MicroRNA expression profiling of sputum for the detection of early and locally advanced non-small-cell lung cancer: a prospective case-control study

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

The diagnostic performance of micro-RNA and metabolites in lung cancer: A meta-analysis

BACKGROUND

The diagnosis of lung cancer is based on the microscopic exam of tissue or liquid. During the recent decade, many biomarkers have been pointed to have a potential diagnostic role. These biomarkers may be assessed in blood, pleural effusion or sputum and they could avoid biopsies or other risky procedures. The authors aimed to assess the diagnostic performances of biomarkers focusing on micro-RNA and metabolites.

METHODS

This meta-analysis was conducted under the PRISMA guidelines during a nine-year-period (2013-2022). the Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP).

RESULTS

According to our inclusion criteria, 165 studies from 79 articles were included. The pooled SEN, SPE and dOR accounted, respectively, for 0.76, 0.79 and 13.927. The AUC was estimated to 0.859 suggesting a good diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the sample, the number of biomarkers, the biomarker subtype, the tumor stage and the ethnicity revealed the biomarker number (p  =  0.009) and the tumor stage (p  =  0.0241) as potential sources of heterogeneity.

CONCLUSION

Even if this meta-analysis highlighted the potential diagnostic utility of biomarkers, more prospective studies should be performed, especially to assess the biomarkers' diagnostic potential in early-stage lung cancers.

miRNA as biomarker in lung cancer

Lung cancer has a high prevalence and mortality due to its late diagnosis and limited treatment, so it is essential to find biomarkers that allow a faster diagnosis and improve the survival of these patients. In this sense, biomarkers based on miRNAs have supposed a considerable advance. miRNAs, which are small RNA sequences, can regulate gene expression, so they play an essential role not only as a diagnostic biomarker but also as a therapeutic and prognostic one. Also, miRNA biomarkers can be obtained from liquid biopsies, which are less intrusive than lung biopsies, and have better accessibility, safety and repeatability, which allows using those biomarkers both for diagnosis and monitoring of patients. In this review, we highlight the importance of miRNAs and collect the existing evidence of their relationship with lung cancer.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Contributions of Circulating microRNAs for Early Detection of Lung Cancer

There is unmet need to develop circulating biomarkers that would enable earlier interception of lung cancer when more effective treatment options are available. Here, a set of 30 miRNAs, selected from a review of the published literature were assessed for their predictive performance in identifying lung cancer cases in the pre-diagnostic setting. The 30 miRNAs were assayed using sera collected from 102 individuals diagnosed with lung cancer within one year following blood draw and 212 controls matched for age, sex, and smoking status. The additive performance of top-performing miRNA candidates in combination with a previously validated four-protein marker panel (4MP) consisting of the precursor form of surfactant protein B (Pro-SFTPB), cancer antigen 125 (CA125), carcinoembryonic antigen (CEA) and cytokeratin-19 fragment (CYFRA21-1) was additionally assessed. Of the 30 miRNAs evaluated, five (miR-320a-3p, miR-210-3p, miR-92a-3p, miR-21-5p, and miR-140-3p) were statistically significantly (Wilcoxon rank sum test p < 0.05) elevated in case sera compared to controls, with individual AUCs ranging from 0.57−0.62. Compared to the 4MP alone, the combination of 3-miRNAs + 4MP improved sensitivity at 95% specificity by 19.1% ((95% CI of difference 0.0−28.6); two-sided p: 0.006). Our findings demonstrate utility for miRNAs for early detection of lung cancer in combination with a four-protein marker panel.

Liquid biopsy: the value of different bodily fluids

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

BACKGROUND

MicroRNAs (miRNAs) are good candidates as biomarkers for Lung cancer (LC). The aim of this article is to figure out the diagnostic value of both single and combined miRNAs in LC.

METHODS

Normative meta-analysis was conducted based on PRISMA. We assessed the diagnostic value by calculating the combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) and the area under the curve (AUC) of single and combined miRNAs for LC and specific subgroups.

