miRNAs as biomarkers for early cancer detection and their application in the development of new diagnostic tools

Artificial intelligence (AI) acceptance in primary care during the coronavirus pandemic: What is the role of patients' gender, age and health awareness? A two-phase pilot study

Background

Artificial intelligence (AI) is steadily entering and transforming the health care and Primary Care (PC) domains. AI-based applications assist physicians in disease detection, medical advice, triage, clinical decision-making, diagnostics and digital public health. Recent literature has explored physicians' perspectives on the potential impact of digital public health on key tasks in PC. However, limited attention has been given to patients' perspectives of AI acceptance in PC, specifically during the coronavirus pandemic. Addressing this research gap, we administered a pilot study to investigate criteria for patients' readiness to use AI-based PC applications by analyzing key factors affecting the adoption of digital public health technology.

Methods

The pilot study utilized a two-phase mixed methods approach. First, we conducted a qualitative study with 18 semi-structured interviews. Second, based on the Technology Readiness and Acceptance Model (TRAM), we conducted an online survey (n = 447).

Results

The results indicate that respondents who scored high on innovativeness had a higher level of readiness to use AI-based technology in PC during the coronavirus pandemic. Surprisingly, patients' health awareness and sociodemographic factors, such as age, gender and education, were not significant predictors of AI-based technology acceptance in PC.

Conclusions

This paper makes two major contributions. First, we highlight key social and behavioral determinants of acceptance of AI-enabled health care and PC applications. Second, we propose that to increase the usability of digital public health tools and accelerate patients' AI adoption, in complex digital public health care ecosystems, we call for implementing adaptive, population-specific promotions of AI technologies and applications.

The diagnostic, prognostic role and molecular mechanism of miR-328 in human cancer

MicroRNA are non-coding small RNAs that bind to their target mRNA and cause mRNA degradation or translation inhibition. MiRNA dysregulation is linked to a variety of human cancers and has a role in the genesis and development of cancer pathology. MiR-328 has been reported to be involved in various human cancers. And miR-328 is considered a key regulator in human cancer. It participates in biological processes such as proliferation, apoptosis, invasion, migration, and EMT. The present review will combine the basic and clinical studies to find that miR-328 promotes tumorigenesis and metastasis in human cancer. And we will describe the diagnostic, prognostic, and therapeutic value of miR-328 in various human cancers.

miRNAs and Multiple Myeloma: Focus on the Pathogenesis, Prognosis, and Drug Resistance

Multiple myeloma (MM) produces clonal plasma cells and aberrant monoclonal antibody accumulation in patients' bone marrow (BM). Around 1% of all cancers and 13% of hematological malignancies are caused by MM, making it one of the most common types of cancer. Diagnostic and therapeutic methods for managing MM are currently undergoing extensive research. MicroRNAs (miRNAs) are short noncoding RNAs that reduce or inhibit the translation of their target mRNA after transcription. Because miRNAs play an influential role in how myeloma develops, resources, and becomes resistant to drugs, miRNA signatures may be used to diagnose, do prognosis, and treat the myeloma response. Consequently, researchers have investigated the levels of miRNA in plasma cells from MM patients and developed tools to test whether they directly impacted tumor growth. This review discusses the latest discoveries in miRNA science and their role in the development of MM. We also emphasize the potential applications of miRNAs to diagnose, prognosticate, and treat MM in the future.

Comprehensive Phenotyping in Inflammatory Bowel Disease: Search for Biomarker Algorithms in the Transkingdom Interactions Context

Inflammatory bowel disease (IBD) is the most common form of intestinal inflammation associated with a dysregulated immune system response to the commensal microbiota in a genetically susceptible host. IBD includes ulcerative colitis (UC) and Crohn's disease (CD), both of which are remarkably heterogeneous in their clinical presentation and response to treatment. This translates into a notable diagnostic challenge, especially in underdeveloped countries where IBD is on the rise and access to diagnosis or treatment is not always accessible for chronic diseases. The present work characterized, for the first time in our region, epigenetic biomarkers and gut microbial profiles associated with UC and CD patients in the Buenos Aires Metropolitan area and revealed differences between non-IBD controls and IBD patients. General metabolic functions associated with the gut microbiota, as well as core microorganisms within groups, were also analyzed. Additionally, the gut microbiota analysis was integrated with relevant clinical, biochemical and epigenetic markers considered in the follow-up of patients with IBD, with the aim of generating more powerful diagnostic tools to discriminate phenotypes. Overall, our study provides new insights into data analysis algorithms to promote comprehensive phenotyping tools using quantitative and qualitative analysis in a transkingdom interactions network context.

