Identification of Serum microRNA-25 as a novel biomarker for pancreatic cancer

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.

An Ultrasensitive and Efficient microRNA Nanosensor Empowered by the CRISPR/Cas Confined in a Nanopore

This work presents a clustered regularly interspaced short palindromic repeat (CRISPR)/Cas-nanopipette nano-electrochemistry (Cas = CRISPR-associated proteins) capable of ultrasensitive microRNA detection. Nanoconfinement of the CRISPR/Cas13a within a nanopipette leads to a high catalytic efficacy of ca. 169 times higher than that in bulk electrolyte, contributing to the amplified electrochemical responses. CRISPR/Cas13a-enabled detection of representative microRNA-25 achieves a low limit of detection down to 10 aM. Practical application of this method is further demonstrated for single-cell and real human serum detection. Its general applicability is validated by addressing microRNA-141 and the SARS-CoV-2 RNA gene fragment. This work introduces a new CRISPR/Cas-empowered nanotechnology for ultrasensitive nano-electrochemistry and bioanalysis.

Phase Separation of DNA-Encoded Artificial Cells Boosts Signal Amplification for Biosensing

Life-like hierarchical architecture shows great potential for advancing intelligent biosensing, but modular expansion of its sensitivity and functionality remains a challenge. Drawing inspiration from intracellular liquid-liquid phase separation, we discovered that a DNA-encoded artificial cell with a liquid core (LAC) can enhance peroxidase-like activity of Hemin and its DNA G-quadruplex aptamer complex (DGAH) without substrate-selectivity, unlike its gelled core (GAC) counterpart. The LAC is easily engineered as an ultrasensitive biosensing system, benefiting from DNA's high programmability and unique signal amplification capability mediated by liquid-liquid phase separation. As proof of concept, its versatility was successfully demonstrated by coupling with two molecular recognition elements to monitor tumor-related microRNA and profile cancer cell phenotypes. This scalable design philosophy offers new insights into the design of next generation of artificial cells-based biosensors.

Diagnostic and Prognostic Performance of MicroRNA-25, Carbohydrate Antigen 19-9, Carcinoembryonic Antigen, and Carbohydrate Antigen 125 in Pancreatic Ductal Adenocarcinoma

Background

Pancreatic cancer is a malignancy with high mortality due to the difficulties in early detection. We investigated and compared the diagnostic and prognostic performance of several blood biomarkers, including microRNA-25 (miR-25), carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and carbohydrate antigen 125 (CA125).

Methods

A retrospective study was conducted at the Chinese People's Liberation Army General Hospital from May 2014 to September 2018. Serum specimens were collected, and miR-25 expression levels were measured using real-time quantitative polymerase chain reaction. Serum CA19-9, CEA, and CA125 levels were measured using enzyme-linked immunosorbent assay (ELISA). Statistical analyses including nonparametric test, receiver operator characteristic (ROC) curves, Kaplan-Meier analysis, and subsequent log-rank test were performed with PRISM 5.0 software. Univariate and multivariate analyses were performed with the R software. P<0.05 was considered statistically significant.

Results

A total of 250 individuals were recruited, including 75 with pancreatic ductal adenocarcinoma (PDAC), 75 with benign lesions, and 100 healthy controls. miR-25, CA19-9, CEA, and CA125 exhibited an area under the curve (AUC) of 0.88, 0.91, 0.81, and 0.76 with a sensitivity of 78.7%, 74.7%, 37.3%, and 35.7% and specificity of 91.5%, 97.0%, 98.2%, and 98.3%, respectively. The combination of miR-25 and CA19-9 further increased the sensitivity to 93.3% with a specificity of 88.5%. Stage-dependent sensitivity was observed with CA19-9, CEA, and CA125. miR-25 levels significantly stratified the prognosis by median level (4,989.97 copies/mL). CA19-9, CEA, and CA125 levels significantly stratified the prognosis by median levels. Univariate and subsequent multivariate analyses identified tumor (T) stage, CA19-9, and CA125 as independent risk factors for PDAC prognosis.

Conclusion

The combination of miR-25 and CA19-9 significantly enhanced the detection sensitivity of PDAC. T stage, CA19-9, and CA125 levels were independent risk factors for PDAC prognosis.