RESULTS

A total of 80 qualified studies with a total of 8971 patients and 10758 controls were included. In non-small cell lung carcinoma (NSCLC), we involved 20 single-miRNAs and found their Sen, Spe and AUC ranged from 0.52-0.81, 0.66-0.88, and 0.68-0.90, respectively, specially, miR-19 with the maximum Sen, miR-20 and miR-10 with the highest Spe as well as miR-17 with the maximum AUC. Additionally, we detected miR-21 with the maximum Sen of 0.74 [95%CI: 0.62-0.83], miR-146 with the maximum Spe and AUC of 0.93 [95%CI: 0.79-0.98] and 0.89 [95%CI: 0.86-0.92] for early-stage NSCLC. We also identified the diagnostic power of available panel (miR-210, miR-31 and miR-21) for NSCLC with satisfying Sen, Spe and AUC of 0.82 [95%CI: 0.78-0.84], 0.87 [95%CI: 0.84-0.89] and 0.91 [95%CI: 0.88-0.93], and furtherly constructed 2 models for better diagnosis.

CONCLUSIONS

We identified several single miRNAs and combined groups with high diagnostic power for NSCLC through pooled quantitative analysis, which shows that specific miRNAs are good biomarker candidates for NSCLC and further researches needed.

The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer

Liquid biopsy is an emerging technology with a potential role in the screening and early detection of lung cancer. Several liquid biopsy-derived biomarkers have been identified and are currently under ongoing investigation. In this article, we review the available data on the use of circulating biomarkers for the early detection of lung cancer, focusing on the circulating tumor cells, circulating cell-free DNA, circulating micro-RNAs, tumor-derived exosomes, and tumor-educated platelets, providing an overview of future potential applicability in the clinical practice. While several biomarkers have shown exciting results, diagnostic performance and clinical applicability is still limited. The combination of different biomarkers, as well as their combination with other diagnostic tools show great promise, although further research is still required to define and validate the role of liquid biopsies in clinical practice.

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.

MicroRNA-based biomarkers for diagnosis of non-small cell lung cancer (NSCLC)

Background

The development of biomarkers for the early detection of non‐small cell lung cancer (NSCLC) is clinically important. We have developed miRNA biomarkers in sputum and plasma, respectively, for NSCLC. Herein, we evaluate whether integrated analysis of the miRNAs across the different types of specimens could improve the early detection of NSCLC.

Methods

Using reverse transcription PCR, we determined expressions of two miRNAs (miRs‐31‐5p and 210‐3p) in sputum and three miRNAs (miRs‐21‐5p, 210‐3p, and 486‐5p) in plasma of a training cohort of 76 NSCLC patients and 72 cancer‐free smokers. The results were validated in a testing cohort of 56 NSCLC patients and 55 cancer‐free smokers.

Results

The panels of two sputum miRNAs and three plasma miRNAs had 65.8–75.0% sensitivities and 83.3–87.5% specificities for diagnosis of NSCLC in the training cohort. The individual sputum or plasma miRNA panel had a higher sensitivity for squamous cell carcinoma or adenocarcinoma of the lung, respectively. From the miRNAs, we optimized an integrated panel of biomarkers consisting of two sputum miRNAs (miRs‐31‐5p and 210‐3p) and one plasma miRNA (miR‐21‐5p) that had higher sensitivity (85.5%) and specificity (91.7%) for diagnosis of NSCLC compared with the individual panels alone. Furthermore, the performance of the integrated panel of biomarkers was independent of histology and stage of NSCLC, and patients' age, sex, and ethnicity. The performance of the integrated panel of biomarkers was confirmed in the testing cohort.

Conclusions

Integrating biomarkers across different body fluids would synergistically improve the early detection of NSCLC.

Key points

Lung cancer is a heterogeneous disease and develops from complex aberrations.

Integrating sputum and plasma miRNAs has higher accuracy than when they are used alone

Regulatory roles of differentially expressed MicroRNAs in metabolic processes in negative Lens-induced myopia Guinea pigs

BACKGROUND

Myopia is one of the most common vision defects worldwide. microRNAs can regulate the target gene expression, influencing the development of diseases.

RESULTS

To investigate the alterations of microRNA profiling in negative lens-induced myopia (NLIM) guinea pigs and to explore the regulatory role of microRNAs in the occurrence and the development of myopia, we first established the NLIM guinea pig model after induction for 2 weeks. Further, we isolated sclera to purify total messenger RNA (mRNA) in both NLIM and NLIM fellow sclera. Using next generation sequencing technique and bioinformatics analysis, we identified the differentially expressed microRNAs in NLIM guinea pigs, performed the bioinformatics annotation for the differentially expressed microRNAs, and validated the expression of differentially expressed microRNAs. As a result, we successfully established an NLIM model in guinea pigs, identified 27 differentially expressed microRNAs in NLIM guinea pig sclera, including 10 upregulated and 17 downregulated microRNAs. The KEGG annotation showed the main signaling pathways were closely associated with PPAR signaling, pyruvate and propanoate metabolisms, and TGF-beta signaling pathways.

