Blood-borne miRNA profile-based diagnostic classifier for lung adenocarcinoma

MicroRNA-486: a dual-function biomarker for diagnosis and tumor immune microenvironment characterization in non-small cell lung cancer

BACKGROUND

This investigation evaluates the clinical significance and molecular mechanisms of microRNA-486 (miR-486) as a potential biomarker in non-small cell lung cancer (NSCLC) through an integrative analytical approach.

METHODS

We conducted systematic search and meta-analysis of diagnostic studies from major biomedical databases from inception through April 04, 2025, followed by comprehensive bioinformatics interrogation. Protein-protein interaction (PPI) networks were constructed using STRING to identify key hub genes regulated by miR-486. Validation of hub genes employed TCGA datasets, while immune infiltration analysis utilized TIMER2.0 platform.

RESULTS

The meta-analysis indicated that miR-486, both individually and in combination, could be effective biomarkers for NSCLC detection. Afterwards, functional enrichment analyses of miR-486 target genes highlighted significant ontology terms and pathways crucial to the initiation and progression of NSCLC. PPI networks revealed key proteins and modules that participate in multiple essential pathways associated with NSCLC pathogenesis. Furthermore, the identified hub genes were validated for differential expression in cancerous versus normal tissues, suggesting their potential diagnostic utility, while subsequent survival analyses confirmed their prognostic value through significant associations with overall survival. Notably, these hub genes were found to be significantly associated with immune infiltration levels, immune microenvironment scores, and immune-related proteins in NSCLC.

CONCLUSIONS

This dual-modality investigation establishes miR-486 as a multi-functional biomarker in NSCLC, demonstrating both diagnostic utility and immunoregulatory potential through tumor microenvironment modulation.

Identification of hypertension subtypes using microRNA profiles and machine learning

OBJECTIVE

Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are classified as "primary hypertension" (PHT), endocrine hypertension (EHT) accounts for ∼10% of cases and is caused by underlying conditions such as primary aldosteronism (PA), Cushing's syndrome (CS), pheochromocytoma or paraganglioma (PPGL). EHT is often misdiagnosed as PHT leading to delays in treatment for the underlying condition, reduced quality of life and costly, often ineffective, antihypertensive treatment. MicroRNA (miRNA) circulating in the plasma is emerging as an attractive potential biomarker for various clinical conditions due to its ease of sampling, the accuracy of its measurement and the correlation of particular disease states with circulating levels of specific miRNAs.

METHODS

This study systematically presents the most discriminating circulating miRNA features responsible for classifying and distinguishing EHT and its subtypes (PA, PPGL, and CS) from PHT using 8 different supervised machine learning (ML) methods for the prediction.

RESULTS

The trained models successfully classified PPGL, CS, and EHT from PHT with area under the curve (AUC) of 0.9 and PA from PHT with AUC 0.8 from the test set. The most prominent circulating miRNA features for hypertension identification of different disease combinations were hsa-miR-15a-5p and hsa-miR-32-5p.

CONCLUSIONS

This study confirms the potential of circulating miRNAs to serve as diagnostic biomarkers for EHT and the viability of ML as a tool for identifying the most informative miRNA species.

Diagnostic value of circulating miRNA in the benign and malignant lung nodules: A systematic review and meta-analysis

BACKGROUND

Lung cancer is the leading cause of death worldwide, and its diagnosis remains a significant challenge. Identifying effective methods to differentiate benign from malignant lung nodules is of paramount importance. This meta-analysis aimed to evaluate the clinical utility of circulating microRNAs (miRNAs) for the differential diagnosis of benign and malignant lung nodules.

METHODS

This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive search was conducted across 4 electronic databases, without any temporal restrictions. The inclusion and exclusion criteria were strictly applied to assess the clinical applications of circulating miRNAs. A robust and transparent quality assessment was performed using the quality assessment of diagnostic accuracy studies-2 tool, and rigorous statistical analyses were conducted to synthesize the various diagnostic measures.

RESULTS

In the meta-analysis of 11 studies, quality assessment of diagnostic accuracy studies-2 assessment revealed < 5% high-risk methodologies, ensuring robustness. Sensitivity and Specificity were consolidated at 0.83 (95% confidence interval [CI]: 0.72-0.90) and 0.81 (95% CI: 0.73-0.88), respectively. The positive likelihood ratio and negative likelihood ratio were 4.45 (95% CI: 3.03-6.54) and 0.21 (95% CI: 0.12-0.35), respectively. The diagnostic odds ratio was 21.31 (95% CI: 10.25-44.30) and area under the receiver operating characteristic curve was 0.89 (95% CI: 0.86-0.91). Subgroup analysis highlighted significant variations in diagnostic accuracy by ethnicity and miRNA source, with non-Asian populations and serum-based tests showing higher diagnostic accuracy.

