Applications of MicroRNAs in the Diagnosis and Prognosis of Lung Cancer

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.

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.

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

We propose to systematically identify a non-coding RNA (ncRNA) profile of exfoliated bronchial epitheliums of sputum from lung cancer patients. Bronchial epithelial cells enriched from sputum of 32 lung cancer patients and 33 cancer-free smokers were analyzed by next-generation sequencing to comprehensively characterize the ncRNA profiles. In addition, 108 miRNAs, 88 small nucleolar RNAs, 13 piwi-interacting RNAs, 6 transfer RNAs, 4 ribosomal RNAs, 19 small nuclear RNAs, and 25 long-noncoding (lnc) RNAs displayed a significantly different level in bronchial epitheliums of sputum of lung cancer patients versus cancer-free smokers (all <0.001). PCR analysis confirmed their different expression levels in the sputum specimens. A high expression of SNHG9, an lncRNA, was validated in 78 lung tumor tissues, and the expression was inversely associated with overall survival of lung cancer patients (p = 0.002). Knockdown of SNHG9 in cancer cells reduced the cell growth, proliferation, and invasion in vitro and tumorigenesis in vivo. The multiple differentially expressed ncRNAs in bronchial epitheliums may contribute to the development and progression of lung cancer and provide potential biomarkers and therapeutic targets for the disease.

Cluster miRNAs and cancer: Diagnostic, prognostic and therapeutic opportunities

MiRNAs are class of noncoding RNA important for gene expression regulation in many plants, animals and viruses. MiRNA clusters contain a set of two or more miRNA encoding genes, transcribed together as polycistronic miRNAs. Currently, there are approximately 159 miRNA clusters reported in the human genome consisting of miRNAs ranging from two or more miRNA genes. A large proportion of clustered miRNAs resides in and around the fragile sites or cancer associated genomic hotspots and plays an important role in carcinogenesis. Altered expression of miRNA cluster can be pro-tumorigenic or anti-tumorigenic and can be targeted for clinical management of cancer. Over the past few years, manipulation of miRNA clusters expression is attempted for experimental purpose as well as for diagnostic, prognostic and therapeutic applications in cancer. Re-expression of miRNAs by epigenetic therapy, genome editing such as clustered regulatory interspaced short palindromic repeats (CRISPR) and miRNA mowers showed promising results in cancer therapy. In this review, we focused on the potential of miRNA clusters as a biomarker for diagnosis, prognosis, targeted therapy as well as strategies for modulating their expression in a therapeutic context. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Processing > Processing of Small RNAs RNA in Disease and Development > RNA in Disease Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

MicroRNA in lung cancer: role, mechanisms, pathways and therapeutic relevance

Lung cancer is the cardinal cause of cancer-related deaths with restricted recourse of therapy throughout the world. Clinical success of therapies is not very promising due to - late diagnosis, limited therapeutic tools, relapse and the development of drug resistance. Recently, small ∼20-24 nucleotides molecules called microRNAs (miRNAs) have come into the limelight as they play outstanding role in the process of tumorigenesis by regulating cell cycle, metastasis, angiogenesis, metabolism and apoptosis. miRNAs essentially regulate gene expression via post-transcriptional regulation of mRNA. Nevertheless, few studies have conceded the role of miRNAs in activation of gene expression. A large body of data generated by numerous studies is suggestive of their tumor-suppressing, oncogenic, diagnostic and prognostic biomarker roles in lung cancer. They have also been implicated in regulating cancer cell metabolism and resistance or sensitivity towards chemotherapy and radiotherapy. Further, miRNAs have also been convoluted in regulation of immune checkpoints - Programmed death 1 (PD-1) and its ligand (PD-L1). These molecules play a significant role in tumor immune escape leading to the generation of a microenvironment favouring tumor growth and progression. Therefore, it is imperative to explore the expression of miRNA and understand its relevance in lung cancer and development of anti-cancer strategies (anti - miRs, miR mimics and micro RNA sponges). In view of the above, the role of miRNA in lung cancer has been dissected and the associated mechanisms and pathways are discussed in this review.

