MicroRNA-31 predicts the presence of lymph node metastases and survival in patients with lung adenocarcinoma

Machine learning-based radiomics for guiding lymph node dissection in clinical stage I lung adenocarcinoma: a multicenter retrospective study

Background

Preoperative assessment of lymph node status is critical in managing lung cancer, as it directly impacts the surgical approach and treatment planning. However, in clinical stage I lung adenocarcinoma (LUAD), determining lymph node metastasis (LNM) is often challenging due to the limited sensitivity of conventional imaging modalities, such as computed tomography (CT) and positron emission tomography/CT (PET/CT). This study aimed to establish an effective radiomics prediction model using multicenter data for early assessment of LNM risk in patients with clinical stage I LUAD. The goal is to provide a basis for formulating lymph node dissection strategies before surgery in early-stage lung cancer patients.

Methods

A total of 578 patients with LUAD from three medical centers [Cancer Hospital, Chinese Academy of Medical Sciences (CCAM), the First Affiliated Hospital of Chongqing Medical University (1CMU), and Beijing Chao-Yang Hospital (BCYH)] who underwent preoperative chest CT were divided into three groups, the training group (n=336), the testing group (n=167), and the independent validation group (n=75). The records of 1,316 radiomics features of each primary tumor were extracted. The least absolute shrinkage and selection operator (LASSO) analysis and multivariable logistic regression were used to reduce the data dimensionality, select features, and construct the prediction models.

Results

In the training group, the area under the curve (AUC) for the clinical model, radiomics model, and composite model were 0.820, 0.871, and 0.883, respectively. In the testing group, the AUC for the clinical model, radiomics model, and composite model were 0.897, 0.915, and 0.934, respectively. In the validation set, the AUC of the radiomics model was the highest at 0.870, while the composite model and clinical model had AUCs of 0.841 and 0.710, respectively. The results of the Delong test showed that the AUCs of the radiomics model and composite model were significantly higher than those of the clinical model in both the training and validation groups. The decision curve analysis showed that the radiomics nomogram was clinically useful.

Conclusions

This study developed and validated a radiomics prediction model, which enables easy LNM prediction in stage I LUAD patients. This model provides a basis for formulating lymph node dissection strategies before surgery and helps to better determine the tumor node metastasis stage of the early-stage LUAD.

CEACAM1 increased the lymphangiogenesis through miR-423-5p and NF- kB in Non-Small Cell Lung Cancer

Background

Lung cancer causes significant mortality, with invasion and metastasis being the main features that cause most cancer deaths. Lymph node metastasis is the primary metastatic route in non-small cell carcinoma (NSCLC) and influences the staging and prognosis of NSCLC. Cumulative studies have reported that Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is involved in the progression of various cancers. However, few studies have discussed the function of CEACAM1 in lymphangiogenesis in NSCLC. Here, we examined how CEACAM1 influences lymphangiogenesis in NSCLC.

Methods

A total of 30 primary squamous cell carcinoma (LUSC) patients diagnosed with LN metastasis were prospectively selected. LUSC tumor tissues, para-cancerous tissues, and positive lymph node tissues were harvested. The expression and subcellular location of CEACAM1, CD31, and LVYE1 in clinical samples were detected by immunohistochemistry. Next, the CEACAM1 and hsa-miR-423-5p expressions were detected by qPCR. The protein expression of lymphangiogenesis-associated proteins and critical cytokines of the NF-κB pathway in HDLECs was detected by Western blot. A tube formation assay was performed to detect the lymphangiogenesis in different groups. The interaction between CEACAM1 and hsa-miR-423-5p was verified using a dual luciferase assay.

Results

CEACAM1 was found to be a potential gene associated with lung cancer prognosis. It was positively correlated with angiogenesis and lymphangiogenesis. Then, we detected the function of CEACAM1 in lymphangiogenesis and found that CEACAM1 promoted lymphangiogenesis. hsa-miR-423-5p overexpression inhibited lymphangiogenesis via targeting CEACAM1. Finally, we observed that CEACAM1 can activate the NF-κB pathway and, therefore, promote lymphangiogenesis.

Conclusion

We found that CEACAM1 enhanced lymphangiogenesis in NSCLC via NF-kB activation and was repressed by miR-423-5p. This suggests the value of CEACAM1 as a new therapeutic marker in NSCLC.

Overexpression of mir-489-3p inhibits proliferation and migration of non-small cell lung cancer cells by suppressing the HER2/PI3K/AKT/Snail signaling pathway

Background

Lung cancer is a highly prevalent malignancy with significant morbidity and mortality rates. MiR-489-3p, a microRNA, has been identified as a regulator of tumor cell proliferation and invasion. Its expression is downregulated in non-small cell lung cancer (NSCLC). Elucidating the molecular mechanisms underlying miR-489-3p's role in NSCLC pathogenesis is crucial for identifying potential diagnostic and therapeutic targets.

Methods

To investigate the molecular mechanism of miR-489-3p in NSCLC, this study utilized A549, a commonly used NSCLC cell line. MiR-489-3p mimics and inhibitors were transfected into A549 cells. Additionally, co-transfection experiments using wortmannin, an inhibitor of the PI3K/AKT pathway, were performed. Expression of miR-489-3p and related proteins was analyzed by Western blotting and quantitative real-time PCR (qRT-PCR). Cell migration and proliferation were assessed by wound healing and colony formation assays, respectively.

Results

Overexpression of miR-489-3p significantly inhibited the proliferation and migration of A549 cells. This inhibitory effect was further enhanced upon co-transfected with wortmannin. Analysis of human lung specimens showed increased expression of HER2, PI3K, and AKT in lung adenocarcinoma tissues compared to adjacent non-cancerous tissues.

Conclusions

These findings suggest that miR-489-3p overexpression may inhibit NSCLC cell proliferation and migration by suppressing the HER2/PI3K/AKT/Snail signaling pathway. This study elucidates miR-489-3p's molecular mechanisms in NSCLC and provides experimental basis for identifying early diagnostic markers and novel therapeutic targets.

Missed Follow-up is associated with worse survival in stage I lung cancer: results from a large multi-site academic hospital system

The purpose of this study is to examine the effect of early incomplete follow-up on overall survival among stage I lung cancer patients. Patients with clinical stage I lung cancer at our institution between 2007 and 2016 were identified (N = 1111). Exclusions included < 18 years of age (N = 2), missing stage or demographics (N = 56), incomplete appointment data or had only one scheduled appointment (N = 351), or did not survive for at least 1 year after diagnosis (N = 120). Missed appointments were defined as unattended follow-up appointments within the first year of diagnosis without an attended appointment in the subsequent 60 days. The primary outcome was the hazard ratio (HR) for death associated per 10% increase in missed oncology follow-up appointments. Univariable and descriptive statistics were performed, and a multivariable landmark Cox regression model was created to examine the effect of missed oncology follow-up on survival. A total of 582 patients were analyzed with median follow-up of 3.2 years and median age of 69 years. On multivariable analysis controlling for age, sex, race, insurance status, and definitive treatment type the HR for death was 1.44 (95% CI 1.05-1.97) for every 10% increase in missed appointments. Incomplete oncologic follow-up may negatively impact overall survival among survivors of early-stage lung cancer.

A four-gene-based methylation signature associated with lymph node metastasis predicts overall survival in lung squamous cell carcinoma

We aimed to identify prognostic methylation genes associated with lymph node metastasis (LNM) in lung squamous cell carcinoma (LUSC). Bioinformatics methods were used to obtain optimal prognostic genes for risk model construction using data from the Cancer Genome Atlas database. ROC curves were adopted to predict the prognostic value of the risk model. Multivariate regression was carried out to identify independent prognostic factors and construct a prognostic nomogram. The differences in overall survival, gene mutation and pathways between high- and low-risk groups were analyzed. Finally, the expression and methylation level of the optimal prognostic genes among different LNM stages were analyzed. FGA, GPR39, RRAD and TINAGL1 were identified as the optimal prognostic genes and were applied to establish a prognostic risk model. Significant differences were found among the different LNM stages. The risk model could predict overall survival, showing a moderate performance with AUC of 0.64-0.68. The model possessed independent prognostic value, and could accurately predict 1-, 3- and 5-year survival. Patients with a high risk score showed poorer survival. Lower gene mutation frequencies and enrichment of leukocyte transendothelial migration and the VEGF signaling pathway in the high-risk group may lead to the poor prognosis. This study identified several specific methylation markers associated with LNM in LUSC and generated a prognostic model to predict overall survival for LUSC patients.

