Identification of mitochondrial function‐associated lncRNAs in septic mice myocardium

The present study aimed to analyze long noncoding RNA (lncRNA) and messenger RNA (mRNA) expression profiles in septic mice heart and to identify potential lncRNAs and mRNAs that be responsible for cardiac mitochondrial dysfunction during sepsis. Mice were treated with 10 mg/kg of lipopolysaccharides to induce sepsis. LncRNAs and mRNAs expression were evaluated by using lncRNA and mRNA microarray or real‐time polymerase chain reaction technique. LncRNA‐mRNA coexpression network assay, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed. The results showed that 1275 lncRNAs were differentially expressed in septic myocardium compared with those in the control group. A total of 2769 mRNAs were dysregulated in septic mice heart, most of which are mainly related to the process of inflammation, mitochondrial metabolism, oxidative stress, and apoptosis. Coexpression network analysis showed that 14 lncRNAs were highly correlated with 11 mitochondria‐related differentially expressed mRNA. Among all lncRNAs and their cis‐acting mRNAs, 41 lncRNAs‐mRNA pairs (such as NONMMUG004378 and Apaf1 gene) were enriched in GO terms and KEGG pathways. In summary, we gained some specific lncRNAs and their potential target mRNAs that might be involved in mitochondrial dysfunction in septic myocardium. These findings provide a panoramic view of lncRNA and might allow developing new treatment strategies for sepsis.     

Microarray analysis of long-noncoding RNAs and mRNA expression profiles in human steroid-induced avascular necrosis of the femoral head

This study performed the first microarray analysis of long-noncoding RNA (lncRNA) and mRNA expression profiles in human steroid-induced avascular necrosis of the femoral head (SAVNFH). Expression levels of lncRNAs and mRNAs in three human SAVNFH samples and three human femoral head fracture samples (controls) were detected using third-generation lncRNA microarrays (KangChen Biotech, Shanghai, China). The fold change, false discovery rate, and P value were utilized to filter genes with significant differential expression in the SAVNFH samples compared with the control samples. In total, there were 1179 upregulated and 3214 downregulated lncRNAs (P2. zerofold, P < 0.05). Meanwhile, 1092 upregulated and 565 downregulated mRNAs were found in the SAVNFH samples compared with the control samples. Then, quantitative real-time polymerase chain reaction was used to confirm the previous microarray results using 8 and 20 selected dysregulated lncRNAs and mRNAs, respectively, and the results generally confirmed the microarray findings. Finally, we used Gene Ontology (GO) and pathway analysis to investigate the functions of the altered mRNAs and their associated GO terms and biological pathways. The Immune system process term (GO:0002376) was the most significantly upregulated GO term, and the Regulation of blood coagulation term (GO:0030193) was the most significantly downregulated GO term in the biological process category for the SAVNFH samples. “Hematopoietic cell lineage - Homo sapiens (human) (Pathway ID: hsa04640)” and “Complement and coagulation cascades - Homo sapiens (human) (Pathway ID: hsa04610)” were the most significantly up- and downregulated pathways in the SAVNFH samples compared with the controls. In conclusion, the differential expression of lncRNAs and mRNAs may be correlated with the pathogenesis of SAVNFH, and these significantly dysregulated lncRNAs and mRNAs may function through networks or participate in several specific biological processes. Further research is needed to understand their exact functions and mechanisms in SAVNFH.     

Distinct Hippocampal Expression Profiles of Long Non-coding RNAs in an Alzheimer’s Disease Model

Alzheimer’s disease (AD), the most prevalent form of dementia worldwide, is a complex neurodegenerative disease characterized by the progressive loss of memory and other cognitive functions. The pathogenesis of AD is not yet completely understood. Although long non-coding RNAs (lncRNAs) have recently been shown to play a role in AD pathogenesis, the specific influences of lncRNAs in AD remain largely unknown; in particular, hippocampal lncRNA expression profiles in AD rats are lacking. In this study, microarray analysis was performed to investigate the hippocampal expression patterns of dysregulated lncRNAs in a rat model of AD. A total of 315 lncRNAs and 311 mRNAs were found to be significantly dysregulated in the AD model (≥2.0 fold, p < 0.05). Then, quantitative real-time PCR was used to validate the expression of selected lncRNAs and mRNAs. Bioinformatics tools and databases were employed to explore the potential lncRNA functions. This is the first study to comprehensively identify dysregulated hippocampal lncRNAs in AD and to demonstrate the involvement of different lncRNA expression patterns in the hippocampal pathogenesis of AD. This information will enable further research on the pathogenesis of AD and facilitate the development of novel AD therapeutics targeting lncRNAs.     