A Plasma Long Noncoding RNA Signature for Early Detection of Lung Cancer

The early detection of lung cancer is a major clinical challenge. Long noncoding RNAs (lncRNAs) have important functions in tumorigenesis. Plasma lncRNAs directly released from primary tumors or the circulating cancer cells might provide cell-free cancer biomarkers. The objective of this study was to investigate whether the lncRNAs could be used as plasma biomarkers for early-stage lung cancer. By using droplet digital polymerase chain reaction, we determined the diagnostic performance of 26 lung cancer–associated lncRNAs in plasma of a development cohort of 63 lung cancer patients and 33 cancer-free individuals, and a validation cohort of 39 lung cancer patients and 28 controls. In the development cohort, 7 of the 26 lncRNAs were reliably measured in plasma. Two (SNHG1 and RMRP) displayed a considerably high plasma level in lung cancer patients vs. cancer-free controls (all P < .001). Combined use of the plasma lncRNAs as a biomarker signature produced 84.13% sensitivity and 87.88% specificity for diagnosis of lung cancer, independent of stage and histological type of lung tumor, and patients' age and sex (all P > .05). The diagnostic value of the plasma lncRNA signature for lung cancer early detection was confirmed in the validation cohort. The plasma lncRNA signature may provide a potential blood-based assay for diagnosing lung cancer at the early stage. Nevertheless, a prospective study is warranted to validate its clinical value.

A Direct Plasma miRNA Assay for Early Detection and Histological Classification of Lung Cancer

Cell-free microRNAs in plasma provide circulating biomarkers for lung cancer. Most techniques for analysis of miRNAs require a large plasma volume to purify a sufficient RNA yield followed by complicated downstream processing. Small differences in the multiple procedures often cause large analytical variations and poor diagnostic values of the plasma biomarkers. Here we investigate whether directly quantifying plasma miRNAs without RNA purification could diagnose lung cancer. FirePlex assay was directly applied to 20 μl plasma of 56 lung cancer patients and 28 cancer free controls for quantifying 11 lung tumor–associated miRNAs. FirePlex assay is easier, less expensive and time-consuming for quantification of plasma miRNAs compared with conventional reverse transcription PCR with an equivalent analytic performance. From the lung tumor–associated miRNAs, a prediction model based on two miRNAs (miRs-205-5p and -210-3p) was developed, producing 78.6% sensitivity and 89.3% specificity for identifying lung cancer. The diagnostic value was independent of stage of lung tumor, and patients’ age and sex (all P > 0.05). Furthermore, based on the same two miRNAs, additional prediction models were developed with 75.0% sensitivity and 89.3% specificity for diagnosis of lung squamous cell carcinoma, and 82.2% sensitivity and 89.3% specificity for lung adenocarcinoma. The direct plasma assay can improve the efficacy of miRNA assessment in a small plasma volume by reducing multiple procedure-associated analytical variables. The developed plasma miRNA biomarkers might be useful for the early detection and histological classification of lung cancer.

An integromic signature for lung cancer early detection

We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not sufficient to be used in the clinics. Given the heterogeneity of lung tumors developed from multifactorial molecular aberrations, we determine whether integrating the different classes of molecular biomarkers can improve diagnosis of lung cancer. By using droplet digital PCR, we analyze expression of the seven genes in plasma of a development cohort of 64 lung cancer patients and 33 cancer-free individuals. The panels of three miRNAs (miRs-21, 210, and 486-5p), two lncRNAs (SNHG1 and RMRP), and two FUTs (FUT8 and POFUT1) have a sensitivity of 81-86% and a specificity of 84-87% for diagnosis of lung cancer. From the seven genes, an integromic plasma signature comprising miR-210, SNHG1, and FUT8 is developed that produces higher sensitivity (95.45%) and specificity (96.97%) compared with the individual biomarker panels (all p<0.05). The diagnostic value of the signature was confirmed in a validation cohort of 40 lung cancer patients and 29 controls, independent of stage and histological type of lung tumor, and patients' age, sex, and smoking status (all p>0.05). The integration of the different categories of biomarkers might improve diagnosis of lung cancer.

Methylation-regulated miR-124-1 suppresses tumorigenesis in hepatocellular carcinoma by targeting CASC3

This study was to investigate the roles and mechanisms of miR-124-1 in hepatocellular carcinoma (HCC). We analyzed the expression of miR-124-1 in human HCC tissues and cell lines. Luciferase reporter assays were used to analyze the target of miR-124-1. Human HCC cell lines were transduced with lentiviruses expressing miR-124-1, and proliferation and colony formation were analyzed. The growth of human HCC cells overexpressing miR-124-1 was assessed in nude mice. The expression of p38-MAPK, JNK, ERK and related signaling molecules was detected by western blotting and immunohistochemistry. Our results showed that miR-124-1 levels were reduced in HCC tissues and cell lines compared with those in adjacent non-cancer tissues and normal liver cell lines respectively. Downregulation of miR-124-1 in HCC cell lines were attributed to hypermethylation of its promoter region. Overexpression of miR-124-1 inhibited HCC cell proliferation in vitro, whereas miR-124-1 was correlated with clinicopathological parameters of HCC patients. HCC cell-mediated overexpression of miR-124-1 in nude mice suppressed tumor growth. Cancer susceptibility candidate 3 (CASC3) was identified as a direct target of miR-124-1 by computational analysis and experimental assays. MiR-124-1-mediated downregulation of CASC3 resulted in the inactivation of p38-MAPK, JNK and ERK. Our findings provide potential new targets for the prevention or treatment of HCC.

