Identifying circulating miRNA biomarkers for early diagnosis and monitoring of lung cancer

Advances in applications of artificial intelligence algorithms for cancer-related miRNA research

MiRNAs are a class of small non-coding RNAs, which regulate gene expression post-transcriptionally by partial complementary base pairing. Aberrant miRNA expressions have been reported in tumor tissues and peripheral blood of cancer patients. In recent years, artificial intelligence algorithms such as machine learning and deep learning have been widely used in bioinformatic research. Compared to traditional bioinformatic tools, miRNA target prediction tools based on artificial intelligence algorithms have higher accuracy, and can successfully predict subcellular localization and redistribution of miRNAs to deepen our understanding. Additionally, the construction of clinical models based on artificial intelligence algorithms could significantly improve the mining efficiency of miRNA used as biomarkers. In this article, we summarize recent development of bioinformatic miRNA tools based on artificial intelligence algorithms, focusing on the potential of machine learning and deep learning in cancer-related miRNA research.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review

With the continuous discovery and research of predictive cancer-related biomarkers, liquid biopsy shows great potential in cancer diagnosis. Surface-enhanced Raman scattering (SERS) and microfluidic technology have received much attention among the various cancer biomarker detection methods. The former has ultrahigh detection sensitivity and can provide a unique fingerprint. In contrast, the latter has the characteristics of miniaturization and integration, which can realize accurate control of the detection samples and high-throughput detection through design. Both have the potential for point-of-care testing (POCT), and their combination (lab-on-a-chip SERS (LoC-SERS)) shows good compatibility. In this paper, the basic situation of circulating proteins, circulating tumor cells, exosomes, circulating tumor DNA (ctDNA), and microRNA (miRNA) in the diagnosis of various cancers is reviewed, and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail. At the same time, the challenges and future development of the platform are discussed at the end of the review. Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review

Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screening. A literature search on PubMed was performed including studies which investigated liquid biopsy non-coding RNAs biomarker lung cancer patients and a control cohort. Micro RNAs were the most widely studied biomarkers in this setting but some preliminary evidence was found also for other non-coding RNAs, suggesting that a multi-biomarker based liquid biopsy approach could enhance their efficacy in the screening context. However, further studies are needed in order to optimize detection techniques as well as diagnostic accuracy before introducing novel biomarkers in the early diagnosis setting.

miRNAs as potential game-changers in bone diseases: Future medicinal and clinical uses

MicroRNAs (miRNAs), short, highly conserved non-coding RNA, influence gene expression by sequential mechanisms such as mRNA breakdown or translational repression. Many biological processes depend on these regulating substances, thus changes in their expression have an impact on the maintenance of cellular homeostasis and result in the emergence of a variety of diseases. Relevant studies have shown in recent years that miRNAs are involved in many stages of bone development and growth. Additionally, abnormal production of miRNA in bone tissues has been closely associated with the development of numerous bone disorders, such as osteonecrosis, bone cancer, and bone metastases. Many pathological processes, including bone loss, metastasis, the proliferation of osteosarcoma cells, and differentiation of osteoblasts and osteoclasts, are under the control of miRNAs. By bringing together the most up-to-date information on the clinical relevance of miRNAs in such diseases, this study hopes to further the study of the biological features of miRNAs in bone disorders and explore their potential as a therapeutic target.

Integration of artificial intelligence in lung cancer: Rise of the machine

The goal of oncology is to provide the longest possible survival outcomes with the therapeutics that are currently available without sacrificing patients' quality of life. In lung cancer, several data points over a patient's diagnostic and treatment course are relevant to optimizing outcomes in the form of precision medicine, and artificial intelligence (AI) provides the opportunity to use available data from molecular information to radiomics, in combination with patient and tumor characteristics, to help clinicians provide individualized care. In doing so, AI can help create models to identify cancer early in diagnosis and deliver tailored therapy on the basis of available information, both at the time of diagnosis and in real time as they are undergoing treatment. The purpose of this review is to summarize the current literature in AI specific to lung cancer and how it applies to the multidisciplinary team taking care of these complex patients.

