Identification of biomarkers for the detection of early stage lung adenocarcinoma by microarray profiling of long noncoding RNAs

Mitochondria-related lncRNAs: predicting prognosis, tumor microenvironment and treatment response in lung adenocarcinoma

Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan-Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.

Histone acetylation-related IncRNA: Potential biomarkers for predicting prognosis and immune response in lung adenocarcinoma, and distinguishing hot and cold tumours

Background

Histone acetylation-related lncRNAs (HARlncRNAs) play significant roles in various cancers, but their impact on lung adenocarcinoma (LUAD) remains unclear. This study aimed to develop a new HARlncRNA-based prognostic model for LUAD and to explore its potential biological mechanisms.

Methods

We identified 77 histone acetylation genes based on previous studies. HARlncRNAs related to prognosis were screened by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator regression (LASSO). Afterward, a prognostic model was established based on the screened HARlncRNAs. We analysed the relationship between the model and immune cell infiltration characteristics, immune checkpoint molecule expression, drug sensitivity, and tumour mutational burden (TMB). Finally, the entire sample was divided into three clusters to further distinguish between hot and cold tumours.

Results

A seven-HARlncRNA-based prognostic model was established for LUAD. The area under the curve (AUC) of the risk score was the highest among all the analysed prognostic factors, indicating the accuracy and robustness of the model. The patients in the high-risk group were predicted to be more sensitive to chemotherapeutic, targeted, and immunotherapeutic drugs. It was worth noting that clusters could effectively identify hot and cold tumours. In our study, clusters 1 and 3 were considered hot tumours that were more sensitive to immunotherapy drugs.

Conclusion

We developed a risk-scoring model based on seven prognostic HARlncRNAs that promises to be a new tool for evaluating the prognosis and efficacy of immunotherapy in patients with LUAD.

Altered genome-wide hippocampal gene expression profiles following early life lead exposure and their potential for reversal by environmental enrichment

Early life lead (Pb) exposure is detrimental to neurobehavioral development. The quality of the environment can modify negative influences from Pb exposure, impacting the developmental trajectory following Pb exposure. Little is known about the molecular underpinnings in the brain of the interaction between Pb and the quality of the environment. We examined relationships between early life Pb exposure and living in an enriched versus a non-enriched postnatal environment on genome-wide transcription profiles in hippocampus CA1. RNA-seq identified differences in the transcriptome of enriched vs. non-enriched Pb-exposed animals. Most of the gene expression changes associated with Pb exposure were reversed by enrichment. This was also true for changes in upstream regulators, splicing events and long noncoding RNAs. Non-enriched rats also had memory impairments; enriched rats had no deficits. The results demonstrate that an enriched environment has a profound impact on behavior and the Pb-modified CA1 transcriptome. These findings show the potential for interactions between Pb exposure and the environment to result in significant transcriptional changes in the brain and, to the extent that this may occur in Pb-exposed children, could influence neuropsychological/educational outcomes, underscoring the importance for early intervention and environmental enrichment for Pb-exposed children.

A learning-based method to predict LncRNA-disease associations by combining CNN and ELM

Background

lncRNAs play a critical role in numerous biological processes and life activities, especially diseases. Considering that traditional wet experiments for identifying uncovered lncRNA-disease associations is limited in terms of time consumption and labor cost. It is imperative to construct reliable and efficient computational models as addition for practice. Deep learning technologies have been proved to make impressive contributions in many areas, but the feasibility of it in bioinformatics has not been adequately verified.

Results

In this paper, a machine learning-based model called LDACE was proposed to predict potential lncRNA-disease associations by combining Extreme Learning Machine (ELM) and Convolutional Neural Network (CNN). Specifically, the representation vectors are constructed by integrating multiple types of biology information including functional similarity and semantic similarity. Then, CNN is applied to mine both local and global features. Finally, ELM is chosen to carry out the prediction task to detect the potential lncRNA-disease associations. The proposed method achieved remarkable Area Under Receiver Operating Characteristic Curve of 0.9086 in Leave-one-out cross-validation and 0.8994 in fivefold cross-validation, respectively. In addition, 2 kinds of case studies based on lung cancer and endometrial cancer indicate the robustness and efficiency of LDACE even in a real environment.

Conclusions

Substantial results demonstrated that the proposed model is expected to be an auxiliary tool to guide and assist biomedical research, and the close integration of deep learning and biology big data will provide life sciences with novel insights.