MicroRNA-630 may confer favorable cisplatin-based chemotherapy and clinical outcomes in non-small cell lung cancer by targeting Bcl-2

MicroRNA-630 (miR-630) plays dual roles in tumor progression in various human cancers. However, the role of miR-630 in chemoresistance and prognosis in non-small cell lung cancer (NSCLC) remains to be elucidated. This retrospective study enrolled 114 surgically resected patients with NSCLC who experienced tumor relapse and underwent cisplatin-based chemotherapy. The aim was to examine the possible association between miR-630 (and its targeting of Bcl-2 expression) and the response to cisplatin-based chemotherapy. Patients with tumors expressing low miR-630, high Bcl-2, and a combination of both were more likely than their counterparts to show unfavorable responses to cisplatin-based chemotherapy. Kaplan–Meier and Cox regression analysis indicated that low miR-630, high Bcl-2, and a combination of both may independently predict poor overall survival and short relapse-free survival in patients with NSCLC. Six types of NSCLC cells were collected to determine the inhibitory concentration of cisplatin yielding 50% viability (IC50) by the MTT assay. The IC50 value for cisplatin was negatively correlated with miR-630 expression levels among these cell types, except for A549 cells. Mechanistically, low miR-630 expression conferred cisplatin resistance and colony formation by de-targeting Bcl-2 in NSCLC cells. We therefore suggest that low miR-630, high Bcl-2, and a combination of both may potentially predict an unfavorable chemotherapeutic response and poor outcome in patients with NSCLC.

Emerging Technologies for Cancer Research: Towards Personalized Medicine with Microfluidic Platforms and 3D Tumor Models

In the present review, we describe three hot topics in cancer research such as circulating tumor cells, exosomes, and 3D environment models. The first section is dedicated to microfluidic platforms for detecting circulating tumor cells, including both affinity-based methods that take advantage of antibodies and aptamers, and "label-free" approaches, exploiting cancer cells physical features and, more recently, abnormal cancer metabolism. In the second section, we briefly describe the biology of exosomes and their role in cancer, as well as conventional techniques for their isolation and innovative microfluidic platforms. In the third section, the importance of tumor microenvironment is highlighted, along with techniques for modeling it in vitro. Finally, we discuss limitations of two-dimensional monolayer methods and describe advantages and disadvantages of different three-dimensional tumor systems for cell-cell interaction analysis and their potential applications in cancer management.

A plasma miRNA signature for lung cancer early detection

The early detection of lung cancer continues to be a major clinical challenge. Using whole-transcriptome next-generation sequencing to analyze lung tumor and the matched noncancerous tissues, we previously identified 54 lung cancer-associated microRNAs (miRNAs). The objective of this study was to investigate whether the miRNAs could be used as plasma biomarkers for lung cancer. We determined expressions of the lung tumor-miRNAs in plasma of a development cohort of 180 subjects by using reverse transcription PCR to develop biomarkers. The development cohort included 92 lung cancer patients and 88 cancer-free smokers. We validated the biomarkers in a validation cohort of 64 individuals comprising 34 lung cancer patients and 30 cancer-free smokers. Of the 54 miRNAs, 30 displayed a significant different expression level in plasma of the lung cancer patients vs. cancer-free controls (all P < 0.05). A plasma miRNA signature (miRs-126, 145, 210, and 205-5p) with the best prediction was developed, producing 91.5% sensitivity and 96.2% specificity for lung cancer detection. Diagnostic performance of the plasma miRNA signature had no association with stage and histological type of lung tumor, and patients' age, sex, and ethnicity (all p > 0.05). The plasma miRNA signature was reproducibly confirmed in the validation cohort. The plasma miRNA signature may provide a blood-based assay for diagnosing lung cancer at the early stage, and thereby reduce the associated mortality and cost.

A classifier integrating plasma biomarkers and radiological characteristics for distinguishing malignant from benign pulmonary nodules

