ObjectiveTo summarize the regulatory role of long non-coding RNA (lncRNA) in peripheral nerve injury (PNI) and neural regeneration.MethodsThe characteristics and mechanisms of lncRNA were summarized and its regulatory role in PNI and neural regeneration were elaborated by referring to relevant domestic and foreign literature in recent years.ResultsNeuropathic pain and denervated muscle atrophy are common complications of PNI, affecting patients’ quality of life. Numerous lncRNAs are upregulated after PNI, which promote the progress of neuropathic pain by regulating nerve excitability and neuroinflammation. Several lncRNAs are found to promote the progress of denervated muscle atrophy. Importantly, peripheral nerve regeneration occurs after PNI. LncRNAs promote peripheral nerve regeneration through promoting neuronal axonal outgrowth and the proliferation and migration of Schwann cells.ConclusionAt present, the research on lncRNA regulating PNI and neural regeneration is still in its infancy. The specific mechanism remains to be further explored. How to achieve clinical translation of experimental results is also a major challenge for future research.
ObjectiveTo explore the differential expressed lncRNA genes associated with formation of cholesterol gallstone, and analyze the biological functions of differential expressed lncRNA through bioinformatics.MethodsA total of 24 C57BL/6 mice were randomly divided into normal control group (n=8) and lithogenic group (n=16), which were treated with chow diets and lithogenic diets respectively for 5 weeks. After 5 weeks, mice of the lithogenic group were randomly divided into model control group (n=8) and ursodeoxycholic acid treatment group (n=8). Afterwards, mice of the normal control group were still fed with chow diets, mice of the model control group were fed with lithogenic diets, mice of the ursodeoxycholic acid treatment group were fed with ursodeoxycholic acid. After 2 weeks, collected liver tissues and gallbladder bile from the three groups, and observed gallbladder gross sample and analyzed lipids component of gallbladder bile, meanwhile detected the differential expressed lncRNA and analyzed the biological functions of differential expressed lncRNA through bioinformatics, including Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis.ResultsWe successfully constructed the mice model of cholesterol gallstone. Total cholesterol level of gallbladder in the model control group had significantly higher than those of the normal control group and ursodeoxycholic acid treatment group (P<0.05), yet there was no significant difference between the normal control group and ursodeoxycholic acid treatment group (P=0.59). The levels of total bile acid, total bilirubin, and direct bilirubin had no significant difference among the three groups (P>0.05). There were 49 kinds of common overlapped difference lncRNA between the ursodeoxycholic acid treatment group and the model control group through differential expression analysis of lncRNA in liver tissues of the mice in three groups. GO and KEGG path analysis were performed separately by differential expressed lncRNA, and 88 kinds of GO terms and 18 kinds of pathways were significantly enriched from the model control group and the normal control group, 205 kinds of GO terms and 20 kinds of pathways were significantly enriched from the ursodeoxycholic acid treatment group and the normal control group.ConclusionsUrsodeoxycholic acid has therapeutic effect for cholesterol gallstone. Differential expressed lncRNAs play an important regulatory role in the formation of cholesterol gallstone and the prevention of gallstone formation by ursodeoxycholic acid treatment, which further lay the foundation in discussing specific mechanism regulated by lncRNA.
ObjectiveTo screen long non-coding RNAs (lncRNAs) relevant to programmed cell death (PCD) and construct a nomogram model predicting prognosis of hepatocellular carcinoma (HCC). MethodsThe HCC patients selected from The Cancer Genome Atlas (TCGA) were randomly divided into training set and validation set according to 1∶1 sampling. The lncRNAs relevant to PCD were screened by Pearson correlation analysis, and which associated with overall survival in the training set were screened by univariate Cox proportional hazards regression (abbreviation as “Cox regression”), and then multivariate Cox regression was further used to analyze the prognostic risk factors of HCC patients, and the risk score function model was constructed. According to the median risk score of HCC patients in the training set, the HCC patients in each set were assigned into a high-risk and low-risk, and then the Kaplan-Meier method was used to draw the overall survival curve, and the log-rank test was used to compare the survival between the HCC patients with high-risk and low-risk. At the same time, the area under receiver operating characteristic curve (AUC) was used to evaluate the value of the risk score function model in predicting the 1-, 3-, and 5-year overall survival rates of HCC patients in the training set, validation set, and integral set. Then the nomogram was constructed based on the risk score function model and factors validated in clinic, and its predictive ability for the prognosis of HCC patients was evaluated. ResultsA total of 374 patients with HCC were downloaded from the TCGA, of which 342 had complete clinicopathologic data, including 171 in the training set and 171 in the validation set. Finally, 8 lncRNAs genes relevant to prognosis (AC099850.3, LINC00942, AC040970.1, AC022613.1, AC009403.1, AL355974.2, AC015908.3, AC009283.1) were screened out, and the prognostic risk score function model was established as follows: prognostic risk score=exp1×β1+exp2×β2...