Circulating Cell-Free Nucleic Acids as Biomarkers for Diagnosis and Prognosis of Pancreatic Cancer

A lack of reliable early diagnostic tools represents a major challenge in the management of pancreatic cancer (PCa), as the disease is often only identified after it reaches an advanced stage. This highlights the urgent need to identify biomarkers that can be used for the early detection, staging, treatment monitoring, and prognosis of PCa. A novel approach called liquid biopsy has emerged in recent years, which is a less- or non-invasive procedure since it focuses on plasmatic biomarkers such as DNA and RNA. In the blood of patients with cancer, circulating tumor cells (CTCs) and cell-free nucleic acids (cfNAs) have been identified such as DNA, mRNA, and non-coding RNA (miRNA and lncRNA). The presence of these molecules encouraged researchers to investigate their potential as biomarkers. In this article, we focused on circulating cfNAs as plasmatic biomarkers of PCa and analyzed their advantages compared to traditional biopsy methods.

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.

Role of epigenetics in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, associated with poor survival outcomes. Lack of early diagnosis, resistance to conventional therapeutic treatments (including immunotherapy) and recurrence are some of the major hurdles in PDAC and contribute to its poor survival rate. While the risk of genetic predisposition to cancers is widely acknowledged and understood, recent advances in whole-genome and next-generation sequencing techniques have led to the acknowledgment of the role played by epigenetics, especially in PDAC. Epigenetic changes are heritable genetic modifications that influence gene expression without altering the DNA sequence. Epigenetic mechanisms (e.g., DNA methylation, post-translational modification of histone complexes and ncRNA) that result in reversible changes in gene expression are increasingly understood to be responsible for tumor initiation, development and even escape from immune surveillance. Our review seeks to highlight the various components of the epigenetic machinery that are known to be implicated in PDAC initiation and development and the feasibility of targeting these components to identify novel pharmacological strategies that could potentially lead to breakthroughs in PDAC treatment.

Clinical Prediction Models for Pancreatic Cancer in General and At-Risk Populations: A Systematic Review

INTRODUCTION

Identifying high-risk individuals using a risk prediction model could be a crucial first stage of screening pathways to improve the early detection of pancreatic cancer. A systematic review was conducted to critically evaluate the published primary literature on the development or validation of clinical risk prediction models for pancreatic cancer risk.

METHODS

MEDLINE, Embase, and Web of Science were searched for relevant articles from the inception of each database up to November 2021. Study selection and data extraction were conducted by 2 independent reviewers. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was applied to assess risk of bias.

RESULTS

In total, 33 studies were included, describing 38 risk prediction models. Excluding studies with an overlapping population, this study consist of 15,848,100 participants, of which 58,313 were diagnosed with pancreatic cancer. Eight studies externally validated their model, and 13 performed internal validation. The studies described risk prediction models for pancreatic cancer in the general population (n = 14), patients with diabetes (n = 8), and individuals with gastrointestinal (and other) symptoms (symptoms included abdominal pain, unexplained weight loss, jaundice, and change in bowel habits and indigestion; n = 11). The commonly used clinical risk factors in the model were cigarette smoking (n = 27), age (n = 25), diabetes history (n = 22), chronic pancreatitis (n = 18), and body mass index (n = 14). In the 25 studies that assessed model performance, C-statistics ranged from 0.61 to 0.98. Of the 33 studies included, 6 were rated as being at a low risk of bias based on PROBAST.

DISCUSSION

Many clinical risk prediction models for pancreatic cancer had been developed for different target populations. Although low risk-of-bias studies were identified, these require external validation and implementation studies to ensure that these will benefit clinical decision making.

Diagnosis of Pancreatic Cancer Using miRNA30e Biosensor

This work describes miRNA-based electrochemical biosensor for detection of miRNA30e, a pancreatic cancer biomarker. The screen-printed gold electrode was functionalized using cysteine hydrochloride followed by immobilization of synthesized colloidal gold nanorods (10-12 nm diameter and 25-65 nm length). The gold nanorods modified electrode surface was amino functionalized for covalent attachment of single-stranded DNA probe against miRNA30e (miR30e). This platform was utilized for electrochemical measurements and response analysis of target miRNA30e. Electrochemical impedance spectroscopic measurements showed very poor sensitivity (13.51 Ω/µg/mL/cm²) using charge transfer resistance calibration plots. Cyclic voltammetry and differential pulse voltammetry-based miR30e quantification showed decreasing current response with increasing concentration of miR30e with detection range of 0.1 fg/mL-0.1 µg/mL (14.9 aM-14.9 nM). The sensitivity of DPV sensing (104.4 µA/µg/mL/cm²) was found to be 1.3 times higher than that of CV-based quantification (79.6 µA/µg/mL/cm²). miRNA-based biosensors have the potential of replacing current invasive, time consuming and technically difficult diagnostic procedures. Furthermore, the lower limit of detection of 14.9 aM miRNA30e makes it a promising tool for detection of cancer at early stages and hence increasing survival rate.

