Novel blood-based microRNA biomarker panel for early diagnosis of pancreatic cancer

Serum hsa-miR-22-3p, hsa-miR-885-5p, Lipase-to-Amylase Ratio, C-Reactive Protein, CA19-9, and Neutrophil-to-Lymphocyte Ratio as Prognostic Factors in Advanced Pancreatic Ductal Adenocarcinoma

Pancreatic cancer (PC) is the seventh most common cause of cancer-related death worldwide. The low survival rate may be due to late diagnosis and asymptomatic early-stage disease. Most patients are diagnosed at an advanced stage of the disease. The search for novel prognostic factors is still needed. Two miRNAs, miR-22-3p and miR-885-5p, which show increased expression in PC, were selected for this study. The aim of this study was to evaluate the utility of these miRNAs in the prognosis of PC. Other prognostic factors such as lipase-to-amylase ratio (LAR), neutrophil-to-lymphocyte ratio (NLR), and carbohydrate antigen 19-9 (CA19-9) were also evaluated in this study. This study was conducted in 50 patients previously diagnosed with pancreatic ductal adenocarcinoma in clinical stage (CS) III and IV. All patients underwent a complete medical history, physical examination, and routine laboratory tests including a complete blood count, C-reactive protein (CRP), CA19-9, lipase, and amylase. Two additional blood samples were taken from each patient to separate plasma and serum. Isolation of miRNA was performed using TRI reagent with cel-miR-39-3p as a spike-in control. Reverse transcription of miRNA was performed using a TaqMan Advanced miRNA cDNA Synthesis Kit. The relative expression levels of miR-22-3p and miR-885-5p were measured using RT-qPCR. Serum hsa-miR-22-3p was detected in 22 cases (44%), while hsa-miR-885-5p was detected in 33 cases (66%). There were no statistically significant differences in serum or plasma miRNA expression levels between patient groups based on clinical stage, gender, or BMI. There were no statistically significant differences in LAR between patients with different CS. For NLR, CRP and CA19-9 thresholds were determined using ROC analysis (6.63, 24.7 mg/L and 4691 U/mL, respectively). Cox's F test for overall survival showed statistically significant differences between groups (p = 0.002 for NLR, p = 0.007 for CRP and p = 0.007 for CA19-9). Utility as prognostic biomarkers was confirmed in univariate and multivariate analysis for CA19-9, CRP, and NLR. The selected miRNAs and LAR were not confirmed as reliable prognostic markers in PC.

Multibiomarker panels in liquid biopsy for early detection of pancreatic cancer - a comprehensive review

Pancreatic ductal adenocarcinoma (PDAC) is frequently detected in late stages, which leads to limited therapeutic options and a dismal overall survival rate. To date, no robust method for the detection of early-stage PDAC that can be used for targeted screening approaches is available. Liquid biopsy allows the minimally invasive collection of body fluids (typically peripheral blood) and the subsequent analysis of circulating tumor cells or tumor-associated molecules such as nucleic acids, proteins, or metabolites that may be useful for the early diagnosis of PDAC. Single biomarkers may lack sensitivity and/or specificity to reliably detect PDAC, while combinations of these circulating biomarkers in multimarker panels may improve the sensitivity and specificity of blood test-based diagnosis. In this narrative review, we present an overview of different liquid biopsy biomarkers for the early diagnosis of PDAC and discuss the validity of multimarker panels.

Expression of the laminin genes family and its relationship to prognosis in pancreatic carcinoma

BACKGROUND AND STUDY AIMS

Laminin is an extracellular matrix molecule that is the major component of the basement membrane and plays a key role in regulating various processes. However, the association between the laminin gene family and the prognosis of pancreatic carcinoma has not been systematically investigated.

PATIENTS AND METHODS

The role of the laminin gene family in pancreatic cancer was evaluated using data from the TCGA database. The effects of different expressions of members of the laminin gene family on pancreatic cancer survival were compared, and their primary cellular roles were examined. The effects of different expressions of positive family genes on proliferation, metastasis, and invasion, as well as EMT and ferroptosis in pancreatic cancer, were also examined.

RESULTS

Based on univariate and multifactorial analysis of pancreatic cancer patients, LAMA3 was identified as an independent prognostic factor for overall survival in pancreatic cancer. LAMA3 was found to be enriched in the actin cytoskeleton, P53 signaling pathway, adhesion molecule junctions, pentose phosphate pathway, and regulatory differences in the cell cycle and focal adhesion. Additionally, high expression of LAMA3 was found to promote cancer proliferation, invasion, and metastasis, facilitate the EMT process, and inhibit ferroptosis.

CONCLUSIONS

Our results identified LAMA3 was associated with the prognosis of patients with pancreatic cancer and may serve as a prognostic biomarker for pancreatic cancer.

Using microRNAs Networks to Understand Pancreatic Cancer-A Literature Review

Pancreatic cancer is a severe disease, challenging to diagnose and treat, and thereby characterized by a poor prognosis and a high mortality rate. Pancreatic ductal adenocarcinoma (PDAC) represents approximately 90% of pancreatic cancer cases, while other cases include neuroendocrine carcinoma. Despite the growing knowledge of the pathophysiology of this cancer, the mortality rate caused by it has not been effectively reduced. Recently, microRNAs have aroused great interest among scientists and clinicians, as they are negative regulators of gene expression, which participate in many processes, including those related to the development of pancreatic cancer. The aim of this review is to show how microRNAs (miRNAs) affect key signaling pathways and related cellular processes in pancreatic cancer development, progression, diagnosis and treatment. We included the results of in vitro studies, animal model of pancreatic cancer and those performed on blood, saliva and tumor tissue isolated from patients suffering from PDAC. Our investigation identified numerous dysregulated miRNAs involved in KRAS, JAK/STAT, PI3/AKT, Wnt/β-catenin and TGF-β signaling pathways participating in cell cycle control, proliferation, differentiation, apoptosis and metastasis. Moreover, some miRNAs (miRNA-23a, miRNA-24, miRNA-29c, miRNA-216a) seem to be engaged in a crosstalk between signaling pathways. Evidence concerning the utility of microRNAs in the diagnosis and therapy of this cancer is poor. Therefore, despite growing knowledge of the involvement of miRNAs in several processes associated with pancreatic cancer, we are beginning to recognize and understand their role and usefulness in clinical practice.

