Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection

The Predictive Value of Blood-Derived Exosomal miRNAs as Biomarkers in Breast Cancer: A Systematic Review

Breast cancer (BC) remains a widespread disease worldwide, despite advances in its detection and treatment. microRNAs (miRNAs) play a significant role in cancer, and their presence within exosomes may confer several advantages in terms of tumor initiation, propagation, immune evasion, and drug resistance compared to freely circulating miRNAs in the blood. The objective of this study was to conduct a systematic review to analyze the role of exosomal miRNAs present in serum or plasma as biomarkers in BC. Bibliographic sources were collected from various databases with no starting date limit until March 2023. The search terms used were related to "breast cancer," "microRNAs," and "exosomes." Following the search, inclusion and exclusion criteria were applied, resulting in a total of 46 articles. Data were extracted from the selected studies and summarized to indicate the miRNAs, type of dysregulation, sample source, number of patients and controls, and clinical relevance of the miRNAs. We carried out an enrichment study of the microRNAs that appeared in at least 3 studies, those that were suitable for selection were miR-16, miR-21 and miR-155. Exosomal miRNAs isolated from blood samples of patients diagnosed with BC could be valuable in the clinical setting. They could provide information about early diagnosis, disease progression, recurrence, treatment response, and metastases. It is crucial to reach a consensus on the specific exosomal miRNAs to detect and the most appropriate type of sample for comprehensive utilization of miRNAs as biomarkers for BC.

miR‑146a‑5p and miR‑191‑5p as novel diagnostic marker candidates for ovarian clear cell carcinoma

Ovarian cancer is a malignant gynecologic disease rarely diagnosed in the early stages. Among the various types of ovarian cancer, clear cell carcinoma has a poor prognosis due to its malignant potential. MicroRNAs (miRNAs/miRs) regulate gene expression in cells by suppressing the translation of target genes or by degrading the target mRNA. miRNAs are also secreted from the cells in the blood, binding to proteins or lipids and assisting in cell-cell communication. Therefore, serum miRNAs may be considered potential diagnostic biomarkers for ovarian cancer. The present study investigated and identified specific miRNAs associated with ovarian clear cell carcinoma and compared them to those in ovarian endometrioma samples and healthy controls. CA125, an ovarian tumor marker, did not differ between patients with ovarian clear cell carcinoma, endometriosis or healthy controls. Subsequently, four miRNAs (miR-146a-5p, miR-191-5p, miR-484 and miR-574-3p) were analyzed. The expression levels of miR-146a-5p and miR-191-5p were significantly increased in the serum samples from patients with ovarian clear cell carcinoma compared with those in the healthy controls, but there was no significant difference compared with in patients with endometriosis. Furthermore, the bioinformatics analysis showed that CCND2 and NOTCH2 were the candidate target genes of miR-146a-5p and miR-191-5p. In conclusion, the results of the present study demonstrated that miR-146a-5p and miR-191-5p may be useful as early and non-invasive diagnostic tools in ovarian clear cell carcinoma. These miRNAs can help in distinguishing between ovarian clear cell carcinoma and ovarian endometrioma. To the best of our knowledge, no previous studies have screened any candidates specifically for ovarian clear cell carcinoma.

Current situation and trend of non-coding RNA in rheumatoid arthritis: a review and bibliometric analysis

Background

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease that affects multiple joints and has adverse effects on various organs throughout the body, often leading to a poor prognosis. Recent studies have shown significant progress in the research of non-coding RNAs (ncRNAs) in RA. Therefore, this study aims to comprehensively assess the current status and research trends of ncRNAs in RA through a bibliometric analysis.

Methods

This study retrieved articles relevant to ncRNAs and RA from the Science Citation Index Expanded Database of the Web of Science Core Collection between January 1st, 2003, and July 31st, 2023. The relevant articles were screened based on the inclusion criteria. VOSviewer and CiteSpace are utilized for bibliometric and visual analysis.

Results

A total of 1697 publications were included in this study, and there was a noticeable increase in annual publications from January 1st, 2003, to July 31st, 2023. China, the United States, and the United Kingdom were the most productive countries in this field, contributing to 43.81%, 13.09%, and 3.87% of the publications. Anhui Medical University and Lu Qianjin were identified as the most influential institution and author. Frontiers In Immunology stood out as the most prolific journal, while Arthritis & Rheumatology was the most co-cited journal. Additionally, the research related to "circular RNA", "oxidative stress", "proliferation", and "migration" have emerged as new hotspots in the field.

Conclusion

In this study, we have summarized the publication characteristics related to ncRNA and RA and identified the most productive countries, institutions, authors, journals, hot topics, and trends.

Recent Progress in Prompt Molecular Detection of Exosomes Using CRISPR/Cas and Microfluidic-Assisted Approaches Toward Smart Cancer Diagnosis and Analysis

Exosomes are essential indicators of molecular mechanisms involved in interacting with cancer cells and the tumor environment. As nanostructures based on lipids and nucleic acids, exosomes provide a communication pathway for information transfer by transporting biomolecules from the target cell to other cells. Importantly, these extracellular vesicles are released into the bloodstream by the most invasive cells, i. e., cancer cells; in this way, they could be considered a promising specific biomarker for cancer diagnosis. In this matter, CRISPR-Cas systems and microfluidic approaches could be considered practical tools for cancer diagnosis and understanding cancer biology. CRISPR-Cas systems, as a genome editing approach, provide a way to inactivate or even remove a target gene from the cell without affecting intracellular mechanisms. These practical systems provide vital information about the factors involved in cancer development that could lead to more effective cancer treatment. Meanwhile, microfluidic approaches can also significantly benefit cancer research due to their proper sensitivity, high throughput, low material consumption, low cost, and advanced spatial and temporal control. Thereby, employing CRISPR-Cas- and microfluidics-based approaches toward exosome monitoring could be considered a valuable source of information for cancer therapy and diagnosis. This review assesses the recent progress in these promising diagnosis approaches toward accurate cancer therapy and in-depth study of cancer cell behavior.

Involvement of FAM170B-AS1, hsa-miR-1202, and hsa-miR-146a-5p in breast cancer

BACKGROUND

FAM170B-AS1 is usually expressed low in all organs except for testicular tissues. No study was performed to explore its role in breast cancer (BC). Contradictory results were reported about hsa-miR-1202 and hsa-miR-146a-5p in BC.

OBJECTIVE

The present study aimed to explore the involvement of FAM170B-AS1 in BC using bioinformatics predictive tools, followed by a practical validation besides exploring the impact of hsa-miR-1202 and hsa-miR-146a-5p in BC.

METHODS

This study enrolled 96 female patients with BC, 30 patients with benign breast diseases (BBD), and 25 control subjects. The expressions of circulating FAM170B-AS1, hsa-miR-1202, and hsa-miR-146a-5p were quantified using qRT-PCR. These ncRNAs' associations, predictive, and diagnostic roles in BC were statistically tested. The underlying miRNA/mRNA targets of FAM170B-AS1 in BC were bioinformatically predicted followed by confirmation based on the GEPIA and TCGA databases.

RESULTS

The expression of FAM170B-AS1 was upregulated in sera of BC patients and hsa-miR-1202 was upregulated in sera of BBD and BC patients while that of hsa-miR-146a-5p was downregulated in BC. These FAM170B-AS1 was significantly associated with BC when compared to BBD. FAM170B-AS1 and hsa-miR-1202 were statistically associated with the BC's stage, grade, and LN metastasis. FAM170B-AS1 and hsa-miR-146a-5p gave the highest specificity and sensitivity for BC. KRAS and EGFR were predicted to be targeted by FAM170B-AS1 through interaction with hsa-miR-143-3p and hsa-miR-7-5p, respectively. Based on the TCGA database, cancer patients having mutations in FAM170B show good overall survival.

CONCLUSIONS

The present study reported that for the first time, FAM170B-AS1 may be a potential risk factor, predictive, and diagnostic marker for BC. In addition, FAM170B-AS1 might be involved in BC by interacting with hsa-miR-143-3p/KRAS and hsa-miR-7-5p/EGFR through enhancement or repression that may present a new therapeutic option for BC.