Metastatic Melanoma: Liquid Biopsy as a New Precision Medicine Approach

Precision medicine has driven a major change in the treatment of many forms of cancer. The discovery that each patient is different and each tumor mass has its own characteristics has shifted the focus of basic and clinical research to the singular individual. Liquid biopsy (LB), in this sense, presents new scenarios in personalized medicine through the study of molecules, factors, and tumor biomarkers in blood such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes and circulating tumor microRNAs (ct-miRNAs). Moreover, its easy application and complete absence of contraindications for the patient make this method applicable in a great many fields. Melanoma, given its highly heterogeneous characteristics, is a cancer form that could significantly benefit from the information linked to liquid biopsy, especially in the treatment management. In this review, we will focus our attention on the latest applications of liquid biopsy in metastatic melanoma and possible developments in the clinical setting.

The expression profiling of serum miR-92a, miR-134 and miR-375 in acute ischemic stroke

Aim

To investigate the expression profile and diagnostic potentials of serum miR-92a, 134, and 375 in acute ischemic stroke (AIS) patients.

Materials & methods

Serum miRs-92a, 134, and 375 expression profiles were estimated by qRT-PCR for 70 AIS patients, age-matched with 25 control subjects. Their diagnostic potential was estimated by ROC analysis.

Results

Down-expression of miR-92a and miR-375 was found (56; 96.5%; -1.86 ± 1.36; and 53; 91.4%; -1.63 ± 1.38, respectively), while miR-134 showed a predominant upregulation (46; 79.3%; 0.853 ± 1.34). The diagnostic accuracy was the highest for miR-92a and miR-375 (area under the curve = 0.9183 and 0.898, respectively), with greater specificity for miR-375 (Sp = 96%).

Conclusion

Serum miR-92a and miR-375 could be promising early detective biomarkers of AIS.

Blood biomarkers for canine cancer, from human to veterinary oncology

In recent decades, interest in circulating tumour biomarkers is increasing both in human and veterinary oncology. An ideal tumour biomarker would allow early diagnosis of neoplasia, identify it specifically, accurately, establish a prognosis and predict its behaviour, especially regarding different therapeutic solutions. It would also allow to monitor its evolution over time and all this in a non-invasive and inexpensive way. Actually, no biomarkers meeting all of these criteria have been identified in veterinary medicine, particularly due to a lack of specificity of the main protein tumour biomarkers studied to date. However, great hope is currently placed in biomarkers grouped under the name of liquid biopsy, which could prove to be effective tools for common clinical use in the near future. This review gives an update on blood cancer biomarkers studied in dogs, such as ions, proteins, nucleic acids and also circulating cells, of which some might become more prominent in the coming years to help improve the management of animal care.

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.

Identidication of novel biomarkers in non-small cell lung cancer using machine learning

Lung cancer is one of the leading causes of cancer-related deaths worldwide, and non-small cell lung cancer (NSCLC) accounts for a large proportion of lung cancer cases, with few diagnostic and therapeutic targets currently available for NSCLC. This study aimed to identify specific biomarkers for NSCLC. We obtained three gene-expression profiles from the Gene Expression Omnibus database (GSE18842, GSE21933, and GSE32863) and screened for differentially expressed genes (DEGs) between NSCLC and normal lung tissue. Enrichment analyses were performed using Gene Ontology, Disease Ontology, and the Kyoto Encyclopedia of Genes and Genomes. Machine learning methods were used to identify the optimal diagnostic biomarkers for NSCLC using least absolute shrinkage and selection operator logistic regression, and support vector machine recursive feature elimination. CIBERSORT was used to assess immune cell infiltration in NSCLC and the correlation between biomarkers and immune cells. Finally, using western blot, small interfering RNA, Cholecystokinin-8, and transwell assays, the biological functions of biomarkers with high predictive value were validated. A total of 371 DEGs (165 up-regulated genes and 206 down-regulated genes) were identified, and enrichment analysis revealed that these DEGs might be linked to the development and progression of NSCLC. ABCA8, ADAMTS8, ASPA, CEP55, FHL1, PYCR1, RAMP3, and TPX2 genes were identified as novel diagnostic biomarkers for NSCLC. Monocytes were the most visible activated immune cells in NSCLC. The knockdown of the TPX2 gene, a biomarker with a high predictive value, inhibited A549 cell proliferation and migration. This study identified eight potential diagnostic biomarkers for NSCLC. Further, the TPX2 gene may be a therapeutic target for NSCLC.