Targeted gene therapy for cancer: the impact of microRNA multipotentiality

Cancer is a life-threatening disease and its management is difficult due to its complex nature. Cancer is characterized by genomic instability and tumor-associated inflammation of the supporting stoma. With the advances in omics science, a treatment strategy for cancer has emerged, which is based on targeting cancer-driving molecules, known as targeted therapy. Gene therapy, a form of targeted therapy, is the introduction of nucleic acids into living cells to replace a defective gene, promote or repress gene expression to treat a disease. MicroRNAs (miRNAs) are non-coding RNAs (ncRNAs) that regulate gene expression and thus are involved in physiological processes like cell proliferation, differentiation, and cell death. miRNAs control the actions of many genes. They are deregulated in cancer and their abnormal expression influences genetic and epigenetic alterations inducing carcinogenesis. In this review, we will explain the role of miRNAs in normal and abnormal gene expression and their usefulness in monitoring cancer patients. Besides, we will discuss miRNA-based therapy as a method of gene therapy and its impact on the success of cancer management.

Differential microRNAs Expression during Cancer Development, and Chemoprevention by Natural Compounds: A Comprehensive Review

MicroRNAs are short non-coding RNAs that inhibit gene expression at the post-transcriptional level. Abnormal microRNA expression has been associated with different human diseases, including cancer. Epigenetic changes, mutation, transcriptional deregulation, DNA copy number abnormalities, and defects in the biogenesis machinery play an important role in abnormal microRNA expression. Modulation of microRNAs by natural agents has emerged to enhance the efficacy of conventional chemotherapy through combinatorial therapeutic approach. This review summarizes the current understanding of abnormal microRNA expression in cancer, the different cellular mechanisms of microRNA, and their prevention by natural compounds. Understanding microRNA expression patterns during cancer development may help to identify stage-specific molecular markers. Natural compounds that exert regulatory effects by modulating microRNAs can be used in better cancer chemopreventive strategies by directly targeting microRNAs or as a way to increase sensitivity to existing chemotherapy regimens.

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

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

Circulating MicroRNAs as Noninvasive Diagnostic and Prognostic Biomarkers in Pancreatic Cancer: A Review

Pancreatic cancer (PC) is one of the most lethal human cancers. Currently, most PC cases are diagnosed at an already advanced stage. Early detection of PC is critical to improving survival rates. Therefore, there is an urgent need to identify biomarkers for the early detection of PC. Recently, circulating miRNAs in whole blood and other body fluids have been reported as promising biomarkers for the early detection of various cancers, including PC. Furthermore, due to minimal invasiveness and technical availability, circulating miRNAs hold promise for further wide usage. As a potential novel molecular marker, circulating miRNAs not only represent promising noninvasive diagnostic and prognostic tools but could also improve the evaluation of tumor classification, metastasis, and curative effect. The purpose of this review is to outline the available information regarding circulating miRNAs as biomarkers for the early detection of PC.

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer-Advances and Challenges

There is an urgent unmet need for robust and reliable biomarkers for early diagnosis, prognosis, and prediction of response to specific treatments of many aggressive and deadly cancers, such as pancreatic cancer, and liquid biopsy-based miRNA profiling has the potential for this. MiRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many cancers, functioning as either oncomes or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling of dysregulated miRNAs in pancreatic cancer has been shown to correlate with disease diagnosis, indicate optimal treatment options and predict response to a specific therapy. Specific miRNA signatures can track the stages of pancreatic cancer and hold potential as diagnostic, prognostic, and predictive markers, as well as therapeutics such as miRNA mimics and miRNA inhibitors (antagomirs). Furthermore, identified specific miRNAs and genes they regulate in pancreatic cancer along with downstream pathways can be used as potential therapeutic targets. However, a limited understanding and validation of the specific roles of miRNAs, lack of tissue specificity, methodological, technical, or analytical reproducibility, harmonization of miRNA isolation and quantification methods, the use of standard operating procedures, and the availability of automated and standardized assays to improve reproducibility between independent studies limit bench-to-bedside translation of the miRNA biomarkers for clinical applications. Here I review recent findings on miRNAs in pancreatic cancer pathogenesis and their potential as diagnostic, prognostic, and predictive markers.

Clinical Value of Circulating miRNA in Diagnosis, Prognosis, Screening and Monitoring Therapy of Pancreatic Ductal Adenocarcinoma-A Review of the Literature

Pancreatic cancer (PC) is considered to be the seventh most common cause of cancer-related deaths. The number of deaths caused by PC is estimated to increase in the future. An early diagnosis of PC is crucial for improving treatment outcomes. The most common histopathological subtype of PC is pancreatic ductal adenocarcinoma (PDAC). MicroRNAs (miRNAs)-which are endogenous non-coding RNAs involved in the posttranscriptional regulation of multiple gene expression-constitute useful diagnostic and prognostic biomarkers in various neoplasms, including PDAC. Circulating miRNAs detected in a patient's serum or plasma are drawing more and more attention. Hence, this review aims at evaluating the clinical value of circulating miRNA in the screening, diagnosis, prognosis and monitoring of pancreatic ductal adenocarcinoma therapy.

Meta-analysis of the Prognostic Value of microRNA-22 in Leukemia Patients

Objective: The pathogenesis of leukemia is complex and there are no effective diagnostic and prognostic indicators. Previous studies showed that microRNA-22 (miR-22) has altered expression level in multiple leukemia subtypes, which is associated with the survival outcomes of leukemia. Methods: According to the constituted retrieval strategy, eligible studies were included from January 2010 to November 2022 by searching database. The pooled Risk Ratio (RR) and 95% confidence intervals (CI) were used to study the relationship between miR-22 and survival. Stata12.0 was used for meta-analysis. Differential expression analysis was conducted based on expression profile of miRNA. Results: Four English articles were included containing a total of 215 leukemia patients. Data showed that the pooled RR for overall survival (OS) was 1.558 (95% CI: 1.197-2.028, P < .01). Subgroup analysis for OS of acute myeloid leukemia patients and the RFS of plasma cell leukemia patients were statistically significant with different expression levels of miR-22 (RR:1.495, 95%CI:1.141-1.958, P < .01 and RR:1.517, 95%CI:1.114-2.065, P < .01, respectively). Moreover, all data included had no significant heterogeneity and publication bias. Conclusions: miR-22 is associated with the survival outcome of leukemia patients suggesting that miR-22 may be a promising prognostic biomarker for this patient population, and the expression level of miR-22 in ALL patients down-regulated.