Investigation of Long Non-coding RNA Expression Profiles in the Substantia Nigra of Parkinson’s Disease

Genetics is considered as an important risk factor in the pathological changes of Parkinson’s disease (PD). Substantia nigra (SN) is thought to be the most vulnerable area in this process. In recent decades, however, few related long non-coding RNAs (lncRNAs) in the SN of PD patients had been identified and the functions of those lncRNAs had been studied even less. In this study, we sought to investigate the lncRNA expression profiles and their potential functions in the SN of PD patients. We screened lncRNA expression profiles in the SN of PD patients using the lncRNA mining approach from the ArrayExpress database, which included GSE20295. The samples were from 11 of PD and 14 of normal tissue samples. We identified 87 lncRNAs that were altered significantly in the SN during the occurrence of PD. Among these lncRNAs, lncRNA AL049437 and lncRNA AK021630 varied most dramatically. AL049437 was up-regulated in the PD samples, while AK021630 was down-regulated. Based on the results, we focused on the potential roles of the two lncRNAs in the pathogenesis of PD by the knockdown of the expression of AL049437 or AK021630 in human neuroblastoma SH-SY5Y cell line. Results indicated that the reduction in AL049437 level increased cell viability, mitochondrial transmembrane potential (Δψm), mitochondrial mass, and tyrosine hydroxylase (TyrH) secretion. By contrast, the knockdown of AK021630 resulted in the opposite effect. Based on these results, we speculated that lncRNA AL049437 likely contributed to the risk of PD, while lncRNA AK021630 likely inhibited the occurrence of PD.     

An eight-long noncoding RNA expression signature for colorectal cancer patients’ prognosis

Long noncoding RNAs (lncRNAs) have recently emerged as important biomarkers of cancer progression. Here, we proposed to develop a lncRNA-based signature with a prognostic value for colorectal cancer (CRC) overall survival (OS). Through mining microarray datasets, we analyzed the lncRNA expression profiles of 122 patients with CRC from Gene Expression Omnibus. Associations between lncRNA and CRC OS were firstly evaluated through univariate Cox regression analysis. A random survival forest method was applied for further screening of the lncRNA signature, which resulted in eight lncRNAs, including PEG3-AS1, LOC100505715, MINCR, DBH-AS1, LINC00664, FAM224A, LOC642852, and LINC00662. Combination of the eight lncRNAs weighted by their multivariate Cox regression coefficients formed a prognostic signature, through which, we could divide the 122 patients with CRC into two subgroups with significantly different OS. Good robustness of the lncRNA signature's prognostic value was verified through an independent data set consisting of 55 patients with CRC. In addition, gene set enrichment analysis indicated the potential association between high prognostic value and oxygen metabolism-related processes. This result should indicate that lncRNAs could be a useful signature for CRC prognosis.     

Role of long non‐coding RNA MIAT in proliferation,apoptosis and migration of lens epithelial cells: a clinical and in vitro study

Age‐related cataract is among the most common chronic disorders of ageing and is the world's leading blinding disorder. Long non‐coding RNAs play important roles in several biological processes and complicated diseases. However, the role of lncRNAs in the setting of cataract is still unknown. Here, we extracted total RNAs from the transparent and age‐matched cataractous human lenses, and determined lncRNA expression profiles using microarray analysis. We found that 38 lncRNAs were differentially expressed between transparent and cataractous lenses. 17 of 20 differentially expressed lncRNAs were further verified by quantitative RT‐PCRs. One top abundant lncRNA, MIAT, was specifically up‐regulated both in the plasma fraction of whole blood and aqueous humor of cataract patients. MIAT knockdown could affect the proliferation, apoptosis and migration of Human lens epithelial cells (HLECs) upon oxidative stress. Posterior capsule opacification (PCO) is a common complication of cataract surgery, which is associated with abnormal production of inflammatory factors. MIAT knockdown could repress tumour necrosis factor‐α‐induced abnormal proliferation and migration of HLECs, suggesting a potential role of MIAT in PCO‐related pathological process. Moreover, we found that MIAT acted as a ceRNA, and formed a feedback loop with Akt and miR‐150‐5p to regulate HLEC function. Collectively, this study provides a novel insight into the pathogenesis of age‐related cataract.     