Lung cancer is primarily caused by cigarette smoking and the leading cancer killer in the USA and across the world. Early detection of lung cancer by low-dose CT (LDCT) can reduce the mortality. However, LDCT dramatically increases the number of indeterminate pulmonary nodules (PNs), leading to overdiagnosis. Having a definitive preoperative diagnosis of malignant PNs is clinically important. Using microarray and droplet digital PCR to directly profile plasma miRNA expressions of 135 patients with PNs, we identified 11 plasma miRNAs that displayed a significant difference between patients with malignant versus benign PNs. Using multivariate logistic regression analysis of the molecular results and clinical/radiological characteristics, we developed an integrated classifier comprising two miRNA biomarkers and one radiological characteristic for distinguishing malignant from benign PNs. The classifier had 89.9% sensitivity and 90.9% specificity, being significantly higher compared with the biomarkers or clinical/radiological characteristics alone (all p < 0.05). The classifier was validated in two independent sets of patients. We have for the first time shown that the integration of plasma biomarkers and radiological characteristics could more accurately identify lung cancer among indeterminate PNs. Future use of the classifier could spare individuals with benign growths from the harmful diagnostic procedures, while allowing effective treatments to be immediately initiated for lung cancer, thereby reduces the mortality and cost. Nevertheless, further prospective validation of this classifier is warranted.

miRNA‑1284 inhibits cell growth and induces apoptosis of lung cancer cells

Lung cancer is the most common cancer worldwide, and morbidity and mortality associated with lung cancer has been increasing annually in recent decades. MicroRNAs (miRNAs), which are short non-coding RNA sequences that are involved in the regulation of gene expression, have been previously demonstrated to be key regulators in cancer. The present study aimed to clarify the role of miRNA (miR)-1284 in lung cancer. A549 lung carcinoma cells were transfected with miR-1284 mimic or miR-1284 inhibitor using Lipofectamine 2000. Subsequently, cell viability, growth and apoptosis of A459 cells in the miR-1284 mimic, miR-1284 inhibitor and control groups were assayed by MTT assay, bromodeoxyuridine assay and flow cytometry, respectively. Furthermore, the protein expression levels of p27, p21, Bax, pro-caspase-3, activated caspase-3 and Myc were detected by western blot analysis to investigate the molecular mechanisms underlying the effect of miR-1284 on A549 cells. The cell viability and growth of A549 cells were significantly decreased in the miR-1284 mimic group compared with the control group, whereas the percentage of apoptotic cells was significantly increased. By contrast, miR-1284 inhibitor transfection significantly increased the cell viability and growth compared with control, and decreased apoptosis. Furthermore, expression of p27 was increased in miR-1284 mimic-transfected A549 cells compared with the control group, whereas p21 was unaffected by miR-1284 overexpression or inhibition. The expression of Myc was decreased by miR-1284 mimic transfection compared with the control group. For the other apoptosis-associated proteins that were investigated (Bax, pro-caspase-3 and active caspase-3), the expression levels in the miR-1284 mimic transfected cells were higher than in the other two groups (control and miR-1284 inhibitor). In conclusion, the results suggest that miR-1284 affects cell proliferation and apoptosis of lung cancer cells, indicating that miR-1284 may have a key role in lung tumorigenesis.

Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC

Advances in molecular analyses based on high-throughput technologies can contribute to a more accurate classification of non-small cell lung cancer (NSCLC), as well as a better prediction of both the disease course and the efficacy of targeted therapies. Here we set out to analyze whether global gene expression profiling performed in a group of early-stage NSCLC patients can contribute to classifying tumor subtypes and predicting the disease prognosis. Gene expression profiling was performed with the use of the microarray technology in a training set of 108 NSCLC samples. Subsequently, the recorded findings were validated further in an independent cohort of 44 samples. We demonstrated that the specific gene patterns differed significantly between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) samples. Furthermore, we developed and validated a novel 53-gene signature distinguishing SCC from AC with 93% accuracy. Evaluation of the classifier performance in the validation set showed that our predictor classified the AC patients with 100% sensitivity and 88% specificity. We revealed that gene expression patterns observed in the early stages of NSCLC may help elucidate the histological distinctions of tumors through identification of different gene-mediated biological processes involved in the pathogenesis of histologically distinct tumors. However, we showed here that the gene expression profiles did not provide additional value in predicting the progression status of the early-stage NSCLC. Nevertheless, the gene expression signature analysis enabled us to perform a reliable subclassification of NSCLC tumors, and it can therefore become a useful diagnostic tool for a more accurate selection of patients for targeted therapies.

A prediction model for distinguishing lung squamous cell carcinoma from adenocarcinoma

Accurate classification of squamous cell carcinoma (SCC) from adenocarcinoma (AC) of non–small cell lung cancer (NSCLC) can lead to personalized treatments of lung cancer. We aimed to develop a miRNA-based prediction model for differentiating SCC from AC in surgical resected tissues and bronchoalveolar lavage (BAL) samples. Expression levels of seven histological subtype-associated miRNAs were determined in 128 snap-frozen surgical lung tumor specimens by using reverse transcription-polymerase chain reaction (RT-PCR) to develop an optimal panel of miRNAs for acutely distinguishing SCC from AC. The biomarkers were validated in an independent cohort of 112 FFPE lung tumor tissues, and a cohort of 127 BAL specimens by using droplet digital PCR for differentiating SCC from AC. A prediction model with two miRNAs (miRs-205-5p and 944) was developed that had 0.988 area under the curve (AUC) with 96.55% sensitivity and 96.43% specificity for differentiating SCC from AC in frozen tissues, and 0.997 AUC with 96.43% sensitivity and 96.43% specificity in FFPE specimens. The diagnostic performance of the prediction model was reproducibly validated in BAL specimens for distinguishing SCC from AC with a higher accuracy compared with cytology (95.69 vs. 68.10%; P < 0.05). The prediction model might have a clinical value for accurately discriminating SCC from AC in both surgical lung tumor tissues and liquid cytological specimens.