A Miniaturized MicroRNA Sensor Identifies Targets Associated with Weight Loss in a Diet and Exercise Intervention among Healthy Overweight Individuals

Weight loss through dietary and exercise intervention is commonly prescribed but is not effective for all individuals. Recent studies have demonstrated that circulating microRNA (miR) biomarkers could potentially be used to identify individuals who will likely lose weight through diet and exercise and attain a healthy body weight. However, accurate detection of miRs in clinical samples is difficult, error-prone, and expensive. To address this issue, we recently developed iLluminate-a low-cost and highly sensitive miR sensor suitable for point-of-care testing. To investigate if miR testing and iLluminate can be used in real-world obesity applications, we developed a pilot diet and exercise intervention and utilized iLluminate to evaluate miR biomarkers. We evaluated the expression of miRs-140, -935, -let-7b, and -99a, which are biomarkers for fat loss, energy metabolism, and adipogenic differentiation. Responders lost more total mass, tissue mass, and fat mass than non-responders. miRs-140, -935, -let-7b, and -99a, collectively accounted for 6.9% and 8.8% of the explained variability in fat and lean mass, respectively. At the level of the individual coefficients, miRs-140 and -935 were significantly associated with fat loss. Collectively, miRs-140 and -935 provide an additional degree of predictive capability in body mass and fat mass alternations.

The Role of miR-29s in Human Cancers—An Update

MicroRNAs (miRNAs) are small non-coding RNAs that directly bind to the 3’ untranslated region (3’-UTR) of the target mRNAs to inhibit their expression. The miRNA-29s (miR-29s) are suggested to be either tumor suppressors or oncogenic miRNAs that are strongly dysregulated in various types of cancer. Their dysregulation alters the expression of their target genes, thereby exerting influence on different cellular pathways including cell proliferation, apoptosis, migration, and invasion, thereby contributing to carcinogenesis. In the present review, we aimed to provide an overview of the current knowledge on the miR-29s biological network and its functions in cancer, as well as its current and potential applications as a diagnostic and prognostic biomarker and/or a therapeutic target in major types of human cancer.

A pilot study to troubleshoot quality control metrics when assessing circulating miRNA expression data reproducibility across study sites

BACKGROUND: Given the growing interest in using microRNAs (miRNAs) as biomarkers of early disease, establishment of robust protocols and platforms for miRNA quantification in biological fluids is critical. OBJECTIVE: The goal of this multi-center pilot study was to evaluate the reproducibility of NanoString nCounter™ technology when analyzing the abundance of miRNAs in plasma and cystic fluid from patients with pancreatic lesions. METHODS: Using sample triplicates analyzed across three study sites, we assessed potential sources of variability (RNA isolation, sample processing/ligation, hybridization, and lot-to-lot variability) that may contribute to suboptimal reproducibility of miRNA abundance when using nCounter™, and evaluated expression of positive and negative controls, housekeeping genes, spike-in genes, and miRNAs. RESULTS: Positive controls showed a high correlation across samples from each site (median correlation coefficient, r> 0.9). Most negative control probes had expression levels below background. Housekeeping and spike-in genes each showed a similar distribution of expression and comparable pairwise correlation coefficients of replicate samples across sites. A total of 804 miRNAs showed a similar distribution of pairwise correlation coefficients between replicate samples (p= 0.93). After normalization and selecting miRNAs with expression levels above zero in 80% of samples, 55 miRNAs were identified; heatmap and principal component analysis revealed similar expression patterns and clustering in replicate samples. CONCLUSIONS: Findings from this pilot investigation suggest the nCounter platform can yield reproducible results across study sites. This study underscores the importance of implementing quality control procedures when designing multi-center evaluations of miRNA abundance.

Distinct Response of Circulating microRNAs to the Treatment of Pancreatic Cancer Xenografts with FGFR and ALK Kinase Inhibitors

Pancreatic adenocarcinoma is typically detected at a late stage and thus shows only limited sensitivity to treatment, making it one of the deadliest malignancies. In this study, we evaluate changes in microRNA (miR) patterns in peripheral blood as a potential readout of treatment responses of pancreatic cancer to inhibitors that target tumor-stroma interactions. Mice with pancreatic cancer cell (COLO357PL) xenografts were treated with inhibitors of either fibroblast growth factor receptor kinase (FGFR; PD173074) or anaplastic lymphoma kinase receptor (ALK; TAE684). While both treatments inhibited tumor angiogenesis, signal transduction, and mitogenesis to a similar extent, they resulted in distinct changes in circulating miR signatures. Comparison of the miR pattern in the tumor versus that in circulation showed that the inhibitors can be distinguished by their differential impact on tumor-derived miRs as well as host-derived circulating miRs. Distinct signatures that include circulating miR-1 and miR-22 are associated with the efficacy of ALK and FGFR inhibition, respectively. We propose that monitoring changes in circulating miR profiles can provide an early signature of treatment response or resistance to pathway-targeted drugs, and thus provide a non-invasive measurement to rapidly assess the efficacy of candidate therapies.

miRNAs in Cancer (Review of Literature)

MicroRNAs (miRNAs) are short, noncoding, single-stranded RNA molecules that regulate gene expression at the post-transcriptional level by binding to mRNAs. miRNAs affect the course of processes of fundamental importance for the proper functioning of the organism. These processes include cell division, proliferation, differentiation, cell apoptosis and the formation of blood vessels. Altered expression of individual miRNAs has been shown in numerous cancers, which may indicate the oncogenic or suppressor potential of the molecules in question. This paper discusses the current knowledge about the possibility of using miRNA as a diagnostic marker and a potential target in modern anticancer therapies.

Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal type of cancer. The 5-year survival rate for patients with early-stage diagnosis can be as high as 20%, suggesting that early diagnosis plays a pivotal role in the prognostic improvement of PDAC cases. In the medical field, the broad availability of biomedical data has led to the advent of the "big data" era. To overcome this deadly disease, how to fully exploit big data is a new challenge in the era of precision medicine. Artificial intelligence (AI) is the ability of a machine to learn and display intelligence to solve problems. AI can help to transform big data into clinically actionable insights more efficiently, reduce inevitable errors to improve diagnostic accuracy, and make real-time predictions. AI-based omics analyses will become the next alterative approach to overcome this poor-prognostic disease by discovering biomarkers for early detection, providing molecular/genomic subtyping, offering treatment guidance, and predicting recurrence and survival. Advances in AI may therefore improve PDAC survival outcomes in the near future. The present review mainly focuses on recent advances of AI in PDAC for clinicians. We believe that breakthroughs will soon emerge to fight this deadly disease using AI-navigated precision medicine.

