MicroRNAs - Important Molecules in Lung Cancer Research

Computational and Bioinformatics Methods for MicroRNA Gene Prediction

MicroRNAs (miRNAs) are 20-24-nucleotide-long noncoding RNAs that bind to the untranslated region (3' UTR) of their target mRNAs. The importance of miRNAs in medicine has grown rapidly in the 20 years since the discovery of them. As the regulatory function of miRNAs on biological processes was discovered, they were advocated to play a role in the underlying mechanisms of human pathogenesis. Functional studies have confirmed that miRNAs are promising in preclinical development through deregulation of genes targeted by miRNAs in many cancer cases. In this chapter, we summarize the miRNAs identified for some specific types of cancer and their functions. Besides, miRNAs function as cancer biomarker and their benefits to diagnosis and treatment of cancer are also discussed.

Role of microRNAs in Obesity-Related Kidney Disease

Obesity is a major global health problem and is associated with a significant risk of renal function decline. Obesity-related nephropathy, as one of the complications of obesity, is characterized by a structural and functional damage of the kidney and represents one of the important contributors to the morbidity and mortality worldwide. Despite increasing data linking hyperlipidemia and lipotoxicity to kidney injury, the apprehension of molecular mechanisms leading to a development of kidney damage is scarce. MicroRNAs (miRNAs) are endogenously produced small noncoding RNA molecules with an important function in post-transcriptional regulation of gene expression. miRNAs have been demonstrated to be important regulators of a vast array of physiological and pathological processes in many organs, kidney being one of them. In this review, we present an overview of miRNAs, focusing on their functional role in the pathogenesis of obesity-associated renal pathologies. We explain novel findings regarding miRNA-mediated signaling in obesity-related nephropathies and highlight advantages and future perspectives of the therapeutic application of miRNAs in renal diseases.

Oncogenic role of MIR516A in human bladder cancer was mediated by its attenuating PHLPP2 expression and BECN1-dependent autophagy

Although MIR516A has been reported to be downregulated and act as a tumor suppressor in multiple cancers, its expression and potential contribution to human bladder cancer (BC) remain unexplored. Unexpectedly, we showed here that MIR516A was markedly upregulated in human BC tissues and cell lines, while inhibition of MIR516A expression attenuated BC cell monolayer growth in vitro and xenograft tumor growth in vivo, accompanied with increased expression of PHLPP2. Further studies showed that MIR516A was able to directly bind to the 3'-untranslated region of PHLPP2 mRNA, which was essential for its attenuating PHLPP2 expression. The knockdown of PHLPP2 expression in MIR516A-inhibited cells could reverse BC cell growth, suggesting that PHLPP2 is a MIR516A downstream mediator responsible for MIR516A oncogenic effect. PHLPP2 was able to mediate BECN1/Beclin1 stabilization indirectly, therefore promoting BECN1-dependent macroautophagy/autophagy, and inhibiting BC tumor cell growth. In addition, our results indicated that the increased autophagy by attenuating MIR516A resulted in a dramatic inhibition of xenograft tumor formation in vivo. Collectively, our results reveal that MIR516A has a novel oncogenic function in BC growth by directing binding to PHLPP2 3'-UTR and inhibiting PHLPP2 expression, in turn at least partly promoting CUL4A-mediated BECN1 protein degradation, thereby attenuating autophagy and promoting BC growth, which is a distinct function of MIR516A identified in other cancers.Abbreviation: ATG3: autophagy related 3; ATG5: autophagy related 5; ATG7: autophagy related 7; ATG12: autophagy related 12; BAF: bafilomycin A1; BC: bladder cancer; CHX: cycloheximide; Co-IP: co-immunoprecipitation; CUL3: cullin 3; CUL4A: cullin 4A; CUL4B: cullin 4B; IF: immunofluorescence: IHC-p: immunohistochemistry-paraffin; MIR516A: microRNA 516a (microRNA 516a1 and microRNA 516a2); MS: mass spectrometry; PHLPP2: PH domain and leucine rich repeat protein phosphatase.

Let-7b-3p inhibits tumor growth and metastasis by targeting the BRF2-mediated MAPK/ERK pathway in human lung adenocarcinoma

Background

Lung cancer is a malignant tumor with the highest morbidity and mortality rates worldwide, of which lung adenocarcinoma (LUAD) is the most common subtype. Overall, current treatments of LUAD are not satisfactory; therefore, novel targets need to be explored. Let-7b-3p is an important member of the let-7 family of microRNAs (miRNAs), and has not been studied separately in LUAD. This study aimed to investigate the role and molecular mechanism of let-7b-3p in LUAD.

Methods

Herein, let-7b-3p expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR) and fluorescence in situ hybridization (FISH) assays. MTT, colony formation assay, flow cytometry analysis, wound-healing, Transwell and in vivo experiments were conducted to assess let-7b-3p’s function in LUAD. The downstream target TFIIB-related factor 2 (BRF2) was predicted using bioinformatics analyses and confirmed by dual-luciferase reporter assay and rescue experiments. Additionally, BRF2 was found to affect the MAPK/ERK pathway through transcriptome sequencing analysis and western blot (WB) assay.