MiRNA expression deregulation correlates with the Oncotype DX® DCIS score

Background

Current clinical criteria do not discriminate well between women who will or those who will not develop ipsilateral invasive breast cancer (IBC), or a DCIS recurrence after a ductal carcinoma in situ (DCIS) diagnosis. The 12-gene Oncotype DX® DCIS assay (RT qPCR gene-based scoring system) was established and shown to predict the risk of subsequent ipsilateral IBC or DCIS recurrence. Recent studies have shown that microRNA (miRNA) expression deregulation can contribute to the development of IBC, but very few have evaluated miRNA deregulation in DCIS lesions. In this study, we sought to determine whether specific miRNA expression changes may correlate with Oncotype DX® DCIS scores.

Methods

For this study, we used archived formalin-fixed, paraffin-embedded (FFPE) specimens from 41 women diagnosed with DCIS between 2012 and 2018. The DCIS lesions were stratified into low (n = 26), intermediate (n = 10), and high (n = 5) risk score groups using the Oncotype DX® DCIS assay. Total RNA was extracted from DCIS lesions by macro-dissection of unstained FFPE sections, and next-generation small-RNA sequencing was performed. We evaluated the correlation between miRNA expression data and Oncotype score, as well as patient age. RT-qPCR validations were performed to validate the topmost differentially expressed miRNAs identified between the different risk score groups.

Results

MiRNA sequencing of 32 FFPE DCIS specimens from the three different risk group scores identified a correlation between expression deregulation of 17 miRNAs and Oncotype scores. Our analyses also revealed a correlation between the expression deregulation of 9 miRNAs and the patient’s age. Based on these results, a total of 15 miRNAs were selected for RT-qPCR validation. Of these, miR-190b (p = 0.043), miR-135a (p = 0.05), miR-205 (p = 0.00056), miR-30c (p = 0.011), and miR-744 (p = 0.038) showed a decreased expression in the intermediate/high Oncotype group when compared to the low-risk score group. A composite risk score was established using these 5 miRNAs and indicated a significant association between miRNA expression deregulation and the Oncotype DX® DCIS Score (p < 0.0021), between high/intermediate and low risk groups.

Conclusions

Our analyses identified a subset of 5 miRNAs able to discriminate between Oncotype DX® DCIS score subgroups. Together, our data suggest that miRNA expression analysis may add value to the predictive and prognostic evaluation of DCIS lesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01558-4.

Sensitive detection of microRNAs using polyadenine-mediated fluorescence spherical nucleic acids and a microfluidic electrokinetic signal amplification chip