+expi×βi (expi was the expression level of target lncRNA, βi was the coefficient of multivariate Cox regression analysis of target lncRNA). According to this prognostic risk score function model, the median risk score was 0.89 in the training set. The patients with low-risk and high-risk were 86 and 85, 86 and 85, 172 and 170 in the training set, validation set, and integral set, respectively. The overall survival curves of HCC patients with low-risk drawn by Kaplan-Meier method were better than those of the HCC patients with high-risk in the training set, validation set, and integral set (P<0.001). The AUCs of the prognostic risk score function model for predicting the 1-, 3-, and 5-year overall survival rates in the training set were 0.814, 0.768, and 0.811, respectively, in the validation set were 0.799, 0.684, and 0.748, respectively, and in the integral set were 0.807, 0.732, and 0.784, respectively. The multivariate Cox regression analysis showed that the prognostic risk score function model was a risk factor affecting the overall survival of patients with HCC [<0.89 points as a reference, RR=1.217, 95%CI (1.151, 1.286), P<0.001]. The AUC (95%CI) of the prognostic risk score function model for predicting the overall survival rate of HCC patients was 0.822 (0.796, 0.873). The AUCs of the nomogram constructed by the prognostic risk score function model in combination with clinicopathologic factors to predict the 1-, 3-, and 5-year overall survival rates were 0.843, 0.839, and 0.834. The calibration curves of the nomogram of 1-, 3-, and 5-year overall survival rates in the training set were close to ideal curve, suggesting that the predicted overall survival rate by the nomogram was more consistent with the actual overall survival rate. ConclusionThe prognostic risk score function model constructed by the lncRNAs relevant to PCD in this study may be a potential marker of prognosis of the patients with HCC, and the nomogram constructed by this model is more effective in predicting the prognosis (overall survival) of patients with HCC.
ObjectiveA competing endogenous RNA (ceRNA) regulatory network associated with long non-coding RNA (lncRNA) specific for lung adenocarcinoma (LUAD) was constructed based on bioinformatics methods, and the functional mechanism of actinfilament-associated protein 1-antisense RNA1 (AFAP1-AS1) in LUAD was analyzed, in order to provide a new direction for the study of LUAD therapeutic targets. MethodsThe gene chip of LUAD was downloaded from the Gene Expression Omnibus (GEO), and lncRNA and mRNA with differential expression between LUAD and normal tissues were screened using GEO2R online software, and their target genes were predicted by online databases to construct ceRNA networks and perform enrichment analysis. In cell experiments, AFAP1-AS1 was genetically knocked down and siRNA was constructed and transfected into LUAD cells A549 by cell transfection. CCK8, transwell, scratch assay and flow cytometry were used to detect the ability of cells to proliferate, invade, migrate and apoptosis. ResultsA total of 6 differentially expressed lncRNA and 494 differentially expressed mRNA were identified in the microarray of LUAD. The ceRNA network involved a total of 6 lncRNA, 22 miRNA, and 55 mRNA. Enrichment analysis revealed that mRNA was associated with cancer-related pathways. In cell assays, knockdown of AFAP1-AS1 inhibited cell proliferation, invasion, and migration, and AFAP1-AS1 promoted apoptosis. ConclusionIn this study, we construct a lncRNA-mediated ceRNA network, which may help to further investigate the mechanism of action of LUAD. In addition, through cellular experiments, AFAP1-AS1 is found to have potential as a therapeutic target for LUAD.
Long non-coding RNA (lncRNA) Dnm3os plays a critical role in peritendinous fibrosis and pulmonary fibrosis, but its role in the process of cardiac fibrosis is still unclear. Therefore, we carried out study by using the myocardial fibrotic tissues obtained by thoracic aortic constriction (TAC) in an early study of our group, and the in vitro cardiac fibroblast activation model induced by transforming growth factor-β1 (TGF-β1). Quantitative real-time polymerase chain reaction (RT-qPCR), Western blot, and collagen gel contraction test were used to identify the changes of activation phenotype and the expression of Dnm3os in cardiac fibroblasts. Small interfering RNA was used to silence Dnm3os to explore its role in the activation of cardiac fibroblasts. The results showed that the expression of Dnm3os was increased significantly in myocardial fibrotic tissues and in the activated cardiac fibroblasts. And the activation of cardiac fibroblasts could be alleviated by Dnm3os silencing. Furthermore, the TGF-β1/Smad2/3 pathway was activated during the process of cardiac fibroblasts activation, while was inhibited after silencing Dnm3os. The results suggest that Dnm3os silencing may affect the process of cardiac fibroblast activation by inhibiting TGF-β1/Smad2/3 signal pathway. Therefore, interfering with the expression of lncRNA Dnm3os may be a potential target for the treatment of cardiac fibrosis.