CONCLUSION

This meta-analysis demonstrated that circulating miRNAs hold substantial diagnostic value in distinguishing between benign and malignant lung nodules.

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review

Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screening. A literature search on PubMed was performed including studies which investigated liquid biopsy non-coding RNAs biomarker lung cancer patients and a control cohort. Micro RNAs were the most widely studied biomarkers in this setting but some preliminary evidence was found also for other non-coding RNAs, suggesting that a multi-biomarker based liquid biopsy approach could enhance their efficacy in the screening context. However, further studies are needed in order to optimize detection techniques as well as diagnostic accuracy before introducing novel biomarkers in the early diagnosis setting.

Meta analysis of the diagnostic value of circulating miRNA in benign and malignant pulmonary nodules

OBJECTIVE

A meta-analysis was conducted to assess the impact of miRNAs in circulation on diagnosing benign and malignant pulmonary nodules (BPNs and MPNs).

METHODS

Electronic databases such as Embase, PubMed, Web of Science, and The Cochrane Library were utilized for diagnostic tests of circulating miRNAs to diagnose BPNs and MPNs from the library creation to February 2023. Meta-analysis of the included literature was performed using Stata 16, Meta-Disc 1.4, and Review Manager 5.4 software. This study determined the combined sensitivity, specificity, diagnostic ratio (DOR), positive/negative likelihood ratios (PLR/NLR), as well as value of area under the receiver operating characteristic (ROC) curve.

RESULTS

This meta-analysis included 14 publications and 17 studies. According to our findings, the pooled sensitivity for miRNA in diagnosing benign and malignant pulmonary nodules was 0.82 [95% CI (0.74, 0.88)], specificity was 0.84 [95% CI (0.79, 0.88)], whereas the DOR was 22.69 [95% CI (13.87, 37.13)], PLR was 5.00 [95% CI (3.87, 6.46)], NLR was 0.22 [95% CI (0.15, 0.32)], and the area under the working characteristic curve (AUC) of the subject was 0.89 [95% CI (0.86, 0.91)].

CONCLUSION

Circulating miRNAs could be used with sensitivity, specificity, DOR, PLR, NLR, and AUC as biomarkers to diagnose pulmonary nodules (PNs). However, more research is needed to determine the optimum miRNA combinations for diagnosing PNs due to the significant heterogeneity on previous studies.

MiRNAs in Lung Adenocarcinoma: Role, Diagnosis, Prognosis, and Therapy

Lung cancer has emerged as a significant public health challenge and remains the leading cause of cancer-related mortality worldwide. Among various types of lung malignancies, lung adenocarcinoma (LUAD) stands as the most prevalent form. MicroRNAs (miRNAs) play a crucial role in gene regulation, and their involvement in cancer has been extensively explored. While several reviews have been published on miRNAs and lung cancer, there remains a gap in the review regarding miRNAs specifically in LUAD. In this review, we not only highlight the potential diagnostic, prognostic, and therapeutic implications of miRNAs in LUAD, but also present an inclusive overview of the extensive research conducted on miRNAs in this particular context.

Selecting optimum miRNA panel for miRNA signature-based companion diagnostic model to predict the response of R-CHOP treatment in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Although the first-line treatment, R-CHOP treatment, shows efficacy in approximately 80% of patients with DLBCL, some patients have refractory disease or relapse after the initial response to therapy, resulting in a significantly poorer prognosis. In this study, we developed a microRNA (miRNA) signature-based companion diagnostic model to predict the response of patients with DLBCL to R-CHOP treatment by integrating two clinical study datasets. To select the optimum miRNA combination as a panel, we examined three feature selection methods (p-value-based ranking, stepwise method, and Boruta), together with 11 types of classifiers systematically. Boruta selection enabled a higher area under the curve (AUC) with a lower number of miRNAs compared with other feature selection methods, leading to an AUC of 0.751 via the random forest classifier using 36 miRNAs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that Boruta avoided multiple selection of miRNAs with similar functions, thereby preventing the decrease in diagnostic ability via collinearity. The AUC value first increased with an increasing number of miRNAs and then became almost constant at approximately 30 miRNAs, suggesting the existence of the optimum number of miRNAs as a panel for future clinical translation of multiple miRNA-based diagnostics.