Differential expression of long non-coding RNAs as diagnostic markers for lung cancer and other malignant tumors

Due to advances in chip and sequencing technology, several types and numbers of long non-coding RNAs (lncRNAs) have been identified. LncRNAs are defined as non-protein-coding RNA molecules longer than 200 nucleotides, and are now thought as a new frontier in the study of human malignant diseases including NSCLC. Diagnosis of numerous malignant tumors has been closely linked to the differential expression of certain lncRNAs. LncRNAs are involved in gene expression regulation at multiple levels of epigenetics, transcriptional regulation, and post-transcriptional regulation. Mutations, deletions, or abnormal expression levels lead to physiological abnormalities, disease occurrence and are closely associated with human tumor diseases. LncRNAs play a crucial role in cancerous processes as either oncogenes or tumor suppressor genes. The expression of lncRNAs can regulate tumor cell in the proliferation, migration, apoptosis, cycle, invasion, and metastasis. As such, lncRNAs are potential diagnostic and treatment targets for cancer. And that, tumor biomarkers need to be detectable in easily accessible body samples, should be characterized by high specificity and sufficient sensitivity. Herein, it is significant clinical importance to screen and supplement new biomarkers for early diagnosis of lung cancer. This study aimed at systematically describing lncRNAs from five aspects based on recent studies: concepts, classification, structure, molecular mechanism, signal pathway, as well as review lncRNA implications in malignant tumor.

Expression profiles of long non-coding RNAs during fetal lung development

With advances in neonatology, a greater percentage of premature infants now survive and consequently, diseases of lung development, including bronchopulmonary dysplasia and neonatal respiratory distress syndrome, have become more common. However, few studies have addressed the association between fetal lung development and long non-coding RNA (lncRNA). In the present study, right lung tissue samples of fetuses at different gestational ages were collected within 2 h of the induction of labor in order to observe morphological discrepancies. An Affymetrix Human GeneChip was used to identify differentially expressed lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. A total of 687 lncRNAs were identified to be differentially expressed among three groups of fetal lung tissue samples corresponding to the three embryonic periods. A total of 34 significantly upregulated and 12 significantly downregulated lncRNAs (fold-change, ≥1.5; P<0.05) were detected at different time points (embryonic weeks 7-16, 16-25 and 25-28) of fetal lung development and compared with healthy tissues Expression changes in lncRNAs n340848, n387037, n336823 and ENST00000445168 were validated by reverse transcription-quantitative PCR and the results were consistent with the GeneChip results. These novel identified lncRNAs may have roles in fetal lung development and the results of the present study may lay the foundation for subsequent in-depth studies into lncRNAs in fetal lung development and subsequent clarification of the pathogenesis of neonatal pulmonary diseases.

Construction of a metastasis-associated ceRNA network reveals a prognostic signature in lung cancer

Background

Lung cancer is the most common cancer worldwide, and metastasis is the leading cause of lung cancer related death. However, the molecular network involved in lung cancer metastasis remains incompletely described. Here, we aimed to construct a metastasis-associated ceRNA network and identify a lncRNA prognostic signature in lung cancer.

Methods

RNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and gene set enrichment analysis (GSEA) were performed to investigate the function of these genes. Using Cox regression analysis, we found that a 6 lncRNA signature may serve as a candidate prognostic factor in lung cancer. Finally, we used Transwell assays with lung cancer cell lines to verify that LINC01010 acts as a tumor suppressor.

Results

We identified 1249 differentially expressed (DE) mRNAs, 440 DE lncRNAs and 26 DE miRNAs between nonmetastatic and metastatic lung cancer tissues. GO and KEGG analyses confirmed that the identified DE mRNAs are involved in lung cancer metastasis. Using bioinformatics tools, we constructed a metastasis-associated ceRNA network for lung cancer that includes 117 mRNAs, 23 lncRNAs and 22 miRNAs. We then identified a 6 lncRNA signature (LINC01287, SNAP25-AS1, LINC00470, AC104809.2, LINC00645 and LINC01010) that had the greatest prognostic value for lung cancer. Furthermore, we found that suppression of LINC01010 promoted lung cancer cell migration and invasion.

Conclusions

This study might provide insight into the identification of potential lncRNA biomarkers for diagnosis and prognosis in lung cancer.

MiR-509-3-5p-NONHSAT112228.2 Axis Regulates p21 and Suppresses Proliferation and Migration of Lung Cancer Cells

Background:

Although the involvement of individual microRNA and lncRNA in the regulation of p21 expression has largely been evidenced, less is known about the roles of functional interactions between miRNAs and lncRNAs in p21 expression. Our previous work demonstrated that miR-509- 3-5p could block cancer cell growth.