Novel biomarkers for post-contrast acute kidney injury identified from long non-coding RNA expression profiles

Background: Post-contrast acute kidney injury (PC-AKI) is a severe complication of cardiac catheterization. Emerging evidence indicated that long non-coding RNAs (lncRNAs) could serve as biomarkers for various diseases. However, the lncRNA expression profile and potential biomarkers in PC-AKI remain unclear. This study aimed to investigate novel lncRNA biomarkers for the early detection of PC-AKI.Methods: lncRNA profile in the kidney tissues of PC-AKI rats was evaluated through RNA sequencing. Potential lncRNA biomarkers were identified through human-rat homology analysis, kidney and blood filtering in rats and verified in 112 clinical samples. The expression patterns of the candidate lncRNAs were detected in HK-2 cells and rat models to evaluate their potential for early detection.Results: In total, 357 lncRNAs were found to be differentially expressed in PC-AKI. We identified lnc-HILPDA and lnc-PRND were conservative and remarkably upregulated in both kidneys and blood from rats and the blood of PC-AKI patients; these lncRNAs can precisely distinguish PC-AKI patients (area under the curve (AUC) values of 0.885 and 0.875, respectively). The combination of these two lncRNAs exhibited improved accuracy for predicting PC-AKI, with 100% sensitivity and 83.93% specificity. Time-course experiments showed that the significant difference was first noted in the blood of PC-AKI rats at 12 h for lnc-HILPDA and 24 h for lnc-PRND.Conclusion: Our study revealed that lnc-HILPDA and lnc-PRND may serve as the novel biomarkers for early detection and profoundly affect the clinical stratification and strategy guidance of PC-AKI.     

A prognostic 11 long noncoding RNA expression signature for breast invasive carcinoma

Breast cancer, the most common cancer in women worldwide, is associated with high mortality. The long non-coding RNAs (lncRNAs) with a little capacity of coding proteins is playing an increasingly important role in the cancer paradigm. Accumulating evidences demonstrate that lncRNAs have crucial connections with breast cancer prognosis while the studies of lncRNAs in breast cancer are still in its primary stage. In this study, we collected 1052 clinical patient samples, a comparatively large sample size, including 13 159 lncRNA expression profiles of breast invasive carcinoma (BRCA) from The Cancer Genome Atlas database to identify prognosis-related lncRNAs. We randomly separated all of these clinical patient samples into training and testing sets. In the training set, we performed univariable Cox regression analysis for primary screening and played the model for Robust likelihood-based survival for 1000 times. Then 11 lncRNAs with a frequency more than 600 were selected for prediction of the prognosis of BRCA. Using the analysis of multivariate Cox regression, we established a signature risk-score formula for 11 lncRNA to identify the relationship between lncRNA signatures and overall survival. The 11 lncRNA signature was validated both in the testing and the complete set and could effectively classify the high-/low-risk group with different OS. We also verified our results in different stages. Moreover, we analyzed the connection between the 11 lncRNAs and the genes of ESR1, PGR, and Her2, of which protein products (ESR, PGR, and HER2) were used to classify the breast cancer subtypes widely. The results indicated correlations between 11 lncRNAs and the gene of PGR and ESR1. Thus, a prognostic model for 11 lncRNA expression was developed to classify the BRAC clinical patient samples, providing new avenues in understanding the potential therapeutic methods of breast cancer.     

Identification of key lncRNAs in the carcinogenesis and progression of colon adenocarcinoma by co-expression network analysis