Noncoding RNAs Emerging as Drugs or Drug Targets: Their Chemical Modification, Bio-Conjugation and Intracellular Regulation

With the increasing understanding of various disease-related noncoding RNAs, ncRNAs are emerging as novel drugs and drug targets. Nucleic acid drugs based on different types of noncoding RNAs have been designed and tested. Chemical modification has been applied to noncoding RNAs such as siRNA or miRNA to increase the resistance to degradation with minimum influence on their biological function. Chemical biological methods have also been developed to regulate relevant noncoding RNAs in the occurrence of various diseases. New strategies such as designing ribonuclease targeting chimeras to degrade endogenous noncoding RNAs are emerging as promising approaches to regulate gene expressions, serving as next-generation drugs. This review summarized the current state of noncoding RNA-based theranostics, major chemical modifications of noncoding RNAs to develop nucleic acid drugs, conjugation of RNA with different functional biomolecules as well as design and screening of potential molecules to regulate the expression or activity of endogenous noncoding RNAs for drug development. Finally, strategies of improving the delivery of noncoding RNAs are discussed.

Noncoding RNome as Enabling Biomarkers for Precision Health

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

MicroRNAs as Potential Tools for Predicting Cancer Patients’ Susceptibility to SARS-CoV-2 Infection and Vaccination Response

Coronavirus disease (COVID-19) is an infectious disease that is caused by a highly contagious and severe acute respiratory syndrome—coronavirus 2 (SARS-CoV-2). This infection started to spread across the world in 2019 and rapidly turned into a global pandemic, causing an urgent necessity for treatment strategies development. The mRNA vaccines against SARS-CoV-2 can trigger an immune response, providing genetic information that allows the production of spike glycoproteins. MiRNAs play a crucial role in diverse key cellular processes, including antiviral defense. Several miRNAs are described as key factors in SARS-CoV-2 human infection through the regulation of ACE2 levels and by the inhibition of SARS-CoV-2 replication and spike expression. Consequently, these molecules have been considered as highly promising biomarkers. In numerous human malignancies, it has been recognized that miRNAs expression is dysregulated. Since miRNAs can target SARS-CoV-2-associated mRNAs, in cancer patients, the deregulation of these molecules can impair the immune response to the vaccines. Therefore, in this review, we propose a miRNA profile of seven SARS-CoV-2-related miRNAs, namely miR-214, miR-98-5p, miR-7-5p, miR-24-3p, miR-145-5p, miR-223-3p and miR-15b-5p, that are deregulated in a high number of cancers and have the potential to be used as prognostic biomarkers to stratify cancer patients.

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.

Quantum Dots for Cancer-Related miRNA Monitoring

Quantum dots (QDs) possess exceptional optoelectronic properties that enable their use in the most diverse applications, namely, in the medical field. The prevalence of cancer has increased and has been considered the major cause of death worldwide. Thus, there has been a great demand for new methodologies for diagnosing and monitoring cancer in cells to provide an earlier prognosis of the disease and contribute to the effectiveness of treatment. Several molecules in the human body can be considered relevant as cancer markers. Studies published over recent years have revealed that micro ribonucleic acids (miRNAs) play a crucial role in this pathology, since they are responsible for some physiological processes of the cell cycle and, most important, they are overexpressed in cancer cells. Thus, the analytical sensing of miRNA has gained importance to provide monitoring during cancer treatment, allowing the evaluation of the disease's evolution. Recent methodologies based on nanochemistry use fluorescent quantum dots for sensing of the miRNA. Combining the unique characteristics of QDs, namely, their fluorescence capacity, and the fact that miRNA presents an aberrant expression in cancer cells, the researchers created diverse strategies for miRNA monitoring. This review aims to present an overview of the recent use of QDs as biosensors in miRNA detection, also highlighting some tutorial descriptions of the synthesis methods of QDs, possible surface modification, and functionalization approaches.