The Role of Circulating MicroRNAs in Patients with Early-Stage Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is increasing in incidence and is still associated with a high rate of mortality. Only a minority of patients are diagnosed in the early stage. Radical surgery is the only potential curative procedure. However, radicality is reached in 20% of patients operated on. Despite the multidisciplinary approach in resectable tumors, early tumor recurrences are common. Options on how to select optimal candidates for resection remain limited. Nevertheless, accumulating evidence shows an important role of circulating non-coding plasma and serum microRNAs (miRNAs), which physiologically regulate the function of a target protein. miRNAs also play a crucial role in carcinogenesis. In PDAC patients, the expression levels of certain miRNAs vary and may modulate the function of oncogenes or tumor suppressor genes. As they can be detected in a patient's blood, they have the potential to become promising non-invasive diagnostic and prognostic biomarkers. Moreover, they may also serve as markers of chemoresistance. Thus, miRNAs could be useful for early and accurate diagnosis, prognostic stratification, and individual treatment planning. In this review, we summarize the latest findings on miRNAs in PDAC patients, focusing on their potential use in the early stage of the disease.

Recent Advances in Pancreatic Cancer: Novel Prognostic Biomarkers and Targeted Therapy-A Review of the Literature

Pancreatic adenocarcinoma carries a devastating prognosis. For locally advanced and metastatic disease, several chemotherapeutic regimens are currently being used. Over the past years, novel approaches have included targeting EGFR, NTRK, PARP, K-Ras as well as stroma and fibrosis, leading to approval of NTRK and PARP inhibitors. Moreover, immune check point inhibitors and different combinational approaches involving immunotherapeutic agents are being investigated in many clinical trials. MiRNAs represent a novel tool and are thought to greatly improve management by allowing for earlier diagnosis and for more precise guidance of treatment.

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.

The role of circulating miRNAs and CA19-9 in pancreatic cancer diagnosis

Diagnosis and treatment of pancreatic ductal adenocarcinoma (PA) remains a challenge in clinical practice. The aim of this study was to assess the role of microRNAs (miRNAs-21, -23a, -100, -107, -181c, -210) in plasma and tissue as possible biomarkers in the diagnosis of PA. Samples of plasma (PAp-n = 13), pancreatic tumors (PAt-n = 18), peritumoral regions (PPT-n = 9) were collected from patients during the surgical procedure. The control group consisted of samples from patients submitted to pancreatic surgery for trauma or cadaveric organs (PC-n = 7) and healthy volunteers donated blood (PCp-n = 6). The expression profile of microRNAs was measured in all groups using RT-PCR, serum CA19-9 levels were determined in PA and PC. In tissue samples, there was a difference in the expression of miRNAs-21, -210 (p < 0.05) across the PAt, PC and PPT groups. The PAp showed overexpression of miRNAs-181c, -210 (p < 0.05) when compared to PCp. The combination of miRNAs-21, -210 tissue expression and serum CA19-9 showed 100% accuracy in the diagnosis of PA, as well as miR-181c expression in the plasma (PApxPCp). The expression of microRNAs in plasma proved to be a promising tool for a noninvasive detection test for PA, as well as further studies will evaluate the utility of microRNAs expression as biomarkers for prognostic and response to therapy in PA.

Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?

Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).

Identification of plasma microRNA-22 as a marker for the diagnosis, prognosis, and chemosensitivity prediction of osteosarcoma

Objective

MicroRNA (miR)-22 plays crucial roles in malignant tumors and is involved in regulation of chemosensitivity. Additionally, altered expression of circulating miR-22 has been reported in various cancers. This study was designed to investigate plasma miR-22 expression in patients with osteosarcoma (OS) and determine its diagnostic, prognostic, and chemosensitivity prediction value.

Methods

Plasma miR-22 levels in 120 patients with OS and 120 healthy controls were detected by real-time quantitative reverse transcription PCR. Associations of plasma miR-22 expression with the patients’ clinicopathological features and prognosis were then assessed.

Results

Plasma miR-22 levels in patients with OS were significantly lower than those in healthy controls. Low plasma miR-22 levels were correlated with large tumor size, advanced clinical stages, positive distant metastasis, and poor tumor response to preoperative chemotherapy. Plasma miR-22 could discriminate OS patients from controls and distinguish patients with a good response to therapy from those with a poor response to therapy. Multivariate analysis revealed that low plasma miR-22 expression was a significant independent predictor of unfavorable prognosis.

Conclusions

Altered plasma levels of miR-22 might serve as a novel, noninvasive biomarker for OS diagnosis, prognosis, and chemosensitivity prediction.

Clinical quantitative MRI and the need for metrology

MRI has been an essential diagnostic tool in healthcare for several decades. It offers unique insights into most tissues without the need for ionising radiation. Historically, MRI has been predominantly used qualitatively, images are formed to allow visual discrimination of tissues types and pathologies, rather than providing quantitative measurements. Increasingly, quantitative MRI (qMRI) is also finding clinical application, where images provide the basis for physical measurements of, e.g. tissue volume measures and represent aspects of tissue composition and microstructure. This article reviews some common current research and clinical applications of qMRI from the perspective of measurement science. qMRI not only offers additional information for radiologists, but also the opportunity for improved harmonisation and calibration between scanners and as such it is well-suited to large-scale investigations such as clinical trials and longitudinal studies. Realising these benefits, however, presents a new kind of technical challenge to MRI practioners. When measuring a parameter quantitatively, it is crucial that the reliability and reproducibility of the technique are well understood. Strictly speaking, a numerical result of a measurement is meaningless unless it is accompanied by a description of the associated measurement uncertainty. It is therefore necessary to produce not just estimates of physical properties in a quantitative image, but also their associated uncertainties. As the process of determining a physical property from the raw MR signal is complicated and multistep, estimation of uncertainty is challenging and there are many aspects of the MRI process that require validation. With the clinical implementation of qMRI techniques and its continued expansion, there is a clear and urgent need for metrology in this field.