Results

Let-7b-3p is downregulated in LUAD cells and tissue samples and low let-7b-3p expression is correlated with a poor prognosis in LUAD patients. Let-7b-3p suppresses the proliferation and metastasis of LUAD cells both in vivo and in vitro by directly targeting the BRF2-mediated MAPK/ERK pathway.

Conclusions

Let-7b-3p inhibits the development of LUAD and is an ideal novel therapeutic target for the treatment of LUAD.

Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients

Importance

The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures.

Objective

To investigate the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants.

Design, Setting, and Participants

This multicenter, cohort study included patients from case-control and cohort studies (TREND and COSYCONET) with 3102 patients being enrolled by convenience sampling between March 3, 2009, and March 19, 2018. For the cohort study TREND, population sampling was performed. Clinical diagnoses were obtained for 3046 patients (606 patients with non-small cell and small cell lung cancer, 593 patients with nontumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). No samples were removed because of experimental issues. The collected data were analyzed between April 2018 and November 2019.

Main Outcomes and Measures

Sensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer.

Results

A total of 3102 patients with a mean (SD) age of 61.1 (16.2) years were enrolled. Data on the sex of the participants were available for 2856 participants; 1727 (60.5%) were men. Genome-wide miRNA profiles of blood samples from 3046 individuals were evaluated by machine-learning methods. Three classification scenarios were investigated by splitting the samples equally into training and validation sets. First, a 15-miRNA signature from the training set was used to distinguish patients diagnosed with lung cancer from all other individuals in the validation set with an accuracy of 91.4% (95% CI, 91.0%-91.9%), a sensitivity of 82.8% (95% CI, 81.5%-84.1%), and a specificity of 93.5% (95% CI, 93.2%-93.8%). Second, a 14-miRNA signature from the training set was used to distinguish patients with lung cancer from patients with nontumor lung diseases in the validation set with an accuracy of 92.5% (95% CI, 92.1%-92.9%), sensitivity of 96.4% (95% CI, 95.9%-96.9%), and specificity of 88.6% (95% CI, 88.1%-89.2%). Third, a 14-miRNA signature from the training set was used to distinguish patients with early-stage lung cancer from all individuals without lung cancer in the validation set with an accuracy of 95.9% (95% CI, 95.7%-96.2%), sensitivity of 76.3% (95% CI, 74.5%-78.0%), and specificity of 97.5% (95% CI, 97.2%-97.7%).

Conclusions and Relevance

The findings of the study suggest that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests.

In silico Prediction of miRNA Interactions With Candidate Atherosclerosis Gene mRNAs

The involvement of genes and miRNAs in the development of atherosclerosis is a challenging problem discussed in recent publications. It is necessary to establish which miRNAs affect the expression of candidate genes. We used known candidate atherosclerosis genes to predict associations. The quantitative characteristics of interactions of miRNAs with mRNA candidate genes were determined using the program, which identifies the localization of miRNA binding sites in mRNA, the free energy interaction of miRNA with mRNA. In mRNAs of GAS6 and NFE2L2 candidate genes, binding sites of 21 miRNAs and of 15 miRNAs, respectively, were identified. In IRS2 mRNA binding sites of 25 miRNAs were located in a cluster of 41 nt. In ADRB3, CD36, FASLG, FLT1, PLA2G7, and PPARGC1A mRNAs, clusters of miR-466, ID00436.3p-miR, and ID01030.3p-miR BS were identified. The organization of overlapping miRNA binding sites in clusters led to their compaction and caused competition among the miRNAs. The binding of 53 miRNAs to the mRNAs of 14 candidate genes with free energy interactions greater than -130 kJ/mole was determined. The miR-619-5p was fully complementary to ADAM17 and CD36 mRNAs, ID01593.5p-miR to ANGPTL4 mRNA, ID01935.5p-miR to NFE2L2, and miR-5096 to IL18 mRNA. Associations of miRNAs and candidate atherosclerosis genes are proposed for the early diagnosis of this disease.

The Role of Non-coding RNAs in Oncology

For decades, research into cancer biology focused on the involvement of protein-coding genes. Only recently was it discovered that an entire class of molecules, termed non-coding RNA (ncRNA), plays key regulatory roles in shaping cellular activity. An explosion of studies into ncRNA biology has since shown that they represent a diverse and prevalent group of RNAs, including both oncogenic molecules and those that work in a tumor suppressive manner. As a result, hundreds of cancer-focused clinical trials involving ncRNAs as novel biomarkers or therapies have begun and these are likely just the beginning.

