MicroRNA markers for the diagnosis of pancreatic and biliary-tract cancers

An overview of challenges associated with exosomal miRNA isolation toward liquid biopsy-based ovarian cancer detection

As one of the deadliest gynaecological cancers, ovarian cancer has been on the list. With lesser-known symptoms and lack of an accurate detection method, it is still difficult to catch it early. In terms of both the diagnosis and outlook for cancer, liquid biopsy has come a long way with significant advancements. Exosomes, extracellular components commonly shed by cancerous cells, are nucleic acid-rich particles floating in almost all body fluids and hold enormous promise, leading to minimallyinvasive molecular diagnostics. They have been shown as potential biomarkers in liquid biopsy, being implicated in tumour growth and metastasis. In order to address the drawbacks of ovarian cancer tumor heterogeneity, a liquid biopsy-based approach is being investigated by detecting cell-free nucleic acids, particularly non-coding RNAs, having the advantage of being less invasive and more prominent in nature. microRNAs are known to actively contribute to cancer development and their existence inside exosomes has also been made quite apparent which can be leveraged to diagnose and treat the disease. Extraction of miRNAs and exosomes is an arduous execution, and while other approaches have been investigated, none have produced results that are as encouraging due to limits in time commitment, yield, and, most significantly, damage to the exosomal structure resulting discrepancies in miRNA-based expression profiling for disease diagnosis. We have briefly outlined and reviewed the difficulties with exosome isolation techniques and the need for their standardization. The several widely used procedures and their drawbacks in terms of the exosomal purity they may produce have also been outlined.

Targeted Nanoparticle-Based Diagnostic and Treatment Options for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest cancers, presents significant challenges in diagnosis and treatment due to its aggressive, metastatic nature and lack of early detection methods. A key obstacle in PDAC treatment is the highly complex tumor environment characterized by dense stroma surrounding the tumor, which hinders effective drug delivery. Nanotechnology can offer innovative solutions to these challenges, particularly in creating novel drug delivery systems for existing anticancer drugs for PDAC, such as gemcitabine and paclitaxel. By using customization methods such as incorporating conjugated targeting ligands, tumor-penetrating peptides, and therapeutic nucleic acids, these nanoparticle-based systems enhance drug solubility, extend circulation time, improve tumor targeting, and control drug release, thereby minimizing side effects and toxicity in healthy tissues. Moreover, nanoparticles have also shown potential in precise diagnostic methods for PDAC. This literature review will delve into targeted mechanisms, pathways, and approaches in treating pancreatic cancer. Additional emphasis is placed on the study of nanoparticle-based delivery systems, with a brief mention of those in clinical trials. Overall, the overview illustrates the significant advances in nanomedicine, underscoring its role in transcending the constraints of conventional PDAC therapies and diagnostics.

MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications

Pancreatic cancer remains a formidable malignancy characterized by high mortality rates, primarily attributable to late-stage diagnosis and a dearth of effective therapeutic interventions. The identification of reliable biomarkers holds paramount importance in enhancing early detection, prognostic evaluation, and targeted treatment modalities. Small non-coding RNAs, particularly microRNAs, have emerged as promising candidates for pancreatic cancer biomarkers in recent years. In this review, we delve into the evolving role of cellular and circulating miRNAs, including exosomal miRNAs, in the diagnosis, prognosis, and therapeutic targeting of pancreatic cancer. Drawing upon the latest research advancements in omics data-driven biomarker discovery, we also perform a case study using public datasets and address commonly identified research discrepancies, challenges, and limitations. Lastly, we discuss analytical approaches that integrate multimodal analyses incorporating clinical and molecular features, presenting new insights into identifying robust miRNA-centric biomarkers.

Influence of analytical procedures on miRNA expression analyses in saliva samples

Aim of this study was to demonstrate the influence of different analytical procedures and techniques on the resulting miRNA expression profile in healthy control subjects and tumor patients using the oral squamous cell carcinoma (OSCC) model and to demonstrate the technical and biological reproducibility. Body fluids such as saliva are suitable for non-invasive miRNA analysis because ubiquitously circulating miRNA can be found in them. It was technically possible to distinguish between healthy and diseased samples based on the miRNA expression profile found. Regardless of the methodology used, good technical reproducibility of the results seems to be achievable. On the other hand, biological reproducibility was inadequate, which is why prompt sampling and sequencing is recommended. The data indicate that malignant lesions can be detected using miRNA signatures extracted from saliva. This could stimulate further research to establish standardized protocols and kits for sample collection, miRNA extraction, sequencing and interpretation of results.

An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction

Breast cancer (BC) is one of the most commonly diagnosed cancers worldwide. As key regulatory molecules in several biological processes, microRNAs (miRNAs) are potential biomarkers for cancer. Understanding the miRNA markers that can detect BC may improve survival rates and develop new targeted therapeutic strategies. To identify a circulating miRNA signature for diagnostic prediction in patients with BC, we developed an evolutionary learning-based method called BSig. BSig established a compact set of miRNAs as potential markers from 1280 patients with BC and 2686 healthy controls retrieved from the serum miRNA expression profiles for the diagnostic prediction. BSig demonstrated outstanding prediction performance, with an independent test accuracy and area under the receiver operating characteristic curve were 99.90% and 0.99, respectively. We identified 12 miRNAs, including hsa-miR-3185, hsa-miR-3648, hsa-miR-4530, hsa-miR-4763-5p, hsa-miR-5100, hsa-miR-5698, hsa-miR-6124, hsa-miR-6768-5p, hsa-miR-6800-5p, hsa-miR-6807-5p, hsa-miR-642a-3p, and hsa-miR-6836-3p, which significantly contributed towards diagnostic prediction in BC. Moreover, through bioinformatics analysis, this study identified 65 miRNA-target genes specific to BC cell lines. A comprehensive gene-set enrichment analysis was also performed to understand the underlying mechanisms of these target genes. BSig, a tool capable of BC detection and facilitating therapeutic selection, is publicly available at https://github.com/mingjutsai/BSig.

A Comprehensive Review of the Potential Role of Liquid Biopsy as a Diagnostic, Prognostic, and Predictive Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most lethal malignant diseases, with a mortality rate being close to incidence. Due to its heterogeneity and plasticity, as well as the lack of distinct symptoms in the early phases, it is very often diagnosed at an advanced stage, resulting in poor prognosis. Traditional tissue biopsies remain the gold standard for making a diagnosis, but have an obvious disadvantage in their inapplicability for frequent sampling. Blood-based biopsies represent a non-invasive method which potentially offers easy and repeated sampling, leading to the early detection and real-time monitoring of the disease and hopefully an accurate prognosis. Given the urgent need for a reliable biomarker that can estimate a patient's condition and response to an assigned treatment, blood-based biopsies are emerging as a potential new tool for improving patients' survival and surveillance. In this article, we discuss the current advances and challenges in using liquid biopsies for pancreatic cancer, focusing on circulating tumour DNA (ctDNA), extracellular vesicles (EVs), and circulating tumour cells (CTCs), and compare the performance and reliability of different biomarkers and combinations of biomarkers.

In severe alcohol-related hepatitis, acute kidney injury is prevalent, associated with mortality independent of liver disease severity, and can be predicted using IL-8 and micro-RNAs

BACKGROUND

The prevalence, prediction and impact of acute kidney injury (AKI) in alcohol-related hepatitis (AH) is uncertain.

AIMS

We aimed to determine AKI incidence; association with mortality; evaluate serum biomarkers and the modifying effects of prednisolone and pentoxifylline in the largest AH cohort to date.

METHODS

Participants in the Steroids or Pentoxifylline for Alcoholic Hepatitis trial with day zero (D0) creatinine available were included. AKI was defined by modified International Club of Ascites criteria; incident AKI as day 7 (D7) AKI without D0-AKI. Survival was compared by Kaplan-Meier; mortality associations by Cox regression; associations with AKI by binary logistic regression; biomarkers by AUROC analyses.

