A Non-Coding RNA Landscape of Bronchial Epitheliums of Lung Cancer Patients

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction

Small nucleolar RNAs (snoRNAs) are increasingly recognized for their critical role in the pathogenesis and characterization of various human diseases. Consequently, the precise identification of snoRNA-disease associations (SDAs) is essential for the progression of diseases and the advancement of treatment strategies. However, conventional biological experimental approaches are costly, time-consuming, and resource-intensive; therefore, machine learning-based computational methods offer a promising solution to mitigate these limitations. This paper proposes a model called 'GBDTSVM', representing a novel and efficient machine learning approach for predicting snoRNA-disease associations by leveraging a Gradient Boosting Decision Tree (GBDT) and Support Vector Machine (SVM). 'GBDTSVM' effectively extracts integrated snoRNA-disease feature representations utilizing GBDT, and SVM is subsequently utilized to classify and identify potential associations. Furthermore, the method enhances the accuracy of these predictions by incorporating Gaussian integrated profile kernel similarity for both snoRNAs and diseases. Experimental evaluation of the GBDTSVM model demonstrates superior performance compared to state-of-the-art methods in the field, achieving an AUROC of 0.96 and an AUPRC of 0.95 on the 'MDRF' dataset. Moreover, our model shows superior performance on two more datasets named 'LSGT' and 'PsnoD'. Additionally, a case study conducted on the predicted snoRNA-disease associations verified the top-ranked snoRNAs across twelve prevalent diseases, further validating the efficacy of the GBDTSVM approach. These results underscore the model's potential as a robust tool for advancing snoRNA-related disease research. Source codes and datasets for our proposed framework can be obtained from: https://github.com/mariamuna04/gbdtsvm.

Exploring RNA cargo in extracellular vesicles for pleural mesothelioma detection

BACKGROUND

Pleural Mesothelioma (PM) is a highly aggressive cancer, for which effective early detection remains a challenge due to limited screening options and low sensitivity of biomarkers discovered so far. While extracellular vesicles (EVs) have emerged as promising candidates for blood-based biomarkers, their role in PM has not been studied yet. In this study, we characterized the transcriptomic profile of EVs secreted by PM primary cells and explored their potential as a biomarker source for PM detection.

METHODS

We collected cell culture supernatant from early-passage PM cell cultures derived from the pleural effusion of 4 PM patients. EVs were isolated from the supernatant using Qiagen exoEasy Maxi kit. RNA isolation from EVs was done using the mirVana PARIS kit. Finally, single-end RNA sequencing was done with Illumina Novaseq 6000.

RESULTS

We identified a range of RNA species expressed in EVs secreted by PM cells, including protein-coding RNA (80%), long non-coding RNA (13%), pseudogenes (4.5%), and short non-coding RNA (1.6%). We detected a subset of genes associated with the previously identified epithelioid (32 genes) and sarcomatoid molecular components (36 genes) in PM-EVs. To investigate whether these markers could serve as biomarkers for PM detection in blood, we compared the RNA content of PM-EVs with the cargo of EVs isolated from the plasma of healthy donors (publicly available data). Majority of upregulated genes in PM-EVs were protein-coding and long non-coding RNAs. Interestingly, 25 of them were the sarcomatoid and epithelioid marker genes. Finally, functional analysis revealed that the PM-EV RNA cargo was associated with Epithelial-Mesenchymal transition, glycolysis, and hypoxia.

CONCLUSIONS

This is the first study to characterize the transcriptomic profile of EVs secreted by PM primary cell cultures, demonstrating their potential as biomarker source for early detection. Further investigation of the functional role of PM-EVs will provide new insights into disease biology and therapeutic avenues.

Identification of ncRNA Biomarkers in Non-Small Cell Lung Cancer to Address Racial Disparities

SIGNIFICANCE

This study identifies ethnicity-related ncRNA biomarkers that differentiate lung cancer in AAs and WAs, offering diagnostic panels with high sensitivity and specificity. These findings provide a promising approach to addressing racial disparities in lung cancer detection and improving early diagnosis across diverse populations.