A 10-year prediagnostic follow-up study shows that serum RNA signals are highly dynamic in lung carcinogenesis

The majority of lung cancer (LC) patients are diagnosed at a late stage, and survival is poor. Circulating RNA molecules are known to have a role in cancer; however, their involvement before diagnosis remains an open question. In this study, we investigated circulating RNA dynamics in prediagnostic LC samples, focusing on smokers, to identify if and when disease-related signals can be detected in serum. We sequenced small RNAs in 542 serum LC samples donated up to 10 years before diagnosis and 519 matched cancer-free controls coming from 905 individuals in the Janus Serum Bank. This sample size provided sufficient statistical power to independently analyze time to diagnosis, stage, and histology. The results showed dynamic changes in differentially expressed circulating RNAs specific to LC histology and stage. The greatest number of differentially expressed RNAs was identified around 7 years before diagnosis for early-stage LC and 1-4 years prior to diagnosis for locally advanced and advanced-stage LC, regardless of LC histology. Furthermore, NSCLC and SCLC histologies have distinct prediagnostic signals. The majority of differentially expressed RNAs were associated with cancer-related pathways. The dynamic RNA signals pinpointed different phases of tumor development over time. Stage-specific RNA profiles may be associated with tumor aggressiveness. Our results improve the molecular understanding of carcinogenesis. They indicate substantial opportunity for screening and improved treatment and will guide further research on early detection of LC. However, the dynamic nature of the RNA signals also suggests challenges for prediagnostic biomarker discovery.

Identification of differentially expressed circulating serum microRNA for the diagnosis and prognosis of Indian non-small cell lung cancer patients

PURPOSE

Identification of noninvasive blood-based biomarkers is of utmost importance for the early diagnosis and predicting prognosis of advance stage lung cancer patients. MicroRNAs (miRNAs) has been implicated in numerous diseases, however, their role as diagnostic and prognostic biomarkers in Indian lung cancer patients has not been evaluated yet.

METHODS

For the identification of differentially expressed miRNAs in the serum of non-small cell lung cancer (NSCLC) patients, we performed small RNA sequencing. We validated the expression of 10 miRNAs in 75 NSCLC patients and 40 controls using quantitative reverse transcription polymerase chain reaction (PCR). miRNA expression was correlated with survival and therapeutic response.

RESULTS

We identified 16 differentially expressed miRNAs in the serum of NSCLC patients as compared to controls. We observed significant downregulation of miR-15a-5p, miR-320a, miR-25-3p, miR-192-5p, let-7d-5p, let-7e-5p, miR-148a-3p, and miR-92a-3p in the serum of NSCLC patients. The expression of miR-375 and miR-10b-5p was significantly downregulated in lung squamous cell carcinoma patients than controls. The expression of miR-320a, miR-25-3p, and miR-148a-3p significantly correlated with stage. None of the miRNAs were correlated with survival outcome and therapeutic response.

CONCLUSIONS

We conclude that the relative abundance of miRNAs in serum may be explored for the development of miRNA-based assays for better diagnosis and prognosis of NSCLC. Moreover, further studies are warranted to elucidate the role of some of the less explored miRNAs, such as miR-375 and miR-320a, in the pathogenesis of NSCLC.

MiR-148b suppressed non-small cell lung cancer progression via inhibiting ALCAM through the NF-κB signaling pathway

Background

Non‐small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. MiRNAs are recognized as important molecules in cancer biology. The aim of the study was to identify a novel biomarker miR‐148b and its mechanism in the modulation of NSCLC progression.

Methods

The expressional level of miR‐148b was analyzed by RT‐PCR. The effect of miR‐4317 on proliferation was evaluated through 3‐(4,5‐Dimethyl‐2‐thiazolyl)‐2,5‐diphenyl‐2Htetrazolium bromide (MTT) assay. The effect of miR‐148b on the metastasis of NSCLC was detected through transwell assays. The verification of the target of miR‐148b was assessed by TargetScan and dual‐luciferase reporter assay. The related proteins in this study were analyzed by western blot.

Results

Our findings confirmed that miR‐148b was decreased in NSCLC and NSCLC patients with lower expression exhibited poorer overall survival (OS). Increasing miR‐148b significantly repressed proliferation, invasion and migration. More importantly, activated leukocyte cell adhesion molecule (ALCAM) was determined as the direct target of miR‐148b, and reintroduction of ALCAM attenuated miR‐148b effect on the progress of NSCLC. In addition, NF‐κB signaling pathway was modulated by miR‐148b/ALCAM axis.

Conclusions

Our results indicated that miR‐148b is able to suppress NSCLC growth and metastasis via targeting ALCAM through the NF‐κB pathway. These findings provided new evidence that miR‐148b serves as a potential biomarker and novel target for NSCLC treatment.

Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity

The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( https://mircarta.cs.uni-saarland.de ).

RNAi-based therapeutics for lung cancer: biomarkers, microRNAs, and nanocarriers

INTRODUCTION

Despite the current advances in the discovery of the lung cancer biomarkers and, consequently, in the diagnosis, this pathology continues to be the primary cause of cancer-related death worldwide. In most cases, the illness is diagnosed in an advanced stage, which limits the current treatment options available and reduces the survival rate. Therefore, RNAi-based therapy arises as a promising option to treat lung cancer.

AREAS COVERED

This review provides an overview on the exploitation of lung cancer biology to develop RNAi-based therapeutics to be applied in the treatment of lung cancer. Furthermore, the review analyzes the main nanocarriers designed to deliver RNAi molecules and induce antitumoral effects in lung cancer, and provides updated information about current RNAi-based therapeutics for lung cancer in clinical trials.