Molecular Approaches Using Body Fluid for the Early Detection of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is the most malignant form of gastrointestinal tumor and is the fourth leading cause of deaths due to cancer in Japan. This cancer shows a poor outcome due to the difficulty of its early diagnosis and its rapid growth. Once this disease becomes clinically evident, it is frequently accompanied by distant metastasis at the time of diagnosis. A recent multicenter study in Japan revealed that patients with the early stage of this disease (stage 0 and I) showed favorable prognosis after surgical resection, indicating the importance of early detection for improvement of PDAC prognosis. PDAC develops through a stepwise progression from the precursor lesion, and over the last few decades molecular analyses have shown the detailed genetic alterations that occur in this process. Since advances in molecular technologies have enabled the detection of genetic changes from a very small quantity of samples, a large number of non-invasive molecular approaches have been utilized in an attempt to find precursor or non-invasive carcinoma lesions. In this review, the current efforts in terms of the molecular approaches applied for the early detection of PDAC-especially using body fluids such as pancreatic juice, blood, and saliva-are summarized.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

Identification of Circulating Serum miRNAs as Novel Biomarkers in Pancreatic Cancer Using a Penalized Algorithm

Pancreatic cancer (PC) is difficult to detect in the early stages; thus, identifying specific and sensitive biomarkers for PC diagnosis is crucial, especially in the case of early-stage tumors. Circulating microRNAs are promising non-invasive biomarkers. Therefore, we aimed to identify non-invasive miRNA biomarkers and build a model for PC diagnosis. For the training model, blood serum samples from 63 PC patients and 63 control subjects were used. We selected 39 miRNA markers using a smoothly clipped absolute deviation-based penalized support vector machine and built a PC diagnosis model. From the double cross-validation, the average test AUC was 0.98. We validated the diagnosis model using independent samples from 25 PC patients and 81 patients with intrahepatic cholangiocarcinoma (ICC) and compared the results with those obtained from the diagnosis using carbohydrate antigen 19-9. For the markers miR-155-5p, miR-4284, miR-346, miR-7145-5p, miR-5100, miR-661, miR-22-3p, miR-4486, let-7b-5p, and miR-4703-5p, we conducted quantitative reverse transcription PCR using samples from 17 independent PC patients, 8 ICC patients, and 8 healthy individuals. Differential expression was observed in samples from PC patients. The diagnosis model based on the identified markers showed high sensitivity and specificity for PC detection and is potentially useful for early PC diagnosis.

Meta-analysis of the Diagnostic Performance of Circulating MicroRNAs for Pancreatic Cancer

Background: Numerous studies have suggested that differentially expressed miRNAs may be promising diagnostic markers for pancreatic cancer (PC), but the results are inconsistent. We aimed to summarize the diagnostic accuracy of circulating miRNAs, carbohydrate antigen 19-9 (CA19-9), and the combination of miRNAs and CA19-9. Material and Methods: A literature search of online databases including PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI) and WanFang was conducted. Relative data were extracted from eligible included studies, and a meta-analysis was performed. Results: A total of 46 studies involving 4,326 PC patients and 4,277 non-PC controls were included. The pooled sensitivity (SEN), specificity (SPE) and AUC of the circulating miRNAs for differentiating PC patients from non-PC controls were 0.79 (0.77-0.81), 0.77 (0.75-0.79), and 0.85 (0.81-0.87), respectively. The combination of miRNAs and CA19-9 greatly improved the SEN, SPE and AUC to 0.84 (0.80-0.87), 0.91 (0.89-0.93) and 0.94 (0.92-0.96), respectively. Moreover, circulating miRNAs also yielded an acceptable diagnostic accuracy for early-stage PC with a SEN of 0.79 (0.76-0.82), a SPE of 0.74 (0.68-0.79) and an AUC of 0.81 (0.77-0.84). Conclusion: Circulating miRNAs exhibited satisfactory diagnostic performance for PC and even early-stage PC. The combination of circulating miRNAs and CA19-9 can further improve the diagnostic accuracy, providing a novel strategy for PC diagnosis.

Cell-free microRNAs as Non-invasive Diagnostic and Prognostic Bio- markers in Pancreatic Cancer

Pancreatic cancer (PaC) is one of the most lethal cancers, with an increasing global incidence rate. Unfavorable prognosis largely results from associated difficulties in early diagnosis and the absence of prognostic and predictive biomarkers that would enable an individualized therapeutic approach. In fact, PaC prognosis has not improved for years, even though much efforts and resources have been devoted to PaC research, and the multimodal management of PaC patients has been used in clinical practice. It is thus imperative to develop optimal biomarkers, which would increase diagnostic precision and improve the post-diagnostic management of PaC patients. Current trends in biomarker research envisage the unique opportunity of cell-free microRNAs (miRNAs) present in circulation to become a convenient, non-invasive tool for accurate diagnosis, prognosis and prediction of response to treatment. This review analyzes studies focused on cell-free miRNAs in PaC. The studies provide solid evidence that miRNAs are detectable in serum, blood plasma, saliva, urine, and stool, and that they present easy-to-acquire biomarkers with strong diagnostic, prognostic and predictive potential.

Exosomal miRNA signatures of pancreatic lesions

BACKGROUND

Pancreatic and peri-pancreatic neoplasms encompass a variety of histotypes characterized by a heterogeneous prognostic impact. miRNAs are considered efficient candidate biomarkers due to their high stability in tissues and body fluids. We applied Nanostring profiling of circulating exosomal miRNAs to distinct pancreatic lesions in order to establish a source for biomarker development.

METHODS

A series of 140 plasma samples obtained from patients affected by pancreatic ductal adenocarcinoma (PDAC, n = 58), pancreatic neuroendocrine tumors (PanNET, n = 42), intraductal papillary mucinous neoplasms (IPMN, n = 20), and ampulla of Vater carcinomas (AVC, n = 20) were analyzed. Comprehensive miRNA profiling was performed on plasma-derived exosomes. Relevant miRNAs were validated by qRT-PCR and in situ hybridization (ISH).

RESULTS

Lesion specific miRNAs were identified through multiple disease comparisons. Selected miRNAs were validated in the plasma by qRT-PCR and at tissue level by ISH. We leveraged the presence of clinical subtypes with each disease cohort to identify miRNAs that are differentially enriched in aggressive phenotypes.

CONCLUSIONS

This study shows that pancreatic lesions are characterized by specific exosomal-miRNA signatures. We also provide the basis for further explorations in order to better understand the relevance of these signatures in pancreatic neoplasms.

miR-934 as a Prognostic Marker Facilitates Cell Proliferation and Migration of Pancreatic Tumor by Targeting PROX1

Background

Pancreatic cancer is an extremely lethal digestive cancer with late diagnosis and poor prognosis. miR-934 has been reported to serve as an oncogene in multiple cancers, such as ovarian cancer and bladder cancer. However, its role in pancreatic cancer remains undiscovered.

Materials and Methods

The expression data of miR-934 were obtained from the Gene Expression Omnibus database and from our own patient samples. The clinicopathological data and corresponding follow-up data were retrieved from The Cancer Genome Atlas database. CCK8 and colony formation assays were conducted to measure cell proliferation capacity in vitro. Wound healing and transwell assays were performed to detect the migration ability of pancreatic cancer cell.

Results

We found that miR-934 was significantly upregulated in pancreatic tumor samples and cell lines. The expression of miR-934 was related to pathological stages. Upregulated miR-934 was associated with poor prognosis in patients with pancreatic cancer. Mir-934 inhibition reduced, while overexpression promoted, cell proliferation and migration. Mechanically, we found  miR-934 could directly bind to 3'-UTR of PROX1 leading to mRNA derogation. Furthermore, increased cell proliferation and migration caused by miR-934 overexpression could be reversed by forced PROX1 expression.