Dysregulation of lncRNA MALAT1 Contributes to Lung Cancer in African Americans by Modulating the Tumor Immune Microenvironment

African American (AA) populations present with notably higher incidence and mortality rates from lung cancer in comparison to other racial groups. Here, we elucidated the contribution of long non-coding RNAs (lncRNAs) in the racial disparities and their potential clinical applications in both diagnosis and therapeutic strategies. AA patients had elevated plasma levels of MALAT1 and PVT1 compared with cancer-free smokers. Incorporating these lncRNAs as plasma biomarkers, along with smoking history, achieved 81% accuracy in diagnosis of lung cancer in AA patients. We observed a rise in MALAT1 expression, correlating with increased levels of monocyte chemoattractant protein-1 (MCP-1) and CD68, CD163, CD206, indicative of tumor-associated macrophages in lung tumors of AA patients. Forced MALAT1 expression led to enhanced growth and invasiveness of lung cancer cells, both in vitro and in vivo, accompanied by elevated levels of MCP-1, CD68, CD163, CD206, and KI67. Mechanistically, MALAT1 acted as a competing endogenous RNA to directly interact with miR-206, subsequently affecting MCP-1 expression and macrophage activity, and enhanced the tumorigenesis. Targeting MALAT1 significantly reduced tumor sizes in animal models. Therefore, dysregulated MALAT1 contributes to lung cancer disparities in AAs by modulating the tumor immune microenvironment through its interaction with miR-206, thereby presenting novel diagnostic and therapeutic targets.

Differential Non-Coding RNA Profiles for Lung Cancer Early Detection in African and White Americans

Introduction

Lung cancer leads in cancer-related deaths. Disparities are observed in lung cancer rates, with African Americans (AAs) experiencing disproportionately higher incidence and mortality compared to other ethnic groups. Non-coding RNAs (ncRNAs) play crucial roles in lung tumorigenesis. Our objective was to identify ncRNA biomarkers associated with the racial disparity in lung cancer.

Methods

Using droplet digital PCR, we examined 93 lung-cancer-associated ncRNAs in the plasma and sputum samples from AA and White American (WA) participants, which included 118 patients and 92 cancer-free smokers. Subsequently, we validated our results with a separate cohort comprising 56 cases and 72 controls.

Results

In the AA population, plasma showed differential expression of ten ncRNAs, while sputum revealed four ncRNAs when comparing lung cancer patients to the control group. In the WA population, the plasma displayed eleven ncRNAs, and the sputum had five ncRNAs showing differential expression between the lung cancer patients and the control group. For AAs, we identified a three-ncRNA panel (plasma miRs-147b, 324-3p, 422a) diagnosing lung cancer in AAs with 86% sensitivity and 89% specificity. For WAs, a four-ncRNA panel was developed, comprising sputum miR-34a-5p and plasma miRs-103-3p, 126-3p, 205-5p, achieving 88% sensitivity and 87% specificity. These panels remained effective across different stages and histological types of lung tumors and were validated in the independent cohort.

Conclusions

The ethnicity-related ncRNA signatures have promise as biomarkers to address the racial disparity in lung cancer.

SAGESDA: Multi-GraphSAGE networks for predicting SnoRNA-disease associations

Over the years, extensive research has highlighted the functional roles of small nucleolar RNAs in various biological processes associated with the development of complex human diseases. Therefore, understanding the existing relationships between different snoRNAs and diseases is crucial for advancing disease diagnosis and treatment. However, classical biological experiments for identifying snoRNA-disease associations are expensive and time-consuming. Therefore, there is an urgent need for cost-effective computational techniques that can enhance the efficiency and accuracy of prediction. While several computational models have already been proposed, many suffer from limitations and suboptimal performance. In this study, we introduced a novel Graph Neural Network-based (GNN) classification model, called SAGESDA, which is implemented through the GraphSAGE architecture with attention for the prediction of snoRNA-disease associations. The classifier leverages local neighbouring nodes in a heterogeneous network to generate new node embeddings through message passing. The mini-batch gradient descent technique was applied to divide the graph into smaller sub-graphs, which enhances the model's accuracy, speed and scalability. With these advancements, SAGESDA attained an area under the receiver operating characteristic (ROC) curve (AUC) of 0.92 using the standard dot product classifier, surpassing previous related studies. This notable performance demonstrates that SAGESDA is a promising model for predicting unknown snoRNA-disease associations with high accuracy. The SAGESDA implementation details can be obtained from https://github.com/momanyibiffon/SAGESDA.git.

Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual's risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs' importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs' role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.

Streptococcus pneumoniae promotes lung cancer development and progression

Streptococcus pneumoniae (SP) is associated with lung cancer, yet its role in the tumorigenesis remains uncertain. Herein we find that SP attaches to lung cancer cells via binding pneumococcal surface protein C (PspC) to platelet-activating factor receptor (PAFR). Interaction between PspC and PAFR stimulates cell proliferation and activates PI3K/AKT and nuclear factor kB (NF-kB) signaling pathways, which trigger a pro-inflammatory response. Lung cancer cells infected with SP form larger tumors in BALB/C mice compared to untreated cells. Mice treated with tobacco carcinogen and SP develop more lung tumors and had shorter survival period than mice treated with the carcinogen alone. Mutating PspC or PAFR abolishes tumor-promoting effects of SP. Overabundance of SP is associated with the survival. SP may play a driving role in lung tumorigenesis by activating PI3K/AKT and NF-kB pathways via binding PspC to PAFR and provide a microbial target for diagnosis and treatment of the disease.

Long non-coding RNA SNHG9 regulates viral replication in rhabdomyosarcoma cells infected with enterovirus D68 via miR-150-5p/c-Fos axis

Background

The Enterovirus D68 (EV-D68) epidemic has increased knowledge of the virus as a pathogen capable of causing serious respiratory and neurological illnesses. It has been shown that long noncoding RNAs (lncRNAs) regulate viral replication and infection via multiple mechanisms or signaling pathways. However, the precise function of lncRNAs in EV-D68 infection remains unknown.

Methods

The differential expression profiles of lncRNA in EV-D68-infected and uninfected rhabdomyosarcoma (RD) cells were studied using high-throughput sequencing technology. The knockdown through small interfering RNA (siRNA) and overexpression of lncRNA SNHG9 (small ribonucleic acid host gene 9) were applied to investigate how lncRNA SNHG9 regulates EV-D68 propagation. The targeted interactions of lncRNA SNHG9 with miR-150-5p and miR-150-5p with c-Fos were validated using dual luciferase reporter system. LncRNA SNHG9 knockdown and miR-150-5p inhibitor were co-transfected with RD cells. QRT-PCR and western blot were used to detect RNA and protein levels, of c-Fos and VP1, respectively. Median tissue culture infectious dose (TCID50) was applied to detect viral titers.

Results

The results demonstrated that a total of 375 lncRNAs were highly dysregulated in the EV-D68 infection model. In the EV-D68 infection model, lncRNA SNHG9 and c-Fos were increased in EV-D68-infected RD cells. However, the expression level of miR-150-5p was downregulated. In addition, overexpression of SNHG9 in RD cells resulted in decreased viral replication levels and viral titers following infection with EV-D68, and further experiments revealed that overexpression of SNHG9 inhibited the viral replication by targeting increased miR-150-5p binding and significantly increased c-Fos expression in RD cells.

Conclusion

Our findings indicate that the SNHG9/miR-150-5p/c-Fos axis influences EV-D68 replication in host cells and that SNHG9 may be a possible target for anti-EV-D68 infection therapies.

A novel regulator in cancer initiation and progression: long noncoding RNA SHNG9

Cancer has become the most common life-threatening disease in the world. Cancers presenting with advanced stages and metastasis show poor prognosis, even with the application of radiotherapy, surgery, chemotherapy and immunotherapy. It is of great importance to explore novel, efficient biomarkers and their internal mechanisms. Recently, it has been reported that long noncoding RNAs (lncRNAs) play important roles in tumor initiation and progression, influencing downstream mRNAs by interacting with miRNAs and functioning as sponges in competing endogenous RNA (ceRNA) networks. Small nucleolar RNA host gene 9 (SNHG9) binds with miRNAs, inducing miRNA downregulation. The downregulated miRNAs enhance downstream target gene expression via ceRNA networks. Dysregulation of SNHG9 is widely observed in tumors and is associated with clinical prognosis features, which makes it a valuable target for cancer biomarkers and therapeutics. Dysregulated SNHG9 in tumor cells also functions in tumor proliferation, colony formation, migration, invasion and inhibition of apoptosis and tumor cell metabolism. This systematic review of SNHG9 in tumors provides new perspectives on cancer diagnosis and treatment.