EXPERT OPINION

RNAi-based therapy uses nanocarriers to perform a targeted and efficient delivery of therapeutic genes into lung cancer cells, by taking advantage of the known biomarkers in lung cancer. These therapeutic genes are key regulatory molecules of crucial cellular pathways involved in cell proliferation, migration, and apoptosis. Thereby, the characteristics and functionalization of the nanocarrier and the knowledge of lung cancer biology have direct influence in improving the therapeutic effect of this therapy.

miR-4317 suppresses non-small cell lung cancer (NSCLC) by targeting fibroblast growth factor 9 (FGF9) and cyclin D2 (CCND2)

Background

Non-small cell lung cancer (NSCLC) is a leading cause of death worldwide. MicroRNAs (miRNAs) have been indicated as crucial actors in cancer biology. Accumulating evidence suggests that miRNAs can be used as diagnostic and prognostic markers for NSCLC.

Methods

The purpose of this study was to characterize and identify the novel biomarker miR-4317 and its targets in NSCLC. The expression of miR-4317 was analyzed by in situ hybridization (ISH) and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The effect of miR-4317 on proliferation was evaluated through 3–4,5-dimethylthiazol-2-yl-5-3–carboxymethoxyphenyl-2-4-sulfophenyl-2H-tetrazolium (MTS) and colony formation assays, and cell migration and invasion were evaluated through transwell assays. The expression of target proteins and downstream molecules was analyzed by qRT-PCR and western blot. Dual-luciferase reporter assay was used to assess the target genes of miR4317 in NSCLC cells.

Results

Our results demonstrated that miR-4317 was downregulated in NSCLC tissues and serum, particularly in lymph node metastasis and advanced clinical stage tissues. Kaplan-Meier survival analysis showed that NSCLC patients with high expression of miR-4317 exhibited better overall survival (OS). Enhanced expression of miR-4317 significantly inhibited proliferation, colony formation, migration and invasion, and hampered cycles of NSCLC cell lines in vitro. Our results suggested that miR-4317 functions by directly targeting fibroblast growth factor 9 (FGF9) and cyclin D2 (CCND2). In concordance with in vitro studies, mouse xenograft, lung, and brain metastatic studies validated that miR-4317 functions as a potent suppressor miRNA of NSCLC in vivo. Systemically delivered agomiR-4317 reduced tumor growth and inhibited FGF9 and CCND2 protein expression. Reintroduction of FGF9 and CCND2 attenuated miR-4317-mediated suppression of migration and invasion in NSCLC.

Conclusions

Our results indicate that miR-4317 can reduce NSCLC cell growth and metastasis by targeting FGF9 and CCND2. These findings provide new evidence of miR-4317 as a potential non-invasive biomarker and therapeutic target for NSCLC.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0882-4) contains supplementary material, which is available to authorized users.

MiR-423-5p in brain metastasis: potential role in diagnostics and molecular biology

During the last several years, a growing number of studies have shown that microRNAs (miRNAs) participate in cancer metastasis. Brain metastasis (BM) is a frequent complication of lung adenocarcinoma (LAD), and the incidence of locally advanced LAD with BM can be as high as 30-50%. This study was performed to identify the miRNA expression patterns of LAD with BM and to determine the biological role that miRNAs play in tumorigenesis. To this end, we conducted microarray and quantitative PCR analyses to evaluate BM-related miRNAs independently validated from a total of 155 patients with LAD. A series of in vivo and in vitro assays were also conducted to verify the impact of miRNAs on BM. We found significantly increased expression of miR-423-5p, and BM was predicted in non-small cell lung cancer when compared to LAD without BM. We next examined the function of miR-423-5p and discovered that it significantly promoted colony formation, cell motility, migration, and invasion in vitro. We computationally and experimentally confirmed that metastasis suppressor 1 (MTSS1) was a direct miR-423-5p target. Through a combination of image, histological, and molecular analyses, we found that miR-423-5p overexpression significantly increased tumor burden, local invasion, and distant BM. The level of MTSS1 expression was inversely correlated with miR-423-5p upregulation in the LAD specimens and was associated with survival of patients with BM. MiR-423-5p promoted BM in LAD and inhibited MTSS1 expression. Together, these results show that MiR-423-5p has the potential to be a marker of BM and/or a therapeutic target in LAD.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases.