Urine Cell-Free MicroRNAs in Localized Prostate Cancer Patients

Prostate cancer (PCa) is the most common cancer in men. Prostate-specific antigen screening is recommended for the detection of PCa. However, its specificity is limited. Thus, there is a need to find more reliable biomarkers that allow non-invasive screening for early-stage PCa. This study aims to explore urine microRNAs (miRs) as diagnostic biomarkers for PCa. We assessed cell-free miR (cfmiR) profiles of urine and plasma samples from pre- and post-operative PCa patients (n = 11) and normal healthy donors (16 urine and 24 plasma) using HTG EdgeSeq miRNA Whole Transcriptome Assay based on next-generation sequencing. Furthermore, tumor-related miRs were detected in formalin-fixed paraffin-embedded tumor tissues obtained from patients with localized PCa. Specific cfmiRs signatures were found in urine samples of localized PCa patients using differential expression analysis. Forty-two cfmiRs that were detected were common to urine, plasma, and tumor samples. These urine cfmiRs may have potential utility in diagnosing early-stage PCa and complementing or improving currently available PCa screening assays. Future studies may validate the findings.

Diagnostic and therapeutic biomarkers in colorectal cancer: a review

Colorectal cancer (CRC) is a public health concern and the second most common type of cancer among men and women causing a significant mortality. Biomarkers closely linked to the disease morbidity could holds potential as diagnostic and/or prognostic biomarker for the disease. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through genomics and proteomics according to clinical function and application. Specifically, a number of biomarkers were identified and discussed. Emphasis was placed on their clinical applications relative to the diagnosis and prognosis of CRC. The discovery of more sensitive and specific markers for CRC is an urgent need, and the study of molecular targets is extremely important in this process, as they will allow for a better understanding of colorectal carcinogenesis, identification and validation of potential genetic signatures.

Microarray analysis and functional prediction of differentially expressed circular RNAs in acquired middle ear cholesteatoma

BACKGROUND

Middle ear cholesteatoma is characterized by hyper-proliferation of keratinocytes. Circular RNA (circRNA) plays an essential role in the pathogenesis of many proliferative diseases. However, the role of circRNA in the etiopathogenesis of middle ear cholesteatoma is rarely investigated so far. We aimed to investigate the differential expression profiling of circRNAs between acquired middle ear cholesteatoma and normal skin, and to identify potential circRNAs contributing to the etiopathogenesis of middle ear cholesteatoma. Microarray analysis and functional prediction were performed to investigate the circRNA expression profiling between middle ear cholesteatoma and normal skin. Validation of differentially expressed circRNAs was conducted by qRT-PCR. Prediction of m⁶A modification was also carried out.

RESULTS

Microarray analysis displayed that totally 93 up-regulated and 85 down-regulated circRNAs were identified in middle ear cholesteatoma. Through validation, expressions of hsa_circRNA_104327 and hsa_circRNA_404655 were significantly higher, while hsa_circRNA_000319 was significantly down-regulated in cholesteatoma. GO classification, KEGG pathway, and ceRNA network analyses suggested that these differentially expressed circRNAs might play important roles in the etiopathogenesis of middle ear cholesteatoma. Prediction of m⁶A modification exhibited that hsa_circRNA_000319 possessed 4 m⁶A sites with very high confidence, and hsa_circRNA_404655 had 3 m⁶A sites with high confidence.

CONCLUSIONS

Our study revealed that these differentially expressed circRNAs might contribute to the etiopathogenesis of middle ear cholesteatoma. Further researches should be conducted to investigate the exact mechanism of these differentially expressed circRNAs in the etiopathogenesis of middle ear cholesteatoma. Targeting on these circRNAs may provide a new strategy for middle ear cholesteatoma therapy in the future.