RESULTS

D0-AKI was present in 198/1051 (19%) participants; incident AKI developed in a further 119/571 (21%) with available data. Participants with D0-AKI had higher 90-day mortality than those without (32% vs. 25%, p = 0.008), as did participants with incident AKI compared to those without D0-AKI or incident AKI (47% vs. 25%, p < 0.001). Incident AKI was associated with D90 mortality adjusted for age and discriminant function (AHR 2.15, 1.56-2.97, p < 0.001); D0-AKI was not. Prednisolone therapy reduced incident AKI (AOR 0.55, 0.36-0.85, p = 0.007) but not mortality. D0 bilirubin and IL-8 combined, miR-6826-5p, and miR-6811-3p predicted incident AKI (AUROCs 0.726, 0.821, 0.770, p < 0.01).

CONCLUSIONS

Incident AKI is associated with 90-day mortality independent of liver function. Prednisolone therapy was associated with reduced incident AKI. IL-8 and several miRNAs are potential biomarkers to predict AKI. Novel therapies to prevent incident AKI should be evaluated in AH to reduce mortality.

MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding

There is a growing body of evidence suggesting that microRNAs (miRNAs), small biological molecules, play a crucial role in the diagnosis, treatment, and prognostic assessment of diseases. However, it is often inefficient to verify the association between miRNAs and diseases (MDA) through traditional experimental methods. Based on this situation, researchers have proposed various computational-based methods, but the existing methods often have many drawbacks in terms of predictive effectiveness and accuracy. Therefore, in order to improve the prediction performance of computational methods, we propose a transformer-based prediction model (MDformer) for multi-source feature information. Specifically, first, we consider multiple features of miRNAs and diseases from the molecular biology perspective and utilize them in a fusion. Then high-quality node feature embeddings were generated using a feature encoder based on the transformer architecture and meta-path instances. Finally, a deep neural network was built for MDA prediction. To evaluate the performance of our model, we performed multiple 5-fold cross-validations as well as comparison experiments on HMDD v3.2 and HMDD v2.0 databases, and the experimental results of the average ROC area under the curve (AUC) were higher than the comparative methods for both databases at 0.9506 and 0.9369. We conducted case studies on five highly lethal cancers (breast, lung, colorectal, gastric, and hepatocellular cancers), and the first 30 predictions for these five diseases achieved 97.3% accuracy. In conclusion, MDformer is a reliable and scientifically sound tool that can be used to accurately predict MDA. In addition, the source code is available at https://github.com/Linda908/MDformer.

Emerging role of exosome-shuttled noncoding RNAs in gastrointestinal cancers: From intercellular crosstalk to clinical utility

Gastrointestinal cancer remains a significant global health burden. The pursuit of advancing the comprehension of tumorigenesis, along with the identification of reliable biomarkers and the development of precise therapeutic strategies, represents imperative objectives in this field. Exosomes, small membranous vesicles released by most cells, commonly carry functional biomolecules, including noncoding RNAs (ncRNAs), which are specifically sorted and encapsulated by exosomes. Exosome-mediated communication involves the release of exosomes from tumor or stromal cells and the uptake by nearby or remote recipient cells. The bioactive cargoes contained within these exosomes exert profound effects on the recipient cells, resulting in significant modifications in the tumor microenvironment (TME) and distinct alterations in gastrointestinal tumor behaviors. Due to the feasibility of isolating exosomes from various bodily fluids, exosomal ncRNAs have shown great potential as liquid biopsy-based indicators for different gastrointestinal cancers, using blood, ascites, saliva, or bile samples. Moreover, exosomes are increasingly recognized as natural delivery vehicles for ncRNA-based therapeutic interventions. In this review, we elucidate the processes of ncRNA-enriched exosome biogenesis and uptake, examine the regulatory and functional roles of exosomal ncRNA-mediated intercellular crosstalk in gastrointestinal TME and tumor behaviors, and explore their potential clinical utility in diagnostics, prognostics, and therapeutics.

Diagnostic utility of quantitative analysis of microRNA in bile samples obtained during endoscopic retrograde cholangiopancreatography for malignant biliary strictures

BACKGROUND

The sensitivity of bile cytology for malignant biliary strictures is not adequate. To overcome this limitation, we evaluated whether quantitative analysis of microRNAs (miRNAs) in bile can provide a precise diagnosis of malignant biliary strictures due to pancreatic cancer (PC) and biliary tract cancer (BTC).

METHODS

This was a retrospective evaluation of miRNA levels in stored bile samples of patients with PC, BTC or benign biliary stricture obtained during biliary drainage from April 2019 to December 2021 at our institution. A total of 113 patients (PC; n = 40, BTC; n = 38, control; n = 35) were enrolled. The miRNA candidates to be quantified were determined with microarray analysis from each 3 patients with PC, BTC and controls.

RESULTS

Using microarray analysis, we confirmed four significantly up-regulated miRNAs (miR-1275, miR-6891-5p, miR-7107-5p, miR-3197) in patients with PC and BTC compared to control patients. Quantitative PCR was then performed in 113 bile samples for these miRNAs. miR-1275 was significantly upregulated in PC (p = 0.003) and BTC (p = 0.049) compared to controls, miR-6891-5p was significantly upregulated in PC compared to controls (p = 0.025). In particular, a combination of bile cytology and miR-1275 in bile showed a sensitivity of 77.5% (95% CI, 70.7-77.5%), specificity of 100% (95% CI, 92.2-100%) and an area under the curve (AUC) of 0.93, and provided a significantly greater additional diagnostic effect than bile cytology alone (p = 0.014).

CONCLUSIONS

This study suggest that bile miRNAs could be potential biomarkers for pancreato-biliary diseases, particularly miR-1275 and miR-6891-5p may be helpful in the diagnosis of PC and BTC.

Prediction of tissue-of-origin of early stage cancers using serum miRNomes

BACKGROUND

Noninvasive detection of early stage cancers with accurate prediction of tumor tissue-of-origin could improve patient prognosis. Because miRNA profiles differ between organs, circulating miRNomics represent a promising method for early detection of cancers, but this has not been shown conclusively.

METHODS

A serum miRNA profile (miRNomes)-based classifier was evaluated for its ability to discriminate cancer types using advanced machine learning. The training set comprised 7931 serum samples from patients with 13 types of solid cancers and 5013 noncancer samples. The validation set consisted of 1990 cancer and 1256 noncancer samples. The contribution of each miRNA to the cancer-type classification was evaluated, and those with a high contribution were identified.

RESULTS

Cancer type was predicted with an accuracy of 0.88 (95% confidence interval [CI] = 0.87 to 0.90) in all stages and an accuracy of 0.90 (95% CI = 0.88 to 0.91) in resectable stages (stages 0-II). The F1 score for the discrimination of the 13 cancer types was 0.93. Optimal classification performance was achieved with at least 100 miRNAs that contributed the strongest to accurate prediction of cancer type. Assessment of tissue expression patterns of these miRNAs suggested that miRNAs secreted from the tumor environment could be used to establish cancer type-specific serum miRNomes.

CONCLUSIONS

This study demonstrates that large-scale serum miRNomics in combination with machine learning could lead to the development of a blood-based cancer classification system. Further investigations of the regulating mechanisms of the miRNAs that contributed strongly to accurate prediction of cancer type could pave the way for the clinical use of circulating miRNA diagnostics.

MicroRNA-125a-3p, -4530, and -92a as a Potential Circulating MicroRNA Panel for Noninvasive Pancreatic Cancer Diagnosis

MicroRNA (miRNA) expression dysregulations in pancreatic ductal adenocarcinoma (PDAC) have been studied widely for their diagnostic and prognostic utility. By the use of bioinformatics-based methods, in our previous study, we identified some potential miRNA panels for diagnosis of pancreatic cancer patients from noncancerous controls (the screening stage). In this report, we used 142 plasma samples from people with and without pancreatic cancer (PC) to conduct RT-qPCR differential expression analysis to assess the strength of the first previously proposed diagnostic panel (consisting of miR-125a-3p, miR-4530, and miR-92a-2-5p). As the result, we identified significant upregulation for all the three considered miRNAs in the serum of PC patients. After that, a three-miRNA panel in serum was developed. The area under the receiver operating characteristic curves (AUC) for the panel were 0.850, 0.910, and 0.86, respectively, indicating that it had a higher diagnostic value than individual miRNAs. Therefore, we detected a promising three-miRNA panel in the plasma for noninvasive PC diagnosis (miR-125a-3p, miR-4530, and miR-92a-2-5p).

Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer

Biliary tract cancer (BTC) is a highly aggressive malignant tumor. Serum microRNAs (ser-miRNAs) serve as noninvasive biomarkers to identify high risk individuals, thereby facilitating the design of precision therapies. The study is to prioritize key synergistic ser-miRNAs for the diagnosis of early BTC. Sampling technology, significant analysis of microarrays, Pearson Correlation Coefficients, t-test, decision tree, and entropy weight were integrated to develop a global optimization algorithm of decision forest. The source code is available at https://github.com/SuFei-lab/GOADF.git. Four key synergistic ser-miRNAs were prioritized and the synergistic classification performance was better than the single miRNA’ s. In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. In the independent test dataset, the single AUC was 0.7280, 0.8313, 0.8957, and 0.8303, and the synergistic AUC was 0.9110 for discriminating between BTC patients and healthy controls. The AUC for discriminating BTC from pancreatic cancer was 0.9000. Hsa-miR-26a-5p was a predictor of prognosis, patients with high expression had shorter survival than those with low expression. In conclusion, hsa-let-7c-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa-miR-26a-5p may act as key synergistic biomarkers and provide important molecular mechanisms that contribute to pathogenesis of BTC.

Emerging micro-nanotechnologies for extracellular vesicles in immuno-oncology: from target specific isolations to immunomodulation

Extracellular vesicles (EVs) have been hypothesized to incorporate a variety of crucial roles ranging from intercellular communication to tumor pathogenesis to cancer immunotherapy capabilities. Traditional EV isolation and characterization techniques cannot accurately and with specificity isolate subgroups of EVs, such as tumor-derived extracellular vesicles (TEVs) and immune-cell derived EVs, and are plagued with burdensome steps. To address these pivotal issues, multiplex microfluidic EV isolation/characterization and on-chip EV engineering may be imperative towards developing the next-generation EV-based immunotherapeutics. Henceforth, our aim is to expound the state of the art in EV isolation/characterization techniques and their limitations. Additionally, we seek to elucidate current work on total analytical system based technologies for simultaneous isolation and characterization and to summarize the immunogenic capabilities of EV subgroups, both innate and adaptive. In this review, we discuss recent state-of-art microfluidic/micro-nanotechnology based EV screening methods and EV engineering methods towards therapeutic use of EVs in immune-oncology. By venturing in this field of EV screening and immunotherapies, it is envisioned that transition into clinical settings can become less convoluted for clinicians.

Isolation and Characterization of Urinary Extracellular Vesicles from Healthy Donors and Patients with Castration-Resistant Prostate Cancer

Prostate cancer (PCa) is the most commonly diagnosed malignancy among men in developed countries. The five-year survival rate for men diagnosed with early-stage PCa is approximately 100%, while it is less than 30% for castration-resistant PCa (CRPC). Currently, the detection of prostate-specific antigens as biomarkers for the prognosis of CRPC is criticized because of its low accuracy, high invasiveness, and high false-positive rate. Therefore, it is important to identify new biomarkers for prediction of CRPC progression. Extracellular vesicles (EVs) derived from tumors have been highlighted as potential markers for cancer diagnosis and prognosis. Specifically, urinary EVs directly reflect changes in the pathophysiological conditions of the urogenital system because it is exposed to prostatic secretions. Thus, detecting biomarkers in urinary EVs provides a promising approach for performing an accurate and non-invasive liquid biopsy for CPRC. In this study, we effectively isolated urinary EVs with low protein impurities using size-exclusion chromatography combined with ultrafiltration. After EV isolation and characterization, we evaluated the miRNAs in urinary EVs from healthy donors and patients with CRPC. The results indicated that miRNAs (miR-21-5p, miR-574-3p, and miR-6880-5p) could be used as potential biomarkers for the prognosis of CRPC. This analysis of urinary EVs contributes to the fast and convenient prognosis of diseases, including CRPC, in the clinical setting.

Divergent Roles of Mitochondria Dynamics in Pancreatic Ductal Adenocarcinoma

Simple Summary

Pancreatic ductal adenocarcinoma is one of the most lethal neoplasia due to the lack of early diagnostic markers and effective therapies. The study of metabolic alterations of PDAC is of crucial importance since it would open the way to the discovery of new potential therapies. Mitochondria represent key organelles that regulate energy metabolism, and they remodel their structure by undergoing modifications by fusing with other mitochondria or dividing to generate smaller ones. The alterations of mitochondria arrangement may influence the metabolism of PDAC cells, thus supporting the proliferative needs of cancer. Shedding light on this topic regarding cancer and, more specifically, PDAC may help identify new potential strategies that hit cancer cells at their “core,” i.e., mitochondria.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive tumors; it is often diagnosed at an advanced stage and is hardly treatable. These issues are strictly linked to the absence of early diagnostic markers and the low efficacy of treatment approaches. Recently, the study of the metabolic alterations in cancer cells has opened the way to important findings that can be exploited to generate new potential therapies. Within this scenario, mitochondria represent important organelles within which many essential functions are necessary for cell survival, including some key reactions involved in energy metabolism. These organelles remodel their shape by dividing or fusing themselves in response to cellular needs or stimuli. Interestingly, many authors have shown that mitochondrial dynamic equilibrium is altered in many different tumor types. However, up to now, it is not clear whether PDAC cells preferentially take advantage of fusion or fission processes since some studies reported a wide range of different results. This review described the role of both mitochondria arrangement processes, i.e., fusion and fission events, in PDAC, showing that a preference for mitochondria fragmentation could sustain tumor needs. In addition, we also highlight the importance of considering the metabolic arrangement and mitochondria assessment of cancer stem cells, which represent the most aggressive tumor cell type that has been shown to have distinctive metabolic features to that of differentiated tumor cells.

Circulating miRNA and cell-free DNA as a potential diagnostic tool in early detection of biliary tract cancer: A meta-analysis

AIM

To investigate the clinical efficacy of miRNA, cell-free DNA, and circulating tumor cells in biliary tract cancer diagnosis.

METHODS

A comprehensive literature search was conducted up to September 2021, using public databases. The quality of the screened articles was evaluated using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS 2) tool followed by statistical analysis. Revman 5.4, Meta-disc 1.4, and MetaEssential were used for the statistical estimation.

RESULTS

A total of 28 studies were retrieved that involved 3,333 participants (1,874 patients and 1,450 control). Overall performance in terms of pooled sensitivity and specificity was 0.84 and 0.91 individually. Moreover, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) were 10.29, 0.15, and 0.9567 respectively. Subgroup analysis based on the sample source revealed that plasma can be a prominent source in diagnosing BTC. Publication bias assessed using Begg's and Egger's test reported that no publication bias was present (p-value: 0.083, 0.162).

CONCLUSIONS

The miRNA and cell-free DNA exhibited a high diagnostic value in early diagnosis. While CTCs might be useful in the later stages.

microRNA-21 Regulates Stemness in Pancreatic Ductal Adenocarcinoma Cells

Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer (PCa) with a low survival rate. microRNAs (miRs) are endogenous, non-coding RNAs that moderate numerous biological processes. miRs have been associated with the chemoresistance and metastasis of PDAC and the presence of a subpopulation of highly plastic "stem"-like cells within the tumor, known as cancer stem cells (CSCs). In this study, we investigated the role of miR-21, which is highly expressed in Panc-1 and MiaPaCa-2 PDAC cells in association with CSCs. Following miR-21 knockouts (KO) from both MiaPaCa-2 and Panc-1 cell lines, reversed expressions of epithelial-mesenchymal transition (EMT) and CSCs markers were observed. The expression patterns of key CSC markers, including CD44, CD133, CX-C chemokine receptor type 4 (CXCR4), and aldehyde dehydrogenase-1 (ALDH1), were changed depending on miR-21 status. miR-21 (KO) suppressed cellular invasion of Panc-1 and MiaPaCa-2 cells, as well as the cellular proliferation of MiaPaCa-2 cells. Our data suggest that miR-21 is involved in the stemness of PDAC cells, may play roles in mesenchymal transition, and that miR-21 poses as a novel, functional biomarker for PDAC aggressiveness.