Identification of four serum miRNAs as potential markers to screen for thirteen cancer types

Introduction

Cancer consistently remains one of the top causes of death in the United States every year, with many cancer deaths preventable if detected early. Circulating serum miRNAs are a promising, minimally invasive supplement or even an alternative to many current screening procedures. Many studies have shown that different serum miRNAs can discriminate healthy individuals from those with certain types of cancer. Although many of those miRNAs are often reported to be significant in one cancer type, they are also altered in other cancer types. Currently, very few studies have investigated serum miRNA biomarkers for multiple cancer types for general cancer screening purposes.

Method

To identify serum miRNAs that would be useful in screening multiple types of cancers, microarray cancer datasets were curated, yielding 13 different types of cancer with a total of 3352 cancer samples and 2809 non-cancer samples. The samples were divided into training and validation sets. One hundred random forest models were built using the training set to select candidate miRNAs. The selected miRNAs were then used in the validation set to see how well they differentiate cancer from normal samples in an independent dataset. Furthermore, the interactions between these miRNAs and their target mRNAs were investigated.

Result

The random forest models achieved an average of 97% accuracy in the training set with 95% bootstrap confidence interval of 0.9544 to 0.9778. The selected miRNAs were hsa-miR-663a, hsa-miR-6802-5p, hsa-miR-6784-5p, hsa-miR-3184-5p, and hsa-miR-8073. Each miRNA exhibited high area under the curve (AUC) value using receiver operating characteristic analysis. Moreover, the combination of four out of five miRNAs achieved the highest AUC value of 0.9815 with high sensitivity of 0.9773, indicating that these miRNAs have a high potential for cancer screening. miRNA-mRNA and protein-protein interaction analysis provided insights into how these miRNAs play a role in cancer.

Identification of Prognosis-Related Molecular Subgroups and Construction of a Prognostic Prediction Model Using Immune-Related Genes in Pancreatic Cancer

Background

Pancreatic cancer patients with similar clinicopathological status exhibit substantially different therapeutic responses, which might be caused by the vast molecular heterogeneity of tumors. In this study, we attempted to identify specific molecular subgroups and construct a prognostic prediction model based on the expression level of immune-related genes in pancreatic cancer. The transcriptome profiling, single nucleotide variation, copy number variation, clinicopathological information, and follow-up data of pancreatic cancer patients were obtained from The Cancer Genome Atlas database. Thereafter, the immune-related genes with prognostic significance were identified for further consensus cluster analysis. The molecular characteristics and clinicopathological information were compared between the identified subgroups, and a weighted correlation network analysis was performed to identify the hub genes associated with the subgroups. Finally, the prognostic prediction model based on immune-related genes was established using the least absolute shrinkage and selection operator (LASSO) analysis.

Results

A total of 67 immune-relevant genes with prognostic significance were selected and used for the consensus cluster analysis. The total samples were divided into two groups, C1 and C2. The subgroup C1 had a significantly worse prognosis than C2, as well as lower levels of immune cell infiltration, which indicate an immunosuppressed state. The mutational rate of the cancer-related genes including KRAS, TP53, and RNF43 was higher in the C1 subgroup. The C1 subgroup was associated with more advanced tumor grade and T stage and with higher mortality. Using LASSO regression, we developed a prognostic prediction model based on the expression levels of 19 immune-related genes, which we validated in three external data sets. In addition, we identified four potential therapeutic and prognostic biomarkers (TNNT1, KCNN4, SH2D3A, and PHLDA2).

Conclusion

We identified two novel molecular subgroups of pancreatic cancer and developed a prognostic prediction model based on the expression levels of immune-related genes, which could be used in a clinical setting and could aid in unraveling the molecular processes leading to the development of pancreatic cancer.

Extracellular vesicle-derived microRNAs in pancreatic juice as biomarkers for detection of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is usually diagnosed in an advanced stage, with minimal likelihood of long-term survival. Only a small subset of patients are diagnosed with early (T1) disease. Early detection is challenging due to the late onset of symptoms and limited visibility of sub-centimeter cancers on imaging. A novel approach is to support the clinical diagnosis with molecular markers. MicroRNA derived from extracellular vehicles (EVs) in blood has shown promise as a potential biomarker for pancreatic neoplasia, but microRNA derived from pancreatic juice (PJ) may be a more sensitive biomarker, given that is in close contact with ductal cells from which PDAC arises. This study aims to evaluate and compare the performance of PJ- and serum-derived EV-miRNA for the detection of PDAC.