The identification of tumor-related microRNAs (miRNAs) exhibits excellent promise for the early diagnosis of cancer and other bioanalytical applications. Therefore, we developed a sensitive and efficient biosensor using polyadenine (polyA)-mediated fluorescent spherical nucleic acid (FSNA) for miRNA analysis based on strand displacement reactions on gold nanoparticle (AuNP) surfaces and electrokinetic signal amplification (ESA) on a microfluidic chip. In this FSNA, polyA-DNA biosensor was anchored on AuNP surfaces via intrinsic affinity between adenine and Au. The upright conformational polyA-DNA recognition block hybridized with 6-carboxyfluorescein-labeled reporter-DNA, resulting in fluorescence quenching of FSNA probes induced by AuNP-based resonance energy transfer. Reporter DNA was replaced in the presence of target miRNA, leading to the recovery of reporter-DNA fluorescence. Subsequently, reporter-DNAs were accumulated and detected in the front of with Nafion membrane in the microchannel by ESA. Our method showed high selectivity and sensitivity with a limit of detection of 1.3 pM. This method could also be used to detect miRNA-21 in human serum and urine samples, with recoveries of 104.0%–113.3% and 104.9%–108.0%, respectively. Furthermore, we constructed a chip with three parallel channels for the simultaneous detection of multiple tumor-related miRNAs (miRNA-21, miRNA-141, and miRNA-375), which increased the detection efficiency. Our universal method can be applied to other DNA/RNA analyses by altering recognition sequences.

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FSNA assisted microfluidic chip was developed for miRNAs detection.

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Three different miRNAs were detected simultaneously.

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The excellent sensitivity and specificity were displayed toward miRNAs.

Tobacco carcinogen 4-[methyl(nitroso)amino]-1-(3-pyridinyl)-1-butanone (NNK) drives metabolic rewiring and epigenetic reprograming in A/J mice lung cancer model and prevention with diallyl sulphide (DAS)

Early detection of biomarkers in lung cancer is one of the best preventive strategies. Although many attempts have been made to understand the early events of lung carcinogenesis including cigarette smoking (CS) induced lung carcinogenesis, the integrative metabolomics and next-generation sequencing approaches are lacking. In this study, we treated the female A/J mice with CS carcinogen 4-[methyl(nitroso)amino]-1-(3-pyridinyl)-1-butanone (NNK) and naturally occurring organosulphur compound, diallyl sulphide (DAS) for 2 and 4 weeks after NNK injection and examined the metabolomic and DNA CpG methylomic and RNA transcriptomic profiles in the lung tissues. NNK drives metabolic changes including mitochondrial tricarboxylic acid (TCA) metabolites and pathways including Nicotine and its derivatives like nicotinamide and nicotinic acid. RNA-seq analysis and Reactome pathway analysis demonstrated metabolism pathways including Phase I and II drug metabolizing enzymes, mitochondrial oxidation and signaling kinase activation pathways modulated in a sequential manner. DNA CpG methyl-seq analyses showed differential global methylation patterns of lung tissues from week 2 versus week 4 in A/J mice including Adenylate Cyclase 6 (ADCY6), Ras-related C3 botulinum toxin substrate 3 (Rac3). Oral DAS treatment partially reversed some of the mitochondrial metabolic pathways, global methylation and transcriptomic changes during this early lung carcinogenesis stage. In summary, our result provides insights into CS carcinogen NNK's effects on driving alterations of metabolomics, epigenomics and transcriptomics and the chemopreventive effect of DAS in early stages of sequential lung carcinogenesis in A/J mouse model.

Overexpression of miR-328-5p influences cell growth and migration to promote NSCLC progression by targeting LOXL4

Background

Lung cancer is the leading cause of cancer-associated mortality worldwide, and most lung cancers are classified as non-small cell lung cancer (NSCLC). MiR-328 influence the progression of multiple tumors, but the role of miR-328-5p in NSCLC has not been elucidated. The aim of this study was to illuminate the oncogenic role and potential molecular mechanisms of the miR-328-5p and lysyl oxidase like 4 (LOXL4) in NSCLC.

Methods

Expression of miR-328-5p was detected by real-time quantitative polymerase chain reaction (qRT-PCR) in tumor and non-tumor adjacent tissues. After Lentivirus-miR-328-5p was employed to intervene this miRNA in NSCLC cell lines, RT-qPCR was used to detect the expression levels of miR-328-5p. Cell Counting Kit-8 (CCK-8), cell colony formation, flow cytometry, wound healing, Transwell assays were used to determine the malignant phenotypes of NSCLC cells. Nude mice models of subcutaneous tumors were established to observe the effect of miR-328-5p on tumorigenesis. Targeting the 3'UTR of LOXL4 by miR-328-5p was verified by integrated analysis including transcriptome sequencing, dual-luciferase and western-blot assays.