Single-walled and multi-walled carbon nanotubes induce sequence-specific epigenetic alterations in 16 HBE cells

Recent studies have identified carbon nanotube (CNT)-induced epigenetic changes as one of the key players in patho-physiological response. In the present study, we investigated whether CNT exposure is associated with epigenetic changes in human bronchial epithelial cells (16 HBE), in vitro. We focused on global DNA methylation, methylation of LINE-1 elements and promoter sequence of twelve functionally important genes (SKI, DNMT1, HDAC4, NPAT, ATM, BCL2L11, MAP3K10, PIK3R2, MYO1C, TCF3, FGFR 1 and AGRN). Additionally, we studied the influence of CNT exposure on miRNA expression. Using a LC-MS/MS method and pyrosequencing for LINE-1, we observed no significant changes in global DNA methylation (%) between the concentrations of multi-walled and single-walled CNT (MWCNT and SWCNT, respectively). Significant changes in sequence-specific methylation was observed in at least one CpG site for DNMT1 (SWCNT), HDAC4 (MWCNT), NPAT/ATM (MWCNT and SWCNT), MAP3K10 (MWCNT), PIK3R2 (MWCNT and SWCNT) and MYO1C (SWCNT). While changes in DNA methylation of the genes were relatively small, these changes were associated with changes in RNA expression, especially for MWCNT. However, the study did not reveal any significant alteration in the miRNA expression, associated with MWCNT and SWCNT exposure. Based on our results, mainly MWCNT influence DNA methylation and expression of the studied genes and could have significant impact on several critical cellular processes.

MicroRNA-1253 suppresses cell proliferation and invasion of non-small-cell lung carcinoma by targeting WNT5A

MicroRNAs (miRNA) are a class of small, noncoding RNA molecules that regulate the expression of target genes. miRNA dysregulation is involved in carcinogenesis and tumor progression. In this study, we identified microRNA-1253 (miR-1253) as being significantly down-regulated in non-small-cell lung carcinoma (NSCLC) tissues and associated with advanced clinical stage, lymph node metastasis, and poor survival. The enhanced expression of miR-1253 significantly inhibited the proliferation, migration, and invasion of NSCLC cells in vitro. Bioinformatics analyses showed that miR-1253 directly targeted WNT5A (long isoform), which was confirmed using the dual-luciferase reporter assay. The inhibitory effects of miR-1253 on the growth and metastasis of NSCLC cells were attenuated and phenocopied by WNT5A (long) overexpression and knockdown, respectively. Consistent with the in vitro results, subcutaneous tumor and metastatic NSCLC mouse models showed that miR-1253 functions as a potent suppressor of NSCLC in vivo. Taken together, our findings indicated that miR-1253 inhibited the proliferation and metastasis of NSCLC cells by targeting WNT5A (long isoform) and provided new evidence of miR-1253 as a potential therapeutic target in NSCLC.

Systems Biology Analysis to Understand Regulatory miRNA Networks in Lung Cancer

Lung cancer has currently the highest cancer-related mortality rate worldwide. MicroRNAs (miRNAs) are small noncoding RNAs that play a fundamental role in gene expression and are linked to disease progression of different cancer types such as lung cancer. However, functional characterization is made difficult by the fact that miRNAs generally regulate several mRNA interaction partners, resulting in complex regulatory networks. Thus, analysis of the network biology of miRNAs is essential for comprehensive understanding of their regulatory effects in lung cancer. A deeper understanding of miRNA networks in cancer could finally serve as a basis for the development of new therapeutic interventions. Here, we present a systems biology approach to analyze regulatory miRNA interaction networks to get better insight into their function.

Improved low-rank matrix recovery method for predicting miRNA-disease association

MicroRNAs (miRNAs) performs crucial roles in various human diseases, but miRNA-related pathogenic mechanisms remain incompletely understood. Revealing the potential relationship between miRNAs and diseases is a critical problem in biomedical research. Considering limitation of existing computational approaches, we develop improved low-rank matrix recovery (ILRMR) for miRNA-disease association prediction. ILRMR is a global method that can simultaneously prioritize potential association for all diseases and does not require negative samples. ILRMR can also identify promising miRNAs for investigating diseases without any known related miRNA. By integrating miRNA-miRNA similarity information, disease-disease similarity information, and miRNA family information to matrix recovery, ILRMR performs better than other methods in cross validation and case studies.

Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm

Identification of the associations between microRNA molecules and human diseases from large-scale heterogeneous biological data is an important step for understanding the pathogenesis of diseases in microRNA level. However, experimental verification of microRNA-disease associations is expensive and time-consuming. To overcome the drawbacks of conventional experimental methods, we presented a combinatorial prioritization algorithm to predict the microRNA-disease associations. Importantly, our method can be used to predict microRNAs (diseases) associated with the diseases (microRNAs) without the known associated microRNAs (diseases). The predictive performance of our proposed approach was evaluated and verified by the internal cross-validations and external independent validations based on standard association datasets. The results demonstrate that our proposed method achieves the impressive performance for predicting the microRNA-disease association with the Area Under receiver operation characteristic Curve (AUC), 86.93%, which is indeed outperform the previous prediction methods. Particularly, we observed that the ensemble-based method by integrating the predictions of multiple algorithms can give more reliable and robust prediction than the single algorithm, with the AUC score improved to 92.26%. We applied our combinatorial prioritization algorithm to lung neoplasms and breast neoplasms, and revealed their top 30 microRNA candidates, which are in consistent with the published literatures and databases.