Methods:

To gain an insight into the role of miR-509-3-5p in the regulation of p21 expression, we performed in silico prediction and showed that miR-509-3-5p might target the NONHSAT112228.2, a sense-overlapping lncRNA transcribed by a non-code gene overlapping with p21 gene. Mutation and luciferase report analysis suggested that miR-509-3-5p could target NONHSAT112228.2, thereby blocking its expression. Consistently, NONHSAT112228.2 expression was inversely correlated with both miR-509-3-5p and p21 expression in cancer cells. Ectopic expression of miR-509-3-5p and knockdown of NONHSAT112228.2 both promoted proliferation and migration of cancer cells.

Results:

Interestingly, high-expression of NONHSAT112228.2 accompanied by low-expression of p21 was observed in lung cancer tissues and associated with lower overall survival.

Conclusion:

Taken together, our study found a new regulatory pathway of p21, in which MiR-509-3-5p functionally interacts with NONHSAT112228.2 to release p21 expression. MiR-509-3-5p— NONHSAT112228.2 regulatory axis can inhibit the proliferation and migration of lung cancer cells.

Biological regulation of diacylglycerol kinases in normal and neoplastic tissues: New opportunities for cancer immunotherapy

In the recent years, the arsenal of anti-cancer therapies has evolved to target T lymphocytes and restore their capacity to destroy tumor cells. However, the clinical success is limited, with a large number of patients that never responds and others that ultimately develop resistances. Overcoming the hypofunctional state imposed by solid tumors to T cells has revealed critical but challenging due to the complex strategies that tumors employ to evade the immune system. The Diacylglycerol kinases (DGK) limit DAG-dependent functions in T lymphocytes and their upregulation in tumor-infiltrating T lymphocytes contribute to limit T cell cytotoxic potential. DGK blockade could reinstate T cell attack on tumors, limiting at the same time tumor cell growth, thanks to the DGK positive input into several oncogenic pathways. In this review we summarize the latest findings regarding the regulation of specific DGK isoforms in healthy and anergic T lymphocytes, as well as their contribution to oncogenic phenotypes. We will also revise the latest advances in the search for pharmacological inhibitors and their potential as anti-cancer agents, either alone or in combination with immunomodulatory agents.

Genome-wide identification of lncRNAs and mRNAs differentially expressed in non-functioning pituitary adenoma and construction of an lncRNA-mRNA co-expression network

The involvement of long non-coding RNAs (lncRNAs) during tumorigenesis is a recent emerging theme. Yet no systematic evaluation of lncRNAs has been previously reported for non-functioning pituitary adenoma (NFPA), a fairly common type of intracranial tumor. Here, we report the first genome-wide expression profile for lncRNAs and mRNAs in NFPA, using formalin-fixed and paraffin-embedded tissue specimens. Using microarray analyses, we identified 113 lncRNAs and 80 mRNAs differentially expressed in NFPA; this list includes lncRNAs previously implicated in a variety of cancers. Using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) we further confirmed differential expression in NFPA for ten of the 113 lncRNAs. Using these ten doubly confirmed lncRNAs, we constructed an lncRNA-mRNA co-expression network comprising of 130 specific lncRNA-mRNA co-expression relationships. In addition, we conducted GO and KEGG analyses for the 80 mRNAs differentially expressed in NFPA. Our microarray and qRT-PCR analyses provided a working list of lncRNAs that may be functionally relevant to NFPA tumorigenesis. Our co-expression network in turn connected these largely uncharacterized lncRNAs to specific mRNAs, whose roles we further elucidated via GO and KEGG analyses, thus providing specific, testable hypotheses for the functions of these lncRNAs. Together, our study laid the foundation for future investigation of the specific function and mechanism by which lncRNAs are involved in NFPA tumorigenesis.

Summary statement: We identified long non-coding RNAs and mRNAs differentially expressed in non-functioning pituitary adenomas via microarray analyses, and provided working hypotheses for how these RNAs may function via co-expression network analyses.