Results

High miR-328-5p level was observed in NSCLC cells from The Cancer Genome Atlas (TCGA) database and tumor tissues collected from NSCLC patients. Overexpressed miR-328-5p promoted NSCLC cell proliferation, survival, and migration, and promoted tumor growth in vivo. Knockdown of miR-328-5p suppressed tumorigenic activities. Transcriptome sequencing analysis revealed that LOXL4 was downregulated by miR-328-5p, which was confirmed by dual-luciferase reporter and western-blot assays.

Conclusions

miR-328-5p showed targeted regulation of LOXL4 to promote cell proliferation and migration in NSCLC.

The Emerging Role of MicroRNAs in Bone Diseases and Their Therapeutic Potential

MicroRNAs (miRNAs) are a class of small (20-24 nucleotides), highly conserved, non-coding RNA molecules whose main function is the post-transcriptional regulation of gene expression through sequence-specific manners, such as mRNA degradation or translational repression. Since these key regulatory molecules are implicated in several biological processes, their altered expression affects the preservation of cellular homeostasis and leads to the development of a wide range of pathologies. Over the last few years, relevant investigations have elucidated that miRNAs participate in different stages of bone growth and development. Moreover, the abnormal expression of these RNA molecules in bone cells and tissues has been significantly associated with the progression of numerous bone diseases, including osteoporosis, osteosarcoma, osteonecrosis and bone metastasis, among others. In fact, miRNAs regulate multiple pathological mechanisms, including altering either osteogenic or osteoblast differentiation, metastasis, osteosarcoma cell proliferation, and bone loss. Therefore, in this present review, aiming to impulse the research arena of the biological implications of miRNA transcriptome in bone diseases and to explore their potentiality as a theragnostic target, we summarize the recent findings associated with the clinical significance of miRNAs in these ailments.

Role of miRNAs In Cancer Diagnostics And Therapy: A Recent Update

The discovery of miRNAs has been one of the revolutionary developments and has led to the advent of new diagnostic and therapeutic opportunities for the management of cancer. In this regard, miRNA dysregulation has been shown to play a critical role in various stages of tumorigenesis, including tumor invasion, metastasis as well as angiogenesis. Therefore, miRNA profiling can provide accurate fingerprints for the development of diagnostic and therapeutic platforms. This review discusses the recent discoveries of miRNA-based tools for early detection of cancer as well as disease monitoring in cancers that are common, like breast, lung, hepatic, colorectal, oral and brain cancer. Based on the involvement of miRNA in different cancers as oncogenic miRNA or tumor suppressor miRNA, the treatment with miRNA inhibitors or mimics is recommended. However, the stability and targeted delivery of miRNA remain the major limitations of miRNA delivery. In relation to this, several nanoparticle-based delivery systems have been reported which have effectively delivered the miRNA mimics or inhibitors and showed the potential for transforming these advanced delivery systems from bench to bedside in the treatment of cancer metastasis and chemoresistance. Based on this, we attempted to uncover recently reported advanced nanotherapeutic approaches to deliver the miRNAs in the management of different cancers.

Gold nanoparticles enhance microRNA 31 detection in colon cancer cells after inhibition with chlorogenic acid

In the present study, the inhibitory effect of chlorogenic acid (CGA), a phenolic compound with potential antitumor effects, on circulating microRNA 31 (miR-31), was evaluated in RKO colon cancer cells. The capacity of gold nanoparticles (AuNPs) to enhance miR-31 quantification after treatment with CGA was assessed. RKO cells were treated with different concentrations of CGA for 24, 48 and 72 h, after which AuNPs coupled to CD81 were added to the supernatants. Total RNA was extracted, and miR-31 was quantified by reverse transcription-quantitative PCR. The results revealed an 85% decrease in miR-31 level following treatment with 1,000 µM CGA for 72 h, and the highest capacity to detect miR-31 (after treatment and isolation with AuNPs + CD81) was observed at 24 h. Furthermore, CGA decreased the expression of the miR-31 oncogene in an in vitro colon cancer model, and the use of AuNPs enhanced the levels of miRNA detection. The results suggest that miR-31 inhibition is one mechanism by which CGA decreases colon cancer cell proliferation. Moreover, AuNPs can increase the capacity of miR-31 quantification, representing a new strategy to develop non-invasive tools for the molecular diagnosis and monitoring of colon cancer.

COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks.

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

A Physically Active Status Affects the Circulating Profile of Cancer-Associated miRNAs

Circulating miRNAs are ideal diagnostics and prognostics biomarkers in cancer since altered levels of specific miRNAs have been associated to development/progression of several cancers. Physical activity is a recognized preventive strategy against several cancers, but it may also modify the baseline levels of cancer-associated miRNAs and, hence, may act as a confounding pre-analytical variable. This study aimed at understanding whether physical activity-dependent changes in cancer-associated circulating miRNAs profile could act as a confounding variable. A panel comprising 179 miRNAs was assayed in plasma from 20 highly trained and 10 sedentary men. RT-qPCR data were analyzed with the 2^−2ΔΔCT methods and normalized on hsa-miR-320d, as determined by bioinformatics analysis. miRNAs associated with the diagnosis of the most prevalent cancers were considered. Only those miRNAs, relevantly associated with cancers, found ≥2-fold up- or downregulated in highly trained subjects compared to sedentary were disclosed. The results reveal that chronic physical activity determined modifications altering the baseline level of several cancer-associated miRNAs and, hence, their diagnostic and prognostic potential. In conclusion, based on our results, a physically active status emerges as an important pre-analytical variable able to alter the basal level of circulating miRNAs, and these alterations might be considered as potentially misleading the analytical output.

circ-ANXA7 facilitates lung adenocarcinoma progression via miR-331/LAD1 axis

Background

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, with a poor prognosis. The roles of circular RNAs (circRNAs) in tumors have been initially clarified. In this study, we probed into the functions and underlying molecular mechanisms of circ-ANXA7 in LUAD.

Methods

According to circRNA microarray analysis based on 40 pairs of LUAD tissues and non-tumor tissues, a novel circ-ANXA7 was up-regulated in LUAD, which was verified in LUAD tissues and cells by RT-qPCR. Correlation between its expression and clinical features of LUAD was analyzed. When transfected with sh-circ-ANXA7, proliferation, invasion, and migration of LUAD cells were determined by a series of functional assays. Furthermore, tumor growth was investigated in nude mice injected with sh-circ-ANXA7. Dual luciferase report and gain and loss assays were used to confirm the relationships between circ-ANXA7 and miR-331, miR-331 and LAD1.

Results

circ-ANXA7 was up-regulated in LUAD tissues and cells. Its high expression promoted proliferation, migration, and invasion of LUAD cells as well as tumor growth. High circ-ANXA7 expression usually predicted a poorer prognosis for LUAD patients. Furthermore, circ-ANXA7 could accelerate proliferation and invasion of LUAD cells by targeting miR-331. miR-331 directly bound to the 3′-UTR of LAD1. LAD1 induced proliferation and invasion of LUAD cells, which was reversed after co-transfection with circ-ANXA7 knockdown. LAD1 expression could be an independent prognostic marker for LUAD by univariate and multivariate analysis.

Conclusions

Our research identified a novel circ-ANXA7 for LUAD, which could facilitate proliferation, migration, and invasion of LUAD cells by miR-331/ LAD1 axis. circ-ANXA7 could become a promising prognosis and treatment target for LUAD.