Identifying MicroRNAs Suitable for Detection of Breast Cancer: A Systematic Review of Discovery Phases Studies on MicroRNA Expression Profiles

The analysis of circulating tumor cells and tumor-derived materials, such as circulating tumor DNA, circulating miRNAs (cfmiRNAs), and extracellular vehicles provides crucial information in cancer research. CfmiRNAs, a group of short noncoding regulatory RNAs, have gained attention as diagnostic and prognostic biomarkers. This review focuses on the discovery phases of cfmiRNA studies in breast cancer patients, aiming to identify altered cfmiRNA levels compared to healthy controls. A systematic literature search was conducted, resulting in 16 eligible publications. The studies included a total of 585 breast cancer cases and 496 healthy controls, with diverse sample types and different cfmiRNA assay panels. Several cfmiRNAs, including MIR16, MIR191, MIR484, MIR106a, and MIR193b, showed differential expressions between breast cancer cases and healthy controls. However, the studies had a high risk of bias and lacked standardized protocols. The findings highlight the need for robust study designs, standardized procedures, and larger sample sizes in discovery phase studies. Furthermore, the identified cfmiRNAs can serve as potential candidates for further validation studies in different populations. Improving the design and implementation of cfmiRNA research in liquid biopsies may enhance their clinical diagnostic utility in breast cancer patients.

Analysis of circulating extracellular vesicle derived microRNAs in breast cancer patients with obesity: a potential role for Let-7a

BACKGROUND

The incidence of obesity, a known risk factor for several metabolic and chronic diseases, including numerous malignancies, has risen sharply in the world. Various clinical studies demonstrate that excessive Body Mass Index (BMI) may worsen the incidence, prognosis, and mortality rates of breast cancer. Thus, understanding the link tying up obesity and breast cancer onset and progression is critically important, as it can impact patients' survival and quality of life. Recently, circulating extracellular vesicle (EV) derived miRNAs have attracted much attention for their diagnostic, prognostic and therapeutic potential in oncology research. Although the potential role of EV-derived miRNAs in the early detection of breast cancer has been repeatedly mentioned, screening of miRNAs packaged within serum EVs has not yet been reported in patients with obesity.

METHODS

Circulating EVs were isolated from normal weight (NW), and overweight/obese (OW/Ob) breast cancer patients and characterized by Transmission Electron Microscopy (TEM), Nanoparticle Tracking Analysis (NTA), and protein marker expression. Evaluation of EV-associated miRNAs was conducted in a screening (RNA-seq) and a validation (qRT-PCR) cohort. Bioinformatic analysis was performed to uncover significantly enriched biological processes, molecular functions and pathways. ROC and Kaplain-Meier survival analyses were used for clinical significance.

RESULTS

Comparison of serum EV-derived miRNAs from NW and OW/Ob patients detected seven differentially expressed miRNAs (let-7a-5p, miR-122-5p, miR-30d-5p, miR-126-3p, miR-27b-3p, miR-4772-3p, and miR-10a-5p) in the screening cohort. GO analysis revealed the enrichment of protein phosphorylation, intracellular signal transduction, signal transduction, and vesicle-mediated transport among the top biological processes. In addition, the target genes were significantly enriched in pathways related to PI3K/Akt, growth hormones, and insulin signalings, which are all involved in obesity-related diseases and/or breast cancer progression. In the validation cohort, qRT-PCR confirmed a significant down-regulation of EV-derived let-7a in the serum of OW/Ob breast cancer patients compared to NW patients. Let-7a levels also exhibited a negative correlation with BMI values. Importantly, decreased let-7a miRNA expression was associated with higher tumor grade and poor survival in patients with breast cancer.

CONCLUSION

These results suggest that serum-EV derived miRNAs may reflect a differential profile in relation to a patient's BMI, which, once validated in larger cohorts of patients, could provide insights into novel specific biomarkers and innovative targets to prevent the progression of obesity-mediated breast cancer.

NCMD: Node2vec-Based Neural Collaborative Filtering for Predicting MiRNA-Disease Association

Numerous studies have reported that micro RNAs (miRNAs) play pivotal roles in disease pathogenesis based on the deregulation of the expressions of target messenger RNAs. Therefore, the identification of disease-related miRNAs is of great significance in understanding human complex diseases, which can also provide insight into the design of novel prognostic markers and disease therapies. Considering the time and cost involved in wet experiments, most recent works have focused on the effective and feasible modeling of computational frameworks to uncover miRNA-disease associations. In this study, we propose a novel framework called node2vec-based neural collaborative filtering for predicting miRNA-disease association (NCMD) based on deep neural networks. Initially, NCMD exploits Node2vec to learn low-dimensional vector representations of miRNAs and diseases. Next, it utilizes a deep learning framework that combines the linear ability of generalized matrix factorization and nonlinear ability of a multilayer perceptron. Experimental results clearly demonstrate the comparable performance of NCMD relative to the state-of-the-art methods according to statistical measures. In addition, case studies on breast cancer, lung cancer and pancreatic cancer validate the effectiveness of NCMD. Extensive experiments demonstrate the benefits of modeling a neural collaborative-filtering-based approach for discovering novel miRNA-disease associations.

An Epidemiological Systematic Review with Meta-Analysis on Biomarker Role of Circulating MicroRNAs in Breast Cancer Incidence

Breast cancer (BC) is a multifactorial disease caused by an interaction between genetic predisposition and environmental exposures. MicroRNAs are a group of small non-coding RNA molecules, which seem to have a role either as tumor suppressor genes or oncogenes and seem to be related to cancer risk factors. We conducted a systematic review and meta-analysis to identify circulating microRNAs related to BC diagnosis, paying special attention to methodological problems in this research field. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seventy-five studies were included in the systematic review. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seven studies were included in the MIR21 and MIR155 meta-analysis, while four studies were included in the MIR10b metanalysis. The pooled sensitivity and specificity of MIR21 for BC diagnosis were 0.86 (95%CI 0.76-0.93) and 0.84 (95%CI 0.71-0.92), 0.83 (95%CI 0.72-0.91) and 0.90 (95%CI 0.69-0.97) for MIR155, and 0.56 (95%CI 0.32-0.71) and 0.95 (95%CI 0.88-0.98) for MIR10b, respectively. Several other microRNAs were found to be dysregulated, distinguishing BC patients from healthy controls. However, there was little consistency between included studies, making it difficult to identify specific microRNAs useful for diagnosis.

Hypoxia-induced paclitaxel resistance in cervical cancer modulated by miR-100 targeting of USP15

Objective

Hypoxia, which occurs during the development of cervical cancer, confers chemotherapy resistance. MicroRNA expression is regulated by hypoxia and is associated with the onset and progression of certain types of cancer. MicroRNA-100 (miR-100) is a microRNA, associated with nasopharyngeal and oral squamous cell carcinomas, whose expression is decreased in cervical cancer. This study aims to ascertain the effect of hypoxia on expression levels of both miR-100 and its target genes, as well as exploring the sensitivity to paclitaxel under hypoxic conditions.

Methods

We investigated the effect of hypoxia on miR-100 expression. We also explored the regulators of paclitaxel response under hypoxic conditions of cervical cancer.

Results

Using RT-qPCR, we found that expression of miR-100 in cervical cancer cell lines SiHa and HeLa is significantly higher under hypoxic conditions (1% O₂). We also confirmed that human ubiquitin-specific protease 15 (USP15) is the one of the target proteins of miR-100. Hypoxia and overexpression of miR-100 both reduced the activity of the luciferase reporter containing the 3'-untranslated region of USP15, which contains the miR-100 binding site. Furthermore, a western blot analysis showed that hypoxia suppresses the expression of the USP15 protein, while RT-qPCR showed hypoxia-induced downregulation of USP15 mRNA levels. We also discovered that overexpression of miR-100 induces paclitaxel resistance, thereby reducing the drug's therapeutic effect on cell death.

Conclusions

Our results are consistent with the hypothesis that cervical cancer cells overexpress miR-100 in response to hypoxia and that miR-100 is a facilitator of USP15 downregulation and inactivation.