Whole exome sequencing and MicroRNA profiling of lung adenocarcinoma identified risk prediction features for tumors at stage I and its substages

OBJECTIVES

About 20% of stage I lung adenocarcinoma (LUAD) patients suffer a relapse after surgical resection. While finer substages have been defined and refined in the AJCC staging system, clinical investigations on the tumor molecular landscape are lacking.

MATERIALS AND METHODS

We performed whole exome sequencing, DNA copy number and microRNA profiling on paired tumor-normal samples from a cohort of 113 treatment-naïve stage I Taiwanese LUAD patients. We searched for molecular features associated with relapse-free survival (RFS) of stage I or its substages and validated the findings with an independent Caucasian LUAD cohort.

RESULTS

We found sixteen nonsynonymous mutations harbored at EGFR, KRAS, TP53, CTNNB1 and six other genes associated with poor RFS in a dose-dependent manner via variant allele fraction (VAF). An index, maxVAF, was constructed to quantify the overall mutation load from genes other than EGFR. High maxVAF scores discriminated a small group of high-risk LUAD at stage I (median RFS: 4.5 versus 69.5 months; HR = 10.5, 95% CI = 4.22-26.12, P < 0.001). At the substage level, higher risk was found for patients with high maxVAF or high miR-31; IA (median RFS: 32.1 versus 122.8 months, P = 0.005) and IB (median RFS: 7.1 versus 26.2, P = 0.049). MicroRNAs, miR-182, miR-183 and miR-196a were found correlated with EGFR mutation and poor RFS in stage IB patients.

CONCLUSION

Distinctive features of somatic gene mutation and microRNA expression of stage I LUAD are characterized to complement the survival prognosis by substaging. The findings open up more options for precision management of stage I LUAD patients.

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

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

miR-31/QKI-5 axis facilitates cell cycle progression of non-small-cell lung cancer cells by interacting and regulating p21 and CDK4/6 expressions

BACKGROUND

RNA-binding protein Quaking-5 (QKI-5), a major isoform of QKIs, inhibits tumor progression in non-small cell lung cancer (NSCLC). However, the underlying molecular mechanisms of QKI-5 in the cell cycle of NSCLC are still largely unknown.

METHODS

MTT, flow cytometry, and colony formation assays were used to investigate cellular phenotypic changes. Mice xenograft model was used to evaluate the antitumor activities of QKI-5. Co-immunoprecipitation, RNA immunoprecipitation (RIP), and RIP sequencing were used to investigate protein-protein interaction and protein-mRNA interaction.

RESULTS

The QKI-5 expression was downregulated in NSCLC tissues compared with that in paired normal adjacent lung tissues. Overexpression of QKI-5 inhibited NSCLC cell proliferative and colony forming ability. In addition, QKI-5 induced cell cycle arrest at G0/G1 phase through upregulating p21^Waf1/Cip1 (p21) expression and downregulating cyclin D1, cyclin-dependent kinase 4 (CDK4), and CDK6 expressions. Further analyses showed that QKI-5 interacts with p21 protein and CDK4, CDK6 mRNAs, suggesting a critical function of QKI-5 in cell cycle regulation. In agreement with in vitro study, the mouse xenograft models validated tumor suppressive functions of QKI-5 in vivo through altering cell cycle G1-phase-associated proteins. Moreover, we demonstrated that QKI-5 is a direct target of miR-31. The QKI-5 expression was anticorrelated with the miR-31 expression in NSCLC patient samples.

CONCLUSION

Our results suggest that the miR-31/QKI-5/p21-CDK4-CDK6 axis might have critical functions in the progression of NSCLC, and targeting this axis could serve as a potential therapeutic strategy for NSCLC.

5-mRNA-based prognostic signature of survival in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common non-small-cell lung cancer, with a high incidence and a poor prognosis.

AIM

To construct effective predictive models to evaluate the prognosis of LUAD patients.

METHODS

In this study, we thoroughly mined LUAD genomic data from the Gene Expression Omnibus (GEO) (GSE43458, GSE32863, and GSE27262) and the Cancer Genome Atlas (TCGA) datasets, including 698 LUAD and 172 healthy (or adjacent normal) lung tissue samples. Univariate regression and LASSO regression analyses were used to screen differentially expressed genes (DEGs) related to patient prognosis, and multivariate Cox regression analysis was applied to establish the risk score equation and construct the survival prognosis model. Receiver operating characteristic curve and Kaplan-Meier survival analyses with clinically independent prognostic parameters were performed to verify the predictive power of the model and further establish a prognostic nomogram.

RESULTS

A total of 380 DEGs were identified in LUAD tissues through GEO and TCGA datasets, and 5 DEGs (TCN1, CENPF, MAOB, CRTAC1 and PLEK2) were screened out by multivariate Cox regression analysis, indicating that the prognostic risk model could be used as an independent prognostic factor (Hazard ratio = 1.520, P < 0.001). Internal and external validation of the model confirmed that the prediction model had good sensitivity and specificity (Area under the curve = 0.754, 0.737). Combining genetic models and clinical prognostic factors, nomograms can also predict overall survival more effectively.

CONCLUSION

A 5-mRNA-based model was constructed to predict the prognosis of lung adenocarcinoma, which may provide clinicians with reliable prognostic assessment tools and help clinical treatment decisions.

Development of a 4-miRNA prognostic signature for endometrial cancer

To develop an effective uterine corpus endometrial carcinoma (UCEC) risk assessment tool to monitor treatment outcomes. Limma package was used to analyze differentially expressed microRNAs (miRNAs) between UCEC tissues and normal tissues in the TCGA database. According to univariate Cox risk regression, least absolute shrinkage, and selection operator (LASSO) Cox analysis were performed to screen prognostic miRNAs and construct a risk scoring model. The prognostic performance of signature was evaluated by Kaplan-Meier and receiver operating characteristic. Multivariate Cox regression analysis was used to determine the independent prognostic factors of UCEC. Nomogram was constructed according to age, clinical stage, and risk score. A 4-miRNA signature based on miR-31-5p, miR-34a-5p, miR-26a-1-3p and miR-4772-3p was established. Risk scores of each patient were calculated by the 4-miRNA signature. After z-score, the patients were divided into high- and low-risk groups. The overall survival of high-risk patients was significantly shorter than that of low-risk patients, pointing to the high performance and independence of the 4-miRNA signature in predicting UCEC prognosis. The nomogram showed a high accuracy in predicting overall survival of UCEC patients. We developed a 4-miRNA signature that could effectively predict the prognosis of UCEC.

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.

A Radiomics Nomogram for Preoperative Prediction of Clinical Occult Lymph Node Metastasis in cT1-2N0M0 Solid Lung Adenocarcinoma

Background

Clinical occult lymph node metastasis (cOLNM) means that the lymph node is negatively diagnosed by preoperative computed tomography (CT), but has been proven to be positive by postoperative pathology. The aim of this study was to establish and validate a nomogram based on radiomics features for the preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.

Methods

A total of 244 patients with clinical T1-2N0M0 solid lung adenocarcinoma who underwent preoperative contrast-enhanced chest CT were divided into a primary group (n = 160) and an independent validation group from another hospital (n = 84). The records of 851 radiomics features of each primary tumor were extracted. LASSO analysis was used to reduce the data dimensionality and select features. Multivariable logistic regression was utilized to identify independent predictors of cOLNM and develop a predictive nomogram. The performance of the predictive model was assessed by its calibration and discrimination. Decision curve analysis (DCA) was performed to estimate the clinical usefulness of the nomogram.

Results

The predictive model consisted of a clinical factor (CT-reported tumor size) and a radiomics feature (Rad-score). The nomogram presented good discrimination, with a C-index of 0.782 (95% CI, 0.768–0.796) in the primary cohort and 0.813 (95% CI, 0.787–0.839) in the validation cohort, and good calibration. DCA showed that the radiomics nomogram was clinically useful.

Conclusion

This study develops and validates a nomogram that incorporates clinical and radiomics factors. It can be tailored for the individualized preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.