Identification of homologous human miRNAs as antivirals towards COVID-19 genome

The COVID-19 fatality rate is ~57% worldwide. The investigation of possible antiviral therapy using host microRNA (miRNA) to inhibit viral replication and transmission is the need of the hour. Computational techniques were used to predict the hairpin precursor miRNA (pre-miRNAs) of COVID-19 genome with high homology towards human (host) miRNA. Top 21 host miRNAs with >80% homology towards 18 viral pre miRNAs were identified. The Gibbs free energy (ΔG) between host miRNAs and viral pre-miRNAs hybridization resulted in the best 5 host miRNAs having the highest base-pair complementarity. miR-4476 had the strongest binding with viral pre-miRNA (ΔG = -21.8 kcal/mol) due to maximum base pairing in the seed sequence. Pre-miR-651 secondary structure was most stable due to the (1) least minimum free energy (ΔG = -24.4 kcal/mol), energy frequency, and noncanonical base pairing and (2) maximum number of stem base pairing and small loop size. Host miRNAs-viral mRNAs interaction can effectively inhibit viral transmission and replication. Furthermore, miRNAs gene network and gene-ontology studies indicate top 5 host miRNAs interaction with host genes involved in transmembrane-receptor signaling, cell migration, RNA splicing, nervous system formation, and tumor necrosis factor-mediated signaling in respiratory diseases. This study identifies host miRNA/virus pre-miRNAs strong interaction, structural stability, and their gene-network analysis provides strong evidence of host miRNAs as antiviral COVID-19 agents.

The Role of microRNA in Pancreatic Cancer

MicroRNAs (miRNAs) are small ribonucleic acid molecules that play a key role in regulating gene expression. The increasing number of studies undertaken on the functioning of microRNAs in the tumor formation clearly indicates their important potential in oncological therapy. Pancreatic cancer is one of the deadliest cancers. The expression of miRNAs released into the bloodstream appears to be a good indicator of progression and evaluation of the aggressiveness of pancreatic cancer, as indicated by studies. The work reviewed the latest literature on the importance of miRNAs for pancreatic cancer development.

Non-coding RNAs in pancreatic ductal adenocarcinoma: New approaches for better diagnosis and therapy

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies with a 5-year survival rate less than 8%, which has remained unchanged over the last 50 years. Early detection is particularly difficult due to the lack of disease-specific symptoms and a reliable biomarker. Multimodality treatment including chemotherapy, radiotherapy (used sparingly) and surgery has become the standard of care for patients with PDAC. Carbohydrate antigen 19-9 (CA 19-9) is the most common diagnostic biomarker; however, it is not specific enough especially for asymptomatic patients. Non-coding RNAs are often deregulated in human malignancies and shown to be involved in cancer-related mechanisms such as cell growth, differentiation, and cell death. Several micro, long non-coding and circular RNAs have been reported to date which are involved in PDAC. Aim of this review is to discuss the roles and functions of non-coding RNAs in diagnosis and treatments of PDAC.

High Diagnostic and Prognostic Value of miRNAs Compared with the Carcinoembryonic Antigen as a Traditional Tumor Marker

A significant challenge in cancer detection and treatment is early diagnosis and accurate prognosis of the disease that enables effective therapies and interventions to improve the patient's condition. Up to now, many parts of research have tended to focus on the carcinoembryonic antigen (CEA) to detect cancers and estimate the survival rates of patients with multiple cancer types, including colorectal, breast, non-small cell lung, and pancreas cancer. Limited sensitivity and specificity of this traditional tumor marker make it an inappropriate biomarker to diagnose cancer, especially in the early stages, while several lines of research have introduced miRNAs as reliable indicators of tumor initiation, development, and therapy response. Indeed, miRNAs have unique properties that provide considerable benefits, such as discriminating benign diseases from malignancies, prediction of cancer possibility and progress, checking sensitivity to treatment, and initial detection of tumors. This review summarizes the relationships between miRNAs and CEA, the diagnostic significance of CEA in combination with miRNAs, and the distinct advantages of miRNAs over CEA as tumor biomarkers. Advancement in our current understanding of miRNAs is essential to discover new and effective biomarkers for diagnostic, prognostic, and therapeutic goals of cancer patients.

Recognition and pathological features of periampullary region adenocarcinoma with an indeterminable origin

Determination of the primary tumor in periampullary region carcinomas can be difficult, and the pathological assessment and clinicopathological characteristics remain elusive. In this study, we investigated the current recognition and practices for periampullary region adenocarcinoma with an indeterminable origin among expert pathologists through a cognitive survey. Simultaneously, we analyzed a prospective collection of cases with an indeterminable primary tumor diagnosed from 2008 to 2018 to elucidate their clinicopathological features. All cases with pathological indeterminable primary tumors were reported and discussed in a clinicopathological conference to elucidate if it was possible to distinguish the primary tumor clinically and pathologically. From the cognitive survey, over 85% of the pathologists had experienced cases with indeterminable primary tumors; however, 70% of the cases was reported as pancreatic cancer without definitive grounds. Interpretation of the main tumor mass varied, and no standardized method was developed to determine the primary tumor. During a prospective study, 42 of the 392 periampullary carcinoma cases (10.7%) were considered as tumors with a pathological indeterminable origin. After the clinicopathological conferences, 21 (5.4%) remained indeterminable and were considered final indeterminable cases. Histological studies showed that the tumors spread along both the bile duct and main pancreatic duct; this was the most representative finding of the final indeterminable cases. This study is the first to elucidate and recognize the current clinicopathological features of periampullary region adenocarcinomas with an indeterminable origin. Adequate assessment of primary tumors in periampullary region carcinomas will help to optimize epidemiological data of pancreatic and bile duct cancer.

Serum microRNAs as Biomarkers for the Noninvasive Early Diagnosis of Biliary Tract Cancer

Background

Biliary tract cancers (BTCs) are aggressive malignancies with difficult early diagnosis and poor prognosis. Studies have shown that microRNAs (miRNAs) are expected to be biomarkers of the disease, which indicates that we can diagnose cancers according to the miRNAs that have significant changes. The aim of this study was to explore miRNA biomarkers of BTCs.

Methods

A total of 163 samples were collected and divided into the control group, the benign group and the malignant group. High-throughput low-density chips were used to screen miRNAs with significant changes. Then, the preliminary screening test and the verification test were performed by quantitative real time PCR (qRT-PCR). Finally, the level of miRNAs in serum exosomes was measured.

Results

MiR-10a, miR-21, miR-135b, miR-221, and miR-214 were upregulated in the BTCs group compared to the control group. The change in the miR-221 level was statistically significant when the malignant group was compared with the benign group (P<0.01). Meanwhile, miR-135b and miR-214 were enriched in serum exosomes.

Conclusion

Five miRNAs in the serum were found to be significantly upregulated in patients with BTCs. Among them, miR-221 can serve as an early diagnostic marker for BTCs patients. MiR-10a, miR-21, miR-135b and miR-214 can be used as biomarkers for the diagnosis of biliary diseases.

Blood biomarkers for differential diagnosis and early detection of pancreatic cancer

Pancreatic cancer is currently the most lethal tumor entity and case numbers are rising. It will soon be the second most frequent cause of cancer-related death in the Western world. Mortality is close to incidence and patient survival after diagnosis stands at about five months. Blood-based diagnostics could be one crucial factor for improving this dismal situation and is at a stage that could make this possible. Here, we are reviewing the current state of affairs with its problems and promises, looking at various molecule types. Reported results are evaluated in the overall context. Also, we are proposing steps toward clinical utility that should advance the development toward clinical application by improving biomarker quality but also by defining distinct clinical objectives and the respective diagnostic accuracies required to achieve them. Many of the discussed points and conclusions are highly relevant to other solid tumors, too.