Diagnostic efficacy of long non-coding RNA in lung cancer: a systematic review and meta-analysis

The detection of long non-coding RNA (lncRNA) is a novel method for lung cancer diagnosis. However, the diagnostic efficacy of lncRNA in different studies is inconsistent. Therefore, we conducted this meta-analysis to elucidate the diagnostic efficacy of lncRNA in identification of lung cancer including small cell lung cancer. The online PubMed, Medline, EMBASE, CNKI and Wanfang literature databases were searched to identify all related articles about the diagnostic efficacy of lncRNA for lung cancer. 28 articles including 3044 patients with lung cancer and 2598 controls were enrolled in our meta-analysis. lncRNA sustained a high diagnostic efficacy, pooled sensitivity of 0.82 (95% CI 0.79 to 0.84), specificity of 0.82 (95% CI 0.78 to 0.84) and area under the curve (AUC) of 0.88 (95% CI 0.85 to 0.91) in identification of patients with lung cancer from controls. Furthermore, the diagnostic efficacy of paralleled lncRNA was better than single lncRNA (sensitivity: 0.86 vs 0.80; specificity: 0.88 vs 0.78; AUC: 0.93 vs 0.86). MALAT1 had a better diagnostic efficacy than GAS5 (AUC: 0.90 vs 0.81; sensitivity: 0.83 vs 0.70; specificity: 0.83 vs 0.78). lncRNA in tissues was observed to achieve lower diagnostic efficacy than that in plasma or serum (AUC: 0.87 vs 0.90 vs 0.90) when stratified by sample types. In summary, our meta-analysis suggests that lncRNA might be a promising biomarker(s) for identifying lung cancer and the combination of lncRNA or with other biomarkers had a better diagnostic efficacy.

Long non-coding RNA-ENST00000434223 suppresses tumor progression in gastric cancer cells through the Wnt/β-catenin signaling pathway

BACKGROUND

Gastric cancer (GC) develops from the lining of the stomach. The present study aimed to explore the effects of long non-coding RNA-ENST00000434223 (lncRNA ENST00000434223) on gastric cancer (GC) cells.

METHODS

One hundred and four GC tissues and paracancerous tissues were collected from GC patients, and expression of ENST00000434223, Wnt2b, β-catenin, cyclinD1, E-cadherin, N-cadherin, vimentin, and snail was subsequently assessed. Morphological changes in cells were assessed using an inverted microscope, and expression of Bcl-2, Bax and caspase-3 was examined.

RESULTS

We found that expression of Wnt2b, β-catenin, cyclinD1, N-cadherin, vimentin, and snail was increased in GC tissues, while expression of ENST00000434223 and E-cadherin was decreased. SGC-7901 cells were closely arranged, and expression of Wnt2b, β-catenin, CyclinD1, N-cadherin, Vimentin, snail and Bcl-2 was increased, whereas expression of ENST00000434223, E-cadherin, Bax and caspase-3 was decreased. Furthermore, the rate of apoptosis was decreased and cell proliferation, invasion and migration were increased in response to downregulation of ENST00000434223. By contrast, upregulation of ENST00000434223 exhibited the opposite effects in MKN-45 cells.

CONCLUSION

The results of this study provide a promising experimental basis for the treatment of gastric cancer through interventional targeting of lncRNA ENST00000434223.

Knockdown of LINC01614 inhibits lung adenocarcinoma cell progression by up-regulating miR-217 and down-regulating FOXP1

We tried to identify the function of LINC01614 in lung adenocarcinoma (LUAD) and reveal its underlying mechanisms. qRT‐PCR was applied to assess the expression of LINC016014 in LUAD tissues, noncancerous tissues and cells. Through colony formation assay, MTT assay and apoptosis analysis, we examined the variation of cell proliferation and apoptosis ability after silencing LINC01614. Moreover, the targeting interactions among LINC01614, miR‐217 and FOXP1 were validated via luciferase reporter assay, and then, we regulated the expression of miR‐217 and FOXP1 to ascertain their importance in cell proliferation and apoptosis. LINC01614 and FOXP1 were found to be up‐regulated in LUAD tumours and cells, whereas miR‐217 was down‐regulated. The experiment showed that target‐specific selectivity exists between LINC01614‐miR‐217 and miR‐217‐FOXP1 3′UTR. Furthermore, we disclosed that inhibition of LINC01614 could activate miR‐217, which subsequently restrained FOXP1. It was proved that LINC01614 promoted FOXP1 by inhibiting miR‐217, which ultimately stimulated the development of LUAD.