The potential diagnostic value of extracellular vesicle miRNA for human non-small cell lung cancer: a systematic review and meta-analysis

Background: This meta-analysis aimed to evaluate the diagnostic accuracy of extracellular vesicles (EV) miRNAs for non-small cell lung cancer (NSCLC).Methods: All eligible studies were searched in an online database. Stata 15.0, Meta-disc 14.0 and Review Manager 5.2 software packages were used to perform all statistical analysis.Results: The analysis included 16 articles and 70 studies. Pooled sensitivity (SEN) and specificity (SPE), positive predictive value and negative predictive value were 0.77 (95% CI: 0.72-0.80), 0.83 (95% CI: 0.78-0.86), 0.88 (95% CI: 0.86-0.90) and 0.63 (95% CI: 0.58-0.68), respectively. The overall diagnostic odds ratio (DOR) was 16 (95% CI: 11-21) and the area under the curve (AUC) was 0.86 (95% CI: 0.83-0.89). 3 EV miRNAs could identify metastatic NSCLC from healthy, and 10 distinguish early-stage NSCLC. The respective targets of EV miR-21, miR-210, and miR-1290 could activate PI3K/AKT-related pathway.Conclusion: EV miRNAs had high diagnostic accuracy (AUC = 0.86) for NSCLC, especially metastatic NSCLC (AUC = 0.90), and early-stage NSCLC (AUC = 0.88). Besides, multitudinous EV miRNAs combined showed higher diagnostic value than alone. EV miR-21, miR-210, and miR-1290 might be associated with PI3K/AKT-related pathway and the valuable diagnostic biomarkers for NSCLC.

Development and Validation of a Nomogram for Preoperative Prediction of Lymph Node Metastasis in Lung Adenocarcinoma Based on Radiomics Signature and Deep Learning Signature

BACKGROUND AND PURPOSE

The preoperative LN (lymph node) status of patients with LUAD (lung adenocarcinoma) is a key factor for determining if systemic nodal dissection is required, which is usually confirmed after surgery. This study aimed to develop and validate a nomogram for preoperative prediction of LN metastasis in LUAD based on a radiomics signature and deep learning signature.

MATERIALS AND METHODS

This retrospective study included a training cohort of 200 patients, an internal validation cohort of 40 patients, and an external validation cohort of 60 patients. Radiomics features were extracted from conventional CT (computed tomography) images. T-test and Extra-trees were performed for feature selection, and the selected features were combined using logistic regression to build the radiomics signature. The features and weights of the last fully connected layer of a CNN (convolutional neural network) were combined to obtain a deep learning signature. By incorporating clinical risk factors, the prediction model was developed using a multivariable logistic regression analysis, based on which the nomogram was developed. The calibration, discrimination and clinical values of the nomogram were evaluated.

RESULTS

Multivariate logistic regression analysis showed that the radiomics signature, deep learning signature, and CT-reported LN status were independent predictors. The prediction model developed by all the independent predictors showed good discrimination (C-index, 0.820; 95% CI, 0.762 to 0.879) and calibration (Hosmer-Lemeshow test, P=0.193) capabilities for the training cohort. Additionally, the model achieved satisfactory discrimination (C-index, 0.861; 95% CI, 0.769 to 0.954) and calibration (Hosmer-Lemeshow test, P=0.775) when applied to the external validation cohort. An analysis of the decision curve showed that the nomogram had potential for clinical application.

CONCLUSIONS

This study presents a prediction model based on radiomics signature, deep learning signature, and CT-reported LN status that can be used to predict preoperative LN metastasis in patients with LUAD.

miR-31 Displays Subtype Specificity in Lung Cancer

miRNA rarely possess pan-oncogenic or tumor-suppressive properties. Most miRNAs function under tissue-specific contexts, acting as either tumor suppressors in one tissue, promoting oncogenesis in another, or having no apparent role in the regulation of processes associated with the hallmarks of cancer. What has been less clear is the role of miRNAs within cell types of the same tissue and the ability within each cell type to contribute to oncogenesis. In this study, we characterize the role of one such tissue-specific miRNA, miR-31, recently identified as the most oncogenic miRNA in lung adenocarcinoma, across the histologic spectrum of human lung cancer. Compared with normal lung tissue, miR-31 was overexpressed in patient lung adenocarcinoma, squamous cell carcinoma, and large-cell neuroendocrine carcinoma, but not small-cell carcinoma or carcinoids. miR-31 promoted tumor growth in mice of xenografted human adenocarcinoma and squamous cell carcinoma cell lines, but not in large- or small-cell carcinoma lines. While miR-31 did not promote primary tumor growth of large- and small-cell carcinoma, it did promote spontaneous metastasis. Mechanistically, miR-31 altered distinct cellular signaling programs within each histologic subtype, resulting in distinct phenotypic differences. This is the first report distinguishing diverse functional roles for this miRNA across the spectrum of lung cancers and suggests that miR-31 has broad clinical value in human lung malignancy. SIGNIFICANCE: These findings demonstrate the oncogenic properties of miR-31 in specific subtypes of lung cancer and highlight it as a potential therapeutic target in these subtypes. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/8/1942/F1.large.jpg.

Frontiers of MicroRNA Signature in Non-small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related deaths worldwide and non-small cell lung cancer (NSCLC) accounts for more than 80% of all lung cancer cases. Recent advancements in diagnostic tools, surgical treatments, chemotherapies, and molecular targeted therapies that improved the therapeutic efficacy in NSCLC. However, the 5-years relative survival rate of NSCLC is only about 20% due to the inadequate screening methods and late onset of clinical symptoms. Dysregulation of microRNAs (miRNAs) was frequently observed in NSCLC and closely associated with NSCLC development, progression, and metastasis through regulating their target genes. In this review, we provide an updated overview of aberrant miRNA signature in NSCLC, and discuss the possibility of miRNAs becoming a diagnostic and therapeutic tool. We also discuss the possible causes of dysregulated miRNAs in NSCLC.

Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

Non-Coding RNAs as Prognostic Biomarkers: A miRNA Signature Specific for Aggressive Early-Stage Lung Adenocarcinomas

Lung cancer burden can be reduced by adopting primary and secondary prevention strategies such as anti-smoking campaigns and low-dose CT screening for high risk subjects (aged >50 and smokers >30 packs/year). Recent CT screening trials demonstrated a stage-shift towards earlier stage lung cancer and reduction of mortality (~20%). However, a sizable fraction of patients (30–50%) with early stage disease still experience relapse and an adverse prognosis. Thus, the identification of effective prognostic biomarkers in stage I lung cancer is nowadays paramount. Here, we applied a multi-tiered approach relying on coupled RNA-seq and miRNA-seq data analysis of a large cohort of lung cancer patients (TCGA-LUAD, n = 510), which enabled us to identify prognostic miRNA signatures in stage I lung adenocarcinoma. Such signatures showed high accuracy (AUC ranging between 0.79 and 0.85) in scoring aggressive disease. Importantly, using a network-based approach we rewired miRNA-mRNA regulatory networks, identifying a minimal signature of 7 miRNAs, which was validated in a cohort of FFPE lung adenocarcinoma samples (CSS, n = 44) and controls a variety of genes overlapping with cancer relevant pathways. Our results further demonstrate the reliability of miRNA-based biomarkers for lung cancer prognostication and make a step forward to the application of miRNA biomarkers in the clinical routine.

miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

Background

The present study is to screen lymph node metastasis-related microRNAs (miRNAs) in lung adenocarcinoma (LUAD) and uncover their underlying mechanisms.

Methods

The miRNA microarray dataset was collected from the Gene Expression Omnibus database under accession number GSE64859. The differentially expressed miRNAs (DEMs) were identified using a t-test. Target genes of DEMs were predicted through the miRWalk2.0 database. The function of these target genes was annotated with the clusterProfiler and the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. Protein-protein interaction network was established using the STRING database to extract hub target genes. The expressions and associations with survival and lymph node metastasis of miRNAs and target genes were validated by analysis of The Cancer Genome Atlas (TCGA) dataset.

Results

Eight DEMs were identified between lymph node metastasis and non-metastasis samples of GSE64859 dataset. miRNA-target gene pairs were predicted between six DEMs and 251 target genes (i.e. hsa-miR-224-PRPF4B, hsa-miR-147b-WDR82 and hsa-miR-31-NR3C2). The clusterProfiler analysis showed WDR82 was involved in the mRNA surveillance pathway, while the GO enrichment analysis using the DAVID database indicated PRPF4B participated in the protein phosphorylation and NR3C2 was related with the transcription, DNA-templated. WDR82 and PRPF4B may be hub genes because they could interact with others. Two DEMs (miR-31-5p and miR-31-3p) and 45 target genes (including PRPF4B and NR3C2) were significantly associated with overall survival. The expressions of miR-224 and miR-147b were validated to be upregulated, while WDR82, PRPF4B and NR3C2 were downregulated in lymph node metastasis samples of TCGA datasets compared with non-metastasis samples. Also, there were significantly negative expression correlations between miR-147b and WDR82, between miR-224 and PRPF4B, as well as between miR-31 and NR3C2 in LUAD samples.