Progress of Endogenous and Exogenous Nanoparticles for Cancer Therapy and Diagnostics

The focus of this brief review is to describe the application of nanoparticles, including endogenous nanoparticles (e.g., extracellular vesicles, EVs, and virus capsids) and exogenous nanoparticles (e.g., organic and inorganic materials) in cancer therapy and diagnostics. In this review, we mainly focused on EVs, where a recent study demonstrated that EVs secreted from cancer cells are associated with malignant alterations in cancer. EVs are expected to be used for cancer diagnostics by analyzing their informative cargo. Exogenous nanoparticles are also used in cancer diagnostics as imaging probes because they can be easily functionalized. Nanoparticles are promising targets for drug delivery system (DDS) development and have recently been actively studied. In this review, we introduce nanoparticles as a powerful tool in the field of cancer therapy and diagnostics and discuss issues and future prospects.

Diagnostic and prognostic value of microRNA-486 in patients with lung cancer: A systematic review and meta-analysis

PURPOSE

There are conflicting opinions on whether miR-486 could be used for cancer diagnosis and prognosis. Therefore, this present study investigated the potential effect of miR-486 on lung cancer diagnosis and prognosis.

METHODS

We researched PubMed, Embase, Wanfang and Chinese National Knowledge Infrastructure databases to select relevant publications. Specificity and sensitivity were obtained for the pooled and subgroup diagnostic meta-analysis while the hazard ratio was for prognostic meta-analysis. Publication analyses and sensitivity analyses were conducted to investigate possible sources of heterogeneity.

RESULTS

The overall sensitivity and specificity with 95% confidence intervals were 0.8 (0.8-0.9) and 0.9 (0.9-0.9). Results of subgroup analysis showed that high diagnostic efficacy might be obtained by miR-486 combined with other microRNAs (area under the curve (AUC): 0.9 (0.9-1.0)) to distinguish lung cancer patients from healthy controls (AUC: 1.0 (0.9-1.0)), especially for lung adenocarcinoma (AUC: 1.0 (1.0-1.0)) in the Asian population (AUC: 0.9 (0.9-1.0)). For prognosis prediction of miR-486 in overall non-small cell lung cancer, the overall hazard ratio with 95% confidence interval was 1.15 (0.85-1.54) for high versus low expression of miR-486, which indicated that a high miR-486 level was not related to the high risk of poor outcome. However, for the subgroup of progression-free survival and patients with chemotherapy, the hazard ratio was 0.41 (0.21-0.77), indicating that the higher miR-486 level would decrease the risk of poor progression-free survival for lung cancer patients with chemotherapy.

CONCLUSION

This study suggested circulating miR-486 combined with other microRNAs could be used as ideal biomarkers in early diagnosis and prognosis prediction for lung cancer, especially for lung adenocarcinoma in the Asian population.

miRNAs in lung cancer. A systematic review identifies predictive and prognostic miRNA candidates for precision medicine in lung cancer

Lung cancer (LC) is the leading cause of cancer-related death worldwide and miRNAs play a key role in LC development. To better diagnose LC and to predict drug treatment responses we evaluated 228 articles encompassing 16,697 patients and 12,582 healthy controls. Based on the criteria of ≥3 independent studies and a sensitivity and specificity of >0.8 we found blood-borne miR-20a, miR-10b, miR-150, and miR-223 to be excellent diagnostic biomarkers for non-small cell LC whereas miR-205 is specific for squamous cell carcinoma. The systematic review also revealed 38 commonly regulated miRNAs in tumor tissue and the circulation, thus enabling the prediction of histological subtypes of LC. Moreover, theranostic biomarker candidates with proven responsiveness to checkpoint inhibitor treatments were identified, notably miR-34a, miR-93, miR-106b, miR-181a, miR-193a-3p, and miR-375. Conversely, miR-103a-3p, miR-152, miR-152-3p, miR-15b, miR-16, miR-194, miR-34b, and miR-506 influence programmed cell death-ligand 1 and programmed cell death-1 receptor expression, therefore providing a rationale for the development of molecularly targeted therapies. Furthermore, miR-21, miR-25, miR-27b, miR-19b, miR-125b, miR-146a, and miR-210 predicted response to platinum-based treatments. We also highlight controversial reports on specific miRNAs. In conclusion, we report diagnostic miRNA biomarkers for in-depth clinical evaluation. Furthermore, in an effort to avoid unnecessary toxicity we propose predictive biomarkers. The biomarker candidates support personalized treatment decisions of LC patients and await their confirmation in randomized clinical trials.