Conclusion

miR-934 is an oncogene in pancreatic cancer and could serve as a prognosis indicator for patients with pancreatic cancer, suggesting that miR-934 is a promising therapeutic target for pancreatic cancer.

MiR-22 suppresses the growth and metastasis of bladder cancer cells by targeting E2F3

Bladder cancer is a common, serious disease worldwide. MicroRNAs (miRNAs) have been reported to participate in the development and progression in many cancers, including bladder cancer. However, the exact roles of miR-22 in bladder cancer process and its underlying mechanism remain largely unknown. The expression levels of miR-22 and E2F3 were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). Western blot was used to detect the protein levels of E2F3, E-cadherin, N-cadherin, and Vimentin in bladder cancer cells. Cell viability, proliferation, migration, and invasion were determined by 3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide (MTT) assay, colony formation assay, and transwell assay, respectively. The potential binding sites between miR-22 and E2F3 were predicted by TargetScan and verified by luciferase report assay. The expression of miR-22 was downregulated and E2F3 expression was upregulated in bladder cancer tissues and cells. Overexpression of miR-22 or E2F3 knockdown inhibited cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in bladder cancer cells. In addition, E2F3 was a direct target of miR-22 and its knockdown attenuated the promotion of cell proliferation, migration, invasion, and EMT induced by miR-22 inhibitor in bladder cancer cells. In conclusion, miR-22 suppressed cell proliferation, migration, invasion, and EMT in bladder cancer cells by regulating E2F3 expression, providing a novel avenue for treatment of bladder cancer.

Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research

OBJECTIVE

The speed of the diagnosis process is vital in pursuing the trial of curing cancer. During the last decade, precision medicine evolved by detecting different types of cancer through microarrays (MA) of deoxyribonucleic acid (DNA) processed by machine learning (ML) algorithms. Personalized diagnosis, followed by personalized treatment, should imply personalized hyperparameters of the ML. The goal of this paper is to propose a novel adaptive ML method that embeds knowledge into the architecture of the algorithm and also filters the features in order to reduce their number, increase computational speed, and decrease computational cost and time.

MATERIALS AND METHODS

fLogSLFN is a novel two-fold theoretically effective ML that can be used in two-class decision problems that embeds the logistic regression in such a manner that the hidden nodes of a single-hidden layer feedforward neural network (SLFN) are problem dependent. A filtering module based on the significance of each attribute is embedded in order to avoid the 'curse of dimensionality' phenomenon. The proposed model has been tested on three publicly available high-dimensional cancer datasets that contain gene expressions provided by complementary DNA (cDNA) array, and DNA microarray. The proposed novel method filtered logistic SLFN (fLogSLFN) has been also compared and statistically benchmarked to four ML algorithms: extreme learning machine (ELM), radial basis function network (RBF), single-hidden layer feedforward neural network trained by the backpropagation algorithm (BPNN), logistic regression with the LASSO penalty, and the adaptive single-hidden layer feedforward network (aSLFN).

MAIN FINDINGS

The experimental results showed that the fLogSLFN is competitive to the other state-of-the-art models, obtaining accuracies between 64.70% and 98.66% depending on the dataset it had been applied on.

CONCLUSIONS

In contrast to other state-of-the-art ML algorithms, the fLogSLFN is capable to embed the knowledge extracted from the data into its architecture, making it problem dependent. The filtering module increases its computational speed, while decreasing computational cost and time. The statistical analysis revealed the fact that by filtering the features the performance is kept, making the algorithm more efficient.

Immune-Related Circulating miR-125b-5p and miR-99a-5p Reveal a High Recurrence Risk Group of Pancreatic Cancer Patients after Tumor Resection

Clinical follow-up aided by changes in the expression of circulating microRNAs (miRs) may improve prognostication of pancreatic ductal adenocarcinoma (PDAC) patients. Changes in 179 circulating miRs due to cancer progression in the transgenic Kras G12D/+; Trp53 R172H/+; P48-Cre (KPC) animal model of PDAC were analyzed for serum miRs that are altered in metastatic disease. In addition, expression levels of 250 miRs were profiled before and after pancreaticoduodenectomy in the serum of two patients with resectable PDAC with different progression free survival (PFS) and analyzed for changes indicative of PDAC recurrence after resection. Three miRs that were upregulated ≥3-fold in progressive PDAC in both mice and patients were selected for validation in 26 additional PDAC patients before and after resection. We found that high serum miR-125b-5p and miR-99a-5p levels after resection are significantly associated with shorter PFS (HR 1.34 and HR 1.73 respectively). In situ hybridization for miR detection in the paired resected human PDAC tissues showed that miR-125b-5p and miR-99a-5p are highly expressed in inflammatory cells in the tumor stroma, located in clusters of CD79A expressing cells of the B-lymphocyte lineage. In conclusion, we found that circulating miR-125b-5p and miR-99a-5p are potential immune-cell related prognostic biomarkers in PDAC patients after surgery.

MicroRNA in Pancreatic Cancer: From Biology to Therapeutic Potential

Pancreatic cancer is one of the most aggressive malignancies, accounting for more than 45,750 deaths annually in the U.S. alone. The aggressive nature and late diagnosis of pancreatic cancer, coupled with the limitations of existing chemotherapy, present the pressing need for the development of novel therapeutic strategies. Recent reports have demonstrated a critical role of microRNAs (miRNAs) in the initiation, progression, and metastasis of cancer. Furthermore, aberrant expressions of miRNAs have often been associated with the cause and consequence of pancreatic cancer, emphasizing the possible use of miRNAs in the effective management of pancreatic cancer patients. In this review, we provide a brief overview of miRNA biogenesis and its role in fundamental cellular process and miRNA studies in pancreatic cancer patients and animal models. Subsequent sections narrate the role of miRNA in, (i) cell cycle and proliferation; (ii) apoptosis; (iii) invasions and metastasis; and (iv) various cellular signaling pathways. We also describe the role of miRNA's in pancreatic cancer; (i) diagnosis; (ii) prognosis and (iii) therapeutic intervention. Conclusion section describes the gist of review with future directions.