Detection of microRNAs Using Chip-Based QuantStudio 3D Digital PCR

Digital PCR (dPCR) is an innovative approach for detection and quantification of nucleic acid that offers an alternative method to conventional real-time quantitative PCR for absolute quantification. dPCR is a highly precise and sensitive technique that does not require a standard reference, making it a suitable method for the detection of microRNAs. The potential of these small noncoding RNA as biomarkers is on the rise, especially due to their presence in body fluids, making them easily accessible. Nevertheless, the problem of lack of consensus regarding an optimal method for miRNAs normalization compromises their use. Here, we describe an innovative method for the absolute quantification of miRNAs across different types of biological samples using a chip-based platform, the QuantStudio 3D digital PCR.

Circulating Neutrophil MicroRNAs as Biomarkers for the Detection of Lung Cancer

Peripheral neutrophils are the predominant circulating leukocytes and an important component of innate and adaptive immune systems, which is a primary defense against cancer. MicroRNAs (miRNAs) can modulate neutrophil functions and play important roles in cancer pathogenesis by regulating neutrophil gene expression. To investigate if assessment of differential miRNA levels of peripheral neutrophils has the potential for diagnosis of non-small-cell lung cancer (NSCLC), we examine neutrophils of 15 patients with stage I NSCLC and 15 smokers without cancer. We identify five neutrophil miRNAs that have an abnormal level in patients with NSCLC versus smokers without cancer. In a training set of 82 patients with lung cancer and 73 controls, a set of two genes (miRs-26a-2-3p and 574-3p) are developed, producing 77.8% sensitivity and 78.1% specificity for NSCLC detection. Furthermore, in a testing set of 60 patients with lung cancer and 58 smokers, the performance of analyzing the two miRNAs for lung cancer detection is confirmed. This study for the first time shows that a neutrophil miRNA profile may serve as a new category of circulating biomarkers for the detection of NSCLC.

MicroRNA (miRNA) Profiling

MicroRNAs (miRNAs) are small, highly conserved noncoding RNA molecules involved in the regulation of gene expression. Since each miRNA regulates the expression of hundreds of target mRNAs, miRNAs could function as master coordinators, efficiently regulating fundamental cellular processes, including proliferation, apoptosis, and development. Furthermore, miRNAs may provide useful diagnostic and therapeutic targets in a variety of diseases. However, miRNA expression profiling is essential for the investigation of the biological functions and clinical applications of miRNAs. Therefore, in this chapter, we review and discuss commonly used techniques for miRNAs profiling, as well as their advantages and restrictions.

Differential miRNA expressions in peripheral blood mononuclear cells for diagnosis of lung cancer

Tremendous efforts have been made to develop cancer biomarkers by detecting circulating extracellular miRNAs directly released from tumors. Yet, none of the cell-free biomarkers has been accepted to be used for early detection of non-small cell lung cancer (NSCLC). Peripheral blood mononucleated cells (PBMCs) act as the first line of defense against malignancy in immune system, their dysfunction may occur as an early event in cancer immunogenicity or immune evasion. We proposed to investigate whether analysis of miRNA expressions of PBMCs has diagnostic value for NSCLC. We first used a microarray to analyze PBMCs of 16 stage I NSCLC patients and 16 cancer-free smokers, and identified seven PBMC miRNAs with a significantly altered expression level in NSCLC patients. In a training set of 84 NSCLC patients and 69 cancer-free smokers, a panel of two miRNAs (miRs-19b-3p and -29b-3p) were developed from the seven PBMC miRNAs, producing 72.62% sensitivity and 82.61% specificity in identifying NSCLC. Furthermore, the miRNAs could identify squamous cell lung carcinoma (SCC), a major type of NSCLC, with 80.00% sensitivity and 89.86% specificity. The expression levels of the miRNAs were independent of disease stage. In a testing set of 56 NSCLC patients and 46 controls, the performance of the biomarkers was reproducibly confirmed. The study presents the first in-depth analysis of PBMC miRNA profile of NSCLC patients. The assessment of PBMC miRNAs may provide a new diagnostic approach for the early detection of NSCLC.

miRNA detection methods and clinical implications in lung cancer

Lung cancer is the leading cause of cancer death worldwide. Therefore, advances in the diagnosis and treatment of the disease are urgently needed. miRNAs are a family of small, noncoding RNAs that regulate gene expression at the transcriptional level. miRNAs have been reported to be deregulated and to play a critical role in different types of cancer, including lung cancer. Thus, miRNA profiling in lung cancer patients has become the core of several investigations. To this end, the development of a multitude of platforms for miRNA profiling analysis has been essential. This article focuses on the different technologies available for assessing miRNAs and the most important results obtained to date in lung cancer.