CONCLUSIONS

Our findings indicate that the development of myopia is mainly involved in the disorder of metabolic processes in NLIM guinea pigs. The PPAR signaling, pyruvate and propanoate metabolism pathways may play roles in the development of myopia.

MicroRNA-371-3 cluster as biomarkers for the diagnosis and prognosis of cancers

Purpose: To date, increasing evidences have demonstrated that the aberrant expression of miR-371–3 cluster has been verified in various cancers and could be potentially used as a biomarker for tumor diagnosis and prognosis. To explore the role of miR-371–3 cluster in tumor diagnosis and prognosis, we conducted this study based on the published data.

Methods: We searched electronic databases (PubMed, EMBASE and Web of Science databases) (Jan 1, 2007 to Jun 1, 2018). The pooled sensitivity, specificity and area under the curve (AUC) of summary receiver operator characteristic (SROC) curve were used for diagnostic values, meanwhile the pooled hazard ration (HR) and 95% CI were used to explore the prognosis capacity of miR-372 and miR-373. In addition, the publication bias of the enrolled studies was tested and a sensitivity analysis of each study was performed to evaluate the stability of the pooled result.

Results: A total of eleven eligible studies containing six eligible studies containing 870 participants for diagnosis and 1218 cancer cases for prognosis were selected for this study. For diagnosis, the pooled results revealed that the miR-371 (sensitivity: 0.85, specificity: 0.92, AUC: 0.92) and miR-373 (sensitivity: 0.81, specificity: 0.93, AUC: 0.93) could be used as diagnostic biomarkers. For prognosis, we observed that elevated miR-372 indicated poor prognosis (HR=2.31, 95% CI: 1.04–5.14), especially in the cutoff value subgroup of median (HR=2.62, 95% CI: 1.54–4.46). In addition, pooled results showed that expression of miR-373 was not related to prognosis because of the significant heterogeneity, and the high miR-373 expression presented favorable prognosis in Asians (HR=0.34, 95% CI: 0.23–0.50) after omitting the study of heterogeneity origin.

Conclusion: The current studies demonstrated that miR-371 and miR-373 could be predictive tumor diagnostic biomarkers and the expression of miR-372 and miR-373 may indicate prognosis of cancer patients.

Elimination of bacterial DNA during RNA isolation from sputum: Bashing bead vortexing is preferable over prolonged DNase treatment

Sputum often contains large amounts of contaminating bacterial DNA that, if not eliminated during RNA isolation, may interfere with gene expression studies. During RNA isolation only repeated DNase treatment can effectively remove contaminating bacterial DNA from samples, but this compromises RNA quality. In this study we tested alternative methods to facilitate the removal of DNA and improve the quality of RNA obtained. Sputum samples obtained from patients with chronic obstructive pulmonary disease were processed with dithiothreitol and subjected to various RNA isolation methods, yet with modified protocols. Modifications included prolonged DNase treatment or vortexing of sputum cells in the presence of beads prior to RNA isolation. Bacterial DNA contamination was tested by PCR using universal bacterial primers, while RNA quality was assessed by real-time PCR using GAPDH primers for amplicons of different length. We found that the RNeasy Plus Mini kit equipped with the gDNA eliminator spin column was able to completely eliminate bacterial DNA, if sputum cells were lysed in the presence of bashing beads. Notably, compared with the standard protocol, the modified procedure yielded better quality RNA as well, as indicated by improved threshold profiles of qPCR. Bead vortexing of cells was less effective when combined with other RNA isolation methods, and the repeated DNase treatment needed to completely remove contaminating DNA from the samples reduced the quality of RNA markedly. Bead vortexing in combination with certain RNA extraction methods greatly facilitates the isolation of sputum RNA that is free of contaminating bacterial DNA, and is suitable for downstream applications.

Are There New Biomarkers in Tissue and Liquid Biopsies for the Early Detection of Non-Small Cell Lung Cancer?