Predicting multiple types of miRNA-disease associations using adaptive weighted nonnegative tensor factorization with self-paced learning and hypergraph regularization

More and more evidence indicates that the dysregulations of microRNAs (miRNAs) lead to diseases through various kinds of underlying mechanisms. Identifying the multiple types of disease-related miRNAs plays an important role in studying the molecular mechanism of miRNAs in diseases. Moreover, compared with traditional biological experiments, computational models are time-saving and cost-minimized. However, most tensor-based computational models still face three main challenges: (i) easy to fall into bad local minima; (ii) preservation of high-order relations; (iii) false-negative samples. To this end, we propose a novel tensor completion framework integrating self-paced learning, hypergraph regularization and adaptive weight tensor into nonnegative tensor factorization, called SPLDHyperAWNTF, for the discovery of potential multiple types of miRNA-disease associations. We first combine self-paced learning with nonnegative tensor factorization to effectively alleviate the model from falling into bad local minima. Then, hypergraphs for miRNAs and diseases are constructed, and hypergraph regularization is used to preserve the high-order complex relations of these hypergraphs. Finally, we innovatively introduce adaptive weight tensor, which can effectively alleviate the impact of false-negative samples on the prediction performance. The average results of 5-fold and 10-fold cross-validation on four datasets show that SPLDHyperAWNTF can achieve better prediction performance than baseline models in terms of Top-1 precision, Top-1 recall and Top-1 F1. Furthermore, we implement case studies to further evaluate the accuracy of SPLDHyperAWNTF. As a result, 98 (MDAv2.0) and 98 (MDAv2.0-2) of top-100 are confirmed by HMDDv3.2 dataset. Moreover, the results of enrichment analysis illustrate that unconfirmed potential associations have biological significance.

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Background:

Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid biopsy (LB) is a non-invasive diagnostic technique that allows the analysis of biomarkers in different body fluids, particularly in peripheral blood and also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal secretions, breast milk, and tears. The objective was to analyze the available evidence related to the use of biomarkers obtained by LB for the early diagnosis of BC.

Methods:

Articles related to the use of biomarkers for the early diagnosis of BC due to LB, published between 2010 and 2022, from the databases (WoS, EMBASE, PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied in the articles to determine their methodological quality (MQ). Descriptive statistics were used, as well as determination of weighted averages of each variable, to analyze the extracted data. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) are described.

Results:

In this systematic review (SR), 136 articles met the selection criteria, representing 17 709 patients with BC. However, 95.6% were case-control studies. In 96.3% of cases, LB was performed in peripheral blood samples. Most of the articles were based on microRNA (miRNA) analysis. The mean MQ score was 25/45 points. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) have been found.

Conclusions:

The determination of biomarkers through LB is a useful mechanism for the diagnosis of BC. The analysis of miRNA in peripheral blood is the most studied methodology. Our results indicate that LB has a high sensitivity and specificity for the diagnosis of BC, especially in early stages.

Identification of Differentially Expressed microRNAs Associated with Ischemic Stroke by Integrated Bioinformatics Approaches

Ischemic stroke (IS) is one of the leading causes of disability and mortality worldwide. This study aims to find the crucial exosomal miRNAs associated with IS by using bioinformatics methods, reveal potential biomarkers for IS, and investigate the association between the identified biomarker and immune cell pattern in the peripheral blood of IS patients. In this study, 3 up-regulated miRNAs (hsa-miR-15b-5p, hsa-miR-184, and hsa-miR-16-5p) miRNAs in the serum exosomes between IS patients and healthy controls from GEO database (GSE199942) and 25 down-regulated genes of peripheral blood mononuclear cells of IS patients from GSE22255 were obtained with the help of the R software. GO annotation and KEGG pathway enrichment analysis showed that the 25 down-regulated genes were associated with coenzyme metabolic process and were mainly enriched in the N-glycan biosynthesis pathway. Furthermore, we performed the LASSO algorithm to narrow down the above 25 intersected genes, and identified 8 key genes which had a good diagnostic value in discriminating IS patients from the healthy controls analyzed with ROC curve. CIBERSORT algorithm indicated that the abundance of M0 macrophages and resting mast cells was significantly lower than that of the control group. The spearman correlation analysis showed that STT3A was negatively correlated with the proportion of follicular helper T cells, activated NK cells and resting dendritic cells. Finally, GSE117064 showed that has-miR-16-5p was more advantageous for diagnosing stroke. In conclusion, hsa-miR-15b-5p, hsa-miR-184, and hsa-miR-16-5p are identified as specific related exosomal miRNAs for IS patients. These genes may provide new targets for the early identification of IS.

Relationship of micro-RNA, mRNA and eIF Expression in Tamoxifen-Adapted MCF-7 Breast Cancer Cells: Impact of miR-1972 on Gene Expression, Proliferation and Migration

Background: Tamoxifen-adapted MCF-7-Tam cells represent an in-vitro model for acquired tamoxifen resistance, which is still a problem in clinics. We here investigated the correlation of microRNA-, mRNA- and eukaryotic initiation factors (eIFs) expression in this model. Methods: MicroRNA- and gene expression were analyzed by nCounter and qRT-PCR technology; eIFs by Western blotting. Protein translation mode was determined using a reporter gene assay. Cells were transfected with a miR-1972-mimic. Results: miR-181b-5p,-3p and miR-455-5p were up-, miR-375, and miR-1972 down-regulated and are significant in survival analysis. About 5% of the predicted target genes were significantly altered. Pathway enrichment analysis suggested a contribution of the FoxO1 pathway. The ratio of polio-IRES driven to cap-dependent protein translation shifted towards cap-dependent initiation. Protein expression of eIF2A, -4G, -4H and -6 decreased, whereas eIF3H was higher in MCF-7-Tam. Significant correlations between tamoxifen-regulated miRNAs and eIFs were found in representative breast cancer cell lines. Transfection with a miR-1972-mimic reverses tamoxifen-induced expression for a subset of genes and increased proliferation in MCF-7, but reduced proliferation in MCF-7-Tam, especially in the presence of 4OH-tamoxifen. Migration was inhibited in MCF-7-Tam cells. Translation mode remained unaffected. Conclusions: miR-1972 contributes to the orchestration of gene-expression and physiological consequences of tamoxifen adaption.

Meta-analysis of diagnostic cell-free circulating microRNAs for breast cancer detection

Background

Breast cancer (BC) is the most frequently diagnosed cancer among women. Numerous studies explored cell-free circulating microRNAs as diagnostic biomarkers of BC. As inconsistent and rarely intersecting microRNA panels have been reported thus far, we aim to evaluate the overall diagnostic performance as well as the sources of heterogeneity between studies.

Methods

Based on the search of three online search engines performed up to March 21^st 2022, 56 eligible publications that investigated diagnostic circulating microRNAs by utilizing Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) were obtained. Primary studies’ potential for bias was evaluated with the revised tool for the quality assessment of diagnostic accuracy studies (QUADAS-2). A bivariate generalized linear mixed-effects model was applied to obtain pooled sensitivity and specificity. A novel methodology was utilized in which the sample and study models’ characteristics were analysed to determine the potential preference of studies for sensitivity or specificity.

Results

Pooled sensitivity and specificity of 0.85 [0.81—0.88] and 0.83 [0.79—0.87] were obtained, respectively. Subgroup analysis showed a significantly better performance of multiple (sensitivity: 0.90 [0.86—0.93]; specificity: 0.86 [0.80—0.90]) vs single (sensitivity: 0.82 [0.77—0.86], specificity: 0.83 [0.78—0.87]) microRNA panels and a comparable pooled diagnostic performance between studies using serum (sensitivity: 0.87 [0.81—0.91]; specificity: 0.83 [0.78—0.87]) and plasma (sensitivity: 0.83 [0.77—0.87]; specificity: 0.85 [0.78—0.91]) as specimen type. In addition, based on bivariate and univariate analyses, miRNA(s) based on endogenous normalizers tend to have a higher diagnostic performance than miRNA(s) based on exogenous ones. Moreover, a slight tendency of studies to prefer specificity over sensitivity was observed.

Conclusions

In this study the diagnostic ability of circulating microRNAs to diagnose BC was reaffirmed. Nonetheless, some subgroup analyses showed between-study heterogeneity. Finally, lack of standardization and of result reproducibility remain the biggest issues regarding the diagnostic application of circulating cell-free microRNAs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09698-8.