An integrated workflow for biomarker development using microRNAs in extracellular vesicles for cancer precision medicine

EV-miRNAs are microRNA (miRNA) molecules encapsulated in extracellular vesicles (EVs), which play crucial roles in tumor pathogenesis, progression, and metastasis. Recent studies about EV-miRNAs have gained novel insights into cancer biology and have demonstrated a great potential to develop novel liquid biopsy assays for various applications. Notably, compared to conventional liquid biomarkers, EV-miRNAs are more advantageous in representing host-cell molecular architecture and exhibiting higher stability and specificity. Despite various available techniques for EV-miRNA separation, concentration, profiling, and data analysis, a standardized approach for EV-miRNA biomarker development is yet lacking. In this review, we performed a substantial literature review and distilled an integrated workflow encompassing important steps for EV-miRNA biomarker development, including sample collection and EV isolation, EV-miRNA extraction and quantification, high-throughput data preprocessing, biomarker prioritization and model construction, functional analysis, as well as validation. With the rapid growth of "big data", we highlight the importance of efficient mining of high-throughput data for the discovery of EV-miRNA biomarkers and integrating multiple independent datasets for in silico and experimental validations to increase the robustness and reproducibility. Furthermore, as an efficient strategy in systems biology, network inference provides insights into the regulatory mechanisms and can be used to select functionally important EV-miRNAs to refine the biomarker candidates. Despite the encouraging development in the field, a number of challenges still hinder the clinical translation. We finally summarize several common challenges in various biomarker studies and discuss potential opportunities emerging in the related fields.

Identifying Potential Biomarkers in Colorectal Cancer and Developing Non-invasive Diagnostic Models Using Bioinformatics Approaches

Background: Colorectal cancer (CRC) is one of the most frequent causes of gastrointestinal tumors. Due to the invasiveness of the current diagnostic methods, there is an urgent need to develop non-invasive diagnostic approaches for CRC. The exact mechanisms and the most important genes associated with the development of CRC are not fully demonstrated. Objectives: This study aimed to identify differentially expressed miRNAs (DEMs), key genes, and their regulators associated with the pathogenesis of CRC. The signaling pathways and biological processes (BPs) that were significantly affected in CRC were also indicated. Moreover, two non-invasive models were constructed for CRC diagnosis. Methods: The miRNA dataset GSE59856 was downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify DEMs in CRC patients compared with healthy controls (HCs). A protein-protein interaction (PPI) network was built and analyzed. Significant clusters in the PPI networks were identified, and the BPs and pathways associated with these clusters were studied. The hub genes in the PPI network, as well as their regulators were identified. Results: A total of 569 DEMs were demonstrated with the criteria of P value <0.001. A total of 110 essential genes and 30 modules were identified in the PPI network. Functional analysis revealed that 1005 BPs, 9 molecular functions (MFs), 14 cellular components (CCs), and 887 pathways were significantly affected in CRC. A total of 22 transcription factors (TFs) were demonstrated as the regulators of the hubs. Conclusion: Our results may provide new insight into the pathogenesis of CRC and advance the diagnostic and therapeutic methods of the disease. However, confirmation is required in the future.

The emerging role of super enhancer-derived noncoding RNAs in human cancer

Super enhancers (SEs) are large clusters of adjacent enhancers that drive the expression of genes which regulate cellular identity; SE regions can be enriched with a high density of transcription factors, co-factors, and enhancer-associated epigenetic modifications. Through enhanced activation of their target genes, SEs play an important role in various diseases and conditions, including cancer. Recent studies have shown that SEs not only activate the transcriptional expression of coding genes to directly regulate biological functions, but also drive the transcriptional expression of non-coding RNAs (ncRNAs) to indirectly regulate biological functions. SE-derived ncRNAs play critical roles in tumorigenesis, including malignant proliferation, metastasis, drug resistance, and inflammatory response. Moreover, the abnormal expression of SE-derived ncRNAs is closely related to the clinical and pathological characterization of tumors. In this review, we summarize the functions and roles of SE-derived ncRNAs in tumorigenesis and discuss their prospective applications in tumor therapy. A deeper understanding of the potential mechanism underlying the action of SE-derived ncRNAs in tumorigenesis may provide new strategies for the early diagnosis of tumors and targeted therapy.

Long noncoding RNA LINC01559 promotes pancreatic cancer progression by acting as a competing endogenous RNA of miR-1343-3p to upregulate RAF1 expression

Background: An increasing number of studies have shown that lncRNAs are involved in the biological processes of pancreatic cancer (PC). Hence, we investigated the role of a novel noncoding RNA, LINC01559, involved in PC progression.

Results: LINC01559 and RAF1 were highly expressed in PC, while miR-1343-3p had low expression. High expression of LINC01559 was significantly associated with large tumors, lymph node metastasis, and poor prognosis. Functional experiment results revealed that silencing of LINC01559 significantly suppressed PC cell proliferation and metastasis. Meanwhile, LINC01559 could act as a ceRNA to competitively sponge miR-1343-3p to up-regulate RAF1 and activate its downstream ERK pathway

Conclusions: LINC01559 functions as an oncogene in PC progression through acting as a ceRNA of miR-1343-3p. Hence, LINC01559 is a potential diagnostic and therapeutic target.

Methods: RT-qPCR was performed to determine the expression of LINC01559 and miR-1343-3p in PC. Individual patient data were collected to investigate the correlation between clinicopathological features and LINC01559 expression. Subsequently, the expression of LINC01559, miR-1343-3p, and RAF1 was altered using transfection of vectors or inhibitors. Gain- and loss-of-function assays and mechanistic assays were applied to verify the effects of LINC01559, miR-1343-3p, and RAF1 on PC cell proliferation and metastasis in vivo and in vitro.

Circulating microRNAs: Next-generation Cancer Detection

Early detection of cancer is crucial for its ultimate control and the prevention of malignant progression. In Japan, a nationwide project was conducted between 2014 and 2019 to develop novel cancer detection tools using serum microRNAs (miRNAs). Using the National Cancer Center Biobank, we collected more than 10,000 serum samples from patients with malignant diseases, including rare cancers such as ovarian cancer, gliomas, and sarcomas. Subsequently, comprehensive miRNA microarray analyses were performed for all samples. This serum miRNA database provides insights regarding miRNA biomarker candidates for each cancer type. Here, we summarize the major achievements of this national project. Notably, although circulating miRNAs packaged in extracellular vesicles are thought to be a cell-to-cell communication tool, the functional characteristics of the miRNAs listed in the project are still unknown. We hope that our findings will help elucidate the biological functions of circulating miRNAs.

Identification of potential microRNA panels for pancreatic cancer diagnosis using microarray datasets and bioinformatics methods

Pancreatic cancer (PC) is a malignancy with little/no warning signs before the disease reaches its ultimate stages. Currently early detection of PC is very difficult because most patients have non-specific symptoms leading to postponing the correct diagnosis. In this study, using multiple bioinformatics tools, we integrated various serum expression profiles of miRNAs to find the most significant miRNA signatures helpful in diagnosis of PC and constructed novel miRNA diagnosis models for PC. Altogether, 27 differentially expressed miRNAs (DEMs) showed area under curve (AUC) score >80%. The most promising miRNAs, miR-1469 and miR-4530, were individually able to distinguish two groups with the highest specificity and sensitivity. By using multivariate cox regression analyses, 5 diagnostic models consisting of different combinations of miRNAs, based on their significant expression algorithms and functional properties were introduced. The correlation model consisting of miR-125a-3p, miR-5100 and miR-642b-3p was the most promising model in the diagnosis of PC patients from healthy controls with an AUC of 0.95, Sensitivity 0.98 and Specificity 0.97. Validation analysis was conducted for considered miRNAs on a final cohort consist of the microarray data from two other datasets (GSE112264 & GSE124158) . These results provide some potential biomarkers for PC diagnosis after testing in large case-control and cohort studies.

The Serum MicroRNA Signatures for Pancreatic Cancer Detection and Operability Evaluation

Pancreatic cancer (PC) has high morbidity and mortality. It is the fourth leading cause of cancer death. Its diagnosis and treatment are difficult. Liquid biopsy makes early diagnosis of pancreatic cancer possible. We analyzed the expression profiles of 2,555 serum miRNAs in 100 pancreatic cancer patients and 150 healthy controls. With advanced feature selection methods, we identified 13 pancreatic cancer signature miRNAs that can classify the pancreatic cancer patients and healthy controls. For pancreatic cancer treatment, operation is still the first choice. But many pancreatic cancer patients are already inoperable. Therefore, we compared the 79 inoperable and 21 operable patients and identified 432 miRNAs that can predict whether a pancreatic cancer patient was operable. The functional analysis of the 13 pancreatic cancer signatures and the 432 operability miRNAs revealed the molecular mechanisms of pancreatic cancer and shield light on the diagnosis and therapy of pancreatic cancer in clinical practice.