Knockdown of Long Noncoding RNA ENST457720 Inhibits Proliferation of Non-Small Cell Lung Cancer Cells In Vitro and In Vivo

Non-small cell lung cancer (NSCLC) represents the leading cause of cancer-related mortality worldwide. More and more reports have identified important roles for long noncoding RNAs (lncRNAs) in cancer development. ENST457720 expression was upregulated in lung adenocarcinoma in a microarray-based lncRNA screen. We determined the expression levels of ENST457720 in NSCLC tissues with quantitative real-time PCR and then studied their clinical significance. We explored the biological significance of ENST457720 with gain- and loss-of-function analyses in vitro and in vivo. In this study, ENST457720 was expressed at higher levels in NSCLC tissues than in paired normal tissues. Higher ENST457720 expression was associated with larger tumor sizes, lymph node metastasis, and advanced TNM stage. ENST457720 silencing suppressed NSCLC cell proliferation in vitro and in vivo. Moreover, ENST457720 knockdown inhibited NSCLC invasion and reversed the epithelial-to-mesenchymal transition. ENST457720 promoted NSCLC proliferation and invasion, which may be a novel potential therapeutic target for NSCLC.

Lung cancer: a brief review of epidemiology and screening

The global burden of lung cancer has been increasing over the past years, and is still a major threat to public health worldwide, leading to disabilities and premature mortality. Despite multifactorial cause, smoking remains as the major etiological factor, followed by occupational exposure to carcinogens, genetic predisposition and other concomitant diseases. In order to reduce the individual and social burden due to the direct and indirect costs related to the lung cancer treatment, accurate methods of screening are needed. Among those, x-ray with cytological analysis of sputum was first proposed. Nowadays, more sensitive methods such as low-dose computed tomography are being used to improve the early detection. In the future, molecular biomarkers may complement low-dose computed tomography and improve the robustness of early lung cancer detection.

TPGLDA: Novel prediction of associations between lncRNAs and diseases via lncRNA-disease-gene tripartite graph

Accumulating evidences have indicated that lncRNAs play an important role in various human complex diseases. However, known disease-related lncRNAs are still comparatively small in number, and experimental identification is time-consuming and labor-intensive. Therefore, developing a useful computational method for inferring potential associations between lncRNAs and diseases has become a hot topic, which can significantly help people to explore complex human diseases at the molecular level and effectively advance the quality of disease diagnostics, therapy, prognosis and prevention. In this paper, we propose a novel prediction of lncRNA-disease associations via lncRNA-disease-gene tripartite graph (TPGLDA), which integrates gene-disease associations with lncRNA-disease associations. Compared to previous studies, TPGLDA can be used to better delineate the heterogeneity of coding-non-coding genes-disease association and can effectively identify potential lncRNA-disease associations. After implementing the leave-one-out cross validation, TPGLDA achieves an AUC value of 93.9% which demonstrates its good predictive performance. Moreover, the top 5 predicted rankings of lung cancer, hepatocellular carcinoma and ovarian cancer are manually confirmed by different relevant databases and literatures, affording convincing evidence of the good performance as well as potential value of TPGLDA in identifying potential lncRNA-disease associations. Matlab and R codes of TPGLDA can be found at following: https://github.com/USTC-HIlab/TPGLDA .

Long noncoding RNA profiling revealed differentially expressed lncRNAs associated with disease activity in PBMCs from patients with rheumatoid arthritis

Long noncoding RNAs (lncRNAs) have recently emerged as important biological regulators, and the aberrant expression of lncRNAs has been reported in numerous diseases. However, the expression of lncRNAs in peripheral blood mononuclear cells (PBMCs) in rheumatoid arthritis (RA) has not been well documented. We applied a microarray analysis to profile the lncRNA and mRNA expression in 3 pairs of samples. Each sample was mixed with equivalent PBMCs from 9 female RA patients and 9 corresponding healthy controls, and the data were validated via qPCR using another cohort that comprised 36 RA patients and 24 healthy controls. A bioinformatic analysis was performed to investigate the potential functions of differentially expressed genes. Overall, 2,099 lncRNAs and 2,307 mRNAs were differentially expressed between the RA patients and healthy controls. The bioinformatic analysis indicated that the differentially expressed lncRNAs regulated the abnormally expressed mRNAs, which were involved in the pathogenesis of RA through several different pathways. The qPCR results showed that the expression levels of ENST00000456270 and NR_002838 were significantly increased in the RA patients, whereas the expression levels of NR_026812 and uc001zwf.1 were significantly decreased. Furthermore, the expression level of ENST00000456270 was strongly associated with the serum levels of IL-6 and TNF-a and the Simplified Disease Activity Index (SDAI) of the RA patients. Our data provided comprehensive evidence regarding the differential expression of lncRNAs in PBMCs of RA patients, which shed light on the understanding of the molecular mechanisms of lncRNAs in the pathogenesis of RA.