Computational Analysis of Specific MicroRNA Biomarkers for Noninvasive Early Cancer Detection

Cancer is a complex disease residing in various tissues of human body, accompanied with many abnormalities and mutations in genomes, transcriptome, and epigenome. Early detection plays a crucial role in extending survival time of all major cancer types. Recent advances in microarray and sequencing techniques have given more support to identifying effective biomarkers for early detection of cancer. MicroRNAs (miRNAs) are more and more frequently used as candidates for biomarkers in cancer related studies due to their regulation of target gene expression. In this paper, the comparative analysis is used to discover miRNA expression patterns in cancer versus normal samples on early stage of eight prevalent cancer types. Our work focuses on the specific miRNAs biomarkers identification and function analysis. Several identified miRNA biomarkers in this paper are matched well with those reported in existing researches, and most of them could serve as potential candidate indicators for clinical early diagnosis applications.

miRsig: a consensus-based network inference methodology to identify pan-cancer miRNA-miRNA interaction signatures

Decoding the patterns of miRNA regulation in diseases are important to properly realize its potential in diagnostic, prog- nostic, and therapeutic applications. Only a handful of studies computationally predict possible miRNA-miRNA interactions; hence, such interactions require a thorough investigation to understand their role in disease progression. In this paper, we design a novel computational pipeline to predict the common signature/core sets of miRNA-miRNA interactions for different diseases using network inference algorithms on the miRNA-disease expression profiles; the individual predictions of these algorithms were then merged using a consensus-based approach to predict miRNA-miRNA associations. We next selected the miRNA-miRNA associations across particular diseases to generate the corresponding disease-specific miRNA-interaction networks. Next, graph intersection analysis was performed on these networks for multiple diseases to identify the common signature/core sets of miRNA interactions. We applied this pipeline to identify the common signature of miRNA-miRNA inter- actions for cancers. The identified signatures when validated using a manual literature search from PubMed Central and the PhenomiR database, show strong relevance with the respective cancers, providing an indirect proof of the high accuracy of our methodology. We developed miRsig, an online tool for analysis and visualization of the disease-specific signature/core miRNA-miRNA interactions, available at: http://bnet.egr.vcu.edu/miRsig.

A novel information fusion strategy based on a regularized framework for identifying disease-related microRNAs

This is the overall flowchart of RLSSLP. RLSSLP is a novel information fusion strategy based on regularized framework for revealing potential miRNA-disease associations.

MiR-150 promotes cellular metastasis in non-small cell lung cancer by targeting FOXO4

Previous studies have shown that dysregulation of microRNA-150 (miR-150) is associated with aberrant proliferation of human non-small cell lung cancer (NSCLC) cells. However, whether miR-150 has a critical role in NSCLC cell metastasis is unknown. Here, we reveal that the critical pro-metastatic role of miR-150 in the regulation of epithelial-mesenchymal-transition (EMT) through down-regulation of FOXO4 in NSCLC. In vitro, miR-150 targets 3'UTR region of FOXO4 mRNA, thereby negatively regulating its expression. Clinically, the expression of miR-150 was frequently up-regulated in metastatic NSCLC cell lines and clinical specimens. Contrarily, FOXO4 was frequently down-regulated in NSCLC cell lines and clinical specimens. Functional studies show that ectopic expression of miR-150 enhanced tumor cell metastasis in vitro and in a mouse xenograft model, and triggered EMT-like changes in NSCLC cells (including E-cadherin repression, N-cadherin and Vimentin induction, and mesenchymal morphology). Correspondingly, FOXO4 knockdown exhibited pro-metastatic and molecular effects resembling the effect of miR-150 over-expression. Moreover, NF-κB/snail/YY1/RKIP circuitry regulated by FOXO4 were likely involved in miR-150-induced EMT event. Simultaneous knockdown of miR-150 and FOXO4 abolished the phenotypic and molecular effects caused by individual knockdown of miR-150. Therefore, our study provides previously unidentified pro-metastatic roles and mechanisms of miR-150 in NSCLC.

The roles of miRNAs as potential biomarkers in lung diseases

MicroRNAs (miRNAs) are small non-coding RNAs which can act as master regulators of gene expression, modulate almost all biological process and are essential for maintaining cellular homeostasis. Dysregulation of miRNA expression has been associated with aberrant gene expression and may lead to pathological conditions. Evidence suggests that miRNA expression profiles are altered between health and disease and as such may be considered as biomarkers of disease. Evidence is increasing that miRNAs are particularly important in lung homeostasis and development and have been demonstrated to be the involved in many pulmonary diseases such as asthma, COPD, sarcoidosis, lung cancer and other smoking related diseases. Better understanding of the function of miRNA and the mechanisms underlying their action in the lung, would help to improve current diagnosis and therapeutics strategies in pulmonary diseases. Recently, some miRNA-based drugs have been introduced as possible therapeutic agents. In this review we aim to summarize the recent findings regarding the role of miRNAs in the airways and lung and emphasise their potential therapeutic roles in pulmonary diseases.