Colon adenocarcinoma (COAD) is one of the most common cancers, and its carcinogenesis and progression is influenced by multiple long non-coding RNAs (lncRNA), especially through the miRNA sponge effect. In this study, more than 4000 lncRNAs were re-annotated from the microarray datasets through probe sequence mapping to obtain reliable lncRNA expression profiles. As a systems biology method for describing the correlation patterns among genes across microarray samples, weighted gene co-expression network analysis was conducted to identify lncRNA modules associated with the five stepwise stages from normal colonic samples to COAD (n = 94). In the most relevant module (R² = −0.78, P = 4E-20), four hub lncRNAs were identified (CTD-2396E7.11, PCGF5, RP11-33O4.1, and RP11-164P12.5). Then, these four hub lncRNAs were validated using two other independent datasets including GSE20916 (n = 145) and GSE39582 (n = 552). The results indicated that all hub lncRNAs were significantly negatively correlated with the three-stage colonic carcinogenesis, as well as TNM stages in COAD (one-way analysis of variance P < 0.05). Kaplan-Meier survival curve showed that patients with higher expression of each hub lncRNA had a significantly higher overall survival rate and lower relapse risk (log-rank P < 0.05). In conclusion, through co-expression analysis, we identified and validated four key lncRNAs in association with the carcinogenesis and progression of COAD, and these lncRNAs might have important clinical implications for improving the risk stratification, therapeutic decision and prognosis prediction in COAD patients.     

LncRNAs Expression in Preeclampsia Placenta Reveals the Potential Role of LncRNAs Contributing to Preeclampsia Pathogenesis

Background

Long non-coding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. They are aberrantly expressed in many types of diseases. In this study, we aimed to investigate the lncRNA profiles in preeclampsia. Preeclampsia has been observed in patients with molar pregnancy where a fetus is absent, which demonstrate that the placenta is sufficient to cause this condition. Thus, we analyzed the lncRNA profiles in preeclampsia placentas.

Methodology/Principal Findings

In this study, we described the lncRNA profiles in six preeclampsia placentas (T) and five normal pregnancy placentas (N) using microarray. With abundant and varied probes accounting for 33,045 LncRNAs in our microarray, 28,443 lncRNAs that were expressed at a specific level were detected. From the data, we found 738 lncRNAs that were differentially expressed (≥1.5-fold-change) among preeclampsia placentas compared with controls. Coding-non-coding gene co-expression networks (CNC network) were constructed based on the correlation analysis between the differentially expressed lncRNAs and mRNAs. According to the CNC network and GO analysis of differentially expressed lncRNAs/mRNAs, we selected three lncRNAs to analyze the relationship between lncRNAs and preeclampsia. LOC391533, LOC284100, and CEACAMP8 were evaluated using qPCR in 40 preeclampsia placentas and 40 controls. These results revealed that three lncRNAs were aberrantly expressed in preeclampsia placentas compared with controls.

Conclusions/Significance

Our study is the first study to determine the genome-wide lncRNAs expression patterns in preeclampsia placenta using microarray. These results revealed that clusters of lncRNAs were aberrantly expressed in preeclampsia placenta compared with controls, which indicated that lncRNAs differentially expressed in preeclampsia placenta might play a partial or key role in preeclampsia development. Misregulation of LOC391533, LOC284100, and CEACAMP8 might contribute to the mechanism underlying preeclampsia. Taken together, this study may provide potential targets for the future treatment of preeclampsia and novel insights into preeclampsia biology.     

Long noncoding RNA expression profiles in chondrogenic and hypertrophic differentiation of mouse mesenchymal stem cells

Long noncoding RNAs (lncRNAs) are important regulators for a variety of biological processes. Chondrogenic differentiation of mesenchymal stem cells (MSCs) is a crucial stage in chondrogenesis while chondrocyte hypertrophy is related to endochondral ossification and osteoarthritis. However, the effects of lncRNAs on chondrogenic and hypertrophic differentiation of mouse MSCs are unclear. To explore the potential mechanisms of lncRNAs during chondrogenesis and chondrocyte hypertrophy, microarray was performed to investigate the expression profiles of lncRNA and mRNA in MSCs, pre-chondrocytes, and hypertrophic chondrocytes. Then, we validated microarray data by RT-PCR and screened three lncRNAs from upregulating groups during chondrogenesis and chondrocyte hypertrophy respectively. After downregulating any of the above lncRNAs, we found that the expression of chondrogenesis-related genes such as Sox9 and Col2a1 and hypertrophy-related genes including Runx2 and Col10a1 was inhibited, respectively. Furthermore, the target genes of above lncRNAs were predicted by bioinformatics approaches. Gene ontology and Kyoto encyclopedia of genes and genome biological pathway analysis were also made to speculate the functions of above lncRNAs. In conclusion, the study first revealed the expression profile of lncRNAs in chondrogenic and hypertrophic differentiations of mouse MSCs and presented a new prospect for the underlying mechanisms of chondrogenesis and endochondral ossification.     