The microRNA-202 as a Diagnostic Biomarker and a Potential Tumor Suppressor

MicroRNA-202 (miR-202) is a member of the highly conserved let-7 family that was discovered in Caenorhabditis elegans and recently reported to be involved in cell differentiation and tumor biology. In humans, miR-202 was initially identified in the testis where it was suggested to play a role in spermatogenesis. Subsequent research showed that miR-202 is one of the micro-RNAs that are dysregulated in different types of cancer. During the last decade, a large number of investigations has fortified a role for miR-202 in cancer. However, its functions can be double-edged, depending on context they may be tumor suppressive or oncogenic. In this review, we highlight miR-202 as a potential diagnostic biomarker and as a suppressor of tumorigenesis and metastasis in several types of tumors. We link miR-202 expression levels in tumor types to its involved upstream and downstream signaling molecules and highlight its potential roles in carcinogenesis. Three well-known upstream long non-coding-RNAs (lncRNAs); MALAT1, NORAD, and NEAT1 target miR-202 and inhibit its tumor suppressive function thus fueling cancer progression. Studies on the downstream targets of miR-202 revealed PTEN, AKT, and various oncogenes such as metadherin (MTDH), MYCN, Forkhead box protein R2 (FOXR2) and Kirsten rat sarcoma virus (KRAS). Interestingly, an upregulated level of miR-202 was shown by most of the studies that estimated its expression level in blood or serum of cancer patients, especially in breast cancer. Reduced expression levels of miR-202 in tumor tissues were found to be associated with progression of different types of cancer. It seems likely that miR-202 is embedded in a complex regulatory network related to the nature and the sensitivity of the tumor type and therapeutic (pre)treatments. Its variable roles in tumorigenesis are mediated in part thought its oncogene effectors. However, the currently available data suggest that the involved signaling pathways determine the anti- or pro-tumorigenic outcomes of miR-202’s dysregulation and its value as a diagnostic biomarker.

MicroRNAs: Novel players in the diagnosis and treatment of cancer cachexia (Review)

Cachexia denotes a complex metabolic syndrome featuring severe loss of weight, fatigue and anorexia. In total, 50-80% of patients suffering from advanced cancer are diagnosed with cancer cachexia, which contributes to 40% of cancer-associated mortalities. MicroRNAs (miRNAs) are non-coding RNAs capable of regulating gene expression. Dysregulated miRNA expression has been observed in muscle tissue, adipose tissue and blood samples from patients with cancer cachexia compared with that of samples from patients with cancer without cachexia or healthy controls. In addition, miRNAs promote and maintain the malignant state of systemic inflammation, while inflammation contributes to cancer cachexia. The present review discusses the role of miRNAs in the progression of cancer cachexia, and assess their diagnostic value and potential therapeutic value.

Near-infrared spectroscopy combined with pattern recognition algorithms to quickly classify raisins

With the development of commodity economy, the emergence of fake and shoddy raisin has seriously harmed the interests of consumers and enterprises. To deal with this problem, a classification method combining near-infrared spectroscopy and pattern recognition algorithms were proposed for adulterated raisins. In this study, the experiment was performed by three kinds of raisins in Xinjiang (Hongxiangfei, Manaiti, Munage). After collecting and normalizing the spectral data, we compared the spectra of three kinds of raisins. Next the principal component analysis (PCA) was preformed to compress the dimension of the spectral data, and then classification models including support vector machine (SVM), multiscale fusion convolutional neural network (MCNN) and improved AlexNet were established to identify raisins. The accuracy of SVM, MCNN, and improved AlexNet is 100%, 92.83%, and 97.78% respectively. This study proves that near-infrared spectroscopy combined with pattern recognition is feasible for the raisin inspection.

MicroRNAs as therapeutic targets in breast cancer metastasis

Breast cancer is a complex disease with multiple risk factors involved in its pathogenesis. Among these factors, microRNAs are considered for playing a fundamental role in the development and progression of malignant breast tumors. In recent years, various studies have demonstrated that several microRNAs exhibit increased or decreased expression in metastatic breast cancer, acting as indicators of metastatic potential in body fluids and tissue samples. The identification of these microRNA expression patterns could prove instrumental for the development of novel therapeutic molecules that either mimic or inhibit microRNA action. Additionally, an efficient delivery system mediated by viral vectors, nonviral carriers, or scaffold biomaterials is a prerequisite for implementing microRNA-based therapies; therefore, this review attempts to highlight essential microRNA molecules involved in the metastatic process of breast cancer and discuss recent advances in microRNA-based therapeutic approaches with potential future applications to the treatment sequence of breast cancer.

The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer

Breast cancer continues to be a major global problem with significant mortality associated with advanced stage and metastases at clinical presentation. However, several findings suggest that metastasis is indeed an early occurrence. The standard diagnostic techniques such as invasive core needle biopsy, serological protein marker assays, and non-invasive radiological imaging do not provide information about the presence and molecular profile of small fractions of early metastatic tumor cells which are prematurely dispersed in the circulatory system. These circulating tumor cells (CTCs) diverge from the primary tumors as clusters with a defined secretome comprised of circulating cell-free nucleic acids and small microRNAs (miRNAs). These circulatory biomarkers provide a blueprint of the mutational profile of the tumor burden and tumor associated alterations in the molecular signaling pathways involved in oncogenesis. Amidst the multitude of circulatory biomarkers, miRNAs serve as relatively stable and precise biomarkers in the blood for the early detection of CTCs, and promote step-wise disease progression by executing paracrine signaling that transforms the microenvironment to guide the metastatic CTCs to anchor at a conducive new organ. Random sampling of easily accessible patient blood or its serum/plasma derivatives and other bodily fluids collectively known as liquid biopsy (LB), forms an efficient alternative to tissue biopsies. In this review, we discuss in detail the divergence of early metastases as CTCs and the involvement of miRNAs as detectable blood-based diagnostic biomarkers that warrant a timely screening of cancer, serial monitoring of therapeutic response, and the dynamic molecular adaptations induced by miRNAs on CTCs in guiding primary and second-line systemic therapy.

New insights into the discovery of drugs for triple-negative breast cancer metastasis

INTRODUCTION

Triple-negative breast cancer (TNBC) is of great concern due to its aggressiveness and lack of targeted therapy. For these reasons, TNBC is one of the main causes of death in women, mainly due to metastases. Tumor dissemination has highlighted a set of possible targets, with extensive research into new single-target drugs, in addition to drug repurposing strategies, being undertaken to discover new classes of potential inhibitors of metastasis.

AREAS COVERED

The authors here describe the main proposed targets and the bases of their pharmacological inhibition with different chemical compounds. The authors also discuss the state-of-the-art from the latest clinical trials and highlight other potential targets for metastatic TNBC.

EXPERT OPINION

In the last decade, oncology research has changed its focus from primary tumors to moving tumor cells, their products, and to the secondary tumor and its surroundings, for the purpose of finding targets to treat metastasis. Consequently, our comprehension of the complexity of the metastatic process has increased drastically, with, furthermore, the discovery of new potential targets. Although promising, the wide range of strategies is still not effective to suppress TNBC metastasis in terms of increasing patient survival or decreasing the number of metastases. Treating or preventing metastasis continues to be a great challenge.

Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts

This study was conducted to confirm the performance of the microRNA (miRNA) biomarker combination as a new breast cancer screening method in Korean women under the age of 50 with a high percentage of dense breasts. To determine the classification performance of a set of miRNA biomarkers (miR-1246, 202, 21, and 219B) useful for breast cancer screening, we determined whether there was a significant difference between the breast cancer and healthy control groups through box plots and the Mann–Whitney U-test, which was further examined in detail by age group. To verify the classification performance of the 4 miRNA biomarker set, 4 classification methods (logistic regression, random forest, XGBoost, and generalized linear model plus random forest) were applied, and 10-fold cross-validation was used as a validation method to improve performance stability. We confirmed that the best breast cancer detection performance was achievable in patients under 50 years of age when the set of 4 miRNAs were used. Under the age of 50, the 4 miRNA biomarkers showed the highest performance with a sensitivity of 85.29%, specificity of 93.33%, and area under the curve (AUC) of 0.961. Examining the results of 4 miRNA biomarkers was found to be an effective strategy for diagnosing breast cancer in Korean women under 50 years of age with dense breasts, and hence has the potential as a new breast cancer screening tool. Further validation in an appropriate screening population with large-scale clinical trials is required.

The miR-200 Family of microRNAs: Fine Tuners of Epithelial-Mesenchymal Transition and Circulating Cancer Biomarkers

The miR-200 family of microRNAs (miRNAs) includes miR-200a, miR-200b, miR-200c, miR-141 and miR-429, five evolutionarily conserved miRNAs that are encoded in two clusters of hairpin precursors located on human chromosome 1 (miR-200b, miR-200a and miR-429) and chromosome 12 (miR-200c and miR-141). The mature -3p products of the precursors are abundantly expressed in epithelial cells, where they contribute to maintaining the epithelial phenotype by repressing expression of factors that favor the process of epithelial-to-mesenchymal transition (EMT), a key hallmark of oncogenic transformation. Extensive studies of the expression and interactions of these miRNAs with cell signaling pathways indicate that they can exert both tumor suppressor- and pro-metastatic functions, and may serve as biomarkers of epithelial cancers. This review provides a summary of the role of miR-200 family members in EMT, factors that regulate their expression, and important targets for miR-200-mediated repression that are involved in EMT. The second part of the review discusses the potential utility of circulating miR-200 family members as diagnostic/prognostic biomarkers for breast, colorectal, lung, ovarian, prostate and bladder cancers.