The oncomiR miR-197 is a novel prognostic indicator for non-small cell lung cancer patients

Background:

MicroRNA expression signatures can promote personalised care for non-small cell lung cancer (NSCLC) patients. Our aim was to evaluate the previously unexplored prognostic potential of miR-197, a key oncogenic molecule for NSCLC.

Methods:

Total RNA isolation (n=124 NSCLC and n=21 tumour-adjacent normal tissues), was performed using the QIAsymphony SP workstation. The quantity and quality of RNA were assessed by spectrophotometric analysis and an Agilent 2100 bioanalyzer. Polyadenylation and reverse transcription were subsequently carried out. MiR-197 expression levels were measured by qPCR, after quality control (inter-assay CV=7.8%). Internal validation procedures were followed by assigning training and test sets and robust biostatistical analyses were performed, including bootstrap resampling.

Results:

MiR-197 is associated with larger tumours (P=0.042) and the squamous cell carcinoma histotype (P=0.032). Interestingly, after adjusting for important prognostic indicators, miR-197 expression was identified as a novel independent predictor of unfavourable prognosis for NSCLC patients (HR=1.97, 95% CI=1.10–3.38, P=0.013). We also demonstrate that miR-197 retains its prognostic performance in both early-stage I (P=0.045) and more advanced-stage individuals (P=0.036).

Conclusions:

The cost-effective expression analysis of miR-197 could constitute a novel molecular tool for NSCLC management.

Characterization of microRNA transcriptome in tumor, adjacent, and normal tissues of lung squamous cell carcinoma

OBJECTIVES

MicroRNAs are a class of regulatory molecules involved in a wide variety of biological processes, including growth, development, and apoptosis. Given the widespread roles of microRNAs in biological processes, understanding their different expression profiles in normal, adjacent, and tumor tissues will provide insights into the consequences of aberrant expression.

METHODS

With the use of next-generation deep sequencing technology, microRNA profiles in 3 pooled samples from normal, adjacent, and tumor tissues of 19 patients with lung squamous cell carcinoma were characterized comprehensively. Quantitative polymerase chain reaction was used to verify the primary findings in another 38 lung squamous cell carcinoma tumor samples. In situ hybridization also was performed for validation.

RESULTS

A total of 368, 306, and 231 known microRNAs were identified from tumor, adjacent, and normal pooled samples, respectively, of which 40, 44, and 26 microRNAs displayed dysregulation with 2-fold or greater change in 3 compared groups of tumor versus normal, tumor versus adjacent, and adjacent versus normal, respectively. Sequencing data also showed that some coexpressed microRNAs displayed a pattern of progressive dysregulation. Some of the microRNAs exhibited consistent changes; among them, miR-425-5p and miR-218-5p were confirmed by quantitative polymerase chain reaction and in situ hybridization, and proved that the microRNA expression levels were closely related to tumor stages and sizes. It is suggested that some microRNAs, such as miR-425 and miR-183, might be a driver for tumor formation, growth, and progression to higher staging, whereas others, such as miR-218, might behave as a tumor suppressor in lung cancer. Functional annotation analysis indicated that the proteoglycan pathway in cancer and mitogen-activated protein kinase, Wnt, PI3K-Akt, and transforming growth factor-beta signaling pathways might be involved in the pathogenesis of lung squamous cell carcinoma.

CONCLUSIONS

This study describes the use of deep sequencing for comprehensive profiling of microRNAs in lung squamous cell carcinoma. The identified microRNA signatures may provide biomarkers for early detection, subclassification, and potential therapeutic targets of lung squamous cell carcinoma. This study also provides some insights into the molecular mechanism underlying the development and progression of lung squamous cell carcinoma, which may prove helpful for early diagnosis and treatment of the disease.