MicroRNAs: Emerging oncogenic and tumor-suppressive regulators, biomarkers and therapeutic targets in lung cancer

Lung cancer is one of the most common solid tumors worldwide and the leading cause of cancer-related deaths, causing a devastating impact on human health. The clinical prognosis of lung cancer is usually restricted by delayed diagnosis and resistance to anticancer therapies. MicroRNAs, a range of small endogenous noncoding RNAs 22 nucleotides in length, have emerged as one of the most important players in cancer initiation and progression in recent decades. Current evidence reveals pivotal roles of microRNAs in regulating cell proliferation, migration, invasion and metastasis in lung cancer. An increasing number of preclinical and clinical studies have also explored the potential of microRNAs as promising biomarkers and new therapeutic targets for lung cancer. The current review summarizes the most recent progress on the functional mechanisms of microRNAs involved in lung cancer development and progression and further discusses the clinical application of miRNAs as putative therapeutic targets for molecular diagnosis and prognostic prediction in lung cancer.

Fentanyl Inhibits Lung Cancer Viability and Invasion via Upregulation of miR-331-3p and Repression of HDAC5

Purpose

Non-small cell lung cancer (NSCLC) accounts for more than 80% of lung cancer cases and remains the primary cause of cancer-related deaths worldwide. Fentanyl is a commonly utilized anesthetic during the process of tumor resection, and exhibits inhibitory effects on the progression of numerous cancer types, including pancreatic cancer, colorectal cancer and gastric cancer. However, the effects of fentanyl on the cell viability and invasion of NSCLC has not been investigated. Current study aimed to investigate the effects and the mechanisms underlying the effects of fentanyl on NSCLC.

Methods

The expression of μ-opioid receptor (MOR) was proved by flow cytometry. The expression of microRNA-331-3p (miR-331-3p) and histone deacetylase 5 (HDAC5) in NSCLC tissues and cell lines are evaluated by reverse transcription-quantitative PCR (RT-qPCR) and Western blot, respectively. Cell viability and invasion are measured by cell counting kit-8 (CCK-8) assay and transwell assay, respectively. The interaction between miR-331-3p and 3ʹ-untranslated region (UTR) of HDAC5 is predicted by TargetScan 7.1 (http://www.targetscan.org/vert_71/), validated by dual luciferase assay, RT-qPCR and Western blot.

Results

There was lower miR-331-3p expression and higher HDAC5 expression in NSCLC cell lines A549 and CALU-1 compared with BEAS-2B, which was reversed by fentanyl administration. miR-331-3p targeted 3ʹ-UTR of HDAC5 in NSCLC cell lines A549 and CALU-1. miR-331-3p inhibitor partially abrogated the inhibitory effects of fentanyl on NSCLC cell viability and invasion by targeting HDAC5. In addition, there was higher HDAC5 expression and lower miR-331-3p expression in tumor tissues which were isolated from patients with NSCLC compared to the adjacent normal tissues, and miR-331-3p was negatively correlated with HDAC5 in NSCLC tumor tissues.

Conclusion

Fentanyl inhibits the viability and invasion of NSCLC cells by induction of miR-331-3p and reduction of HDAC5.

MiR-30b-5p inhibits proliferation and promotes apoptosis of medulloblastoma cells via targeting MYB proto-oncogene like 2 (MYBL2)

Medulloblastoma (MB) is the most common malignant brain tumors among children. MiR-30b-5p is a potential tumor suppressor in a variety of human cancers. However, its expression and function in MB remain poorly understood. This study aimed to investigate the expression, role and regulatory mechanism of miR-30b-5p in MB. The expression of miR-30b-5p in MB tissues and cell lines was detected by real-time PCR. The effects of miR-30b-5p on cell proliferation and apoptosis were monitored by CCK-8 (Cell Counting Kit-8) assay, colony formation assay and flow cytometry, respectively. Bioinformatics database TargetScan predicted the target genes of miR-30b-5p. The interaction between miR-30b-5p and MYB proto-oncogene Like 2 (MYBL2) was determined by luciferase reporter gene assay. We demonstrated that the expression of miR-30b-5p was significantly downregulated in MB. Upregulated miR-30b-5p could inhibit the proliferation and induce apoptosis of MB.

