investigate the involvement of competing endogenous RNAs (ceRNAs) in PC. Using mature miRNA expression profiles from The Cancer Genome Atlas, differentially expressed miRNAs in tissues derived from patients exhibiting early PC and tissues from healthy individuals were compared. The least absolute shrinkage and selection operator regression method was used to construct a miRNA-based signature for predicting prognosis. The miRNet tool, gene set enrichment analysis (GSEA) and the LncRNADisease database were utilized to explore the mechanistic involvement of ceRNAs. A total of seven downregulated miRNAs in PC (miR-424-5p, miR-139-5p, miR-5586-5p, miR-126-3p, miR-3613-5p, miR-454-3p and miR-1271-5p) were selected to generate a signature. Based on this seven-miRNA signature, it was possible to stratify patients with PC into low- and high-risk groups. The overall survival of the low-risk group was significantly longer than that of the high-risk group (P<0.001). The seven-miRNA signature was able to predict the 2-year-survival rate of patients with early PC with an area under the curve of 0.750. Furthermore, as opposed to routine clinicopathological features, this seven-miRNA signature was an independent prognostic factor according to multivariate Cox regression analysis. GSEA indicated that the extracellular matrix receptor interaction pathway and the transforming growth factor-β signaling pathway were enriched in the high-risk group. A ceRNA network of the seven-miR signature was constructed. In conclusion, the present study provided a seven-miRNA signature, according to which patients with early PC may be divided into high- and low-risk groups. The ceRNA network of the prognostic signature was preliminarily explored.

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

Background: Sensitive and specific non-invasive biomarkers are urgently needed in order to improve the survival of patients with pancreatic ductal adenocarcinoma (PDAC), which is the fourth leading cause of cancer-related death. We aim to identify serum hub miRNAs as potential diagnostic and prognostic biomarkers for PDAC.

Methods: A total of 2578 serum miRNA expression data from 88 PDAC patients and 19 healthy subjects were downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was constructed and significant modules were extracted from the network by WGCNA R package. Network modules and hub miRNAs closely related to PDAC were identified. The prognostic value of hub miRNAs was assessed by Kaplan-Meier overall survival analysis.

Results: Two modules strongly associated with PDAC were identified by WGCNA, which were labeled as turquoise and brown respectively. Within each module, twenty hub miRNAs were found. At the functional level, turquoise module was mainly associated with tumorigenesis pathways such as P53 and WNT signaling pathway, while the brown module was mostly related to the pathways of cancer such as RNA transport and MAPK signaling pathway. Utilizing overall survival analyses, five “real” miRNAs were able to stratify PDAC patients into low-risk and high-risk groups.

Conclusions: The association of specific Hub miRNAs with the development of pancreatic cancer was established by WGCNA analysis. Five miRNAs (mir-16-2-3p, mir-890, mir-3201, mir-602, and mir-877) were identified as potential diagnostic and prognostic biomarkers for PDAC.

Clinical Impact of Epithelial-to-Mesenchymal Transition Regulating MicroRNAs in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive carcinoma entities worldwide with early and rapid dissemination. Recently, we discussed the role of microRNAs as epigenetic regulators of Epithelial-to-Mesenchymal Transition (EMT) in PDAC. In this study, we investigated their value as diagnostic and prognostic markers in tissue and blood samples of 185 patients including PDAC, non-malignant pancreatic disorders, and age-matched healthy controls. Expression of the microRNA-200-family (microRNAs -141, -200a, -200b, -200c, -429) and microRNA-148a was significantly downregulated in tissue of PDAC Union internationale contre le cancer (UICC) Stage II. Correspondingly, stromal PDAC tissue showed strong expression of Fibronectin, Vimentin, and ZEB-1 (Zinc finger E-box-binding homeobox) versus low expression of E-cadherin. Transient transfection of microRNA-200b and microRNA-200c mimics resulted in the downregulation of their key target ZEB-1. Inversely, blood serum analyses of patients with PDAC UICC Stages II, III, and IV showed a significant over-expression of microRNA-200-family members, microRNA-148a, microRNA-10b, and microRNA-34a. Correspondingly, Enzyme-linked Immunosorbent Assay (ELISA) analyses revealed a significant over-expression of soluble E-cadherin in serum samples of PDAC patients versus healthy controls. The best diagnostic accuracy to distinguish between PDAC and non-PDAC in this patient collective could be achieved in tissue by microRNA-148a with an area under the receiver-operating-characteristic (ROC) curve (AUC) of 0.885 and in blood serum by a panel of microRNA-141, -200b, -200c, and CA.19-9 with an AUC of 0.890. Both diagnostic tools outreach the diagnostic performance of the currently most common diagnostic biomarker CA.19-9 (AUC of 0.834). Kaplan Meier survival analysis of this patient collective revealed an improved overall survival in PDAC patients with high expression of tissue-related microRNA-34a, -141, -200b, -200c, and -429. In conclusion, EMT-regulating microRNAs have great potential as liquid and solid biopsy markers in PDAC patients. Their prognostic and therapeutic benefits remain important tasks for future studies.