A miRNA-based diagnostic model predicts resectable lung cancer in humans with high accuracy

Lung cancer, the leading cause of cancer death worldwide, is most frequently detected through imaging tests. In this study, we investigated serum microRNAs (miRNAs) as a possible early screening tool for resectable lung cancer. First, we used serum samples from participants with and without lung cancer to comprehensively create 2588 miRNAs profiles; next, we established a diagnostic model based on the combined expression levels of two miRNAs (miR-1268b and miR-6075) in the discovery set (208 lung cancer patients and 208 non-cancer participants). The model displayed a sensitivity of 99% and specificity of 99% in the validation set (1358 patients and 1970 non-cancer participants) and exhibited high sensitivity regardless of histological type and pathological TNM stage of the cancer. Moreover, the diagnostic index markedly decreased after lung cancer resection. Thus, the model we developed has the potential to markedly improve screening for resectable lung cancer.

Asakura, Kadota et al. demonstrate the diagnostic potential of serum microRNAs for resectable lung cancer. Their diagnostic model based on the combined expression levels of two miRNAs predicts resectable lung cancer with 99% sensitivity, regardless of histological types and pathological stages of cancer, suggesting its promising, diagnostic utility.

The permissive role of TCTP in PM2.5/NNK-induced epithelial-mesenchymal transition in lung cells

Background

Translationally controlled tumor protein (TCTP) is linked to lung cancer. However, upon lung cancer carcinogens stimulation, there were no reports on the relationship between TCTP and lung cell carcinogenic epithelial–mesenchymal transition (EMT). This study was designed to investigate the molecular mechanism of regulation of TCTP expression and its role in lung carcinogens-induced EMT.

Methods

To study the role of TCTP in lung carcinogens [particulate matter 2.5 (PM_2.5) or 4-methylnitrosamino-l-3-pyridyl-butanone (NNK)]-induced EMT, PM_2.5/NNK-treated lung epithelial and non-small cell lung cancer (NSCLC) cells were tested. Cell derived xenografts, human lung cancer samples and online survival analysis were used to confirm the results. MassArray assay, Real-time PCR and Reporter assays were performed to elucidate the mechanism of regulation of TCTP expression. All statistical analyses were performed using GraphPad Prism version 6.0 or SPSS version 20.0.

Results

Translationally controlled tumor protein and vimentin expression were up-regulated in PM_2.5/NNK-treated lung cells and orthotopic implantation tumors. TCTP expression was positively correlated with vimentin in human NSCLC samples. Patients with high expression of TCTP displayed reduced overall and disease-free survival. TCTP overexpression could increase vimentin expression and promote cell metastasis. Furthermore, PM_2.5/NNK stimulation brought a synergistic effect on EMT in TCTP-transfected cells. TCTP knockdown blocked PM_2.5/NNK carcinogenic effect. Mechanically, PM_2.5/NNK-induced TCTP expression was regulated by one microRNA, namely miR-125a-3p, but not by methylation on TCTP gene promoter. The level of TCTP was regulated by its specific microRNA during the process of PM_2.5/NNK stimulation, which in turn enhanced vimentin expression and played a permissive role in carcinogenic EMT.

Conclusions

Our results provided new insights into the mechanisms of TCTP regulatory expression in lung carcinogens-induced EMT. TCTP and miR-125a-3p might act as potential prognostic biomarkers and therapeutic targets for NSCLC.

Long noncoding RNA OR3A4 promotes the proliferation and invasion of osteosarcoma cells by sponging miR-1227-5p

Background

Long noncoding RNAs (lncRNAs) have been identified as key players in promoting tumourigenesis in osteosarcoma. LncRNA OR3A4 (OR3A4) has been reported as an oncogene in a number of tumours. However, the clinical value of OR3A4 in osteosarcoma and the role of OR3A4 in osteosarcoma progression are still unknown.

Methods

The expression levels of OR3A4 in the tumour tissue of osteosarcoma patients and osteosarcoma cell lines were detected by RT-PCR. Kaplan-Meier analysis and log-rank test were performed to evaluate the relationship between the level of OR3A4 expression and the prognosis of osteosarcoma patients. We investigated the association between the tissue expression levels of OR3A4 and different clinicopathological characteristics of osteosarcoma patients by χ² tests. Bioinformatic databases and luciferase reporter assays were used to predict and validate the target microRNA of OR3A4. Finally, the role of OR3A4 in the proliferation and invasion of osteosarcoma cells was tested by MTT and Transwell assays, respectively.

Results

We observed that the expression level of OR3A4 was upregulated in the tumour tissue of osteosarcoma patients (p < 0.001) and osteosarcoma cell lines (p < 0.01) compared with the normal adjacent tissue and a normal human foetal osteoblastic cell line, respectively. The survival curve revealed that patients with high expression levels of OR3A4 had lower overall survival. Increased OR3A4 expression in osteosarcoma patients was associated with distant metastasis (p = 0.02) and advanced clinical stage (p < 0.001). In addition, bioinformatics analysis and luciferase reporter assays verified the complementary binding between OR3A4 and miR-1227-5p. Furthermore, we found that OR3A4 acted as a miR-1227-5p “sponge” to modulate osteosarcoma cell proliferation and invasion via downregulation of miR-1227-5p.

Conclusion

OR3A4 promotes osteosarcoma cell proliferation and invasion by sponging miR-1227-5p, which might be related to the metastasis of osteosarcoma and could be used as a potential prognostic biomarker and therapeutic target in osteosarcoma.

RCMF: a robust collaborative matrix factorization method to predict miRNA-disease associations

Background

Predicting miRNA-disease associations (MDAs) is time-consuming and expensive. It is imminent to improve the accuracy of prediction results. So it is crucial to develop a novel computing technology to predict new MDAs. Although some existing methods can effectively predict novel MDAs, there are still some shortcomings. Especially when the disease matrix is processed, its sparsity is an important factor affecting the final results.

Results

A robust collaborative matrix factorization (RCMF) is proposed to predict novel MDAs. The L_2,1-norm are introduced to our method to achieve the highest AUC value than other advanced methods.

Conclusions

5-fold cross validation is used to evaluate our method, and simulation experiments are used to predict novel associations on Gold Standard Dataset. Finally, our prediction accuracy is better than other existing advanced methods. Therefore, our approach is effective and feasible in predicting novel MDAs.

Comparison of tumour and serum specific microRNA changes dissecting their role in pancreatic ductal adenocarcinoma: a meta-analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is considered as one of the most aggressive cancers lacking efficient early detection biomarkers. Circulating miRNAs are now being considered to have potency to be used as diagnostic and prognostic biomarkers in different diseases as well as cancers. In case of cancer, a fraction of the circulating miRNAs is actually derived from the tumour tissue. This fraction would function as stable biomarker for the disease and also would contribute to the understanding of the disease development. There are not many studies exploring this aspect in pancreatic cancer and even there is not much overlap of results between existing studies.

Methods

In order to address that gap, we performed a miRNA microarray analysis to identify differentially expressed circulating miRNAs between PDAC patients and normal healthy individuals and also found two more similar datasets to perform a meta-analysis using a total of 182 PDAC patients and 170 normal, identifying a set of miRNAs significantly altered in patient serum. Next, we found five datasets studying miRNA expression profile in tumour tissues of PDAC patients as compared to normal pancreas and performed a second meta-analysis using data from a total of 183 pancreatic tumour and 47 normal pancreas to detect significantly deregulated miRNAs in pancreatic carcinoma. Comparison of these two lists and subsequent search for their target genes which were also deregulated in PDAC in inverse direction to miRNAs was done followed by investigation of their role in disease development.

Results

We identified 21 miRNAs altered in both pancreatic tumour tissue and serum. While deciphering the functions of their target genes, we characterized key miR-Gene interactions perturbing the biological pathways. We identified important cancer related pathways, pancreas specific pathways, AGE-RAGE signaling, prolactin signaling and insulin resistance signaling pathways among the most affected ones. We also reported the possible involvement of crucial transcription factors in the process.

Conclusions

Our study identified a unique meta-signature of 21 miRNAs capable of explaining pancreatic carcinogenesis and possibly holding the potential to act as biomarker for the disease detection which could be explored further.