Conclusions

The present study identified several crucial miRNA-mRNA interaction pairs, which may provide novel explanations for the lymph node metastasis and poor prognosis for LUAD patients.

MicroRNA-31 Regulates Expression of Wntless in Both Drosophila melanogaster and Human Oral Cancer Cells

Recent comparative studies have indicated distinct expression profiles of short, non-coding microRNAs (miRNAs) in various types of cancer, including oral squamous cell carcinoma (OSCC). In this study, we employed a hybrid approach using Drosophila melanogaster as well as OSCC cell lines to validate putative targets of oral cancer-related miRNAs both in vivo and in vitro. Following overexpression of Drosophila miR-31, we found a significant decrease in the size of the imaginal wing discs and downregulation of a subset of putative targets, including wntless (wls), an important regulator of the Wnt signaling pathway. Parallel experiments performed in OSCC cells have also confirmed a similar miR-31-dependent regulation of human WLS that was not initially predicted as targets of human miR-31. Furthermore, we found subsequent downregulation of cyclin D1 and c-MYC, two of the main transcriptional targets of Wnt signaling, suggesting a potential role of miR-31 in regulating the cell cycle and proliferation of OSCC cells. Taken together, our Drosophila-based in vivo system in conjunction with the human in vitro platform will thus provide a novel insight into a mammal-to-Drosophila-to-mammal approach to validate putative targets of human miRNA and to better understand the miRNA-target relationships that play an important role in the pathophysiology of oral cancer.

Dynamical network analysis reveals key microRNAs in progressive stages of lung cancer

Non-coding RNAs are fundamental to the competing endogenous RNA (CeRNA) hypothesis in oncology. Previous work focused on static CeRNA networks. We construct and analyze CeRNA networks for four sequential stages of lung adenocarcinoma (LUAD) based on multi-omics data of long non-coding RNAs (lncRNAs), microRNAs and mRNAs. We find that the networks possess a two-level bipartite structure: common competing endogenous network (CCEN) composed of an invariant set of microRNAs over all the stages and stage-dependent, unique competing endogenous networks (UCENs). A systematic enrichment analysis of the pathways of the mRNAs in CCEN reveals that they are strongly associated with cancer development. We also find that the microRNA-linked mRNAs from UCENs have a higher enrichment efficiency. A key finding is six microRNAs from CCEN that impact patient survival at all stages, and four microRNAs that affect the survival from a specific stage. The ten microRNAs can then serve as potential biomarkers and prognostic tools for LUAD.

NF-κB-Induced Upregulation of miR-548as-3p Increases Invasion of NSCLC by Targeting PTEN

BACKGROUND

Non-Small Cell Lung Cancer (NSCLC) is an aggressive cancer type due to high metastatic capacity. Nuclear Factor Kappa B (NF-κB) is a consistently active transcription factor in malignant lung cancer cells and has crucial significance in NSCLC progression. It is also implicated in the transcriptional regulation of many genes including microRNAs (miRNAs) that function as tumor suppressor or oncogene. It has been increasingly reported that several miRNAs defined as gene members are induced by NF-κB. The present study aimed to find novel miRNAs that are regulated by NF-κB.

METHODS

Chromatin İmmunoprecipitation Sequencing (ChIP-Seq) experiment and bioinformatic analysis were used to determine NF-κB-dependent miRNAs. Western blot analysis, quantitative real-time polymerase chain reaction (qRT-PCR), luciferase reporter gene assays were carried out to investigate the target genes of miRNAs. To determine biologic activity, transwell invasion and MTT assay were carried out on H1299 NSCLC cell line. miRNA expression level was evaluated in metastatic and non-metastatic tissue samples of NSCLC patients.

RESULTS

ChIP-Seq and qRT-PCR experiments showed that miR-548as-3p is transcriptionally regulated by NF- κB in response to Tumor Necrosis Factor-α (TNF-α) treatment. Then, we found that tumor suppressor Phosphatase and Tension homolog (PTEN) is a direct target of miR-548as-3p. Furthermore, miR-548as-3p mediates phosphatidylinositol-3-OH kinase (PI3K)/Akt pathway and NF-κB-implicated genes including Matrix Metalloproteinases 9 (MMP9), Slug and Zeb1. We further showed that miR-548as-3p increased invasiveness of NSCLC cells and was upregulated in metastatic tumor tissues compared to non-metastatic ones.

CONCLUSION

All these findings provide a miRNAs-mediated novel mechanism for NF-κB signaling and that miR-548as-3p could be a biomarker for NSCLC metastasis.

Upregulation of microRNA-31 is associated with poor prognosis in patients with advanced colorectal cancer

Colorectal cancer (CRC) manifests after the accumulation of genetic and epigenetic alterations along with tumor microenvironments. MicroRNA (miRNA/miR) molecules have been revealed to serve in critical roles in the progression various types of cancer, and their expression level is often an important diagnostic, predictive or prognostic biomarker. The aim of the present study was to evaluate the potential of miRNAs as prognostic biomarkers for patients with advanced CRC. miRNA arrays were performed on CRC specimens obtained from tumors with various molecular statuses [e.g. KRAS proto-oncogene, GTPase (KRAS)/B-Raf proto-oncogene, serine/threonine kinase (BRAF)/microsatellite instability (MSI)], and their paired normal mucosal specimens. The miRNA array revealed that miR-31-5p (miR-31) was specifically upregulated in CRCs with the BRAF V600E mutation, the results of which were supported by subsequent analysis of a dataset retrieved from The Cancer Genome Atlas (TCGA) database, which contained information regarding 170 patients with CRC including 51 BRAF-mutant CRCs. Of our cohort of 67 patients with stage IV CRC, 15 (22%) and 4 (6%) showed KRAS and BRAF V600E mutations, respectively. Since the median miR-31 expression was 3.45 (range, 0.004–6330.531), the cut-off value was chosen as 3.5, and all tumors were categorized into two groups accordingly (high-/low-miR-31 expression). The high miR-31 expression group (n=33) was significantly associated with a poorer mortality (univariate hazard ratio=2.12; 95% confidence interval, 0.23–0.95; P=0.03) and exhibited a shorter median survival time (MST; 20.1 months) compared with the low miR-31 expression group (n=34) (MST, 38.3 months; P=0.03), indicating that miR-31 is a promising prognostic biomarker for patients with advanced CRC. Thus, performing a functional analysis of miR-31 expression may lead to the development of new targeted therapies for the various genetic subtypes of CRC.

[Differential expression of miR-126-5p in lung adenocarcinoma and the possible mechanism]

OBJECTIVE

To investigate the differential expression of miR-126-5p in patients with lung adenocarcinoma and explore the possible mechanism.

METHODS

We searched STARBASE database to analyze the differential expression of miR-126-5p between lung adenocarcinoma tissues and normal lung tissues. The prognosis of patients with lung adenocarcinoma was analyzed on Kaplan-Meier Plotter online website, and the survival curves of the patients with different expression levels of miR-126-5p were generated. The target gene of mir-126-5p was predicted by STARBASE database, and the expression level of the target gene and its influence on the patients' prognosis were analyzed using online website tool. We also examined the expression levels of miR-126-5p in peripheral serum of 30 healthy control subjects and 30 patients with lung adenocarcinoma using qPCR.

RESULTS

Analysis of the data from STARBASE database showed a high expression of miR-126-5p in normal lung tissues but a low expression in lung adenocarcinoma tissues. Kaplan-Meier Plotter online analysis based on big data analysis showed that patients with a high expression of miR-126-5p had a better survival prognosis than those with a low expression (HR=0.68, P=0.015). MiR-126-5p was predicted to bind to the 3'UTR region of BRCC3 mRNA, and their expression levels were negatively correlated (r=0.197, P < 0.05). Compared with normal tissues, lung adenocarcinoma tissues expressed high levels of BRCC3, which was associated with a poor prognosis of the patients (HR=1.39, P < 0.05). The serum level of miR-126-5p was significantly higher in healthy control subjects than in patients with lung adenocarcinoma (1.23 ± 0.21 vs 0.63 ± 0.12, P < 0.05).