Moreover, overexpressed miR-30b-5p could increase the expression of BAX but decrease that of Bcl-2. Downregulated miR-30b-5p exerted the opposite effect. MYBL2 was proved to be the target gene of miR-30b-5p and was negatively regulated by miR-30b-5p. These results indicate that miR-30b-5p inhibits the progression of MB via targeting the expression of MYBL2.

Machine Learning-Based Ensemble Recursive Feature Selection of Circulating miRNAs for Cancer Tumor Classification

Circulating microRNAs (miRNA) are small noncoding RNA molecules that can be detected in bodily fluids without the need for major invasive procedures on patients. miRNAs have shown great promise as biomarkers for tumors to both assess their presence and to predict their type and subtype. Recently, thanks to the availability of miRNAs datasets, machine learning techniques have been successfully applied to tumor classification. The results, however, are difficult to assess and interpret by medical experts because the algorithms exploit information from thousands of miRNAs. In this work, we propose a novel technique that aims at reducing the necessary information to the smallest possible set of circulating miRNAs. The dimensionality reduction achieved reflects a very important first step in a potential, clinically actionable, circulating miRNA-based precision medicine pipeline. While it is currently under discussion whether this first step can be taken, we demonstrate here that it is possible to perform classification tasks by exploiting a recursive feature elimination procedure that integrates a heterogeneous ensemble of high-quality, state-of-the-art classifiers on circulating miRNAs. Heterogeneous ensembles can compensate inherent biases of classifiers by using different classification algorithms. Selecting features then further eliminates biases emerging from using data from different studies or batches, yielding more robust and reliable outcomes. The proposed approach is first tested on a tumor classification problem in order to separate 10 different types of cancer, with samples collected over 10 different clinical trials, and later is assessed on a cancer subtype classification task, with the aim to distinguish triple negative breast cancer from other subtypes of breast cancer. Overall, the presented methodology proves to be effective and compares favorably to other state-of-the-art feature selection methods.

Downregulation of microRNA-126 is inversely correlated with insulin receptor substrate-1 protein expression in colorectal cancer and is associated with advanced stages of disease

Colorectal cancer (CRC) is a common human malignant tumor, and the fourth most common cause of cancer-associated mortality in China. However, the pathogenesis of CRC is not yet fully understood. The present study aimed to investigate the expression and clinical significance of microRNA (miR)-126 and insulin receptor substrate-1 (IRS-1), as well as the role of miR-126 in the prognosis of patients with CRC. A total of 86 colorectal tissue specimens, including 40 CRC and adjacent normal tissue, 26 colorectal adenoma tissue and 20 normal colorectal tissue samples, were collected for the present study. Reverse transcription-quantitative PCR analysis was performed to determine miR-126 and IRS-1 mRNA expression levels, while western blotting and immunohistochemistry (IHC) analyses were performed to determine IRS-1 protein expression levels. The correlation between miR-126 and IRS-1 expression, as well as the association between altered miR-126 and IRS-1 expression levels and clinicopathological characteristics, and the overall survival time of patients with CRC were assessed. The results demonstrated that miR-126 expression was significantly downregulated, while IRS-1 protein expression was upregulated in CRC tissues compared with that in adjacent normal tissues, colorectal adenoma tissues and normal colorectal tissues, respectively. IHC analysis exhibited strong positive staining of IRS-1 protein in CRC tissues, while absent or weak staining of IRS-1 protein was detected in adjacent normal tissues, colorectal adenoma tissues and normal colorectal tissues. miR-126 expression was inversely correlated with IRS-1 protein expression in CRC tissues (r=−0.420; P<0.05). Furthermore, downregulated miR-126 expression was associated with advanced clinicopathological characteristics of the disease and a shorter overall survival time in patients with CRC. Taken together, the results of the present study suggest that miR-126 downregulation may be a candidate molecular marker predictive of poor prognosis of patients with CRC.