The Impact of Air Pollution Exposure on the MicroRNA Machinery and Lung Cancer Development

Small non-coding RNA molecules (miRNAs) play an important role in the epigenetic regulation of gene expression. As these molecules have been repeatedly implicated in human cancers, they have been suggested as biomarkers of the disease. Additionally, miRNA levels have been shown to be affected by environmental pollutants, including airborne contaminants. In this review, we searched the current literature for miRNAs involved in lung cancer, as well as miRNAs deregulated as a result of exposure to air pollutants. We then performed a synthesis of the data and identified those molecules commonly deregulated under both conditions. We detected a total of 25 miRNAs meeting the criteria, among them, miR-222, miR-21, miR-126-3p, miR-155 and miR-425 being the most prominent. We propose these miRNAs as biomarkers of choice for the identification of human populations exposed to air pollution with a significant risk of developing lung cancer.

Circulating miR-16-5p, miR-92a-3p, and miR-451a in Plasma from Lung Cancer Patients: Potential Application in Early Detection and a Regulatory Role in Tumorigenesis Pathways

BACKGROUND

Micro(mi)RNAs, potent gene expression regulators associated with tumorigenesis, are stable, abundant circulating molecules, and detectable in plasma. Thus, miRNAs could potentially be useful in early lung cancer detection. We aimed to identify circulating miRNA signatures in plasma from patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and to verify whether miRNAs regulate lung oncogenesis pathways.

METHODS

RNA isolated from 139 plasma samples (40 LUAD, 38 LUSC; 61 healthy/non-diseased individuals) were divided into discovery (38 patients; 21 controls for expression quantification using an 800-miRNA panel; Nanostring nCounter®) and validation (40 patients; 40 controls; TaqMan® RT-qPCR) cohorts. Elastic net, Maximizing-R-Square Analysis (MARSA), and C-Statistics were applied for miRNA signature identification.

RESULTS

When compared to healthy individuals, 580 of 606 deregulated miRNAs in LUAD and 221 of 226 deregulated miRNAs in LUSC had significantly increased levels. Among the 10 most significantly overexpressed miRNAs, 6 were common to patients with LUAD and LUSC. Further analysis identified three signatures composed of 12 miRNAs. Signatures included miRNAs commonly overexpressed in patient plasma. Enriched pathways included target genes modulated by three miRNAs in the C-Statistics signature: miR-16-5p, miR-92a-3p, and miR-451a.

CONCLUSIONS

The 3-miRNA signature (miR-16-5p, miR-92a-3p, miR-451a) had high specificity (100%) and sensitivity (84%) to predict cancer (LUAD and LUSC). These miRNAs are predicted to modulate genes and pathways with known roles in lung tumorigenesis, including EGFR, K-RAS, and PI3K/AKT signaling, suggesting that the 3-miRNA signature is biologically relevant in adenocarcinoma and squamous cell carcinoma of the lung.

Hsa-let-7c exerts an anti-tumor function by negatively regulating ANP32E in lung adenocarcinoma

We attempted to investigate the relationship between hsa-let-7c and ANP32E, as well as their influence on the cells phenotype of lung adenocarcinoma. Expression of hsa-let-7c and prognostic values were assessed by bioinformatics analysis based on TCGA database. Quantitative real-time PCR and western blot was employed to measure relative expression of hsa-let-7c or ANP32E. The targeting relationship between let-7c and ANP32E was predicted by biological software and validated by dual luciferase reporter assay. With gene transfection technology, cell proliferation, invasion and migration were appraised by cell counting Kit-8, clone formation and Transwell assays. The results showed that hsa-let-7c was downregulated in lung adenocarcinoma. Downregulation of hsa-let-7c notably led to a poor survival. ANP32E was forecasted and confirmed as a directly target of hsa-let-7c, and was upregulated in lung adenocarcinoma. Furthermore, upregulation of ANP32E had a significant correlation with unsatisfactory survival. Meanwhile, the levels of ANP32E were negatively regulated by hsa-let-7c. Upregulation of hsa-let-7c remarkably suppressed the Calu-3 cell proliferation, invasion and migration, while ANP32E overexpression plasmids rescued the downtrend. Inversely, hsa-let-7c silencing in NCI-H209 cells presented the opposite outcomes. Collectively, hsa-let-7c shows an anti-tumor effect in lung adenocarcinoma by targeting ANP32E and is expected to be a potential therapeutic target for lung adenocarcinoma.