CONCLUSIONS

The expression level of miR-126-5p is lowered in lung adenocarcinoma tissue, and patients with lung adenocarcinoma have lower serum level of miR-126-5p than healthy subjects. A high expression of miR-126-5p is associated with a more favorable prognosis of the patients than a low expression. miR-126-5p may play a role against cancer by regulating BRCC3.

miR-134-5p Promotes Stage I Lung Adenocarcinoma Metastasis and Chemoresistance by Targeting DAB2

Despite surgery and adjuvant therapy, early-stage lung adenocarcinoma (LUAD) treatment often fails due to local or metastatic recurrence. However, the mechanism is largely unknown. Here, we report that increased expression levels of miR-134-5p and decreased levels of disabled-2 (DAB2) were significantly correlated with recurrence in stage I LUAD patients. Our data show that miR-134-5p overexpression or DAB2 silencing strongly stimulated LUAD cell metastasis and chemoresistance. In contrast, inhibition of miR-134-5p or overexpression of DAB2 strongly suppressed LUAD cell metastasis and overcame the insensitivity of chemoresistant LUAD cells to chemotherapy. In addition, we demonstrated that DAB2 is a target of miR-134-5p and that miR-134-5p stimulates chemoresistance and metastasis through DAB2 in LUAD. Taken together, these findings suggest that miR-134-5p and its target gene DAB2 have potential as a biomarker for predicting recurrence in stage I LUAD patients. Additionally, miR-134-5p inhibition or DAB2 restoration may be a novel strategy for inhibiting LUAD metastasis and overcoming LUAD cell resistance to chemotherapy.

MicroRNA in Lung Cancer Metastasis

Tumor metastasis is a hallmark of cancer, with distant metastasis frequently developing in lung cancer, even at initial diagnosis, resulting in poor prognosis and high mortality. However, available biomarkers cannot reliably predict cancer spreading sites. The metastatic cascade involves highly complicated processes including invasion, migration, angiogenesis, and epithelial-to-mesenchymal transition that are tightly controlled by various genetic expression modalities along with interaction between cancer cells and the extracellular matrix. In particular, microRNAs (miRNAs), a group of small non-coding RNAs, can influence the transcriptional and post-transcriptional processes, with dysregulation of miRNA expression contributing to the regulation of cancer metastasis. Nevertheless, although miRNA-targeted therapy is widely studied in vitro and in vivo, this strategy currently affords limited feasibility and a few miRNA-targeted therapies for lung cancer have entered into clinical trials to date. Advances in understanding the molecular mechanism of metastasis will thus provide additional potential targets for lung cancer treatment. This review discusses the current research related to the role of miRNAs in lung cancer invasion and metastasis, with a particular focus on the different metastatic lesions and potential miRNA-targeted treatments for lung cancer with the expectation that further exploration of miRNA-targeted therapy may establish a new spectrum of lung cancer treatments.

Functions and mechanisms of microRNA-31 in human cancers

MicroRNAs can exhibit opposite functions in different tumors. MiR-31 is a representative example as it can not only enhance tumor development and progression in pancreatic cancer, colorectal cancer and so on, but also inhibit tumorigenesis and induce apoptosis in ovarian cancer, prostate cancer and etc. The mechanism underlying its' pleiotropy remains unknown. Several recent studies that focused on the global gene expression changes caused by aberrant miR-31 provided information on the upstream and downstream events associated with deregulated miR-31. MiR-31 might interact with a number of signaling pathways including RAS/MARK, PI3K/AKT and RB/E2F to play its opposite functions. This review summarizes the target genes and pathways associated with miR-31 and examines the mechanisms underlying the function of miR-31. The resulting hypothesis is possible that the tissue-specific features of adenocarcinoma and squamous cell cancer and the positive feedback loop consists of miR-31 and its upstream and downstream may account for the diversity of miR-31 functions.

Identification of SPP1 as a promising biomarker to predict clinical outcome of lung adenocarcinoma individuals

We identified and investigated the prognostic value of secreted phosphoprotein 1 (SPP1) in lung adenocarcinoma (LUAD) patients and evaluate the relationship between the SPP1 expression level and clinical characteristics. First, SPP1 was identified through four LUAD datasets in GEO database and validated by the TCGA database. Then a total of 149 lung adenocarcinoma patients were included, as well as their clinicopathological characteristics collected in the study. The expression levels of SPP1 and adjacent normal tissues were assessed by immunohistochemistry. The association between SPP1 and its prognostic value was systematically evaluated. Results showed high SPP1 level predicted poorer LUAD survival by univariate Cox analysis (P = 0.017), and the multivariate result was also significant (P = 0.021). Subgroup analysis suggested the prognostic value of SPP1 was significant in stage T1 (log rank P = 0.011), stage N0 (log rank P = 0.046) and stage N1 (log rank P = 0.009) patients. After including these markers into a nomogram, the Harrell's C-index of the nomogram was 0.694. In summary, our findings suggest that SPP1 is an independent biomarker with prognostic significance in LUAD.

Tumor suppressive microRNA-124a inhibits stemness and enhances gefitinib sensitivity of non-small cell lung cancer cells by targeting ubiquitin-specific protease 14

Increasing evidence has shown that microRNAs (miRNAs) play a significant functional role by directly regulating respective targets in cancer stem cell (CSC)-induced non-small cell lung cancer (NSCLC) progression and resistance to therapy. In this study, we found that hsa-miR-124a was downregulated during spheroid formation of the NSCLC cell lines SPC-A1 and NCI-H1650 and NSCLC tissues compared with normal lung cells and tissues. Patients with lower hsa-miR-124a expression had shorter overall survival (OS) and progression free survival (PFS). Moreover, ubiquitin-specific protease 14 (USP14) was confirmed to be a direct target of hsa-miR-124a. Furthermore, concomitant low hsa-miR-124a expression and high USP14 expression were correlated with a shorter median OS and PFS in NSCLC patients. Cellular functional analysis verified that the tumor suppressor hsa-miR-124a negatively regulated cell growth and self-renewal, and promoted apoptosis and gefitinib sensitivity of lung cancer stem cells by suppressing its target gene USP14. Our results provide the first evidence that USP14 is a direct target of hsa-miR-124a, and that hsa-miR-124a inhibits stemness and enhances the gefitinib sensitivity of NSCLC cells by targeting USP14. Thus, hsa-miR-124a and USP14 may be useful as tumor biomarkers for the diagnosis and treatment of NSCLC.

A new approach to predict lymph node metastasis in solid lung adenocarcinoma: a radiomics nomogram

Background

Lymph node metastasis (LNM) of lung cancer is an important factor related to survival and recurrence. The association between radiomics features of lung cancer and LNM remains unclear. We developed and validated a radiomics nomogram to predict LNM in solid lung adenocarcinoma.

Methods

A total of 159 eligible patients with solid lung adenocarcinoma were divided into training (n=106) and validation cohorts (n=53). Radiomics features were extracted from venous-phase CT images. We built a radiomics nomogram using a multivariate logistic regression model combined with CT-reported lymph node (LN) status. The performance of the radiomics nomogram was evaluated using the area under curve (AUC) of receiver operating characteristic curve. We performed decision curve analysis (DCA) within training and validation cohorts to assess the clinical usefulness of the nomogram.

Results

Fourteen radiomics features were chosen from 94 candidate features to build a radiomics signature that significantly correlated with LNM. The model showed good calibration and discrimination in the training cohort, with an AUC of 0.871 (95% CI: 0.804-0.937), sensitivity of 85.71% and specificity of 77.19%. In the validation cohort, AUC was 0.856 (95% CI: 0.745-0.966), sensitivity was 91.66%, and specificity was 82.14%. DCA demonstrated that the nomogram was clinically useful. The nomogram also showed good predictive ability in patients at high risk for LNM in the CT-reported LN negative (cN0) subgroup.

Conclusions

The radiomics nomogram, based on preoperative CT images, can be used as a noninvasive method to predict LNM in patients with solid lung adenocarcinoma.

Decoding the Emerging Patterns Exhibited in Non-coding RNAs Characteristic of Lung Cancer with Regard to their Clinical Significance

Lung cancer continues to be the leading topic concerning global mortality rate caused by can-cer; it needs to be further investigated to reduce these dramatic unfavorable statistic data. Non-coding RNAs (ncRNAs) have been shown to be important cellular regulatory factors and the alteration of their expression levels has become correlated to extensive number of pathologies. Specifically, their expres-sion profiles are correlated with development and progression of lung cancer, generating great interest for further investigation. This review focuses on the complex role of non-coding RNAs, namely miR-NAs, piwi-interacting RNAs, small nucleolar RNAs, long non-coding RNAs and circular RNAs in the process of developing novel biomarkers for diagnostic and prognostic factors that can then be utilized for personalized therapies toward this devastating disease. To support the concept of personalized medi-cine, we will focus on the roles of miRNAs in lung cancer tumorigenesis, their use as diagnostic and prognostic biomarkers and their application for patient therapy.