The State of the Art on Blood MicroRNAs in Pancreatic Ductal Adenocarcinoma

Despite enormous advances being made in diagnosis and therapeutic interventions, pancreatic ductal adenocarcinoma (PDAC) is still recognized as one of the most lethal malignancies. Early diagnosis and timely curative surgery can markedly improve the prognosis; hence, there is an unmet necessity to explore efficient biomarkers for patients' benefit. Recently, blood miRNAs (miRNAs) have been reported to be a novel biomarker in human cancers. Part of it is selectively packaged by plasma exosomes released from cells via exocytosis and is highly sensitive to changes in the tumor microenvironment. Furthermore, due to less invasiveness and technical availability, miRNA-based liquid biopsy holds promise for further wide usage. Therefore, this review is aimed at presenting an update on the association between blood miRNAs and the biology of PDAC, then discussing its clinical utilization further.

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.

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

BACKGROUND

MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.

RESULTS

Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.

CONCLUSIONS

Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .

Identification of two microRNA signatures in whole blood as novel biomarkers for diagnosis of nasopharyngeal carcinoma

Background

Early diagnosis is critical to reduce the mortality caused by nasopharyngeal carcinoma (NPC). MicroRNAs (miRNAs) are dysregulated and play important roles in carcinogenesis. Therefore, this study aimed to identify diagnostically relevant circulating miRNA signatures in patients with NPC.

Methods

Total RNA was extracted from whole blood samples obtained from 120 patients with NPC, 30 patients with head-neck tumors (HNT), and 30 healthy subjects (HSs), and examined by using a custom microarray. The expression levels of four miRNAs identified by using the microarray were validated with quantitative real-time reverse transcription polymerase chain reaction. The 120 patients with NPC and 30 HSs were randomly assigned to training group-1 and validation group-1, respectively. By using significance analysis of microarray (SAM), the specific miRNA expression profiles in whole blood from patients with NPC are obtained. By using lasso regression and adaptive boosting, a diagnostic signature was identified in training group-1, and its accuracy was verified in validation group-1. By using the same methods, another signature to distinguish patients with NPC from those with HNT and HSs was identified in training group-2 and confirmed in validation group-2.

Results

There were 117 differentially expressed miRNAs (upregulated and downregulated fold change ≥ 1.5) between the patients with NPC and HSs, among which an 8-miRNA signature was identified with 96.43% sensitivity and 100% specificity [area under the curve (AUC) = 0.995] to diagnose NPC in training group-1 and 86.11% sensitivity and 88.89% specificity (AUC = 0.941) in validation group-1. Compared with traditional Epstein–Barr virus (EBV) seromarkers, this signature was more specific for NPC. Furthermore, a 16-miRNA signature to differentiate NPC from HNT and HS (HNT-HS) was established from 164 differentially expressed miRNAs, which diagnosed NPC and HNT-HS with 100% accuracy (AUC = 1.000) in training group-2 and 87.04% (AUC = 0.924) in validation group-2.

Conclusions

The present study identified two miRNA signatures for the highly accurate diagnosis and differential diagnosis of patients with NPC from HSs and patients with HNT. The identified miRNAs might represent novel serological biomarkers and potential therapeutic targets for NPC.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1923-2) contains supplementary material, which is available to authorized users.

Plasma Micro-RNA Alterations Appear Late in Pancreatic Cancer

Objectives:

The aim of this research was to study whether plasma microRNAs (miRNA) can be used for early detection of pancreatic cancer (PC) by analyzing prediagnostic plasma samples collected before a PC diagnosis.

Background:

PC has a poor prognosis due to late presenting symptoms and early metastasis. Circulating miRNAs are altered in PC at diagnosis but have not been evaluated in a prediagnostic setting.

Methods:

We first performed an initial screen using a panel of 372 miRNAs in a retrospective case-control cohort that included early-stage PC patients and healthy controls. Significantly altered miRNAs at diagnosis were then measured in an early detection case-control cohort wherein plasma samples in the cases are collected before a PC diagnosis. Carbohydrate antigen 19–9 (Ca 19–9) levels were measured in all samples for comparison.

Results:

Our initial screen, including 23 stage I-II PC cases and 22 controls, revealed 15 candidate miRNAs that were differentially expressed in plasma samples at PC diagnosis. We combined all 15 miRNAs into a multivariate statistical model, which outperformed Ca 19–9 in receiver-operating characteristics analysis. However, none of the candidate miRNAs, individually or in combination, were significantly altered in prediagnostic plasma samples from 67 future PC patients compared with 132 matched controls. In comparison, Ca 19–9 levels were significantly higher in the cases at <5 years before diagnosis.

Conclusion:

Plasma miRNAs are altered in PC patients at diagnosis, but the candidate miRNAs found in this study appear late in the course of the disease and cannot be used for early detection of the disease.

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

PURPOSE

The purpose of this study was to establish a risk scoring system based on miRNAs to evaluate the prognosis in pancreatic adenocarcinoma.

METHODS

Using a miRNA microarray dataset (179 pancreatic adenocarcinoma specimens and 4 normal control specimens) from TCGA, differentially expressed miRNAs were identified. Cox proportional hazards regression analysis was used to identify significant prognostic miRNAs, with which a risk scoring system was established and tested on a validation set. Cox regression analysis was performed to identify independent predictors of survival from clinical characteristics. Stratified Cox regression analyses were conducted to unravel the associations of clinical characteristics with survival. Differentially expressed genes (DEGs) were screened followed by functional annotation of the DEGs.

RESULTS

Eight miRNAs (miR-1301, miR-598, miR-1180, miR-155, miR-496, miR-203, miR-193b, miR-135b) were independent predictors for survival. A risk scoring system was established with the 8 signature miRNAs. Upon Cox multivariate regression analysis, risk score, new tumor and targeted molecular therapy were independent predictors of prognosis. Stratified Cox regression analyses found that targeted molecular therapy and new tumor are associated with survival of patients. Survival-related DEGs were significantly enriched with regulation of transforming growth factor beta receptor, potassium ion transport and MAPK signaling pathway.

CONCLUSIONS

The study proposes 8-miRNA expression-based risk scoring system to predict prognosis in pancreatic adenocarcinoma. New tumor and targeted molecular therapy were independent predictors of prognosis. Transforming growth factor beta receptor, potassium ion transport and MAPK signaling pathway may be related to prognosis in pancreatic adenocarcinoma.