Expression of long non‑coding RNAs in chondrocytes from proximal interphalangeal joints

Osteoarthritis (OA) of hand is a common disease, resulting in disability of the hands. The pathogenesis of hand (H) OA remains to be elucidated, and findings from knee and hip joints cannot be simply applied to HOA. To improve knowledge on the specific biology and pathobiology of HOA, the present study performed bioinformatics analyses to analyze the long non-coding (lnc) RNA expression profile in human chondrocytes of proximal interphalangeal (PIP) finger joints and knee joints. Gene expression data were downloaded from the Gene Expression Omnibus database, and PIP and knee chondrocytes were analyzed (n=3/group). Probes of the Affymetrix Human Gene 2.0 ST Microarray were annotated to obtain information about lncRNA expression profile. Compared with chondrocytes from knee joints, chondrocytes derived from PIP joints had significantly different lncRNA expression profiles, and 1,172 lncRNAs were differentially expressed. Compared with chondrocyte from knee joints, 534 lncRNAs were upregulated and 638 lncRNAs were downregulated in chondrocytes from PIP joints. A co-expression network was constructed to analyze the correlation between lncRNAs and protein-coding genes. Function annotation analyses suggested that protein-coding genes that are co-expressed with lncRNAs are enriched in the biological processes of bone morphogenesis, bone development and cartilage development. In conclusion, the present study demonstrated that chondrocytes derived from PIP joints exhibit a significant difference in lncRNA expression compared with chondrocytes derived from knee joints.

Intersecting transcriptomic profiling technologies and long non-coding RNA function in lung adenocarcinoma: discovery, mechanisms, and therapeutic applications

Previously thought of as junk transcripts and pseudogene remnants, long non-coding RNAs (lncRNAs) have come into their own over the last decade as an essential component of cellular activity, regulating a plethora of functions within multicellular organisms. lncRNAs are now known to participate in development, cellular homeostasis, immunological processes, and the development of disease. With the advent of next generation sequencing technology, hundreds of thousands of lncRNAs have been identified. However, movement beyond mere discovery to the understanding of molecular processes has been stymied by the complicated genomic structure, tissue-restricted expression, and diverse regulatory roles lncRNAs play. In this review, we will focus on lncRNAs involved in lung cancer, the most common cause of cancer-related death in the United States and worldwide. We will summarize their various methods of discovery, provide consensus rankings of deregulated lncRNAs in lung cancer, and describe in detail the limited functional analysis that has been undertaken so far.

Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma

Lung adenocarcinoma (LADC) and squamous cell carcinoma (LSCC) are the most common non-small cell lung cancer histological phenotypes. Accurate diagnosis distinguishing between these two lung cancer types has clinical significance. For this study, we analyzed four Gene Expression Omnibus (GEO) datasets (GSE28571, GSE37745, GSE43580, and GSE50081). We then imported the datasets into the Gene-Cloud of Biotechnology Information online platform to identify genes differentially expressed in LADC and LSCC. We identified DSG3 (desmoglein 3), KRT5 (keratin 5), KRT6A (keratin 6A), KRT6B (keratin 6B), NKX2-1 (NK2 homeobox 1), SFTA2 (surfactant associated 2), SFTA3 (surfactant associated 3), and TMC5 (transmembrane channel-like 5) as potential biomarkers for distinguishing between LADC and LSCC. Receiver operating characteristic curve analysis suggested that KRT5 had the highest diagnostic value for discriminating between these two cancer types. Using the PrognoScan online survival analysis tool and the Kaplan-Meier Plotter, we found that high KRT6A or KRT6B levels, or low NKX2-1, SFTA3, or TMC5 levels correlated with unfavorable prognoses in LADC patients. Further studies will be needed to verify our findings in additional patient samples, and to elucidate the mechanisms of action of these potential biomarkers in non-small cell lung cancer.

Identification of long noncoding RNAs for the detection of early stage lung squamous cell carcinoma by microarray analysis

The aberrant expressions of long noncoding RNAs have been reported in numerous cancers, which have facilitated the cancer diagnosis. However, the expression profile of lncRNAs in early stage lung squamous cell carcinoma has not been well discussed. The present study aimed to examine the expression profile of lncRNAs in early stage lung squamous cell carcinoma and identify lncRNA biomarkers for diagnosis. Through high-throughput lncRNA microarray, we screened thousands of aberrantly expressed lncRNAs and mRNAs in early stage lung squamous cell carcinoma tissues compared to their corresponding adjacent nontumorous tissues. Bioinformatics analyses were used to investigate the functions of aberrantly expressed mRNAs and their associated lncRNAs. After that, in order to identify lncRNA biomarkers for early detection, candidate lncRNA biomarkers were selected based on our established filtering pipeline and validated by real-time quantitative polymerase chain reaction on a total of 63 pairs of tumor samples. Five lncRNAs were finally identified which were able to distinguish early stage tumor and normal samples with high sensitivity (92%) and specificity (83%). These results imply that lncRNAs may be powerful biomarker for early diagnosis.