Functional Prediction of Candidate MicroRNAs for CRC Management Using in Silico Approach

Approximately 30–50% of malignant growths can be prevented by avoiding risk factors and implementing evidence-based strategies. Colorectal cancer (CRC) accounted for the second most common cancer and the third most common cause of cancer death worldwide. This cancer subtype can be reduced by early detection and patients’ management. In this study, the functional roles of the identified microRNAs were determined using an in silico pipeline. Five microRNAs identified using an in silico approach alongside their seven target genes from our previous study were used as datasets in this study. Furthermore, the secondary structure and the thermodynamic energies of the microRNAs were revealed by Mfold algorithm. The triplex binding ability of the oligonucleotide with the target promoters were analyzed by Trident. Finally, evolutionary stage-specific somatic events and co-expression analysis of the target genes in CRC were analyzed by SEECancer and GeneMANIA plugin in Cytoscape. Four of the five microRNAs have the potential to form more than one secondary structure. The ranges of the observed/expected ratio of CpG dinucleotides of these genes range from 0.60 to 1.22. Three of the candidate microRNA were capable of forming multiple triplexes along with three of the target mRNAs. Four of the total targets were involved in either early or metastatic stage-specific events while three other genes were either a product of antecedent or subsequent events of the four genes implicated in CRC. The secondary structure of the candidate microRNAs can be used to explain the different degrees of genetic regulation in CRC due to their conformational role to modulate target interaction. Furthermore, due to the regulation of important genes in the CRC pathway and the enrichment of the microRNA with triplex binding sites, they may be a useful diagnostic biomarker for the disease subtype.

Upregulation of miR‑132‑3p in cholangiocarcinoma tissues: A study based on RT‑qPCR, The Cancer Genome Atlas miRNA sequencing, Gene Expression Omnibus microarray data and bioinformatics analyses

MicroRNAs (miRNAs/miRs) have been reported to be closely associated with numerous human diseases, including cholangiocarcinoma (CCA). However, the number of miRNAs known to be involved in CCA is limited, and the association between miR-132-3p and CCA remains unknown. In the present study, the clinical role of miR-132-3p and its potential signaling pathways were investigated by multiple approaches. Reverse transcription-quantitative PCR (RT-qPCR), CCA-associated Gene Expression Omnibus (GEO), ArrayExpress and Sequence Read Archive (SRA) miRNA-microarray or miRNA-sequencing data were screened, and meta-analyses were conducted, in order to calculate the receiver operating characteristic (ROC) curve and standardized mean difference (SMD). The predicted target genes of miR-132-3p were obtained from 12 online databases and were combined with the downregulated differentially expressed genes identified in the RNA-sequencing data of CCA. Gene Ontology annotation and pathway analysis were performed in WebGestalt. Protein-protein interaction analyses were conducted in STRING. The Cancer Genome Atlas (TCGA) mRNA expression profiles were used to validate the expression levels of hub genes at the mRNA level. The Human Protein Atlas was used to identify the protein expression levels of hub genes in CCA tissues and non-tumor biliary epithelium. The meta-analyses comprised 10 groups of RT-qPCR data, eight GEO microarray datasets and one TCGA miRNA-sequencing dataset. The SMD of miR-132-3p in CCA was 0.75 (95% CI: 0.25, 1.24), which indicated that miR-132-3p was overexpressed in CCA tissues. This finding was supported by a summary ROC value of 0.80 (95% CI: 0.76, 0.83). The pooled sensitivity and specificity were 0.81 (95% CI: 0.59, 0.93) and 0.71 (95% CI: 0.58, 0.81), respectively. The relative expression level of miR-132-3p in the early stage of CCA (stages I–II) was 6.8754±0.5279, which was markedly lower than that in the advanced stage (stages III–IVB), 7.3034±0.3267 (P=0.003). Consistently, the miR-132-3p level in low-grade CCA (grades G1-G2) was 6.7581±0.5297, whereas it was 7.1191±0.4651 in patients with high-grade CCA (grades G3-G4) (P=0.037). Furthermore, 555 potential target genes of miR-132-3p in CCA were mainly enriched in the ‘Focal Adhesion-PI3K-Akt-mTOR-signaling pathway’. In conclusion, upregulation of miR-132-3p may serve a pivotal role in the tumorigenesis and progression of CCA by targeting different pathways. Further in vitro and in vivo studies are required to support the current findings.

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.

Circulating microRNAs as promising diagnostic biomarkers for pancreatic cancer: a systematic review

Pancreatic cancer (PC) is one of the most common forms of malignant tumors and causes of tumor-related death worldwide. The current prognosis of PC still remains poor due to the lack of effective early detection method. Recently, there is strong support that circulating miRNAs can be used as biomarkers for early detection of various cancers, including PC. The purpose of this review is to provide an overview of previous published studies on circulating miRNAs in plasma/serum for early detection of PC and summarize their diagnostic value. PubMed, Embase and Web of Science were systematically searched for eligible studies on circulating miRNAs for PC detection. Overall, 29 studies published between 2009 and 2018 evaluating 51 individual miRNAs (no P-value exceeding 0.05) and 13 miRNAs panels were included. Generally, the diagnostic performance of circulating miRNAs for PC detection was strong, with both the sensitivity and specificity of 36% individual miRNAs and 40% miRNAs panels exceeding 80%. Moreover, two promising miRNA panels were discovered and verified externally with all AUC values exceeding 0.95. Therefore, circulating miRNAs may hold potential to be used as noninvasive diagnostic biomarkers for PC, but large-scale studies are still needed to validate the promising miRNAs and optimize the miRNA panels. Since, the tremendous heterogeneity of studies in this field hampers translating miRNA markers into clinical practice, miRNA analytical procedures are also needed to be standardized in the future.

Biochemical diagnostics of pancreatic cancer - Present and future

Pancreatic cancer is one of the deadliest cancers having an exceptionally high mortality rate. Despite a relatively low incidence (10th among cancers), it is the fourth leading cause of cancer-related deaths in most developed countries. Improving early diagnosis of pancreatic cancer and strengthening the standardised comprehensive treatment remain the main focus of pancreatic cancer research. Tumor markers are usually tumor-associated proteins of clinical relevance in these patients. Although tumor markers carbohydrate antigen (CA 19-9) and carcino-embryonic antigen (CEA) are commonly used, neither demonstrate high diagnostic accuracy. Recently, hematopoietic growth factors (HGFs) and various enzymes have been reported as potential biomarkers for pancreatic cancer. These include macrophage-colony stimulating factor (M-CSF) and granulocyte-colony stimulating factor (G-CSF), interleukin-3 (IL-3), macrophage inhibitory cytokine (MIC-1) and various enzymes (alcohol dehydrogenase, aldehyde dehydrogenase, lysosomal exoglycosidases). With the development of molecular technology, detecting K-ras mutation in serum via polymerase chain reaction (PCR) is becoming more common and efficient. Because K-ras mutation rates are high in many cancers, some regard it as a potential tumor marker. Others have shown the value of serum miRNAs in detection of pancreatic cancer. Unfortunately, there are currently no effective methods of sufficient diagnostic accuracy to detect early-stage surgically resectable pancreatic cancer. In this article we highlight these biomarkers and summarise recent developments in the diagnosis and treatment of pancreatic cancer.

Unravelling the Diagnostic Dilemma: A MicroRNA Panel of Circulating MiR-16 and MiR-877 as A Diagnostic Classifier for Distal Bile Duct Tumors

Accurate diagnosis of pancreatic head lesions remains challenging as no minimally invasive biomarkers are available to discriminate distal cholangiocarcinoma (CCA) from pancreatic ductal adenocarcinoma (PDAC). The aim of this study is to identify specific circulating microRNAs (miRNAs) to diagnose distal CCA. In the discovery phase, PCR profiling of 752 miRNAs was performed on fourteen patients with distal CCA and age- and sex-matched healthy controls. Candidate miRNAs were selected for evaluation and validation by RT-qPCR in an independent cohort of distal CCA (N = 24), healthy controls (N = 32), benign diseases (N = 20), and PDAC (N = 24). The optimal diagnostic combination of miRNAs was determined by multivariate logistic regression analysis and evaluated by ROC curves with AUC values. The discovery phase revealed 19 significantly dysregulated miRNAs, of which six were validated in the evaluation phase. The validation phase confirmed downregulated miR-16 in patients with distal CCA compared to benign disease or PDAC (P = 0.048 and P = 0.012), while miR-877 was significantly upregulated (P = 0.003 and P = 0.006). This two-miRNA panel was validated as a CCA-specific profile, discriminating distal CCA from benign disease (AUC = 0.90) and from PDAC (AUC = 0.88). In conclusion, the present study identified a two-miRNA panel of downregulated miR-16 and upregulated miR-877 with promising capability to diagnose patients with distal CCA.