The clinical relevance of the miR-197/CKS1B/STAT3-mediated PD-L1 network in chemoresistant non-small-cell lung cancer

Programmed cell death ligand-1 (PD-L1) has recently gained considerable attention for its role in tumor immune escape. Here, we identify a miR-197/CKS1B/STAT3-mediated PD-L1 network in chemoresistant non-small-cell lung cancer (NSCLC), independent of immunoinhibitory signals. miR-197 is downregulated in platinum-resistant NSCLC specimens, resulting in the promotion of chemoresistance, tumorigenicity, and pulmonary metastasis in vitro and in vivo. Mechanistic investigations reveal that a miR-197-mediated CKS1B/STAT3 axis exerts tumor progression regulated by various oncogenic genes (Bcl-2, c-Myc, and cyclin D1), and PD-L1 is a putative biomarker of this axis. Furthermore, we demonstrate that a miR-197 mimic sensitizes PD-L1^high drug-resistant cells to chemotherapy. These results indicate that the biological interaction between PD-L1 and chemoresistance occurs through the microRNA regulatory cascade. More importantly, expression levels of miR-197 are inversely correlated with PD-L1 expression (n = 177; P = 0.026) and are associated with worse overall survival (P = 0.015). Our discoveries suggest that the miR-197/CKS1B/STAT3-mediated network can drive tumor PD-L1 expression as a biomarker of this cascade, and miR-197 replacement therapy may be a potential treatment strategy for chemoresistant NSCLC.

Early Detection of Lung Cancer in Serum by a Panel of MicroRNA Biomarkers

INTRODUCTION

The objective of the study was to develop a panel of microRNAs (miRNAs) as highly sensitive and specific biomarkers for lung cancer early detection.

MATERIALS AND METHODS

The study contained 2 phases: first, preliminary marker selection based on previous reports on the serum of 24 early stage lung cancer patients and 24 healthy control subjects by TaqMan probe-based real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR); and second, validation of miRNA markers on 94 early stage lung cancer, 48 stage III to IV lung cancer, and 111 healthy control serum samples.

RESULTS

A total of 3 miRNAs (miR-125a-5p, miR-25, and miR-126) were selected for further analysis in this study. The combination of the 3 miRNAs could produce 0.936 area under the receiver operating characteristic curve value in distinguishing early stage lung cancer patients from control subjects with 87.5% sensitivity and 87.5% specificity, respectively. The diagnostic value of the miRNA panel in an independent set of lung cancer patients confirmed the sensitivity and specificity.

CONCLUSION

The results demonstrated that the panel of miRNA biomarkers had the potential for the early detection of lung cancer.

Characterization of microRNA transcriptome in lung cancer by next-generation deep sequencing

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death. Systematically characterizing miRNAs in NSCLC will help develop biomarkers for its diagnosis and subclassification, and identify therapeutic targets for the treatment. We used next-generation deep sequencing to comprehensively characterize miRNA profiles in eight lung tumor tissues consisting of two major types of NSCLC, squamous cell carcinoma (SCC) and adenocarcinoma (AC). We used quantitative PCR (qPCR) to verify the findings in 40 pairs of stage I NSCLC tissues and the paired normal tissues, and 60 NSCLC tissues of different types and stages. We also investigated the function of identified miRNAs in lung tumorigenesis. Deep sequencing identified 896 known miRNAs and 14 novel miRNAs, of which, 24 miRNAs displayed dysregulation with fold change ≥4.5 in either stage I ACs or SCCs or both relative to normal tissues. qPCR validation showed that 14 of 24 miRNAs exhibited consistent changes with deep sequencing data. Seven miRNAs displayed distinctive expressions between SCC and AC, from which, a panel of four miRNAs (miRs-944, 205-3p, 135a-5p, and 577) was identified that cold differentiate SCC from AC with 93.3% sensitivity and 86.7% specificity. Manipulation of miR-944 expression in NSCLC cells affected cell growth, proliferation, and invasion by targeting a tumor suppressor, SOCS4. Evaluating miR-944 in 52 formalin-fixed paraffin-embedded SCC tissues revealed that miR-944 expression was associated with lymph node metastasis. This study presents the earliest use of deep sequencing for profiling miRNAs in lung tumor specimens. The identified miRNA signatures may provide biomarkers for early detection, subclassification, and predicting metastasis, and potential therapeutic targets of NSCLC.

Digital PCR quantification of miRNAs in sputum for diagnosis of lung cancer

PURPOSE

MicroRNAs (miRNAs) play important roles in the initiation and progression of lung cancer. Measuring miRNA expression levels in sputum could provide a potential approach for the diagnosis of lung cancer. The emerging digital PCR is a straightforward technique for precise, direct, and absolute quantification of nucleic acids. The objective of the study was to investigate whether digital PCR could be used to quantify miRNAs in sputum for lung cancer diagnosis.

METHODS

We first determined and compared dynamic ranges of digital PCR and conventional quantitative reverse transcriptase PCR (qRT-PCR) for miRNA quantification using RNA isolated from sputum of five healthy individuals. We then used digital PCR to quantify copy number of two lung cancer-associated miRNAs (miR-31 and miR-210) in 35 lung cancer patients and 40 cancer-free controls.