Microarray expression profile analysis of mRNAs and long non-coding RNAs in pulmonary tuberculosis with different traditional Chinese medicine syndromes

Background

Combination chemotherapy with Western anti-tuberculosis (TB) drugs is the mainstay of TB treatment. Chinese herbal medicines with either heat clearing and detoxifying effects or nourishing Yin and reducing fire effects have been used to treat TB based on the Traditional Chinese Medicine (TCM) syndromes of TB patients. This study analyzed the expression profiles of long non-coding RNAs (lncRNAs) and mRNAs in TB patients with different TCM syndromes.

Methods

TB patients were classified as pulmonary Yin deficiency (PYD) syndrome, hyperactivity of fire due to Yin deficiency (HFYD) syndrome, and deficiency of Qi and Yin (DQY) syndrome. Total RNA from 44 TB patients and healthy controls was extracted and hybridized with a human lncRNA microarray containing 30586 lncRNAs and 26109 mRNAs probes. Bioinformatics analyses, including gene ontology (GO) and pathways, were performed. Related clinical data were also analyzed.

Results

Differentially expressed mRNAs and lncRNAs were identified (fold change >2, and P < 0.05) in PYD (634 mRNAs and 566 lncRNAs), HFYD (47 mRNAs and 55 lncRNAs), and DQY (63 mRNAs and 60 lncRNAs) patients. The most enriched pathways were the hippo signaling pathway (P = 0.000164) and the protein digestion and absorption pathway (P = 5.89017E-05). Clinical analyses revealed that the lipid indexes of TB patients were abnormal and that the triglyceride concentration was significantly higher in DQY patients (P = 0.0252). Our study is the first to acquire the microarray expression profiles of lncRNAs and mRNAs and analyze pathway enrichment in PYD, HFYD, and DQY patients with TB.

Conclusions

Our analyses of the expression profiles of lncRNAs and mRNAs may represent a novel method to explore the biological essence of TCM syndromes of TB.

Electronic supplementary material

The online version of this article (doi:10.1186/s12906-016-1436-y) contains supplementary material, which is available to authorized users.

Long noncoding RNA ENST00000434223 suppressed tumor progression in non-small cell lung cancer

In spite of the fact that the great progress has been made in the treatment of non-small cell lung cancer (NSCLC), the prognosis of NSCLC remains comparatively dismal. Therefore, it is of great value to identify novel effective diagnostic biomarkers and therapeutic targets of NSCLC. Emerging evidence has demonstrated the vital roles of long noncoding RNAs (lncRNAs) in cancer development. ENST00000434223 was recently identified as a lncRNA that is downregulated in early stage lung adenocarcinoma in a profiling study. However, little is known about its role in the development of NSCLC. In the present study, we found that ENST00000434223 was greatly downregulated in cancer tissues compared to adjacent normal tissues. ENST00000434223 overexpression suppressed the proliferation and migration in NSCLC cell lines in vitro. Moreover, ENST00000434223 overexpression reversed the epithelial-mesenchymal transition in NSCLC cell line. Our study suggests that ENST00000434223 may be a potential biomarker and a therapeutic target of NSCLC.

Microarray expression profiling of dysregulated long non-coding RNAs in Hirschsprung's disease reveals their potential role in molecular diagnosis

BACKGROUND

Hirschsprung's disease (HSCR) is one of the common digestive disorders in the new born. Long non-coding RNAs (lncRNAs) play an important role in various biological processes. However, knowledge on lncRNAs in HSCR is limited.

METHODS

The expression profile of lncRNAs in HSCR was obtained using microarray. A total of 2078 differentially expressed lncRNAs were detected by microarray in HSCR tissues compared with matched normal colon tissues (fold change ≥2, p < 0.05). Candidate biomarkers were selected from these differentially expressed lncRNAs based on artificial criterion (raw signal intensity ≥50; fold change ≥8) and then validated in 80 pairs of HSCR and normal tissues using quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the computational analysis was used to evaluate the lncRNA-microRNA and lncRNA-protein relationships.