A novel panel of blood-based microRNAs capable of discrimination between benign breast disease and breast cancer at early stages

Breast cancer (BC) as a leading cause of cancer death among women, exhibits a wide range of genetic heterogeneity in affected individuals. Satisfactory management of BC depends on early diagnosis and proper monitoring of patients' response to therapy. In this study, we aimed to assess the relation between the expression patterns of blood-based microRNAs (miRNAs) with demographic characteristics of the patients with BC in an attempt to find novel diagnostic markers for BC with acceptable precision in clinical applications. To this end, we performed comprehensive statistical analysis of the data of the Cancer Genome Atlas (TCGA) database and the blood miRNome dataset (GSE31309). As a result, 21 miRNAs were selected for experimental verification by quantitative RT-PCR on blood samples of 70 BC patients and 60 normal individuals (without any lesions or benign breast diseases). Statistical one-way ANOVA revealed no significant difference in the blood levels of the selected miRNAs in BC patients compared to any lesions or benign breast diseases. However, the multi-marker panel consisting of hsa-miR-106b-5p, -126-3p, -140-3p, -193a-5p, and -10b-5p could detect early-stages of BC with 0.79 sensitivity, 0.86 specificity and 0.82 accuracy. Furthermore, this multi-marker panel showed the potential of detecting benign breast diseases from BC patients with 0.67 sensitivity, 0.80 specificity, and 0.74 accuracy. In conclusion, these data indicate that the present panel might be considered an asset in detecting benign breast disease and BC.

Identification of cumin and fennel from different regions based on generative adversarial networks and near infrared spectroscopy

Cumin (Cuminum cyminum) and fennel (Foeniculum vulgare) are widely used seasonings and play a very important role in industries such as breeding, cosmetics, winemaking, drug discovery, and nano-synthetic materials. However, studies have shown that cumin and fennel from different regions not only differ greatly in the content of lipids, phenols and proteins but also the substances contained in their essential oils are also different. Therefore, realizing precise identification of cumin and fennel from different regions will greatly help in quality control, market fraud and production industrialization. In this experiment, cumin and fennel samples were collected from each region, a total of 480 NIR spectra were collected. We used deep learning and traditional machine learning algorithms combined with near infrared (NIR) spectroscopy to identify their origin. To obtain the model with the best generalization performance and classification accuracy, we used principal component analysis (PCA) to reduce spectral data dimensionality after Rubberband baseline correction, and then established classification models including quadratic discriminant analysis based on PCA (PCA-QDA) and multilayer perceptron based on PCA (PCA-MLP). We also directly input the spectral data after baseline correction into convolutional neural networks (CNN) and generative adversarial networks (GAN). The experimental results show that GAN is more accurate than the PCA-QDA, PCA-MLP and CNN models, and the classification accuracy reached 100%. In the cumin and fennel classification experiment in the same region, the four models achieve great classification results from three regions under the condition that all model parameters remain unchanged. The experimental results show that when the training data are limited and the dimension is high, the model obtained by GAN using competitive learning has more generalization ability and higher classification accuracy. It also provides a new method for solving the problem of limited training data in food research and medical diagnosis in the future.

Circulating and tissue miR-100 acts as a potential diagnostic biomarker for cervical cancer

BACKGROUND

MicroRNAs (miRNA) are promising biomarkers for cancer diagnosis and prognosis; miR-100 expression is decreased in cervical cancer tissues.

OBJECTIVE

To determine whether miR-100 is a useful biomarker for early cervical cancer diagnosis.

METHODS

Total RNA was extracted from the sera of 34 healthy controls (HC), 64 cervical intraepithelial neoplasia patients (CIN), and 46 cervical cancer patients (CC). miR-100 expression levels were measured with quantitative real-time PCR. Correlations between clinicopathological factors and miR-100 expression levels were also assessed. The cut-off value for miR-100 was calculated from the Receiver Operating Characteristic (ROC) curve.

RESULTS

Relative expression levels of miR-100 in serum were 1.84 ± 1.72, 3.93 ± 2.52, and 5.32 ± 3.39 in CC, CIN, and HC, respectively; it was significantly lower in CC (p< 0.001). The area under the ROC curve was 0.879 and the cut-off value was 2.451. miR-100 expression levels were significantly higher in metastasis cases that were lymph node negative than positive (p< 0.05). CC patients with miR-100 expression levels below the cut-off value tended to have a poor prognosis.

CONCLUSIONS

Serum miR-100 may be a useful diagnostic biomarker for CC, and for predicting lymph node metastasis and disease free survival in CC patients.

Prognostic Implications of microRNA-155, -133a, -21 and -205 in Breast Cancer Patients' Plasma

BACKGROUND

Breast cancer, being a heterogenous disease at the intra-tumoral and intertumoral levels, presents challenges in following the progress of the disease. Tumour-secreted aberrantly expressed miRNAs obtained from peripheral blood represent a non-invasive alternative resource for detecting and monitoring the development of the disease. This study evaluates the expression of miR-155, miR-133a, miR-21 and miR-205 as non-invasive, prognostic and follow-up markers for breast cancer.

METHODS

Plasma expression levels of miR-155, miR-133a, miR-21 and miR-205 were measured using real-time PCR in breast cancer patients (n=63) at presentation, healthy controls (n=25), and in post-treatment samples of 31 patients. A meta-analysis was performed using 43 studies identified from PubMed, Google Scholar and Scopus databases. Hedge's g values were used to calculate the overall effect size.

RESULTS

Plasma miR-21 levels were higher in breast cancer patients at presentation compared to controls, while no difference was observed for miR-155, miR-133a and miR-205. These results were further supported by the meta-analysis. The altered levels of miR-155 during tamoxifen treatment indicated a potential role for miR-155 in monitoring treatment response. Further, high expressions of at least three miRNAs correlated with poor overall survival in the breast cancer patients.

CONCLUSION

Plasma levels of miR-155, miR-133a, miR-21 and miR-205 may be useful as prognostic and follow-up markers for breast cancer with further validation in a large cohort of patients.

NMCMDA: neural multicategory MiRNA-disease association prediction

MOTIVATION

There is growing evidence showing that the dysregulations of miRNAs cause diseases through various kinds of the underlying mechanism. Thus, predicting the multiple-category associations between microRNAs (miRNAs) and diseases plays an important role in investigating the roles of miRNAs in diseases. Moreover, in contrast with traditional biological experiments which are time-consuming and expensive, computational approaches for the prediction of multicategory miRNA-disease associations are time-saving and cost-effective that are highly desired for us.

RESULTS

We present a novel data-driven end-to-end learning-based method of neural multiple-category miRNA-disease association prediction (NMCMDA) for predicting multiple-category miRNA-disease associations. The NMCMDA has two main components: (i) encoder operates directly on the miRNA-disease heterogeneous network and leverages Graph Neural Network to learn miRNA and disease latent representations, respectively. (ii) Decoder yields miRNA-disease association scores with the learned latent representations as input. Various kinds of encoders and decoders are proposed for NMCMDA. Finally, the NMCMDA with the encoder of Relational Graph Convolutional Network and the neural multirelational decoder (NMR-RGCN) achieves the best prediction performance. We compared the NMCMDA with other baselines on three experimental datasets. The experimental results show that the NMR-RGCN is significantly superior to the state-of-the-art method TDRC in terms of Top-1 precision, Top-1 Recall, and Top-1 F1. Additionally, case studies are provided for two high-risk human diseases (namely, breast cancer and lung cancer) and we also provide the prediction and validation of top-10 miRNA-disease-category associations based on all known data of HMDD v3.2, which further validate the effectiveness and feasibility of the proposed method.

miR-202-3p negatively regulates MMP-1 to inhibit the proliferation, migration and invasion of lung adenocarcinoma cells

Lung adenocarcinoma (LUAD) is one of the common cancers. Studies show that MMP-1 is involved in tumor progression, yet relevant regulatory mechanism in LUAD remains to be further elucidated. Here, we demonstrated from bioinformatics analysis for GEO data that MMP-1 was differentially up-regulated in LUAD. miR-202-3p, identified as the upstream regulator of MMP-1 by both bioinformatics and dual-luciferase assays, was differentially down-regulated in LUAD and presented a negative correlation with MMP-1. Following cell biological experiments proved that knocking down the expression of MMP-1 inhibited the proliferation, migration and invasion of LUAD cells, while overexpressed miR-202-3p posed a similar suppressive effect on cancer progression. Additionally, rescue assay further identified that overexpression of MMP-1 attenuated the suppressive effect of up-regulated miR-202-3p on malignant progression of LUAD cells. In all, this research suggests a mechanism by which MMP-1 under the regulation of miR-202-3p modulates the proliferation, migration and invasion of LUAD cells, which may contribute to the development of new therapeutic strategies.