METHODS

PJ was collected from the duodenum during EUS after secretin stimulation from 54 patients with PDAC and 118 non-malignant controls. Serum was available for a subset of these individuals. MiR-16, miR-21, miR-25, miR-155 and miR-210 derived from EVs isolated from PJ and serum were analyzed by qPCR, and serum CA19-9 levels were determined by electrochemiluminescence immunoassay. For statistical analysis, either a Mann-Whitney U test or a Wilcoxon Signed Rank test was performed. ROC curves and AUC were used to assess the sensitivity and specificity of miR expression for PDAC detection.

RESULTS

Expression of EV-miR-21, EV-miR-25 and EV-miR-16 were increased in cases vs controls in PJ, while only EV-miR-210 was increased in serum. The potential to detect PC was good for a combination of PJ EV-miR-21, EV-miR-25, EV-miR-16 and serum miR-210, CA-19-9, with an area under the curve of 0.91, a specificity of 84.2% and a sensitivity of 81.5%.

CONCLUSION

Detection of miRNA from EVs in PJ is feasible. A combined panel of PJ EV-miR-21, EV-miR-25, EV-miR-16, and serum EV-miR-210 and CA19-9 distinguishes cases with PDAC from controls undergoing surveillance with a specificity of 81.5% and sensitivity of 84.2%.

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.

MicroRNAs as biomarkers and perspectives in the therapy of pancreatic cancer

Pancreatic cancer is considered as one of the most aggressive tumor types, representing over 45,750 mortality cases annually in the USA solely. The aggressive nature and late identification of pancreatic cancer, combined with the restrictions of existing chemotherapeutics, present the mandatory need for the advancement of novel treatment systems. Ongoing reports have shown an important role of microRNAs (miRNAs) in the initiation, migration, and metastasis of malignancies. Besides, abnormal transcriptional levels of miRNAs have regularly been related with etiopathogenesis of pancreatic malignancy, underlining the conceivable utilization of miRNAs in the management of pancreatic disease patients. In this review article, we give a concise outline of molecular pathways involved in etiopathogenesis of pancreatic cancer patients as well as miRNA implications in pancreatic cancer patients. Ensuing sections describe the involvement of miRNAs in the diagnosis, prognosis, and therapy of pancreatic cancer patients. The involvement of miRNAs in the chemoresistance of pancreatic cancers was also discussed. End area portrays the substance of survey with future headings.

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).

Emerging roles of miRNAs in the development of pancreatic cancer

Pancreatic cancer is a fatal cancer which is expected to exceed breast cancer as the third foremost source of cancer mortality by 2025. This cancer has been associated with several somatic genetic aberrations including mutations in the KRAS, CDKN2A/p16, TP53, and SMAD4. In addition, epigenetic alterations have been shown to affect development of this cancer. miRNAs are among the mostly appreciated epigenetic factors in this regard. Several oncomiRs such as miR-212, miR 506, miR-196b, miR-221-3p, miR-301a-3p, miR-23a and miR-29a have been found to promote proliferation of pancreatic cancer cells and block apoptotic pathways in these cells. On the other hand, miR-451a, miR-506, miR-142, miR-216b, miR-519d-3p, miR-1181, miR-340, miR-143-3p, miR-203a-3p, miR-455, miR-15a, miR-135a and miR-202 are among tumor suppressor miRNAs that modulate proliferation and cell cycle transition in these cells. In the current paper, we will discuss the role of oncomiRs and tumor suppressor miRNAs in the evolution of pancreatic cancer. Moreover, we will summarize the application of miRNAs as diagnostic and prognostic markers in pancreatic cancer. These studies have shown the ability of miRNAs to be served as non-invasive markers for pancreatic cancer.

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.

Early Detection of Pancreatic Cancer: Risk Factors and the Current State of Screening Modalities

Pancreatic cancer (PC) is expected to become the second leading cause of cancer-related mortality in the United States within the next decade. Patients often present at late stages of the disease, when they become symptomatic; in many cases, these patients have unresectable disease that is associated with a poor prognosis. Considering the low incidence of PC in the general population, routine screening of average-risk individuals is not feasible and not recommended. Individuals with familial germline mutations or familial PC are at higher risk of developing PC. Improving detection of PC at an earlier stage entails the recognition of high-risk individuals who may benefit from a long-term screening program. This article identifies patients who may be at increased risk of developing PC, discusses PC screening recommendations, and compares imaging-based modalities and biomarkers for early detection of PC.