Noncoding RNAs in Extracellular Fluids as Cancer Biomarkers: The New Frontier of Liquid Biopsies

The last two decades of cancer research have been devoted in two directions: (1) understanding the mechanism of carcinogenesis for an effective treatment, and (2) improving cancer prevention and screening for early detection of the disease. This last aspect has been developed, especially for certain types of cancers, thanks also to the introduction of new concepts such as liquid biopsies and precision medicine. In this context, there is a growing interest in the application of alternative and noninvasive methodologies to search for cancer biomarkers. The new frontiers of the research lead to a search for RNA molecules circulating in body fluids. Searching for biomarkers in extracellular body fluids represents a better option for patients because they are easier to access, less painful, and potentially more economical. Moreover, the possibility for these types of samples to be taken repeatedly, allows a better monitoring of the disease progression or treatment efficacy for a better intervention and dynamic treatment of the patient, which is the fundamental basis of personalized medicine. RNA molecules, freely circulating in body fluids or packed in microvesicles, have all the characteristics of the ideal biomarkers owing to their high stability under storage and handling conditions and being able to be sampled several times for monitoring. Moreover, as demonstrated for many cancers, their plasma/serum levels mirror those in the primary tumor. There are a large variety of RNA species noncoding for proteins that could be used as cancer biomarkers in liquid biopsies. Among them, the most studied are microRNAs, but recently the attention of the researcher has been also directed towards Piwi-interacting RNAs, circular RNAs, and other small noncoding RNAs. Another class of RNA species, the long noncoding RNAs, is larger than microRNAs and represents a very versatile and promising group of molecules which, apart from their use as biomarkers, have also a possible therapeutic role. In this review, we will give an overview of the most common noncoding RNA species detectable in extracellular fluids and will provide an update concerning the situation of the research on these molecules as cancer biomarkers.

HNRNPA2/B1 is upregulated in endocrine-resistant LCC9 breast cancer cells and alters the miRNA transcriptome when overexpressed in MCF-7 cells

MicroRNAs are dysregulated in breast cancer. Heterogeneous Nuclear Ribonucleoprotein A2/B1 (HNRNPA2/B1) is a reader of the N(6)-methyladenosine (m6A) mark in primary-miRNAs (pri-miRNAs) and promotes DROSHA processing to precursor-miRNAs (pre-miRNAs). We examined the expression of writers, readers, and erasers of m6A and report that HNRNPA2/B1 expression is higher in tamoxifen-resistant LCC9 breast cancer cells as compared to parental, tamoxifen-sensitive MCF-7 cells. To examine how increased expression of HNRNPA2/B1 affects miRNA expression, HNRNPA2/B1 was transiently overexpressed (~5.4-fold) in MCF-7 cells for whole genome miRNA profiling (miRNA-seq). 148 and 88 miRNAs were up- and down-regulated, respectively, 48 h after transfection and 177 and 172 up- and down-regulated, respectively, 72 h after transfection. MetaCore Enrichment analysis identified progesterone receptor action and transforming growth factor β (TGFβ) signaling via miRNA in breast cancer as pathways downstream of the upregulated miRNAs and TGFβ signaling via SMADs and Notch signaling as pathways of the downregulated miRNAs. GO biological processes for mRNA targets of HNRNPA2/B1-regulated miRNAs included response to estradiol and cell-substrate adhesion. qPCR confirmed HNRNPA2B1 downregulation of miR-29a-3p, miR-29b-3p, and miR-222 and upregulation of miR-1266-5p, miR-1268a, miR-671-3p. Transient overexpression of HNRNPA2/B1 reduced MCF-7 sensitivity to 4-hydroxytamoxifen and fulvestrant, suggesting a role for HNRNPA2/B1 in endocrine-resistance.

Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors

Background

The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors.

Methods

The study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis.

Results

Microarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10 × 10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20, LCOR, PFKFB2, SYNJ2BP and TPD52 genes were noted.

Conclusions

Our data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5739-5) contains supplementary material, which is available to authorized users.

Identification of potential biomarkers for diagnosis of pancreatic and biliary tract cancers by sequencing of serum microRNAs

BACKGROUND

Pancreatic and biliary tract cancer (PC and BTC, respectively) are difficult to diagnose because of their clinical characteristics; however, recent studies suggest that serum microRNAs (miRNAs) might be the key to developing more efficient diagnostic methods for these cancers.

METHODS

We analysed the genome-wide expression of serum miRNAs in PC and BTC patients to identify novel biomarker candidates using high-throughput sequencing and experimentally validated miRNAs on clinical samples.

RESULTS

Statistical and classification analysis of the serum miRNA-expression profiles of 55 patient samples showed distinguishable patterns between cancer patients and healthy controls; however, we were unable to distinguish the two cancers. We found that three of the highest performing miRNAs were capable of distinguishing cancer patients from controls, with an accuracy of 92.7%. Additionally, dysregulation of these three cancer-specific miRNAs was demonstrated in an independent sample group by quantitative reverse transcription polymerase chain reaction.

CONCLUSIONS

These results suggested three candidate serum miRNAs (mir-744-5p, mir-409-3p, and mir-128-3p) as potential biomarkers for PC and BTC diagnosis.

Development and Validation of an Esophageal Squamous Cell Carcinoma Detection Model by Large-Scale MicroRNA Profiling

IMPORTANCE

Patients with late-stage esophageal squamous cell carcinoma (ESCC) have a poor prognosis. Noninvasive screening tests using serum microRNAs (miRNAs) to accurately detect early-stage ESCC are needed to improve mortality.

OBJECTIVE

To establish a model using serum miRNAs to distinguish patients with ESCC from noncancer controls.

DESIGN, SETTING, AND PARTICIPANTS

In this case-control study, serum miRNA expression profiles of patients with ESCC (n = 566) and control patients without cancer (n = 4965) were retrospectively analyzed to establish a diagnostic model, which was tested in a training set and confirmed in a validation set. Patients histologically diagnosed as having ESCC who did not receive prior therapy or have a past or concurrent cancer other than ESCC were enrolled from the National Cancer Center Hospital in Tokyo, Japan. Between October 2010 and November 2015, control samples were collected from the National Cancer Center Biobank, the Biobank of the National Center for Geriatrics and Gerontology, and the general population undergoing routine health examination. Data analysis was performed between August 2015 and October 2018. Serum samples were randomly divided into discovery and validation sets.

MAIN OUTCOMES AND MEASURES

The expression of 2565 miRNAs was assessed in each sample. The discriminant model (named the EC index) was evaluated in the training set using Fisher linear discriminant analysis with a greedy algorithm. Receiver operating characteristic curve analysis evaluated the diagnostic ability of the model in the validation set.

RESULTS

In the training set, 283 patients with esophageal cancer (median age, 67 years [range, 37-90 years]; 83.4% male) were compared with 283 control patients (median age, 54 years [range, 22-100 years]; 43.1% male), and the EC index was constructed using 6 miRNAs (miR-8073, miR-6820-5p, miR-6794-5p, miR-3196, miR-744-5p, and miR-6799-5p). The area under the receiver operating characteristic curve was 1.00, with sensitivity of 1.00 and specificity of 0.98. The validation set included 283 patients (median age, 66 years [range, 42-87 years]; 83.0% male) and 4682 control patients (median age, 68 years [range, 20-98 years]; 44.7% male), and the area under the receiver operating characteristic curve for the EC index was 1.00, with sensitivity of 0.96 and specificity of 0.98.

CONCLUSIONS AND RELEVANCE

What appears to be novel serum miRNA discriminant model was developed for the diagnosis of ESCC. A multicenter prospective study is ongoing to confirm the present observations.