The Use of Three Long Non-Coding RNAs as Potential Prognostic Indicators of Astrocytoma

Long noncoding RNAs (lncRNAs) are pervasively transcribed and play a key role in tumorigenesis. The aim of the study was to determine the lncRNA expression profile in astrocytomas and to assess its potential clinical value. We performed a three-step analysis to establish the lncRNA profile for astrocytoma: a) the lncRNA expression was examined on 3 astrocytomas as well as 3 NATs (normal adjacent tissues) using the lncRNA microarray; b) the top-hits were validated in 40 astrocytomas (WHO grade II-IV) by quantitative real time-PCR (qRT-PCR); c) the hits with significant differences were re-evaluated using qRT-PCR in 90 astrocytomas. Finally, 7 lncRNAs were found to have a significantly different expression profile in astrocytoma samples compared to the NAT samples. Unsupervised clustering analysis further revealed the potential of the 7-lncRNA profile to differentiate between tumors and NAT samples. The upregulation of ENST00000545440 and NR_002809 was associated with advanced clinical stages of astrocytoma. Using Kaplan-Meier survival analysis, we showed that the low expression of BC002811 or XLOC_010967, or the high expression of NR_002809 was significantly associated with poor patient survival. Moreover, Cox proportional hazard regression analysis revealed that this prognostic impact was independent of other clinicopathological factors. Our results indicate that the lncRNA profile may be a potential prognostic biomarker for the prediction of post-surgical outcomes.     

Integrative analysis of OIP5-AS1/HUR1 to discover new potential biomarkers and therapeutic targets in multiple sclerosis

Multiple sclerosis (MS) is a devastating autoimmune disease of the central nervous system associated with demyelination and axonal injury. This study was designed to find potential lncRNAs and their targets that are associated with the molecular basis of MS pathogenesis. In this study, peripheral blood samples were obtained from 50 relapsing-remitting MS (RR-MS) patients and 50 healthy controls. lncRNAs and their target were selected for validation using TaqMan Real-Time PCR. Interactions were studied based on approaches that used to investigation biological functions and signaling pathways affected by differentially expressed messenger RNAs (mRNAs). The results of this study indicate an increase in the expression of HUR1 (p = 0.0001), CPSF7 (p = 0.02), and reduction of CSTF2 expression (p = 0.04). Also, an increase in the expression of OIP5-AS1 (p = 0.01) was observed in men less than 30 years old. We performed a comparative analysis of the long noncoding RNAs (lncRNAs), and then we ranked them as candidate biomarkers according to a decreasing area under the receiver operating characteristic (ROC) curve (AUC) and plotted the results. Dysregulation of lncRNA expression has been linked to diseases. Further studies on the HUR1 gene can be used as diagnostic tools for the identification of high-risk individuals in families with a history of disease before, during, and even after treatment. Our data uncovered the expression profiles of lncRNAs and mRNAs in MS patients, which will help delineate the molecular mechanisms in MS pathogenesis. However, further studies need to determine the precise role of these genes in the pathological process in MS.     

Temporal expression and functional analysis of long non‐coding RNAs in colorectal cancer initiation

Long non‐coding RNAs (lncRNAs) have potential applications in clinical diagnosis and targeted cancer therapies. However, the expression profile of lncRNAs in colorectal cancer (CRC) initiation is still unclear. In this study, the expression profiles of lncRNAs and mRNAs were determined by microarray at specific tumour stages in an AOM/DSS‐induced primary colon cancer model. The temporal expression of lncRNAs was analysed by K‐means clustering. Additionally, weighted correlation network analysis (WGCNA) and gene ontology analysis were performed to construct co‐expression networks and establish functions of the identified lncRNAs and mRNAs. Our results suggested that 4307 lncRNAs and 5798 mRNAs are deregulated during CRC initiation. These differential expression genes (DEGs) exhibited a clear correlation with the differential stage of tumour initiation. WGCNA results suggested that a series of hub lncRNAs are involved in regulating cell stemness, colon inflammation, oxidative stress response and cell death at each stage. Among them, lncRNA H19 was up‐regulated in colon tumours and correlated with poor patient prognosis. Collectively, we have been the first to demonstrate the temporal expression and function of lncRNAs in CRC initiation. These results provide novel diagnosis and therapy targets for CRC.