Single-Vesicle Assays Using Liposomes and Cell-Derived Vesicles: From Modeling Complex Membrane Processes to Synthetic Biology and Biomedical Applications

The plasma membrane is of central importance for defining the closed volume of cells in contradistinction to the extracellular environment. The plasma membrane not only serves as a boundary, but it also mediates the exchange of physical and chemical information between the cell and its environment in order to maintain intra- and intercellular functions. Artificial lipid- and cell-derived membrane vesicles have been used as closed-volume containers, representing the simplest cell model systems to study transmembrane processes and intracellular biochemistry. Classical examples are studies of membrane translocation processes in plasma membrane vesicles and proteoliposomes mediated by transport proteins and ion channels. Liposomes and native membrane vesicles are widely used as model membranes for investigating the binding and bilayer insertion of proteins, the structure and function of membrane proteins, the intramembrane composition and distribution of lipids and proteins, and the intermembrane interactions during exo- and endocytosis. In addition, natural cell-released microvesicles have gained importance for early detection of diseases and for their use as nanoreactors and minimal protocells. Yet, in most studies, ensembles of vesicles have been employed. More recently, new micro- and nanotechnological tools as well as novel developments in both optical and electron microscopy have allowed the isolation and investigation of individual (sub)micrometer-sized vesicles. Such single-vesicle experiments have revealed large heterogeneities in the structure and function of membrane components of single vesicles, which were hidden in ensemble studies. These results have opened enormous possibilities for bioanalysis and biotechnological applications involving unprecedented miniaturization at the nanometer and attoliter range. This review will cover important developments toward single-vesicle analysis and the central discoveries made in this exciting field of research.

Clinical utilization of serum- or plasma-based miRNAs as early detection biomarkers for pancreatic cancer: A meta-analysis up to now

BACKGROUND

Pancreatic cancer (PC) is a lethal disease, however current screening methods unable to achieve early diagnosis. Blood-based microRNAs (miRNAs) are promising molecular biomarkers for detecting PC. This meta-analysis summaries studies identifying serum- or plasma-based miRNAs dysregulated in PC patients compared to non-PC cases to evaluate their diagnostic accuracy for characterizing PC.

METHODS

A systematically reviews and meta-analysis of published studies was conducted to compare the serum or plasma miRNAs expressions between PC patients and non-PC cases. Summary estimates for sensitivity, specificity, along with other measures of accuracy of miRNAs in the diagnosis of PC were pooled using the random-effects model. I and Q tests were used to assess the heterogeneity of included studies. The Spearman test was used to analyze the threshold effect.

RESULTS

Twenty-seven eligible studies were identified after electronic search and literature selection. For single miRNA dysregulation, 32 miRNAs were found to be upregulated in PC patients, and 5 miRNAs were downregulated. Four studies identified a 2-miRNA panel, and 10 studies identified a panel consisting of 3 or more miRNAs which were used to detect PC patients. Additionally, 8 studies combined miRNA panels and carbohydrate antigen 19-9 (CA 19-9) to diagnose PC. The pooled sensitivities for these 4 groups were 0.77 to 0.85, and specificities were 0.70 to 0.87. The highest area under the curve (AUC), 0.9308, was identified using 2 miRNA panels with sensitivity and specificity of 0.79 (0.74-0.83) and 0.85 (0.81-0.89), respectively. There was great heterogeneity of these 4 miRNA groups. Results of Spearman test revealed that there existed a threshold effect on single miRNA group (r=-0.437, P=.001), and none of the other groups (P all>.05).

CONCLUSIONS

Serum- or plasma-based miRNAs are capable of distinguishing PC from non-PC with relatively high sensitivity and specificity. In future, miRNAs may be used as promising diagnostic biomarkers for detection of PC.

Pancreatic cancer and associated exosomes

Pancreatic cancers with poor prognosis are highly malignant, readily metastatic and of immune tolerance, mainly due to delayed detection. The metastatic progression and immune tolerance of pancreatic cancer is greatly attributed to the intercellular communication. However, exosomes are deemed to be the most important tool of intercellular communicators. Thus, we present a review of pancreatic cancer and exosomes in this article. We intensively summarize the progress of early pancreatic cancer and the relationship of the proliferation, progression and metastasis of pancreatic cancer and pancreatic cancer-derived exosomes, and propose new ideas of the study of pancreatic cancer.

Learning a single-hidden layer feedforward neural network using a rank correlation-based strategy with application to high dimensional gene expression and proteomic spectra datasets in cancer detection

Methods based on microarrays (MA), mass spectrometry (MS), and machine learning (ML) algorithms have evolved rapidly in recent years, allowing for early detection of several types of cancer. A pitfall of these approaches, however, is the overfitting of data due to large number of attributes and small number of instances -- a phenomenon known as the 'curse of dimensionality'. A potentially fruitful idea to avoid this drawback is to develop algorithms that combine fast computation with a filtering module for the attributes. The goal of this paper is to propose a statistical strategy to initiate the hidden nodes of a single-hidden layer feedforward neural network (SLFN) by using both the knowledge embedded in data and a filtering mechanism for attribute relevance. In order to attest its feasibility, the proposed model has been tested on five publicly available high-dimensional datasets: breast, lung, colon, and ovarian cancer regarding gene expression and proteomic spectra provided by cDNA arrays, DNA microarray, and MS. The novel algorithm, called adaptive SLFN (aSLFN), has been compared with four major classification algorithms: traditional ELM, radial basis function network (RBF), single-hidden layer feedforward neural network trained by backpropagation algorithm (BP-SLFN), and support vector-machine (SVM). Experimental results showed that the classification performance of aSLFN is competitive with the comparison models.

Systematic Review and Meta-Analysis of Diagnostic Accuracy of miRNAs in Patients with Pancreatic Cancer

Background

It is reported that miRNAs are aberrantly expressed in patients with pancreatic cancer. However, the diagnostic value of miRNAs in pancreatic cancer remains controversial. The meta-analysis was to access diagnostic accuracy of miRNAs in pancreatic cancer.

Methods

PubMed, Scopus, Web of Science, Chinese National Knowledge Infrastructure (CNKI), WANFANG Data, China Biomedical Literature Database (CBM), and VIP databases were retrieved up to June 30, 2016, to collect articles concerning the diagnosis of miRNAs in pancreatic cancer. The methodological quality of each study was assessed by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). This meta-analysis was conducted using RevMan5.0, MetaDiSc 1.4, and Stata 12.0 software.

Results

There are 40 articles including 109 studies. The pooled SEN was 0.81 (95% CI, 0.80–0.82), the pooled SPE was 0.78 (95% CI, 0.77–0.79), the pooled +LR was 3.32 (95% CI, 2.92–3.80), the pooled −LR was 0.27 (95% CI, 0.24–0.31), the pooled DOR was 14.56 (95% CI, 11.55–18.34), and pooled AUC was 0.86 (95% CI, 0.84–0.88).

Discussion

This meta-analysis demonstrated that miRNA makes a significant impact in the pancreatic cancer diagnosis with a high SEN and SPE, particularly using multiple miRNAs.