Role of Exosomal Noncoding RNAs in Lung Carcinogenesis

Lung cancer is the major cause of cancer death worldwide. Novel, recently discovered classes of noncoding RNAs (ncRNAs) have diverse functional and regulatory activities and increasing evidence suggests crucial roles for deregulated ncRNAs in the onset and progression of cancer, including lung cancer. Exosomes are small extracellular membrane vesicles of endocytic origin that are released by many cells and are found in most body fluids. Tumor-derived exosomes mediate tumorigenesis by facilitating tumor growth and metastasis. MicroRNAs (miRNAs) are a subclass of ncRNAs that are present in exosomes. miRNAs are taken up by neighboring or distant cells and modulate various functions of recipient cells. Here, we review exosome-derived ncRNAs with a focus on miRNAs and their role in lung cancer biology.

What makes a blood cell based miRNA expression pattern disease specific?--a miRNome analysis of blood cell subsets in lung cancer patients and healthy controls

There is evidence of blood-borne miRNA signatures for various human diseases. To dissect the origin of disease-specific miRNA expression in human blood, we separately analyzed the miRNome of different immune cell subtypes, each in lung cancer patients and healthy individuals. Each immune cell type revealed a specific miRNA expression pattern also dependinging on the cell origin, line of defense, and function. The overall expression pattern of each leukocyte subtype showed great similarities between patients and controls. However, for each cell subtype we identified miRNAs that were deregulated in lung cancer patients including hsa-miR-21, a well-known oncomiR associated with poor lung cancer prognosis that was up-regulated in all leukocyte subtype comparisons of cancer versus controls. While the miRNome of cells of the adaptive immune system allowed only a weak separation between patients and controls, cells of the innate immune system allowed perfect or nearly perfect classification. Leukocytes of lung cancer patients show a cancer-specific miRNA expression profile. Our data also show that cancer specific miRNA expression pattern of whole blood samples are not determined by a single cell type. The data indicate that additional blood components, like erythrocytes, platelets, or exosomes might contribute to the disease specificity of a miRNA signature.

Analysis of plasma MicroRNAs to identifying early diagnostic molecule for gastric cancer

Gastric cancer (GC) remains the second leading cause of cancer-related death worldwide. Owing to the lack of early diagnostic techniques, GC is often diagnosed at advanced stage and that leading to low survival rate. Growing evidences have been suggesting that circulating microRNAs play an important role in earlier diagnostic of disease. In the present study, we analyze the circulating miRNAs expression in plasma of volunteers with/without GC aiming to identifying early diagnostic biomarkers. Plasma samples were collected form 6 volunteers including 3 early patients with GC and 3 healthy adults. And then miRNAs microarrays were performed to detect the expression profile of miRNAs in these plasma samples. For further validate the results from miRNAs microarray, qRT-PCR was performed. Finally, target genes of miRNAs were predicted by bioinformatic means. Compared to control plasma, 11 up-regulated and 13 down-regulated miRNAs were detected in the plasma from earlier patients with GC (fold change ≥ 2, P < 0.05). Then, 5 differential expression miRNAs (miR-223, miR-19b-2*, miR-194*, miR-141, miR-1233) were chose to confirm by qRT-PCR. The result is nearly consistent with previous data from miRNAs microarray. Finally, 53 target genes of the 5 miRNAs are predicted by bioinformatics. These differential expression miRNAs may be used as biomarker candidates for minimally invasive diagnosis of early patients with GC in the future.

The Tumor Cytosol miRNAs, Fluid miRNAs, and Exosome miRNAs in Lung Cancer

The focus of this review is to provide an update on the progress of microRNAs (miRNAs) as potential biomarkers for lung cancer. miRNAs are single-stranded, small non-coding RNAs that regulate gene expression and show tissue-specific signatures. Accumulating evidence indicates that miRNA expression patterns represent the in vivo status in physiology and disease. Moreover, miRNAs are stable in serum and other clinically convenient and available tissue sources, so they are being developed as biomarkers for cancer and other diseases. Cancer is currently the primary driver of the field, but miRNA biomarkers are being developed for many other diseases such as cardiovascular and central nervous system diseases. Here, we examine the framework and scope of the miRNA landscape as it specifically relates to the translation of miRNA expression patterns/signatures into biomarkers for developing diagnostics for lung cancer. We focus on examining tumor cytosol miRNAs, fluid miRNAs, and exosome miRNAs in lung cancer, the connections among these miRNAs, and the potential of miRNA biomarkers for the development of diagnostics. In lung cancer, miRNAs have been studied in both cell populations and in the circulation. However, a major challenge is to develop biomarkers to monitor cancer development and to identify circulating miRNAs that are linked to cancer stage. Importantly, the fact that miRNAs can be successfully harvested from biological fluids allows for the development of biofluid biopsies, in which miRNAs as circulating biomarkers can be captured and analyzed ex vivo. Our hope is that these minimally invasive entities provide a window to the in vivo milieu of the patients without the need for costly, complex invasive procedures, rapidly moving miRNAs from research to the clinic.