KEY RESULTS

A panel of 5-lncRNAs was identified to distinguish HSCR from normal tissues with remarkable sensitivity and specificity. The area under the receiver operating characteristic curve (AUC) for HSCR identification in the validation set was 0.875. The bioinformatics analysis reveals that these dysregulated lncRNAs are mainly involved in RNA-protein relationships, including RNA splicing, binding, transport, processing, and localization.

CONCLUSIONS & INFERENCES

Our results are the first to report the expression profile of dysregulated lncRNAs in HSCR and infer that lncRNAs may serve as novel diagnostic biomarkers for HSCR.

Long noncoding RNAs: new insights into non-small cell lung cancer biology, diagnosis and therapy

Recent advances in tiling array and high throughput analyses revealed that at least 87.3 % of the human genome is actively transcribed, though <3 % of the human genome encodes proteins. This unexpected truth suggests that most of the transcriptome is constituted by noncoding RNA. Among them, high-resolution microarray and massively parallel sequencing analyses identified long noncoding RNAs (lncRNAs) as nonprotein-coding transcripts. lncRNAs are largely polyadenylated and >200 nucleotides in length transcripts, involved in gene expression through epigenetic and transcriptional regulation, splicing, imprinting and subcellular transport. Although lncRNAs functions are largely uncharacterized, accumulating data indicate that they are involved in fundamental biological functions. Conversely, their dysregulation has increasingly been recognized to contribute to the development and progression of several human malignancies, especially lung cancer, which represents the leading cause of cancer-related deaths worldwide. We conducted a comprehensive review of the published literature focusing on lncRNAs function and disruption in nonsmall cell lung cancer biology, also highlighting their value as biomarkers and potential therapeutic targets. lncRNAs are involved in NSCLC pathogenesis, modulating fundamental cellular processes such as proliferation, cell growth, apoptosis, migration, stem cell maintenance and epithelial to mesenchymal transition, also serving as signaling transducers, molecular decoys and scaffolds. Also, lncRNAs represent very promising biomarkers in early-stage NSCLC patients and may become particularly useful in noninvasive screening protocols. lncRNAs may be used as predictive biomarkers for chemotherapy and targeted therapies sensitivity. Furthermore, selectively targeting oncogenic lncRNAs could provide a new therapeutic tool in treating NSCLC patients. lncRNAs disruption plays a pivotal role in NSCLC development and progression. These molecules also serve as diagnostic, prognostic and predictive biomarkers. Characterization of lncRNA genes and their mechanisms of action will enable us to develop a more comprehensive clinical approach, with the final goal to benefit our patients.

Long noncoding RNAs in lung cancer: what we know in 2015

Lung cancer ranks as the first most common cancer and the first leading cause of cancer-related death in China and worldwide. Due to the difficulty in early diagnosis and the onset of cancer metastasis, the 5-year survival rate of lung cancer remains extremely low. Long noncoding RNAs (lncRNAs), which lacking protein-coding ability, have recently emerged as pivotal participants in biological processes, often dysregulated in a range of cancers, including lung cancer. In this review, we highlight the recent findings of lncRNAs in lung cancer pathogenesis. While our understanding of lncRNAs in the onset and progression of lung cancer is still in its infancy, there is no doubt that understanding the activities of lncRNAs will certainly secure strong biomarkers and improve treatment options for lung cancer patients.

Emerging role of long noncoding RNAs in lung cancer: Current status and future prospects

Lung cancer is the leading cause of cancer-related death worldwide with a 5-year survival rate of less than 15%, despite significant advances in both diagnostic and therapeutic approaches. Combined genomic and transcriptomic sequencing studies have identified numerous genetic driver mutations that are responsible for the development of lung cancer. Importantly, these approaches have also uncovered the widespread expression of "noncoding RNAs" including long noncoding RNAs (LncRNAs), which impact biologic responses through the regulation of mRNA transcription or translation. To date, most studies of the role of noncoding RNAs have focused on LncRNAs, which regulate mRNA translation via the RNA interference pathway. Although many of their attributes, such as patterns of expression, remain largely unknown, LncRNAs have key functions in transcriptional, post-transcriptional, and epigenetic gene regulation. Recent research showed that LncRNAs regulate flowering time in the lung cancer. In this review, we discuss these investigations into long noncoding RNAs were performed almost exclusively in lung cancer. Future work will need to extend these into lung cancer and to analyze how LncRNAs interact to regulate mRNA expression. From a clinical perspective, the targeting of LncRNAs as a novel therapeutic approach will require a deeper understanding of their function and mechanism of action.