Hsa-mir-3163 and CCNB1 may be potential biomarkers and therapeutic targets for androgen receptor positive triple-negative breast cancer

Breast cancer (BC) is the most common malignancy in female, but the role of androgen receptor (AR) in triple-negative breast cancer (TNBC) is still unclear. This study aimed to exam the performance of innovative biomarkers for AR positive TNBC in diagnosis and therapies. Four datasets (GSE42568, GSE45827, GSE54002 and GSE76124) were analyzed by bioinformatic methods and the differential expression genes (DEGs) between the AR positive TNBC tissues and normal tissues were firstly identified by limma package and Venn diagrams. Next, Gene Ontologies (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to explore the relationship between these DEGs. Then, the Protein-protein interaction (PPI) network was constructed. CytoHubba and bioinformatic approaches including Molecular Complex Detection (MCODE), Gene Expression Profiling Interactive Analysis (GEPIA), the Kaplan–Meier (KM) plotter and The Human Pro-tein Atlas (THPA) were used to identify the hub genes. Lastly, a miRNA-hub-gene regulatory axis was constructed by use of Target Scan database and ENCORI database. As a result, a total of 390 common DEGs were identified, including 250 up-regulated and 140 down-regulated. GO and KEGG enrichment analysis showed that the up-regulated DEGs were mostly enriched in the cell division, mitotic nuclear division, nucleosome, midbody, protein heterodimerization activity, cadherin binding involved in cell−cell adhesion, systemic lupus erythematosus and alcoholism, while the down-regulated DEGs were mainly enriched in carbohydrate metabolic process, extracellular space, extracellular region, zinc ion binding and microRNAs in cancer. Then, 13 hub genes (CCNB2, FOXM1, HMMR, MAD2L1, RRM2, TPX2, TYMS, CEP55, AURKA, CCNB1, CDK1, TOP2A, PBK) were selected. The survival analysis revealed that only CCNB1 was associated with significantly poor survival (P <0.05) in TNBC patients. Finally, we found that hsa-miR-3163 took part in the regulation of CCNB1 and constructed a potential hsa-miR-3163-CCNB1 regulatory axis. The results of current study suggest that CCNB1 and hsa-miR-3163 may serve as highly potential prognostic markers and therapeutic targets for AR positive TNBC. Our findings may make contributions to the diagnosis and therapies of AR positive TNBC.

Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions

Noncoding RNAs (ncRNAs) play prominent roles in the regulation of gene expression via their interactions with other biological molecules such as proteins and nucleic acids. Although much of our knowledge about how these ncRNAs operate in different biological processes has been obtained from experimental findings, computational biology can also clearly substantially boost this knowledge by suggesting possible novel interactions of these ncRNAs with other molecules. Computational predictions are thus used as an alternative source of new insights through a process of mutual enrichment because the information obtained through experiments continuously feeds through into computational methods. The results of these predictions in turn shed light on possible interactions that are subsequently validated experimentally. This review describes the latest advances in databases, bioinformatic tools, and new in silico strategies that allow the establishment or prediction of biological interactions of ncRNAs, particularly miRNAs and lncRNAs. The ncRNA species described in this work have a special emphasis on those found in humans, but information on ncRNA of other species is also included.

A novel microfluidic RNA chip for direct, single-nucleotide specific, rapid and partially-degraded RNA detection

Direct RNA detection is critical for providing the RNA insights into gene expression profiling, noncoding RNAs, RNA-associated diseases and pathogens, without reverse transcription. However, classical RNA analysis usually requires RT-PCR, which can cause bias amplification and quantitation errors. To address this challenge, herein we report a microfluidic RNA chip (the microchip prototype) for direct RNA detection, which is primarily based on RNA extension and labeling with DNA polymerase. This detection strategy is of high specificity (discriminating against single-nucleotide differences), rapidity, accuracy, nuclease resistance, and reusability. Further, we have successfully detected disease-associated RNAs in clinical samples, demonstrating its great potentials in biomedical research and clinical diagnosis.

Plasma-Derived Exosome MiR-19b Acts as a Diagnostic Marker for Pancreatic Cancer

Background

Diagnosis of pancreatic cancer (Pca) is challenging. This study investigated the value of plasma-derived exosome miR-19b (Exo-miR-19b) in diagnosing patients with Pca.