Transcriptomic Analyses Reveal Long Non-Coding RNA in Peripheral Blood Mononuclear Cells as a Novel Biomarker for Diagnosis and Prognosis of Hepatocellular Carcinoma

Novel biomarkers are highly required for the diagnosis and predicting prognosis of hepatocellular carcinoma (HCC). In this study, we investigated the profiles of long non-coding RNAs (lncRNAs) obtained from the peripheral blood mononuclear cells (PBMCs) of patients with HCC and PBMCs from a co-culture model using transcriptomic analysis. The differentially expressed lncRNAs (DElncRNAs) were then characterized and integrated as cancer-induced lncRNAs. Among them, three up-regulating DElncRNAs including MIR4435-2HG, SNHG9 and lnc-LCP2-1 and one down-regulating, lnc-POLD3-2, were identified. The functional analysis showed that these enriched lncRNAs were mainly associated with carcinogenesis and immune responses. Following further validation in PBMCs samples (100 HBV-related HCC, 100 chronic hepatitis B and 100 healthy controls), MIR4435-2HG, lnc-POLD3-2 and their combination were revealed to be sensitive biomarkers in discriminating HCC from non-HCC (AUROC = 0.78, 0.80, and 0.87, respectively), particularly among individuals with normal serum alpha-fetoprotein levels. Additionally, high circulating SNHG9 expression was shown to be an independent prognostic factor of overall survival in patients with HCC. These results indicate that determining these lncRNAs in PBMCs could serve as novel diagnostic and prognostic biomarkers for HBV-related HCC.

PIWI-interacting RNA (piRNA): a narrative review of its biogenesis, function, and emerging role in lung cancer

Cancer remains elusive in many aspects, especially in its causes and control. After protein profiling, genetic screening, and mutation studies, scientists now have turned their attention to epigenetic modulation. This new arena has brought to light the world of noncoding RNA (ncRNA). Although very complicated and often confusing, ncRNA domains are now among the most attractive molecular markers for epigenetic control of cancer. Long ncRNA and microRNA (miRNA) have been studied best among the noncoding genome and huge data have accumulated regarding their inhibitory and promoting effects in cancer. Another sector of ncRNAs is the world of PIWI-interacting RNAs (piRNAs). Initially discovered with the asymmetric division of germline stem cells in the Drosophila ovary, piRNAs have a unique capability to associate with mammalian proteins analogous to P-element induced wimpy testis (PIWI) in Drosophila and are capable of silencing transposons. After a brief introduction to its discovery timelines, the present narrative review covers the biogenesis, function, and role of piRNAs in lung cancer. The effects on lung cancer are highlighted under sections of cell proliferation, stemness maintenance, metastasis, and overall survival, and the review concludes with a discussion of recent discoveries of another class of small ncRNAs, the piRNA-like RNAs (piR-Ls).

High-Throughput Detection of Multiple miRNAs and Methylated DNA by Droplet Digital PCR

Altered miRNA expression and DNA methylation have highly active and diverse roles in carcinogenesis. Simultaneous detection of the molecular aberrations may have a synergistic effect on the diagnosis of malignancies. Herein, we develop a high-throughput assay for detecting multiple miRNAs and DNA methylation using droplet digital PCR (ddPCR) coupled with a 96-microwell plate. The microplate-based ddPCR could absolutely and reproducibly quantify 15 miRNAs and 14 DNA methylation sites with a high sensitivity (one copy/µL and 0.1%, respectively). Analyzing sputum and plasma of 40 lung cancer patients and 36 cancer-free smokers by this approach identified an integrated biomarker panel consisting of two sputum miRNAs (miRs-31-5p and 210-3p), one sputum DNA methylation (RASSF1A), and two plasma miRNAs (miR-21-5p and 126) for the diagnosis of lung cancer with higher sensitivity and specificity compared with a single type of biomarker. The diagnostic value of the integrated biomarker panel for the early detection of lung cancer was confirmed in a different cohort of 36 lung cancer patients and 39 cancer-free smokers. The high-throughput assay for quantification of multiple molecular aberrations across sputum and plasma could improve the early detection of lung cancer.