Lung cancer is one of the most lethal malignancies worldwide, mainly due to its late diagnoses. The detection of molecular markers on samples provided from routine bronchoscopy including several liquid-based cytology tests (e.g., bronchoaspirate, bronchoalveolar lavage) and/or on easily obtained specimens such as sputum could represent a new approach to improve the sensitivity in lung cancer diagnoses. Recently growing interest has been reported for "noninvasive" liquid biopsy as a valuable source for molecular profiling. Unfortunately, a biomarker and/or composition of biomarkers capable of detecting early-stage lung cancer has yet to be discovered even if in the last few years there has been, through the use of revolutionary new technologies, an explosion of lung cancer biomarkers. Assay sensitivity and specificity need to be improved particularly when new approaches and/or tools are used. We have focused on the most important markers detected in tissue, and on several cytological specimens and liquid biopsies overall.

Tumor-suppressive effects of microRNA-181d-5p on non-small-cell lung cancer through the CDKN3-mediated Akt signaling pathway in vivo and in vitro

The involvement of several microRNAs (miRs) in the initiation and development of tumors through the suppression of the target gene expression has been highlighted. The aberrant expression of miR-181d-5p and cyclin-dependent kinase inhibitor 3 (CDKN3) in non-small-cell lung cancer (NSCLC) was then screened by microarray analysis. In the present study, we performed a series of in vivo and in vitro experiments for the purpose of investigating their roles in NSCLC and the underlying mechanism. There was a high expression of CDKN3, whereas miR-181d-5p was downregulated in NSCLC. Quantitative RT-PCR, Western blot analysis, and dual-luciferase reporter gene assay further identified that CDKN3 could be negatively regulated by miR-181d-5p. Moreover, the upregulation of miR-181d-5p or silencing of CDKN3 could inactivate the Akt signaling pathway. A549 with the lowest miR-181d-5p and H1975 with the highest CDKN3 among the five NSCLC cell lines (H1299, A549, H1975, NCI-H157, and GLC-82) were adopted for in vitro experiments, in which expression of miR-181d-5p and CDKN3 was altered by transfection of miR-181d-5p mimic/inhibitor or siRNA-targeting CDKN3. Afterwards, cell proliferation, apoptosis, invasion, migration, and angiogenesis, as well as epithelial-mesenchymal transition (EMT), were evaluated, and tumorigenicity was assessed. In addition, an elevation in miR-181d-5p or depletion in CDKN3 led to significant reductions in proliferation, invasion, migration, angiogenesis, EMT, and tumorigenicity of NSCLC cells, coupling with increased cell apoptosis. In conclusion, this study highlights the tumor-suppressive effects of miR-181d-5p on NSCLC via Akt signaling pathway inactivation by suppressing CDKN3, thus providing a promising therapeutic strategy for the treatment of NSCLC.

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.

MicroRNA-21: A promising biomarker for the prognosis and diagnosis of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer worldwide. The high mortality rate of NSCLC is due to a limited number of diagnosis being made at an early stage of disease. Therefore, the development of a novel biological marker for the diagnosis and prognosis prediction of NSCLC remains urgent. Current literature shows that microRNA-21 (miRNA-21/miR-21), as an oncogenic miRNA, is involved in the growth, metastasis and apoptosis of NSCLC cells through its control of various target molecules and signaling pathways. Notably, a growing body of evidence further shows that miR-21 is closely associated with the prognosis prediction, recurrence and diagnosis of cancer patients, indicating that miR-21 may be a novel promising biomarker for the diagnosis and prognosis prediction of NSCLC. The present review aimed to provide a summary of recent findings on the associated progression toward finding a novel biomarker for NSCLC.

On the performance of pre-microRNA detection algorithms

MicroRNAs are crucial for post-transcriptional gene regulation, and their dysregulation has been associated with diseases like cancer and, therefore, their analysis has become popular. The experimental discovery of miRNAs is cumbersome and, thus, many computational tools have been proposed. Here we assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new ones, and combining multiple approaches into ensemble methods. In an exhaustive attempt, we condense the results of millions of computations and show that no method is clearly superior; however, we provide a guideline for biomedical researchers to select a tool. Finally, we demonstrate that combining all of the methods into one ensemble approach, for the first time, allows reliable purely computational pre-miRNA detection in large eukaryotic genomes.As the experimental discovery of microRNAs (miRNAs) is cumbersome, computational tools have been developed for the prediction of pre-miRNAs. Here the authors develop a framework to assess the performance of existing and novel pre-miRNA prediction tools and provide guidelines for selecting an appropriate approach for a given data set.