Differentially expressed and survival-related proteins of lung adenocarcinoma with bone metastasis

Despite recent advances in targeted and immune‐based therapies, the poor prognosis of lung adenocarcinoma (LUAD) with bone metastasis (BM) remains a challenge. First, two‐dimensional gel electrophoresis (2‐DE) was used to identify proteins that were differentially expressed in LUAD with BM, and then matrix‐assisted laser desorption/ionization time of flight mass spectrometry (MALDI‐TOF‐MS) was used to identify these proteins. Second, the Cancer Genome Atlas (TCGA) was used to identify mutations in these differentially expressed proteins and Kaplan–Meier plotter (KM Plotter) was used to generate survival curves for the analyzed cases. Immunohistochemistry (IHC) was used to check the expression of proteins in 28 patients with BM and nine patients with LUAD. Lastly, the results were analyzed with respect to clinical features and patient's follow‐up. We identified a number of matched proteins from 2‐DE. High expression of enolase 1 (ENO1) (HR = 1.67, logrank P = 1.9E‐05), ribosomal protein lateral stalk subunit P2 (RPLP2) (HR = 1.77, logrank P = 2.9e‐06), and NME/NM23 nucleoside diphosphate kinase 2 (NME1‐NME2) (HR = 2.65, logrank P = 3.9E‐15) was all significantly associated with poor survival (P < 0.05). Further, ENO1 was upregulated (P = 0.0004) and calcyphosine (CAPS1) was downregulated (P = 5.34E‐07) in TCGA LUAD RNA‐seq expression data. IHC revealed that prominent ENO1 staining (OR = 7.5, P = 0.034) and low levels of CAPS1 (OR = 0.01, P < 0.0001) staining were associated with BM incidence. Finally, we found that LUAD patients with high expression of ENO1 and RPLP2 had worse overall survival. This is the first instance where the genes ENO1, RPLP2, NME1‐NME2 and CAPS1 were associated with disease severity and progression in LUAD patients with BM. Thus, with this study, we have identified potential biomarkers and therapeutic targets for this disease.

MiR-1260b promotes the migration and invasion in non-small cell lung cancer via targeting PTPRK

OBJECTIVE

Non-small cell lung cancer (NSCLC) accounts for 80-85% of lung cancer cases which cause most of cancer-related deaths globally. As our previous study discovered miR-1260b can be regarded as a specific signature for metastasis in NSCLC patients. However, the molecular mechanisms of miR-1260b underlying NSCLC progression and metastasis remain dismal.

METHODS

The expression of miR-1260b in NSCLC tissues and cell lines were examined by real-time PCR, the effects of miR-1260b on cell migration, invasion and proliferation were evaluated in vitro. Furthermore, luciferase reporter assay was performed to identify the targets of miR-1260b, and the association between miR-1260b and its target gene was determined by real-time PCR and western blot assay.

RESULTS

The results showed that miR-1260b was significantly upregulated in NSCLC cell lines. The inhibition of miR-1260b expression decreased the migratory and invasive rates in A549 cells while miR-1260b overexpression had the opposite effect. Furthermore, PTPRK was identified as a direct target of miR-1260b, and PTPRK expression was inversely correlated with miR-1260b in NSCLC cell lines and clinical tissues.

CONCLUSIONS

These results suggested that miR-1260b may play an important role in NSCLC metastasis progression and could serve as a putative target for diagnosis and treatment of NSCLC.

MiR-31-5p-ACOX1 Axis Enhances Tumorigenic Fitness in Oral Squamous Cell Carcinoma Via the Promigratory Prostaglandin E2

During neoplastic development, a multitude of changes in genome-encoded information are progressively selected to confer growth and survival advantages to tumor cells. microRNAs-mRNAs regulatory networks, given their role as a critical layer of robust gene expression control, are frequently altered in neoplasm. However, whether and how these gene perturbations impact metabolic homeostasis remains largely unresolved.

Methods: Through targeted miRNA expression screening, we uncovered an oral squamous cell carcinoma (OSCC)-associated miRNAome, among which miR-31-5p was identified based on extent of up-regulation, functional impact on OSCC cell migration and invasion, and direct regulation of the rate-limiting enzyme in peroxisomal β-oxidation, ACOX1.

Results: We further found that both miR-31-5p and ACOX1 underpin, in an antagonistic manner, the overall cellular lipidome profiles as well as the migratory and invasive abilities of OSCC cells. Interestingly, the extracellular levels of prostaglandin E2 (PGE2), a key substrate of ACOX1, were controlled by the miR-31-5p-ACOX1 axis, and were shown to positively influence the extent of cell motility in correlation with metastatic status. The promigratory effect of this metabolite was mediated by an elevation in EP1-ERK-MMP9 signaling. Of note, functional significance of this regulatory pathway was further corroborated by its clinicopathologically-correlated expression in OSCC patient specimens.

Conclusions: Collectively, our findings outlined a model whereby misregulated miR-31-5p-ACOX1 axis in tumor alters lipid metabolomes, consequently eliciting an intracellular signaling change to enhance cell motility. Our clinical analysis also unveiled PGE2 as a viable salivary biomarker for prognosticating oral cancer progression, further underscoring the importance of lipid metabolism in tumorigenesis.

Prediction of potential drivers connecting different dysfunctional levels in lung adenocarcinoma via a protein-protein interaction network

Lung cancer is a serious disease that threatens an affected individual's life. Its pathogenesis has not yet to be fully described, thereby impeding the development of effective treatments and preventive measures. "Cancer driver" theory considers that tumor initiation can be associated with a number of specific mutations in genes called cancer driver genes. Four omics levels, namely, (1) methylation, (2) microRNA, (3) mutation, and (4) mRNA levels, are utilized to cluster cancer driver genes. In this study, the known dysfunctional genes of these four levels were used to identify novel driver genes of lung adenocarcinoma, a subtype of lung cancer. These genes could contribute to the initiation and progression of lung adenocarcinoma in at least two levels. First, random walk with restart algorithm was performed on a protein-protein interaction (PPI) network constructed with PPI information in STRING by using known dysfunctional genes as seed nodes for each level, thereby yielding four groups of possible genes. Second, these genes were further evaluated in a test strategy to exclude false positives and select the most important ones. Finally, after conducting an intersection operation in any two groups of genes, we obtained several inferred driver genes that contributed to the initiation of lung adenocarcinoma in at least two omics levels. Several genes from these groups could be confirmed according to recently published studies. The inferred genes reported in this study were also different from those described in a previous study, suggesting that they can be used as essential supplementary data for investigations on the initiation of lung adenocarcinoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Differential Expression of miRNAs in the Respiratory Tree of the Sea Cucumber Apostichopus japonicus Under Hypoxia Stress

The sea cucumber, an important economic species, has encountered high mortality since 2013 in northern China because of seasonal environmental stress such as hypoxia, high temperature, and low salinity. MicroRNAs (miRNAs) are important in regulating gene expression in marine organisms in response to environmental change. In this study, high-throughput sequencing was used to investigate alterations in miRNA expression in the sea cucumber under different levels of dissolved oxygen (DO). Nine small RNA libraries were constructed from the sea cucumber respiratory trees. A total of 26 differentially expressed miRNAs, including 12 upregulated and 14 downregulated miRNAs, were observed in severe hypoxia (DO 2 mg/L) compared with mild hypoxia (DO 4 mg/L) and normoxic conditions (DO 8 mg/L). Twelve differentially expressed miRNAs were clustered in severe hypoxia. In addition, real-time PCR revealed that 14 randomly selected differentially expressed miRNAs showed significantly increased expressions in severe hypoxia and the expressions of nine miRNAs, including key miRNAs such as Aja-miR-1, Aja-miR-2008, and Aja-miR-184, were consistent with the sequencing results. Moreover, gene ontology and pathway analyses of putative target genes suggest that these miRNAs are important in redox, transport, transcription, and hydrolysis under hypoxia stress. Notably, novel-miR-1, novel-miR-2, and novel-miR-3 were specifically clustered and upregulated in severe hypoxia, which may provide new insights into novel “hypoxamiR” identification. These results will provide a basis for future studies of miRNA regulation and molecular adaptive mechanisms in sea cucumbers under hypoxia stress.