Knockdown of long non-coding RNA small nucleolar RNA host gene 9 or hexokinase 2 both suppress endometrial cancer cell proliferation and glycolysis

AIM

Endometrial cancer (EC) is a common type of malignant gynecological cancer. Small nucleolar RNA host gene 9 (SNHG9) has been discovered to serve a role in several types of cancer; however, the role of SNHG9 in EC remains unclear. The present study aimed to investigate the effects of lncRNA SNHG9 on cell proliferation and glycolysis in EC cells.

METHODS

SNHG9 and hexokinase 2 (HK2) mRNA expression levels were measured by reverse transcription-quantitative PCR. Glucose consumption and lactate production were detected by the glycolysis cell-based assay kit. Cell Counting Kit-8 and colony formation assays were conducted to detect cell proliferation. The knockdown experiments of SNHG9 and HK2 were carried out by transfection of corresponding small interference RNAs (siRNA). The SNHG9-overexpressed plasmid was transfected into the cells to upregulate SNHG9. HK2 protein levels were analyzed by western blotting assay.

RESULTS

SNHG9 expression levels were significantly upregulated in EC tissues and cells. The knockdown of SNHG9 subsequently effectively attenuated cell proliferation and glycolysis in vitro, while SNHG9 overexpression reported the opposite effects. Notably, the transfection of 2-DG partially reversed the promoting effect of SNHG9 on glycolysis. Downregulation of HK2 markedly decreased cell proliferation and glycolysis in EC cells antagonized SNHG9.

CONCLUSION

Either downregulation of SNHG9 or HK2 inhibits EC cell proliferation and glycolysis via repressing EC cell proliferation and glycolysis.

Microbiota Biomarkers for Lung Cancer

Non-small cell lung cancer (NSCLC) is the number one cancer killer and its early detection can reduce mortality. Accumulating evidences suggest an etiopathogenic role of microorganisms in lung tumorigenesis. Certain bacteria are found to be associated with NSCLC. Herein we evaluated the potential use of microbiome as biomarkers for the early detection of NSCLC. We used droplet digital PCR to analyze 25 NSCLC-associated bacterial genera in 31 lung tumor and the paired noncancerous lung tissues and sputum of 17 NSCLC patients and ten cancer-free smokers. Of the bacterial genera, four had altered abundances in lung tumor tissues, while five were aberrantly abundant in sputum of NSCLC patients compared with their normal counterparts (all p < 0.05). Acidovorax and Veillonella were further developed as a panel of sputum biomarkers that could diagnose lung squamous cell carcinoma (SCC) with 80% sensitivity and 89% specificity. The use of Capnocytophaga as a sputum biomarker identified lung adenocarcinoma (AC) with 72% sensitivity and 85% specificity. The use of Acidovorax as a sputum biomarker had 63% sensitivity and 96% specificity for distinguishing between SCC and AC, the two major types of NSCLC. The sputum biomarkers were further validated for the diagnostic values in a different cohort of 69 NSCLC cases and 79 cancer-free controls. Sputum microbiome might provide noninvasive biomarkers for the early detection and classification of NSCLC.

Field Cancerization in NSCLC: A New Perspective on MicroRNAs in Macrophage Polarization

Lung cancer is currently the first cause of cancer-related death. The major lung cancer subtype is non-small cell lung cancers (NSCLC), which accounts for approximatively 85% of cases. The major carcinogenic associated with lung cancer is tobacco smoke, which produces long-lasting and progressive damage to the respiratory tract. The progressive and diffuse alterations that occur in the respiratory tract of patients with cancer and premalignant lesions have been described as field cancerization. At the level of tumor cells, adjacent tumor microenvironment (TME) and cancerized field are taking place dynamic interactions through direct cell-to-cell communication or through extracellular vesicles. These molecular messages exchanged between tumor and nontumor cells are represented by proteins, noncoding RNAs (ncRNAs) and microRNAs (miRNAs). In this paper, we analyze the miRNA roles in the macrophage polarization at the level of TME and cancerized field in NSCLC. Identifying molecular players that can influence the phenotypic states at the level of malignant cells, tumor microenvironment and cancerized field can provide us new insights into tumor regulatory mechanisms that can be further modulated to restore the immunogenic capacity of the TME. This approach could revert alterations in the cancerized field and could enhance currently available therapy approaches.