RESULTS

Copy number of the miRNAs measured by digital PCR displayed a linear response to input cDNA amount in a twofold dilution series over seven orders of magnitude. miRNA quantification determined by digital PCR assay was in good agreement with that obtained from qRT-PCR analysis in sputum. Furthermore, combined quantification of miR-31 and miR-210 copy number by using digital PCR in sputum of the cases and controls provided 65.71 % sensitivity and 85.00 % specificity for lung cancer diagnosis.

CONCLUSION

As digital PCR becomes more established, it would be a robust tool for quantitative assessment of miRNA copy number in sputum for lung cancer diagnosis.

Quantification of Plasma miRNAs by Digital PCR for Cancer Diagnosis

Analysis of plasma microRNAs (miRNAs) by quantitative polymerase chain reaction (qPCR) provides a potential approach for cancer diagnosis. However, absolutely quantifying low abundant plasma miRNAs is challenging with qPCR. Digital PCR offers a unique means for assessment of nucleic acids presenting at low levels in plasma. This study aimed to evaluate the efficacy of digital PCR for quantification of plasma miRNAs and the potential utility of this technique for cancer diagnosis. We used digital PCR to quantify the copy number of plasma microRNA-21-5p (miR-21–5p) and microRNA-335–3p (miR-335–3p) in 36 lung cancer patients and 38 controls. Digital PCR showed a high degree of linearity and quantitative correlation with miRNAs in a dynamic range from 1 to 10,000 copies/μL of input, with high reproducibility. qPCR exhibited a dynamic range from 100 to 1×10⁷ copies/μL of input. Digital PCR had a higher sensitivity to detect copy number of the miRNAs compared with qPCR. In plasma, digital PCR could detect copy number of both miR-21–5p and miR-335–3p, whereas qPCR was only able to assess miR-21–5p. Quantification of the plasma miRNAs by digital PCR provided 71.8% sensitivity and 80.6% specificity in distinguishing lung cancer patients from cancer-free subjects.

Insulin growth factor signaling is regulated by microRNA-486, an underexpressed microRNA in lung cancer

MicroRNAs (miRNAs) are small 19- to 24-nt noncoding RNAs that have the capacity to regulate fundamental biological processes essential for cancer initiation and progression. In cancer, miRNAs may function as oncogenes or tumor suppressors. Here, we conducted global profiling for miRNAs in a cohort of stage 1 nonsmall cell lung cancers (n = 81) and determined that miR-486 was the most down-regulated miRNA in tumors compared with adjacent uninvolved lung tissues, suggesting that miR-486 loss may be important in lung cancer development. We report that miR-486 directly targets components of insulin growth factor (IGF) signaling including insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and phosphoinositide-3-kinase, regulatory subunit 1 (alpha) (PIK3R1, or p85a) and functions as a potent tumor suppressor of lung cancer both in vitro and in vivo. Our findings support the role for miR-486 loss in lung cancer and suggest a potential biological link to p53.

MicroRNAs as potential biomarkers in human solid tumors

MicroRNAs (miRNAs) regulate the expression of approximately 30% of protein-coding genes. Functions of miRNAs are essential to maintain a steady state of cellular machinery. Dysregulations of miRNAs play pivotal roles in the initiation and progression of malignancies. Abnormal miRNA expressions have been found in a variety of human solid tumors. Furthermore, extracellular miRNAs could circulate in body fluids, and hence show great promise for refining diagnosis and prognosis of cancer. Here we review the progress of analysis of microRNAs as a potential approach for diagnosis and prognosis of solid cancer. We will also discuss obstacles in developing miRNAs as circulating biomarkers.

High expression of miR-210 predicts poor survival in patients with breast cancer: a meta-analysis

BACKGROUND

Many microRNAs (miRNAs) exhibit altered expression levels in cancers, and they may be considered as valuable prognostic biomarkers for cancers. Here we aimed to summarize the recent advances in miR-210 involvement in human breast cancer and analyze the predicting role of miR-210 for survival.

METHODS

A meta-analysis was performed by searching PubMed, Cochrane Library, and Science Direct databases. Data were extracted from studies comparing survival in patients with breast cancer having higher expression of miR-210 with those having lower expression. Pooled hazard ratios (HRs) and 95% confidence intervals (CI) were calculated.

RESULTS

A total of 511 cases of breast cancer were involved for this global meta-analysis. For post-operational survival, the HR of higher miR-210 expression in breast cancer tissue was 3.39 (95% CI: 2.04-5.63, P<0.05), which could significantly predict poorer survival.

CONCLUSIONS

High expression of miR-210 might predict poor survival in patients with breast cancer.