Detection of breast cancer of various clinical stages based on serum FT-IR spectroscopy combined with multiple algorithms

BACKGROUND

Breast cancer screening is time consuming, requires expensive equipment, and has demanding requirements for doctors. Hence, a large number of breast cancer patients may miss screening and early treatment, which greatly threatens their health around the world. Infrared spectroscopy may be able to be used as a screening tool for breast cancer detection. Fourier transform infrared (FT-IR) spectroscopy of serum was combined with traditional machine learning algorithms to achieve an auxiliary diagnosis that could quickly and accurately distinguish patients with different stages of breast cancer, including stage 1 disease, from control subjects without breast cancer.

MATERIALS AND METHODS

FT-IR spectroscopy were performed on the serum of 114 non-cancer control subjects, 35 patients with stage I, 43 patients with stage II, and 29 patients with stage III & IV breast cancer. Due to the experimental sample imbalance, we used the oversampling to process the four classes of sample. The oversampling selected Synthetic Minority Oversampling Technique (SMOTE). Subsequently, we used the random discarding method in undersampling to do experiments as well. The average FT-IR spectroscopy results for the four groups showed differences in phospholipids, nucleic acids, lipids, and proteins between non-cancer control subjects and breast cancer patients at different stages. Based on these differences, four classification models were used to classify stage I, II, III & IV breast cancer patients and non-cancer control subjects. First, standard normal variate transformation (SNV) was used to preprocess the original data, and then partial least squares (PLS) was used for feature extraction. Finally, the five models were established including extreme learning machine (ELM), k-nearest neighbor (KNN), genetic algorithms based on support vector machine (GA-SVM), particle swarm optimization-support vector machine (PSO-SVM) and grid search-support vector machine (GS-SVM).

CONCLUSION

In oversampling experiment, the GS-SVM classifier obtained the highest average classification accuracy of 95.45 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 90 %; breast cancer stage II was 84.62 %; and breast cancer stage III & IV was 100 %. In undersampling experiment, the GA-SVM model obtained the highest average classification accuracy of 100 %; the diagnostic accuracy of non-cancer control subjects was 100 %; breast cancer stage I was 100 %; breast cancer stage II was 100 %; and breast cancer stage III & IV was 100 %. The results show that FT-IR spectroscopy combined with powerful classification algorithms has great potential in distinguishing patients with different stages of breast cancer from non-cancer control subjects. In addition, this research provides a reference for future multiclassification studies of cervical cancer, ovarian cancer and other female high-incidence cancers through serum FT-IR spectroscopy.

Plasma miR-193a-3p can be a potential biomarker for the diagnosis of diabetic nephropathy

BACKGROUND

Diabetic nephropathy is one of the most common microvascular complications in patients with diabetes. MicroRNA (miRNA, miR) is closely related to the formation, development and pathophysiology of diabetic nephropathy. We aimed to investigate whether miR-193a-3p could be used as a potential biomarker for the diagnosis of diabetic nephropathy.

METHODS

Plasma samples were collected from all the participants. TaqMan Low Density Array analysis was employed to obtain the miRNA profiles of plasma samples, and qRT-PCR was used to confirm the result. Receiver operating characteristic curves were employed to evaluate the specificity and sensitivity of miR-193a-3p for predicting diabetic nephropathy.

RESULTS

The expression of miR-193a-3p and miR-320c was elevated and miR-27a-3p was decreased in diabetic nephropathy patients compared to patients with type 2 diabetes and healthy controls. We found that, in diabetic nephropathy patients, the elevated miR-193a-3p expression had a negative correlation with the level of evaluate glomerular filtration rate, while a positive correlation with the level of proteinuria. We further demonstrated that miR-193a-3p could be employed to distinguish patients with diabetic nephropathy. The Kaplan-Meier analysis showed that the high expression of miR-193a-3p significantly shortened the dialysis-free survival of diabetic nephropathy patients.

CONCLUSION

In conclusion, miR-193a-3p is involved in diabetic nephropathy pathogenesis and may serve as a potentially novel diagnostic biomarker for diabetic nephropathy.

A Novel Computational Approach for Biomarker Detection for Gene Expression-Based Computer-Aided Diagnostic Systems for Breast Cancer

Cancer produces complex cellular changes. Microarrays have become crucial to identifying genes involved in causing these changes; however, microarray data analysis is challenged by the high-dimensionality of data compared to the number of samples. This has contributed to inconsistent cancer biomarkers from various gene expression studies. Also, identification of crucial genes in cancer can be expedited through expression profiling of peripheral blood cells. We introduce a novel feature selection method for microarrays involving a two-step filtering process to select a minimum set of genes with greater consistency and relevance, and demonstrate that the selected gene set considerably enhances the diagnostic accuracy of cancer. The preliminary filtering (Bi-biological filter) involves building gene coexpression networks for cancer and healthy conditions using a topological overlap matrix (TOM) and finding cancer specific gene clusters using Spectral Clustering (SC). This is followed by a filtering step to extract a much-reduced set of crucial genes using best first search with support vector machine (BFS-SVM). Finally, artificial neural networks, SVM, and K-nearest neighbor classifiers are used to assess the predictive power of the selected genes as well as to select the most effective diagnostic system. The approach was applied to peripheral blood profiling for breast cancer where Bi-biological filter selected 415 biologically consistent genes, from which BFS-SVM extracted 13 highly cancer specific genes for breast cancer identification. ANN was the superior classifier with 93.2% classification accuracy, a 14% improvement over the study from which data were obtained for this study (Aaroe et al., Breast Cancer Res 12:R7, 2010).

Serum Micro-RNA-122 Level as a Simple Noninvasive Marker of MAFLD Severity

BACKGROUND

Metabolic-associated fatty liver disease (MAFLD) is a common disease worldwide. Micro-RNA-122 is known to be the most abundant micro-RNA expressed in the liver.

OBJECTIVE

To evaluate the association of micro-RNA-122 and the degree of steatosis and fibrosis in obese patients with MAFLD.

METHODS

The study included 120 obese Egyptian patients with MAFLD, which were diagnosed and classified according to ultra-sonographic liver findings. All patients enrolled in the study were subjected to thorough clinical examination and laboratory investigations (serum micro-RNA-122 levels by PCR, lipid profile, liver biochemistry, and functions). Fibro-scan was used to assess the level of fibrosis.

RESULTS

There was a significant increase in levels of micro-RNA-122 in obese patients with MAFLD compared to controls (p<0.001). Micro-RNA-122 level was lower in patients with mild liver steatosis than patients with moderate or severe steatosis (p<0.001). It was lower in patients with a mild degree of fibrosis than those with mild or moderate fibrosis (p<0.001). Micro-RNA-122 was significantly positively correlated with low-density cholesterol and triglycerides level, and liver enzymes, and negatively correlated to high-density cholesterol (p<0.001).

CONCLUSION

Serum micro-RNA-122 could be a useful predictor of assessing MAFLD severity regarding level of steatosis or fibrosis.