Non-coding RNAs in lung cancer

The discovery that protein-coding genes represent less than 2% of all human genome, and the evidence that more than 90% of it is actively transcribed, changed the classical point of view of the central dogma of molecular biology, which was always based on the assumption that RNA functions mainly as an intermediate bridge between DNA sequences and protein synthesis machinery. Accumulating data indicates that non-coding RNAs are involved in different physiological processes, providing for the maintenance of cellular homeostasis. They are important regulators of gene expression, cellular differentiation, proliferation, migration, apoptosis, and stem cell maintenance. Alterations and disruptions of their expression or activity have increasingly been associated with pathological changes of cancer cells, this evidence and the prospect of using these molecules as diagnostic markers and therapeutic targets, make currently non-coding RNAs among the most relevant molecules in cancer research. In this paper we will provide an overview of non-coding RNA function and disruption in lung cancer biology, also focusing on their potential as diagnostic, prognostic and predictive biomarkers.

Restoration of miR-101 suppresses lung tumorigenesis through inhibition of DNMT3a-dependent DNA methylation

The deregulation of miR-101 and DNMT3a has been implicated in the pathogenesis of multiple tumor types, but whether and how miR-101 silencing and DNMT3a overexpression contribute to lung tumorigenesis remain elusive. Here we show that miR-101 downregulation associates with DNMT3a overexpression in lung cancer cell lines and patient tissues. Ectopic miR-101 expression remarkably abrogated the DNMT3a 3′-UTR luciferase activity corresponding to the miR-101 binding site and caused an attenuated expression of endogenous DNMT3a, which led to a reduction of global DNA methylation and the re-expression of tumor suppressor CDH1 via its promoter DNA hypomethylation. Functionally, restoration of miR-101 expression suppressed lung cancer cell clonability and migration, which recapitulated the DNMT3a knockdown effects. Interestingly, miR-101 synergized with decitabine to downregulate DNMT3a and to reduce DNA methylation. Importantly, ectopic miR-101 expression was sufficient to trigger in vivo lung tumor regression and the blockage of metastasis. Consistent with these phenotypes, examination of xenograft tumors disclosed an increase of miR-101, a decrease of DNMT3a and the subsequent DNA demethylation. These findings support that the loss or suppression of miR-101 function accelerates lung tumorigenesis through DNMT3a-dependent DNA methylation, and suggest that miR-101-DNMT3a axis may have therapeutic value in treating refractory lung cancer.

Buccal microRNA dysregulation in lung field carcinogenesis: gender-specific implications

MicroRNAs (miRNAs) have been shown to be reliable early biomarkers in a variety of cancers including that of lung. We ascertained whether the biomarker potential of miRNAs could be validated in microscopically normal and easily accessible buccal epithelial brushings from cigarette smokers as a consequence of lung cancer linked ‘field carcinogenesis’. We found that compared to neoplasia-free subjects, a panel of 68 miRNAs were upregulated and 3 downregulated in the normal appearing buccal mucosal cells collected from patients harboring lung cancer (n=76). The performance characteristics of selected miRNAs (with ≥1-fold change) were excellent with an average under the receiver operator characteristic curve (AUROC) of >0.80. Several miRNAs also displayed gender specificity between the groups. These results provide the first proof-of-concept scenario in which minimally intrusive cheek brushings could provide an initial screening tool in a large at-risk population.

Prediction of microRNAs associated with human diseases based on weighted k most similar neighbors

BACKGROUND

The identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies.

METHODOLOGY/PRINCIPAL FINDINGS

It is known that miRNAs with similar functions are often associated with similar diseases and vice versa. Therefore, the functional similarity of two miRNAs has been successfully estimated by measuring the semantic similarity of their associated diseases. To effectively predict disease miRNAs, we calculated the functional similarity by incorporating the information content of disease terms and phenotype similarity between diseases. Furthermore, the members of miRNA family or cluster are assigned higher weight since they are more probably associated with similar diseases. A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates.

CONCLUSIONS

The superior performance of HDMP can be attributed to the accurate measurement of miRNA functional similarity, the weight assignment based on miRNA family or cluster, and the effective prediction based on weighted k most similar neighbors. The online prediction and analysis tool is freely available at http://nclab.hit.edu.cn/hdmpred.

MicroRNA-31-5p modulates cell cycle by targeting human mutL homolog 1 in human cancer cells

MicroRNAs (miRNAs) and DNA mismatch repair (MMR) have been linked to human cancer progression. Human mutL homolog 1 (hMLH1), one of the core MMR genes, defects in lung cancer development. However, the interaction between miRNAs and MMR genes and their regulatory effect on cell cycle remain poorly understood. In this study, we investigated the role of miR-31-5p in hMLH1 gene expression and the effect of miR-31-5p on cell cycle in non-small cell lung cancer (NSCLC). We found that miR-31-5p was inversely correlated with hMLH1 expression in NSCLC cell lines and hMLH1 was a direct target of miR-31-5p. Knockdown of miR-31-5p induced a cell cycle arrest at G2/M phase and increased hMLH1 protein expression in NSCLC cells. Conversely, overexpression of miR-31-5p significantly induced cell cycle arrest at S phase and decreased hMLH1 protein expression. Furthermore, knockdown of hMLH1 upregulated miR-31-5p expression and caused cell cycle arrest at S phase. Data from this study revealed that miR-31-5p modulates cell cycle by targeting hMLH1 protein at the posttranscriptional level in NSCLC, which may represent a novel therapy strategy for lung cancer by targeting miR-31-5p.