Could microRNA be used as a diagnostic tool for lung cancer?

OBJECTIVES

Current methods for diagnosing lung cancer (LC) have varying degrees of risks and complications. MicroRNA (miRNA) is a small molecule noncoding RNA with gene regulation functions. Many studies have shown that miRNA can be used for the diagnosis of LC, but there are differences in diagnostic accuracy. Therefore, we aim to systematically review and meta-analyze published articles to comprehensively evaluate the diagnostic value of miRNA for LC.

MATERIALS AND METHODS

We searched the PubMed, Embase, and Cochrane databases, and calculated the area under the curve (AUC) by plotting the summary receiver operator characteristic curve using the sensitivity and specificity of each included study. The AUC was calculated and the likelihood ratio was plotted to assess the diagnostic accuracy of miRNA. We used QUADAS-2 in Review Manager 5.3 to evaluate the quality of all the articles. The other analyses were performed using the STATA 12.0 software.

RESULTS

We included a total of 29 articles, 98 studies, and the qualities of all the articles were satisfactory. The overall pooled parameters calculated from all studies were as follows: sensitivity = 0.77, specificity = 0.83, positive likelihood ratio (PLR) = 4.6, negative likelihood ratio (NLR) = 0.28, and AUC = 0.87 for miRNA diagnosis. It had significant advantages over other biomarkers. Subgroup analysis showed that when combined four or more miRNA for the diagnosis of LC, the parameters were as follows: sensitivity = 0.90, specificity = 0.93, PLR = 13.2, NLR = 0.11, and AUC = 0.97.

CONCLUSION

Four or more miRNA combination could be used for the diagnosis of LC. Besides this, we also found that miRNA showed a greater advantage in distinguishing LC from benign lung diseases than distinguishing between LC and normal people. Our findings provided a new way of thinking about the clinical diagnosis of LC from a nonmorphological aspect.

Circulating MicroRNA Biomarkers for Lung Cancer Detection in East Asian Populations

BACKGROUND

Lung cancer (LC) is the leading cause of cancer-related death in Eastern Asia. The prognosis of LC highly depends on tumor stages and early detection could substantially reduce LC mortality. Accumulating evidence suggested that circulating miRNAs in plasma or serum may have applications in early LC detection. We thus conducted a systematic literature review on the diagnostic value of miRNAs markers for LC in East Asian populations.

METHODS

PubMed and ISI Web of Knowledge were searched to retrieve relevant articles published up to 17 September 2018. Information on study design, population characteristics, investigated miRNAs and diagnostic accuracy (including sensitivity, specificity and area under the curve (AUC)) were independently extracted by two reviewers.

RESULTS

Overall, 46 studies that evaluated a total of 88 miRNA markers for LC diagnosis in East Asian populations were identified. Sixteen of the 46 studies have incorporated individual miRNA markers as panels (with 2⁻20 markers). Three promising miRNA panels with ≥90% sensitivity and ≥90% specificity were discovered, two of which were externally validated. Diagnostic performance of circulating miRNAs in East Asian populations was comparable to previously summarized performance in Western populations. Forty-four miRNAs were reported in both populations. No major differences in diagnostic performance by ethnicity of the same miRNA was observed.

CONCLUSIONS

Circulating miRNAs or miRNA panels, possibly in combination with other promising molecular markers including epigenetic and genetic markers, may be promising candidates for noninvasive LC early detection. However, large studies with samples collected prospectively in true screening settings are required to validate the promising markers or marker panels.

Clinically Correlated MicroRNAs in the Diagnosis of Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

(1) Background. Non-small cell lung cancer (NSCLC) has a high mortality rate. MiRNAs have been found to be diagnostic biomarkers for NSCLC. However, controversial results exist. We conducted this meta-analysis to evaluate the diagnostic value of miRNAs for NSCLC. (2) Methods. Databases and reference lists were searched. Pooled sensitivity (SEN), specificity (SPE), and area under the curve (AUC) were applied to examine the general diagnostic efficacy, and subgroup analysis was also performed. (3) Results. Pooled SEN, SPE, and AUC were 85%, 88%, and 0.93, respectively, for 71 studies. Multiple miRNAs (AUC: 0.96) obtained higher diagnostic value than single miRNA (AUC: 0.86), and the same result was found for Caucasian population (AUC: 0.97) when compared with Asian (AUC: 0.91) and Caucasian/African population (AUC: 0.92). MiRNA had higher diagnostic efficacy when participants contained both smokers and nonsmokers (AUC is 0.95 for imbalanced group and 0.91 for balanced group) than when containing only smokers (AUC: 0.90). Meanwhile, AUC was 0.91 for both miR-21 and miR-210. (4) Conclusions. Multiple miRNAs such as miR-21 and miR-210 could be used as diagnostic tools for NSCLC, especially for the Caucasian and nonsmoking NSCLC.