miR-31 Functions as an Oncomir Which Promotes Epithelial-Mesenchymal Transition via Regulating BAP1 in Cervical Cancer

MicroRNA-31 (miR-31) functions as tumor suppressors or oncogenes that are involved in tumor behavior. However, the function of miR-31 in cervical carcinogenesis remains unclear. The aim of this study was to validate the potential role of miR-31 and BRCA1-associated protein-1 (BAP1) on regulating epithelial-mesenchymal transition (EMT) in cervical cancer. In the present study, qRT-PCR assay revealed that the expression of miR-31 was upregulated in human cervical cancer cells and clinical tissues. Results of wound healing and cell migration assay revealed that knockdown of miR-31 inhibited cell metastasis and migration. Bioinformatic and dual-luciferase reporter gene assay showed that BAP1 was the direct target of miR-31. Furthermore, the results revealed that miR-31 promoted proliferation and EMT in cervical cancer cells and accelerated the development of tumor growth in vivo xenograft experiment by inhibiting BAP1 expression. Overall, these results highlight an important role of miR-31 functioning as an oncomir which could promote EMT in cervical cancer via downregulating BAP1 expression. Thus, downregulation of miR-31 could be a novel approach for the molecular treatment of cervical cancers and other malignancies.

miR-181c contributes to cisplatin resistance in non-small cell lung cancer cells by targeting Wnt inhibition factor 1

PURPOSE

miRNAs are implicated in drug resistance of multiple cancers including non-small cell lung cancer (NSCLC), highlighting the potential of miRNAs as chemoresistance regulators in cancer treatment. This study aims to explore the relationship between miR-181c and chemoresistance of NSCLC cells.

METHODS

qRT-PCR was conducted to examine the expression of miR-181c in NSCLC tissues, and parental and cisplatin (DDP)-resistant NSCLC cells. MTT assay and flow cytometry were performed to detect the survival rate and apoptosis in NSCLC cells. Luciferase reporter assay was performed to confirm the potential target of miR-181c. Xenograft tumor experiment was applied to confirm the effect of miR-181c on DDP sensitivity of DDP-resistant NSCLC cells in vivo.

RESULTS

miR-181c was upregulated in NSCLC tissues, and parental and DDP-resistant NSCLC cells. miR-181c downregulation or WIF1 overexpression increased DDP sensitivity of DDP-resistant NSCLC cells by decreasing survival rate and promoting DDP-induced apoptosis. miR-181c was demonstrated to be able to bind to WIF1 and negatively regulate the expression of WIF1. WIF1 knockdown abolished anti-miR-181c-induced DDP sensitivity. Moreover, anti-miR-181c suppressed the Wnt/β-catenin pathway by regulating WIF1. XAV939 treatment reversed miR-181c-induced increase in IC50 value and miR-181c-triggered decrease in apoptosis. Finally, anti-miR-181c improved DDP sensitivity of DDP-resistant NSCLC cells in vivo.

CONCLUSION

miR-181c contributed to DDP resistance in NSCLC cells through activation of the Wnt/β-catenin pathway by targeting WIF1, providing a potential therapeutic application for the treatment of patients with DDP-resistant NSCLC in the future.

miR-124 Inhibits Lung Tumorigenesis Induced by K-ras Mutation and NNK

Dysregulated miRNAs play important role in K-ras mutation or smoking caused lung tumorigenesis. Here, we investigate the role and mechanism of miR-124 in K-ras mutation or smoking-caused lung tumorigenesis and evaluate the therapeutic potential of miR-124 agomiR in K-ras mutation or smoking-caused lung cancer treatment. Our data show that smoking suppresses miR-124 expression, and decreased miR-124 expression is inversely correlated with the p-Akt level and predicts poor overall survival in non-small-cell lung cancer (NSCLC) patients. The overexpression of miR-124 suppressed NSCLC growth by inhibiting the Akt pathway by targeting Akt1 and Akt2. In addition, the systemic delivery of miR-124 agomiR dramatically suppressed tumorigenesis in both NNK-induced lung cancer model and K-ras^LA1 transgenic mice by increasing apoptosis and inhibiting cell proliferation. Our findings suggest that smoking inhibits the expression of miR-124, and decreased miR-124 contributes to Akt activation, thereby promoting NSCLC progression. Our findings also represent a novel potential therapeutic strategy for lung cancer.

MicroRNA-125a-3p downregulation correlates with tumorigenesis and poor prognosis in patients with non-small cell lung cancer

MicroRNA (miR)-125a-3p is derived from the 3'-end of pre-miR-125a, which is associated with several types of cancer, such as gastric and prostate cancer, and glioma. The aim of the present study was to identify the prognostic significance of miR-125a-3p expression levels in patients with NSCLC. The gene expression omnibus database was used to analyze miR-125a-3p expression in NSCLC in silico, and 148 NSCLC samples and 30 adjacent normal lung tissue specimens were analyzed for the expression of miR-125a-3p by qPCR. The results showed that the expression levels of miR-125a-3p in the adjacent normal tissues was higher than the expression level in the NSCLC tissues. There were several clinical parameters demonstrated to be associated with miR-125a-3p expression, such as lymph node metastasis, tumor node metastasis classification of malignant tumor stage and tumor diameter. Furthermore, high expression levels of miR-125a-3p with chemotherapy prolonged the overall survival rate and disease free survival rate compared with untreated patients with low expression of miR-125a-3p. Thus, miR-125a-3p is a significant prognostic biomarker for patients with NSCLC, from which a novel therapeutic strategy to combat NSCLC may be derived.

Comprehensive analysis of aberrantly expressed microRNA profiles reveals potential biomarkers of human lung adenocarcinoma progression

Lung adenocarcinoma (LUAD) is a complex disease that poses challenges for diagnosis and treatment. The aim of the present study is to investigate LUAD-specific key microRNAs (miRNAs) from large-scale samples in The Cancer Genome Atlas (TCGA) database. We used an integrative computational method to identify LUAD-specific key miRNAs related to TNM stage and lymphatic metastasis from the TCGA database. Twenty-five LUAD-specific key miRNAs (fold change >2, p<0.05) from the TCGA database were investigated, and 15 were found to be aberrantly expressed with respect to clinical features. Three miRNAs were correlated with overall survival (log-rank p<0.05). Then, 5 miRNAs were randomly selected for verification of expression in 53 LUAD patient tissues using qRT-PCR. Diagnostic value of these above 5 miRNAs was determined by areas under receiver operating characteristic curves (ROC). Finally, the LUAD-related miRNA miR-30a-3p was selected for verification of biologic function in A549 cells. The results of tests for cell proliferation, apoptosis, and target genes suggested that miR-30a-3p decreases cell proliferation and promotes apoptosis through targeting AKT3. Therefore, miR-30a-3p may be a promising biomarker for the early screening of high-risk populations and early diagnosis of LUAD. Our studies provide insights into identifying novel potential biomarkers for diagnosis and prognosis of LUAD.

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.

MicroRNA profiling associated with non-small cell lung cancer: next generation sequencing detection, experimental validation, and prognostic value

Background

The average five-year survival for non-small cell lung cancer (NSCLC) patients is approximately 15%. Emerging evidence indicates that microRNAs (miRNAs) constitute a new class of gene regulators in humans that may play an important role in tumorigenesis. Hence, there is growing interest in studying their role as possible new biomarkers whose expression is aberrant in cancer. Therefore, in this study we identified dysregulated miRNAs by next generation sequencing (NGS) and analyzed their prognostic value.

Methods

Sequencing by oligo ligation detection technology was used to identify dysregulated miRNAs in a training cohort comprising paired tumor/normal tissue samples (N = 32). We validated 22 randomly selected differentially-expressed miRNAs by quantitative real time PCR in tumor and adjacent normal tissue samples (N = 178). Kaplan-Meier survival analysis and Cox regression were used in multivariate analysis to identify independent prognostic biomarkers.

Results

NGS analysis revealed that 39 miRNAs were dysregulated in NSCLC: 28 were upregulated and 11 were downregulated. Twenty-two miRNAs were validated in an independent cohort. Interestingly, the group of patients with high expression of both miRNAs (miR-21^high and miR-188^high) showed shorter relapse-free survival (RFS) and overall survival (OS) times. Multivariate analysis confirmed that this combined signature is an independent prognostic marker for RFS and OS (p = 0.001 and p < 0.0001, respectively).