Multiple microRNAs as biomarkers for early breast cancer diagnosis

MicroRNA (miRNA or miR) is stably present in plasma. It has been reported that miRNA could be used for detecting cancer. Circulating miRNAs are being increasingly recognized as powerful biomarkers in a number of different pathologies, including in breast cancer. The aim of the current study was to establish and validate miRNA sets that are useful for the early diagnosis of breast cancer. Specifically, the current study intended to determine whether miRNA biomarkers were tumor-specific and to statistically verify whether circulating miRNA analysis could be used for breast cancer diagnosis. In the present study, a total of nine candidate miRNA biomarkers were selected by examining reference miRNAs associated with the generation and progression of breast cancer to identify novel miRNAs that could be used to detect early breast cancer. A total of 226 plasma samples from patients with breast cancer were used. In addition, 146 plasma healthy samples were used as non-cancer controls. These samples were divided into training and validation cohorts. The training cohort was used to identify a combination of miRNA that could detect breast cancer. The validation cohort was used to validate this combination of miRNA. Total RNAs were isolated from collected samples. A total of 9 miRNAs were quantified using reverse-transcription quantitative PCR. A total of nine candidate miRNA expression levels were compared between patients with breast cancer and healthy controls. It was indicated that combinations of two or more of the nine miRNAs could detect breast cancer with higher accuracy than the use of a single biomarker. As a representative example, combinations of four miRNAs (miR-1246+miR-206+miR-24+miR-373) of the nine miRNAs had a sensitivity of 98%, a specificity of 96% and an accuracy of 97% for breast cancer detection in the validation cohort. The results of the present study suggest that multiple miRNAs could be used as potential biomarkers for early diagnosis of breast cancer. These biomarkers are expected to overcome limitations of mammography when used as an auxiliary diagnosis of mammography.

Cell-free nucleic acid patterns in disease prediction and monitoring-hype or hope?

Interest in the use of cell-free nucleic acids (CFNAs) as clinical non-invasive biomarker panels for prediction and prevention of multiple diseases has greatly increased over the last decade. Indeed, circulating CFNAs are attributable to many physiological and pathological processes such as imbalanced stress conditions, physical activities, extensive apoptosis of different origin, systemic hypoxic-ischemic events and tumour progression, amongst others. This article highlights the involvement of circulating CFNAs in local and systemic processes dealing with the question, whether specific patterns of CFNAs in blood, their detection, quantity and quality (such as their methylation status) might be instrumental to predict a disease development/progression and could be further utilised for accompanying diagnostics, targeted prevention, creation of individualised therapy algorithms, therapy monitoring and prognosis. Presented considerations conform with principles of 3P medicine and serve for improving individual outcomes and cost efficacy of medical services provided to the population.

Prediction of miRNA-disease associations based on Weighted [Formula: see text]-Nearest known neighbors and network consistency projection

MicroRNAs (miRNA) are a type of non-coding RNA molecules that are effective on the formation and the progression of many different diseases. Various researches have reported that miRNAs play a major role in the prevention, diagnosis, and treatment of complex human diseases. In recent years, researchers have made a tremendous effort to find the potential relationships between miRNAs and diseases. Since the experimental techniques used to find that new miRNA-disease relationships are time-consuming and expensive, many computational techniques have been developed. In this study, Weighted [Formula: see text]-Nearest Known Neighbors and Network Consistency Projection techniques were suggested to predict new miRNA-disease relationships using various types of knowledge such as known miRNA-disease relationships, functional similarity of miRNA, and disease semantic similarity. An average AUC of 0.9037 and 0.9168 were calculated in our method by 5-fold and leave-one-out cross validation, respectively. Case studies of breast, lung, and colon neoplasms were applied to prove the performance of our proposed technique, and the results confirmed the predictive reliability of this method. Therefore, reported experimental results have shown that our proposed method can be used as a reliable computational model to reveal potential relationships between miRNAs and diseases.

Liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers

Improvement of breast cancer (BC) patient's outcome is directly related to early detection. However, there is still a lack of reliable biomarkers for diagnosis, prognosis and, treatment follow up in BC, leading researchers to study the potential of liquid biopsy based on circulating microRNAs (c-miRNAs). These c-miRNAs can be cell-free or associated with extracellular vesicles (EVs), and have great advantages such as stability in biofluids, noninvasive accessibility compared to current techniques (core-biopsy and surgery), and expression associated with pathogenic conditions. Recently, a new promising field of EV-derived miRNAs (EV-miRNAs) as cancer biomarkers has emerged, receiving special attention due to their selective vesicle sorting which makes them accurate for disease detection. In this review, we discuss new findings about c-miRNA and their potential as biomarkers for BC diagnosis, prognosis, and therapy. Additionally, we address the impact of limitations associated with the standardization of analysis techniques and methods on the implementation of these biomarkers in the clinical setting.

Evaluation of MiR-1908-3p as a novel serum biomarker for breast cancer and analysis its oncogenic function and target genes

Background

Breast cancer is one of the most common tumors for women globally. Various miRNAs have been reported to play a crucial role in breast cancer, however the clinical significance of miR-1908-3p in breast cancer remains unclear. The present study aimed to explore the role of miR-1908-3p in breast cancer.

Methods

The expression of miR-1908-3p was detected in 50 pairs of breast cancer tissues and adjacent normal tissues, 60 breast cancer patient serum and 60 healthy volunteer serum. The functional roles of miR-1908-3p in breast cancer cells such as proliferation, migration and invasion were evaluated using CCK8, SRB, wound healing and transwell chambers. In addition, bioinformatics tools were used to identify potential targets of miR-1908-3p.

Results

The results showed that the expression of miR-1908-3p were increased in breast cancer tissues and serum compared with normal breast tissues and serum of healthy volunteers respectively. Furthermore, the young breast cancer patients and HER2-positive patients had a higher level of tissues’ miR-1908-3p than elder breast cancer patients and HER2-negative patients, respectively. The young breast cancer patients had a higher level of serum miR-1908-3p than elder breast cancer patients, ROC analysis suggested that miR-1908-3p had the potential as a promising serum diagnostic biomarker of breast cancer. Up-regulation of miR-1908-3p promoted the cells proliferation, migration and invasion while knockdown of miR-1908-3p inhibited these processes in breast cancer cell MCF-7 and MDA-MB-231. The potential target genes of miR-1908-3p in breast cancer included ID4, LTBP4, GPM6B, RGMA, EFCAB1, ALX4, OSR1 and PPARA. Higher expression of these eight genes correlated with a better prognosis for breast cancer patients.

Conclusions

These results suggest that miR-1908-3p may exert its oncogenic functions via suppression of these eight genes in breast cancer.

Diagnostic Value of Circulating miR-202 in Early-Stage Breast Cancer in South Korea

Background and objectives: Breast cancer is the most common cancer among women worldwide. Early stage diagnosis is important for predicting increases in treatment success rates and decreases in patient mortality. Recently, circulating biomarkers such as circulating tumor cells, circulating tumor DNA, exosomes, and circulating microRNAs have been examined as blood-based markers for the diagnosis of breast cancer. Although miR-202 has been studied for its function or expression in breast cancer, its potential diagnostic value in a clinical setting remains elusive and miR-202 has not been investigated in South Korea. In this study, we aimed to evaluate the diagnostic utility of miR-202 in plasma samples of breast cancer patients in South Korea. Materials and Methods: We investigated miR-202 expression in the plasma of 30 breast cancer patients during diagnosis along with 30 healthy controls in South Korea by quantitative reverse transcription PCR. Results: The results showed that circulating miR-202 levels were significantly elevated in the breast cancer patients compared with those in healthy controls (p < 0.001). The sensitivity and specificity of circulating miR-202 were 90.0% and 93.0%, respectively. Additionally, circulating miR-202 showed high positivity at early stage. The positive rate of miR-202 was as follows: 100% (10/10) for stage I, 90% (9/10) for stage II, and 80% (8/10) for stage III. miR-202 was also a predictor of a 9.6-fold high risk for breast cancer (p < 0.001). Conclusions: Additional alternative molecular biomarkers for diagnosis and management of pre-cancer patients are needed. Circulating miR-202 might be potential diagnostic tool for detecting early stage breast cancer.

Advanced diagnostic aids for oral cancer

Oral cancer, a universal malady, has become a stumbling block over the years due to its significant morbidity and mortality rates. The greater morbidity associated with this deadly disease is attributed to delay in its diagnosis / its presentation in advanced stage. Being multifactorial, Oral squamous cell carcinoma (OSCC) is the outcome of genetic and epigenetic instability. However, in many instances, oral cancer is preceded by precursor lesions named as oral potentially malignant disorders (OPMDs), the early detection of which makes it beneficial for patients with the possible increase in the productive longevity. Many diagnostic tools / aids have been explored with the aim of early detection of oral precancer and cancer. The basic chair-side procedures or relatively advanced aids come with a set of limitations along with subjectivity as one of the setbacks. The advent and exploitation of molecular techniques in the field of health diagnostics, is demanding the molecular typing of the OPMDs and also of oral cancer. The saga of various diagnostic aids for OSCC has witnessed the so-called latest trends such as lab-on-chip, microfluidics, nano diagnostics, liquid biopsy, omics technology and synthetic biology in early detection of oral precancer and cancer. Oral cancer being multifactorial in origin with the chief participation of altered genetics and epigenetics would demand high-end diagnostics for designing personalized therapy. Hence, the present paper highlights the role of various advanced diagnostic aids including 'omics' technology and synthetic biology in oral precancer and cancer.