MiR-486 as an effective biomarker in cancer diagnosis and prognosis: a systematic review and meta-analysis

Purpose

MiR-486 was found to be associated with cancer’s diagnosis and prognosis. This meta-analysis aimed to investigate the potential effect of miR-486 on cancer detection and prognosis.

Materials and Methods

We searched PubMed, Cochrane library, Embase, Chinese National Knowledge Infrastructure (CNKI) and Wanfang databases to find all correlated articles. The STATA 11.0 was applied to estimate the pooled effects, heterogeneity and publication bias.

Results

The pooled sensitivity (SEN), specificity (SPE) and Area under the curve (AUC) were 82% (95% CI: 78–85%), 88% (95% CI: 83–92%) and 0.91 (95% CI: 0.88–0.93). Subgroup analysis indicated miR-486 from circulating samples exhibited higher diagnostic accuracy with the AUC was 0.90 (95% CI: 0.87–0.92) than miR-486 from other specimen with the AUC of 0.78 (95% CI: 0.75–0.82) and miR-486 obtained a better diagnostic value in the Asian population with the AUC of 0.94 (95% CI: 0.91–0.95) than the Caucasian and Caucasian/African population with the AUC of 0.80 (95% CI: 0.76–0.83) and 0.89 (95% CI: 0.86–0.91) respectively. MiR-486 obtained high value for the diagnosis of non-small cell lung cancer with SEN, SPE and AUC were 0.82 (95% CI: 0.0.77–0.87), 0.90 (95% CI: 0.84–0.94) as well as 0.92 (95% CI: 0.89–0.94) respectively. For the 7 prognostic tests, the pooled hazard ratio (HR) was 0.48 (95% CI: –0.13–1.08) for low versus high miR-486 expression.

Conclusions

This meta-analysis indicated that miR-486 can be used as ideal biomarkers in the cancer’s diagnosis. However, Low miR-486 expression did not increase the risk of poor outcome.

The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers

Many studies have investigated the diagnostic role of circulating microRNAs (miRNAs) in patients with lung cancer; however, the results still remain inconclusive. An updated system review and meta-analysis was necessary to give a comprehensive evaluation of diagnostic role of circulating miRNAs in lung cancer. Eligible studies were searched in electronical databases. The sensitivity and specificity were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the curve (AUC). The between-study heterogeneity was evaluated by Q test and I² statistics. Subgroup analyses and meta-regression were further performed to explore the potential sources of heterogeneity. A total of 134 studies from 65 articles (6,919 patients with lung cancer and 7,064 controls) were included for analysis. Overall analysis showed that circulating miRNAs had a good diagnostic performance in lung cancers, with a sensitivity of 0.83, a specificity of 0.84, and an AUC of 0.90. Subgroup analysis suggested that combined miRNAs and Caucasian populations may yield relatively higher diagnostic performance. In addition, we found serum might serve as an ideal material to detecting miRNA as good diagnostic performance. We also found the diagnostic role of miRNAs in early stage lung cancer was still relatively high (the sensitivity, specificity and an AUC of stage I/II was 0.81, 0.82 and 0.88; and for stage I, it was 0.80, 0.81, and 0.88). We also identified a panel of miRNAs such as miR-21-5p, miR-223-3p, miR-155-5p and miR-126-3p might serve as potential biomarkers for lung cancer. As a result, circulating miRNAs, particularly the combination of multiple miRNAs, may serve as promising biomarkers for the diagnosis of lung cancer.

A new function for miRNAs as regulators of autophagy

Autophagy is a self-digestive process regulated by an intricate network of factors able either to ensure the prosurvival function of autophagy or to convert it in a death pathway. Recently, the involvement of miRNAs in the regulation of autophagy networks has been reported. This review will summarize the main features of these small noncoding endogenous RNAs, focusing on their relevance in cancer and finally addressing their impact on autophagy.