Conclusions

NGS technology can specifically identify dysregulated miRNA profiles in resectable NSCLC samples. MiR-21 or miR-188 overexpression correlated with a negative prognosis, and their combined signature may represent a new independent prognostic biomarker for RFS and OS.

Identification of miR‑124a as a novel diagnostic and prognostic biomarker in non‑small cell lung cancer for chemotherapy

Previous studies have suggested that dysregulation of microRNA (miR) −124a is associated with various types of human cancer. However, there are few studies reporting the level of miR-124a expression in non-small cell lung cancer (NSCLC). The present study investigated the association between miR-124a and NSCLC by analyzing the differential expression of miR-124a in NSCLC using the GEO database, as well as subsequently performing reverse transcription-quantitative polymerase chain reaction analysis on 160 NSCLC biopsies, 32 of which were paired with adjacent normal tissues. The results indicated that mir-124a expression levels were decreased in NSCLC tumor biopsies compared with adjacent normal tissues. The overall survival (OS) in patients with a high expression of miR-124a was prolonged relative to patients with low expression of miR-124a. The expression levels of miR-124a were associated with clinical characteristics, including lymph-node metastasis, tumor differentiation, tumor node metastasis (TNM) stage and diameter. Frequently, lymph-node metastasis, TNM stage, diameter and lack of chemotherapy have been associated with a worse prognosis in patients. In addition, the present study identified that high expression of miR-124awith chemotherapy may increase OS. In conclusion, the current study demonstrated that miR-124a was downregulated in NSCLC, and miR-124a was a potential prognostic tumor biomarker response to chemotherapy.

Expression of circulating miRNAs associated with lymphocyte differentiation and activation in CLL-another piece in the puzzle

Expression of microRNAs is altered in cancer. Circulating miRNA level assessed in body fluids commonly reflects their expression in tumor cells. In leukemias, however, both leukemic and nonleukemic cells compose circulating miRNA expression profile of peripheral blood. The latter contribution to extracellular miRNA pool may result in specific microenvironmental signaling, which promotes proliferation and survival. In our study, we used qT-PCR to assay peripheral blood serum of 22 chronic lymphocytic leukemia (CLL) patients for the expression of 84 miRNAs associated with activation and differentiation of B and T lymphocytes. Results were analyzed regarding the most important prognostic factors. We have found that the general expression of examined miRNAs in CLL patients was lower as compared to healthy volunteers. Only miR-34a-5p, miR31-5p, miR-155-5p, miR-150-5p, miR-15a-3p, and miR-29a-3p were expressed on a higher level. Alterations of expression observed in CLL patients involved miRNAs associated both with B and T lymphocyte differentiation and activation. The most important discriminating factors for all functional miRNA groups were trisomy 12, CD38 expression, B2M level, WBC, and NOTCH1 gene mutation. Correlation of expression of miRNAs related to T lymphocytes with prognostic factors proves their supportive function in a leukemic microenvironment. Further studies utilizing a larger test group of patients may warrant the identification of circulating miRNAs that are key players in intercellular interactions and should be considered in the design of microenvironment-targeted therapies.

A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma

We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2 %, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5 %, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95 % CI, 5.110–27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.

The Novel miR-9600 Suppresses Tumor Progression and Promotes Paclitaxel Sensitivity in Non-small-cell Lung Cancer Through Altering STAT3 Expression

MicroRNAs have been identified to be involved in center stage of cancer biology. They accommodate cell proliferation and migration by negatively regulate gene expression either by hampering the translation of targeted mRNAs or by promoting their degradation. We characterized and identified the novel miR-9600 and its target in human non-small-cell lung cancer (NSCLC). Our results demonstrated that the miR-9600 were downregulated in NSCLC tissues and cells. It is confirmed that signal transducer and activator of transcription 3 (STAT3), a putative target gene, is directly inhibited by miR-9600. The miR-9600 markedly suppressed the protein expression of STAT3, but with no significant influence in corresponding mRNA levels, and the direct combination of miR-9600 and STAT3 was confirmed by a luciferase reporter assay. miR-9600 inhibited cell growth, hampered expression of cell cycle-related proteins and inhibited cell migration and invasion in human NSCLC cell lines. Further, miR-9600 significantly suppressed tumor growth in nude mice. Similarly, miR-9600 impeded tumorigenesis and metastasis through directly targeting STAT3. Furthermore, we identified that miR-9600 augmented paclitaxel and cisplatin sensitivity by downregulating STAT3 and promoting chemotherapy-induced apoptosis. These data demonstrate that miR-9600 might be a useful and novel therapeutic target for NSCLC.

Identification of lymph node metastasis-related microRNAs in lung adenocarcinoma and analysis of the underlying mechanisms using a bioinformatics approach

This study aimed to screen lymphatic metastasis-related microRNAs (miRNAs) in lung adenocarcinoma and explore their underlying mechanisms using bioinformatics. The miRNA expression in primary lung adenocarcinoma, matched adjacent non-tumorigenic and lymph node metastasis tissues of patients were profiled via microarray. The screened metastasis-related miRNAs were then validated using quantitative real-time PCR in a second cohort of lung adenocarcinoma patients with lymphatic metastasis. Significance was determined using a paired t-test. Target genes of the metastasis-related miRNAs were predicted using TargetScan, and transcription factors (TFs) were predicted based on the TRANSFAC and ENCODE databases. Furthermore, the related long non-coding RNAs (lncRNAs) were screened with starBase v2.0. The miRNA-TF-mRNA and lncRNA-miRNA-mRNA networks were constructed to determine the key interactions associated with lung adenocarcinoma metastasis. According to the miRNA microarray results, there were 10 miRNAs that were differentially expressed in metastatic tissues compared with primary tumor and adjacent non-tumorigenic tissues. Among them were increased levels of miR-146a-5p, miR-342-3p, and miR-150-5p, which were validated in the second cohort. Based on the miRNA-TF-mRNA network, vascular endothelial growth factor A and transcription factors (TFs) including TP53, SMAD4, and EP300 were recognized as critical targets of the three miRNAs. Interactions involving SNHG16-miR-146a-5p-SMAD4 and RP6-24A23.7-miR-342-3p/miR-150-5p-EP300 were highlighted according to the lncRNA-miRNA-mRNA network. miR-146a-5p, miR-342-3p, and miR-150-5p are lymphatic metastasis-related miRNAs in lung adenocarcinoma. Bioinformatics analyses demonstrated that SNHG16 might inhibit the interaction between miR-146a-5p and SMAD4, while RP6-24A23.7 might weaken miR-342-3p-EP300 and miR-150-5p-EP300 interactions in metastasis.

The transcriptome of lung tumor-infiltrating dendritic cells reveals a tumor-supporting phenotype and a microRNA signature with negative impact on clinical outcome

Targeting immunomodulatory pathways has ushered a new era in lung cancer therapy. Further progress requires deeper insights into the biology of immune cells in the lung cancer micro-environment.

Dendritic cells (DCs) represent a heterogeneous and highly plastic immune cell system with a central role in controlling immune responses. The intratumoral infiltration and activation status of DCs are emerging as clinically relevant parameters in lung cancer.

In this study, we used an orthotopic preclinical model of lung cancer to dissect how the lung tumor micro-environment affects tissue-resident DCs and extract novel biologically and clinically relevant information.

Lung tumor-infiltrating leukocytes expressing generic DC markers were found to predominantly consist of CD11b⁺ cells that, compare with peritumoral lung DC counterparts, strongly overexpress the T-cell inhibitory molecule PD-L1 and acquire classical surface markers of tumor-associated macrophages (TAMs). Transcriptome analysis of these CD11b⁺ tumor-infiltrating DCs (TIDCs) indicates impaired antitumoral immunogenicity, confirms the skewing toward TAM-related features, and indicates exposure to a hypoxic environment. In parallel, TIDCs display a specific microRNA (miRNA) signature dominated by the prototypical lung cancer oncomir miR-31. In vitro, hypoxia drives intrinsic miR-31 expression in CD11b⁺ DCs. Conditioned medium of miR-31 overexpressing CD11b⁺ DCs induces pro-invasive lung cancer cell shape changes and is enriched with pro-metastatic soluble factors. Finally, analysis of TCGA datasets reveals that the TIDC-associated miRNA signature has a negative prognostic impact in non-small cell lung cancer.

Together, these data suggest a novel mechanism through which the lung cancer micro-environment exploits the plasticity of the DC system to support tumoral progression.