Epithelial-to-Mesenchymal Transition and MicroRNAs in Lung Cancer

Despite major advances, non-small cell lung cancer (NSCLC) remains the major cause of cancer-related death in developed countries. Metastasis and drug resistance are the main factors contributing to relapse and death. Epithelial-to-mesenchymal transition (EMT) is a complex molecular and cellular process involved in tissue remodelling that was extensively studied as an actor of tumour progression, metastasis and drug resistance in many cancer types and in lung cancers. Here we described with an emphasis on NSCLC how the changes in signalling pathways, transcription factors expression or microRNAs that occur in cancer promote EMT. Understanding the biology of EMT will help to define reversing process and treatment strategies. We will see that this complex mechanism is related to inflammation, cell mobility and stem cell features and that it is a dynamic process. The existence of intermediate phenotypes and tumour heterogeneity may be debated in the literature concerning EMT markers, EMT signatures and clinical consequences in NSCLC. However, given the role of EMT in metastasis and in drug resistance the development of EMT inhibitors is an interesting approach to counteract tumour progression and drug resistance. This review describes EMT involvement in cancer with an emphasis on NSCLC and microRNA regulation.

Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer

Lung cancer is one of the most lethal malignancies worldwide. To reduce the high morbidity and mortality of the disease, sensitive and specific biomarkers for early detection are urgently needed. Tumor-specific microRNAs (miRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In this study, the microarray of miRNAs and mRNAs on the same samples was performed and the intersection taken with The Cancer Genome Atlas (TCGA) lung cancer miRNA/RNAseq dataset. Then, miRNA-mRNA regulatory network was constructed to identify miRNA candidates associated with lung cancer through integrating gene expression and miRNA-target prediction. Furthermore, the expression levels of miRNA candidates were validated by stem-loop real-time reverse transcription PCR (qRT-PCR) in larger lung cancer population. The relationship between signature miRNAs and the risk of lung cancer were assessed by conditional logistic regression analysis. Diagnostic value of these miRNAs was determined by areas under receiver operating characteristic curves (ROC). The Affymetrix microarray analysis identified a total of 116 miRNAs and 502 mRNAs that could distinguish lung tumor tissues from adjacent non-tumor tissues, of which 70 miRNAs and 136 mRNAs were upregulated, while 46 miRNAs and 366 mRNAs were downregulated, respectively. In combination with TCGA analysis, we identified 32 miRNAs and 377 mRNAs related to lung cancer. Then, 28 key miRNAs related to 61 inter-section mRNAs were identified by miRNA-mRNA network analysis. The miRNA function analysis was indicative of that 18 upregulated and 10 downregulated miRNAs involved in signaling pathways related to Environmental Information Processing and Human Diseases. Population result showed that the expression of 7 miRNAs (miR-205-5p, miR-3917, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p and miR-27a-5p) was consistent with the analysis result of microarray and TCGA. In addition, upregulation of miR-205-5p, miR-3917 and downregulation of miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p, miR-27a-5p increased the risk of lung cancer by conditional logistic regression analysis. The diagnostic accuracy of miR-205-5p, miR-3917, miR-27a-5p, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p showed that their corresponding AUCs were 0.728, 0.661, 0.637, 0.758, 0.772, 0.734, 0.776, respectively. Therefore, there are a set of signature miRNAs which may be promising biomarkers for the early screening of high-risk populations and early diagnosis of lung cancer.

Discovering MicroRNA-Regulatory Modules in Multi-Dimensional Cancer Genomic Data: A Survey of Computational Methods

MicroRNAs (miRs) are small single-stranded noncoding RNA that function in RNA silencing and post-transcriptional regulation of gene expression. An increasing number of studies have shown that miRs play an important role in tumorigenesis, and understanding the regulatory mechanism of miRs in this gene regulatory network will help elucidate the complex biological processes at play during malignancy. Despite advances, determination of miR–target interactions (MTIs) and identification of functional modules composed of miRs and their specific targets remain a challenge. A large amount of data generated by high-throughput methods from various sources are available to investigate MTIs. The development of data-driven tools to harness these multi-dimensional data has resulted in significant progress over the past decade. In parallel, large-scale cancer genomic projects are allowing new insights into the commonalities and disparities of miR–target regulation across cancers. In the first half of this review, we explore methods for identification of pairwise MTIs, and in the second half, we explore computational tools for discovery of miR-regulatory modules in a cancer-specific and pan-cancer context. We highlight strengths and limitations of each of these tools as a practical guide for the computational biologists.