Methods

Plasma was collected from 62 patients with Pca, 30 patients with other pancreatic tumor (OPT), 23 patients with chronic pancreatitis (CP), and 53 healthy volunteers. MiR-19b levels in plasma-derived exosomes were detected.

Results

Plasma-derived Exo-miR-19b levels normalized using miR-1228 were significantly lower in Pca patients than in patients with OPT, CP patients, and healthy volunteers. The diagnostic values of Exo-miR-19b normalized using miR-1228 were superior to those of serum cancer antigen 19-9 (CA19-9) in differentiating Pca patients from healthy volunteers (area under the curve (AUC): 0.942 vs. 0.813, p = 0.0054), potentially better than those of CA19-9 in differentiating Pca patients from CP patients (AUC: 0.898 vs. 0.792, p = 0.0720), and equivalent to those of CA19-9 in differentiating Pca patients from patients with OPT (AUC: 0.810 vs. 0.793, p = 0.8206). When normalized using Caenorhabditis elegans miR-39 (cel-miR-39), Exo-miR-19b levels in Pca patients were significantly higher than those in patients with OPT, CP patients, and healthy volunteers. The diagnostic values of Exo-miR-19b normalized using cel-miR-39 were equivalent to those of CA19-9 in differentiating Pca patients from healthy volunteers (AUC: 0.781 vs. 0.813, p = 0.6118) and CP patients (AUC: 0.672 vs. 0.792, p = 0.1235), while they were inferior to those of CA19-9 in differentiating Pca patients from patients with OPT (AUC: 0.631 vs. 0.793, p = 0.0353).

Conclusion

Plasma-derived Exo-miR-19b is a promising diagnostic marker for Pca. The diagnostic value of plasma-derived Exo-miR-19b normalized using miR-1228 is superior to that of serum CA19-9 in differentiating patients with Pca from healthy volunteers.

MiR-92b-3p Inhibits Proliferation of HER2-Positive Breast Cancer Cell by Targeting circCDYL

Objectives

Circular RNA (circRNA) is a novel class of RNA, which exhibits powerful biological function in regulating cellular fate of various tumors. Previously, we had demonstrated that over-expression of circRNA circCDYL promoted progression of HER2-negative (HER2^–) breast cancer via miR-1275-ULK1/ATG7-autophagic axis. However, the role of circCDYL in HER2-positive (HER2⁺) breast cancer, in particular its role in modulating cell proliferation, one of the most important characteristics of cellular fate, is unclear.

Materials and methods

qRT-PCR and in situ hybridization analyses were performed to examine the expression of circCDYL and miR-92b-3p in breast cancer tissues or cell lines. The biological function of circCDYL and miR-92b-3p were assessed by plate colony formation and cell viability assays and orthotopic animal models. In mechanistic study, circRNAs pull-down, RNA immunoprecipitation, dual luciferase report, western blot, immunohistochemical and immunofluorescence staining assays were performed.

Results

CircCDYL was high-expressed in HER2⁺ breast cancer tissue, similar with that in HER2^– breast cancer tissue. Silencing HER2 gene had no effect on expression of circCDYL in HER2⁺ breast cancer cells. Over-expression of circCDYL promoted proliferation of HER2⁺ breast cancer cells but not through miR-1275-ULK1/ATG7-autophagic axis. CircRNA pull down and miRNA deep-sequencing demonstrated the binding of miR-92b-3p and circCDYL. Interestingly, circCDYL did not act as miR-92b-3p sponge, but was degraded in miR-92b-3p-dependent silencing manner. Clinically, expression of circCDYL and miR-92b-3p was associated with clinical outcome of HER2⁺ breast cancer patients.

Conclusion

MiR-92b-3p-dependent cleavage of circCDYL was an essential mechanism in regulating cell proliferation of HER2⁺ breast cancer cells. CircCDYL was proved to be a potential therapeutic target for HER2⁺ breast cancer, and both circCDYL and miR-92b-3p might be potential biomarkers in predicting clinical outcome of HER2⁺ breast cancer patients.