Towards a more precise and individualized assessment of breast cancer risk

Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention.

Exosomal miRNAs in hepatitis B virus related liver disease: a new hope for biomarker

The World Health Organisation, in its 2019 progress report on HIV, viral hepatitis and STDs indicates that 257 million people are afflicted with chronic HBV infections, of which, 1 million patients lose their lives every year due to HBV related chronic liver diseases including serious complications such as liver cirrhosis and hepatocellular carcinoma. The course of HBV infection and associated liver injury depend on several host factors, genetic variability of the virus, and the host viral interplay. The challenge of medical science is the early diagnosis/identification of the potential for development of fatal complications like liver cirrhosis and HCC so that timely medical intervention can improve the chances of survival. Currently, neither the vaccination regime nor the diagnostic methods are completely effective as reflected in the high number of annual deaths. It is evident from numerous publications that microRNAs (miRNAs) are the critical regulators of gene expression and various cellular processes like proliferation, development, differentiation, apoptosis and tumorigenesis. Expressions of these diminutive RNAs are significantly affected in cancerous tissues as a result of numerous genomic and epigenetic modifications. Exosomes are membrane-derived vesicles (30–100 nm) secreted by normal as well as malignant cells, and are present in all body fluids. They are recognized as critical molecules in intercellular communication between cells through horizontal transfer of information via their cargo, which includes selective proteins, mRNAs and miRNAs. Exosomal miRNAs are transferred to recipient cells where they can regulate target gene expression. This provides an insight into the elementary biology of cancer progression and therefore the development of therapeutic approaches. This concise review outlines various on-going research on miRNA mediated regulation of HBV pathogenesis with special emphasis on association of exosomal miRNA in advanced stage liver disease like hepatocellular carcinoma. This review also discusses the possible use of exosomal miRNAs as biomarkers in the early detection of HCC and liver cirrhosis.

Predicting the presence of breast cancer using circulating small RNAs, including those in the extracellular vesicles

Emerging evidence indicates that small RNAs, including microRNAs (miRNAs) and their isoforms (isomiRs), and transfer RNA fragments (tRFs), are differently expressed in breast cancer (BC) and can be detected in blood circulation. Circulating small RNAs and small RNAs in extracellular vesicles (EVs) have emerged as ideal markers in small RNA‐based applications for cancer detection. In this study, we first undertook small RNA sequencing to assess the expression of circulating small RNAs in the serum of BC patients and cancer‐free individuals (controls). Expression of 3 small RNAs, namely isomiR of miR‐21‐5p (3′ addition C), miR‐23a‐3p and tRF‐Lys (TTT), was significantly higher in BC samples and was validated by small RNA sequencing in an independent cohort. Our constructed model using 3 small RNAs showed high diagnostic accuracy with an area under the receiver operating characteristic curve of 0.92 and discriminated early‐stage BCs at stage 0 from control. To test the possibility that these small RNAs are released from cancer cells, we next examined EVs from the serum of BC patients and controls. Two of the 3 candidate small RNAs were identified, and shown to be abundant in EVs of BC patients. Interestingly, these 2 small RNAs are also more abundantly detected in culture media of breast cancer cell lines (MCF‐7 and MDA‐MB‐231). The same tendency in selective elevation seen in total serum, serum EV, and EV derived from cell culture media could indicate the efficiency of this model using total serum of patients. These findings indicate that small RNAs serve as significant biomarkers for BC detection.

Multiple functions of microfluidic platforms: Characterization and applications in tissue engineering and diagnosis of cancer

Microfluidic system, or lab-on-a-chip, has grown explosively. This system has been used in research for the first time and then entered in the clinical section. Due to economic reasons, this technique has been used for screening of laboratory and clinical indices. The microfluidic system solves some difficulties accompanied by clinical and biological applications. In this review, the interpretation and analysis of some recent developments in microfluidic systems in biomedical applications with more emphasis on tissue engineering and cancer will be discussed. Moreover, we try to discuss the features and functions of microfluidic systems.

Cell-free miRNAs as non-invasive biomarkers in breast cancer: Significance in early diagnosis and metastasis prediction

Breast cancer is one of the genetic diseases causing a high mortality among women around the world. Despite the availability of advanced diagnostic tools and treatment strategies, the incidence of breast cancer is increasing every year. This is due to the lack of accurate and reliable biomarkers whose deficiency creates difficulty in early breast cancer recognition, subtypes determination, and metastasis prophecy. Although biomarkers such as ER, PR, Her2, Ki-67, and other genetic platforms e.g. MammaPrint®, Oncotype DX®, Prosigna® or EndoPredict® are available for determination of breast cancer diagnosis and prognosis. However, pertaining to heterogeneous nature, lack of sensitivity, and specificity of these markers, it is still incessant to overcome breast cancer burden. Therefore, a novel biomarker is urgently needed for therapeutic diagnosis and improving prognosis. Lately, it has become more evident that cell-free miRNAs might be useful as good non-invasive biomarkers that are associated with different events in carcinogenesis. For example, some known biomarkers such as miR-21, miR-23a, miR-34a are associated with molecular subtyping and different biomolecular aspects i.e. apoptosis, angiogenesis, metastasis, and miR-1, miR-10b, miR-16 are associated with drug response. Cell-free miRNAs present in human body fluids have proven to be potential biomarkers with significant prognostic and predictive values. Numerous studies have found a distinct expression profile of circulating miRNAs in breast tumour versus non-tumour and in early and advanced-stage, thus implicating its clinical relevance. This review article will highlight the importance of different cell-free miRNAs as a biomarker for early breast cancer detection, subtype classification, and metastasis forecast.

Identification of miRNAs Enriched in Extracellular Vesicles Derived from Serum Samples of Breast Cancer Patients

MicroRNAs derived from extracellular vesicles (EV-miRNAs) are circulating miRNAs considered as potential new diagnostic markers for cancer that can be easily detected in liquid biopsies. In this study, we performed RNA sequencing analysis as a screening strategy to identify EV-miRNAs derived from serum of clinically well-annotated breast cancer (BC) patients from the south of Brazil. EVs from three groups of samples (healthy controls (CT), luminal A (LA), and triple-negative (TNBC)) were isolated from serum using a precipitation method and analyzed by RNA-seq (screening phase). Subsequently, four EV-miRNAs (miR-142-5p, miR-150-5p, miR-320a, and miR-4433b-5p) were selected to be quantified by quantitative real-time PCR (RT-qPCR) in individual samples (test phase). A panel composed of miR-142-5p, miR-320a, and miR-4433b-5p distinguished BC patients from CT with an area under the curve (AUC) of 0.8387 (93.33% sensitivity, 68.75% specificity). The combination of miR-142-5p and miR-320a distinguished LA patients from CT with an AUC of 0.9410 (100% sensitivity, 93.80% specificity). Interestingly, decreased expression of miR-142-5p and miR-150-5p were significantly associated with more advanced tumor grades (grade III), while the decreased expression of miR-142-5p and miR-320a was associated with a larger tumor size. These results provide insights into the potential application of EVs-miRNAs from serum as novel specific markers for early diagnosis of BC.

Noncoding RNAs in Unexplained Recurrent Spontaneous Abortions and Their Diagnostic Potential

Unexplained recurrent spontaneous abortion (URSA) is defined as the loss of two or more consecutive pregnancies before the 20th week of gestation with normal findings on routine screening tests. Our understanding of the cellular and molecular pathogenesis of URSA is still far from complete. Noncoding RNAs (ncRNAs) play a pivotal role in transcription and expression. The functions of ncRNAs may also improve understanding of URSA pathogenesis. Because of their stability in the circulatory system and at the maternal-fetal interface, it may be possible to use ncRNAs as biomarkers for certain disease states. Here, we provide a narrative review of the current state of knowledge about ncRNAs associated with URSA. The possibility of developing a diagnostic tool using ncRNAs is discussed. The underlying mechanisms of how ncRNAs may lead to the onset of URSA are explored in this review.