LncRNA SNHG9 is a prognostic biomarker and correlated with immune infiltrates in prostate cancer

BACKGROUND

Expression of Long non-coding RNA (LncRNA) small nucleolar RNA host gene 9 (SNHG9) is observed in some cancer types, while its role in prostate cancer (PCa) is unclear. We aimed to demonstrate the relationship between SNHG9 and PCa based on The Cancer Genome Atlas (TCGA) database.

METHODS

Kruskal-Wallis test, Wilcoxon signed-rank test, and logistic regression were used to evaluate relationships between clinical-pathologic features and SNHG9 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of SNHG9 using area under curve (AUC) score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed to identify the significantly involved functions of SNHG9.

RESULTS

Increased SNHG9 expression in PCa was associated with N stage (P<0.001), Gleason score (P=0.002), primary therapy outcome (P=0.001), residual tumor (P<0.001) and prostate specific antigen (PSA) (P=0.007). ROC curve suggested the significant diagnostic and prognostic ability of SNHG9 (AUC =0.815). High SNHG9 expression predicted a poorer progression-free survival (PFS) (P=0.002), and SNHG9 expression (HR: 1.776; 95% CI: 1.067-2.955; P=0.027) was independently correlated with PFS in PCa patients. GSEA and immune infiltration analysis showed that SNHG9 expression was correlated with regulating the function of ribosome and some types of immune infiltrating cells.

CONCLUSIONS

SNHG9 expression was significantly correlated with poor survival and immune infiltrations in PCa, and it may be a promising prognostic biomarker in PCa.

Integrated analysis of miRNAs and DNA methylation identifies miR-132-3p as a tumor suppressor in lung adenocarcinoma

BACKGROUND

Aberrant miRNA expression and DNA methylation are two major epigenetic events in lung adenocarcinoma (LUAD). We conducted a combined analysis of the molecular changes in LUAD.

METHODS

We analyzed differentially expressed miRNAs and methylated CpG loci in 489 LUAD tissues versus 49 normal lung tissues of the Cancer Genome Atlas (TCGA). The results were validated in cell lines and xenograft mouse models and additional pairs of 36 LUAD and 36 normal lung tissues.

RESULTS

A total of 125 differentially expressed miRNAs and 145 differentially methylated CpG loci were identified in the LUAD versus normal lung tissues of TCGA data. Expression of the 22 miRNAs was inversely correlated with the 47 differentially methylated sites located in the miRNAs. Molecular and cellular function analysis showed that the abnormally methylated miRNAs were mainly involved in cell-to-cell signaling and interaction in airway cells. The DNA methylation status and altered expressions of miRNAs and their target genes were confirmed in 36 pairs of lung tumor and noncancerous lung tissues. Furthermore, aberrant miRNA expressions or DNA methylations alone could be involved in tumorigenesis of LUAD via different pathways. In addition, elevated miR-132-3p expression, reduced expression of its targeted gene (ZEB2), and decreased cell proliferation was observed in lung cancer cells treated with DNA methyltransferase inhibitor. Moreover, in vitro and in vivo analyses showed that miR-132-3p-3p downregulation via DNA methylation promoted tumorigenicity of lung cancer by directly regulating ZEB2.

CONCLUSIONS

The interaction between two epigenetic aberrations could have important functions in LUAD. miR-132-3p might act as a tumor suppressor in the tumorigenicity of LUAD.

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: Systemically investigating relationship between aberrant miRNA expression and DNA methylation in lung cancer could improve understanding of lung tumorigenesis and develop diagnostic and therapeutic targets.

WHAT THIS STUDY ADDS

Three forms of relationships between the two epigenetic changes are defined. miR-132-3p is further identified as a tumor suppressor in lung cancer.