ObjectiveTo summarize research progress of non-coding RNAs (ncRNAs) in acute pancreatitis (AP), so as to provide new ideas for pathogenesis, diagnosis, and therapy of AP.MethodThe literatures on studies of ncRNAs in AP in recent years were read and reviewed.ResultsThe incidence of AP was currently increasing, but its etiology was diverse, and its pathogenesis was still fully unclear. In recent years, a large number of studies had confirmed that the ncRNA played an important role in the occurrence of many cellulars and diseases processes. Through continuous exploration for potential mechanisms of AP based on ncRNA (including long non-coding RNA and microRNA) function, it was found that the specificity and sensitivity of ncRNAs in the diagnosis of AP were better than of the traditional biomarkers. Meanwhile, ncRNAs were involved in the regulation of inflammatory response through a variety of ways.ConclusionsncRNAs are involved in altering gene expression (including up-regulation or down-regulation) in the key physiological functions of AP through a variety of ways, it might provide new ideas for understanding pathogenesis of AP and help to find new therapeutic targets. A variety of ncRNAs closely related to AP are expected to become biomarkers and molecular targets for early diagnosis and treatment of AP, so as to achieve early diagnosis and targeted treatment of AP.
Objective The aim of this study is to review the association between long non-coding RNA (lncRNA) and papillary thyroid carcinoma (PTC). Method The relevant literatures about lncRNA associated with PTC were retrospectively analyzed and summarized. Results The expression levels of noncoding RNA associated with MAP kinase pathway and growth arrest (NAMA), PTC susceptibility candidate 3 (PTCSC3), BRAF activated non-coding RNA (BANCR), maternally expressed gene 3 (MEG3), NONHSAT037832, and GAS8-AS1 in PTC tissues were significantly lower than those in non-thyroid carcinoma tissues. The expression levels of ENST00000537266, ENST00000426615, XLOC051122, XLOC006074, HOX transcript antisense RNA (HOTAIR), antisense noncoding RNA in the INK4 locus (ANRIL), and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in PTC tissues were upregulated in PTC tissues, comparing with the non-thyroid carcinoma tissues. These lncRNAs were possibly involved in cell proliferation, migration, and apoptosis of PTC. Conclusion LncRNAs may provide new insights into the molecular mechanism and gene-targeted therapy of PTC and become new molecular marker for the diagnosis of PTC.
ObjectiveTo investigate the expression level of long non-coding RNA Down’s syndrome critical region 8 (LncRNA DSCR8) in gastric cancer and its clinical significance.MethodsEighty-six patients with gastric cancer who were hospitalized in our hospital from August 2014 to August 2015 were selected as the research object. Real-time quantitative PCR (qRT-PCR) was used to detect the expression level of LncRNA DSCR8 mRNA in gastric cancer tissues and its adjacent tissues. The relationship between the expression level of LncRNA DSCR8 mRNA and clinicopathological features of gastric cancer was analyzed. Kaplan-Meier method was used to analyze the relationship between the expression of LncRNA DSCR8 mRNA and the survival rate of patients, and multivariate Cox proportional hazards regression analysis was used to analyze the prognostic factors of gastric cancer.ResultsThe expression level of LncRNA DSCR8 mRNA in gastric cancer tissues was higher than that in the paracancerous tissues (P<0.001). The expression levels of LncRNA DSCR8 mRNA in patients with poorly differentiated, TNM Ⅲ–Ⅳ and lymph node metastasis were higher than those in patients with well/moderately differentiated, TNM Ⅰ–Ⅱ and no lymph node metastasis (P<0.05). The 1, 3 and 5-year survival rate of patients with low LncRNA DSCR8 mRNA expression (97.62%, 92.86%, 83.33%, respectively) were higher than those of patients with high LncRNA DSCR8 mRNA expression (63.64%, 38.64%, 31.82%, respectively), P<0.05. LncRNA DSCR8 mRNA and TNM stage were independent risk factors of death in patients with gastric cancer (P<0.05).ConclusionsLncRNA DSCR8 is associated with the occurrence, development and prognosis of gastric cancer. It may be an important molecular marker of tumor stage and lymph node metastasis in patients with gastric cancer.
ObjectiveTo summarize the recent advances in the relationship between long non-coding RNA (LncRNA) and tumor autophagy, autophagy and drug resistance regulation.MethodsReviewed the relevant literatures at home and abroad, and reviewed the recent research progress of LncRNA regulation of autophagy to affect tumor resistance.ResultsDrug resistance was a common problem in the process of anti-tumor therapy. Autophagy played an important role in the process of tumor resistance as an important mechanism to maintain cell homeostasis. Abnormal regulation of LncRNA could contribute to the occurrence and development of tumors, and could also mediate the resistance of tumor cells to anti-tumor drugs by promoting or inhibiting autophagy.ConclusionsLncRNA can mediate tumor autophagy in a positive or negative direction, and autophagy is a " double-edged sword” for tumor resistance. LncRNA may improve tumor resistance to drugs by regulating autophagy.
Objective To summarize the latest research progress of tumor energy metabolism regulated by long non-coding RNA (lncRNA). Method Literatures about the recent studies on the bioenergetic metabolic mechanisms regulated by lncRNA in tumor cells were reviewed according to the results searched from PubMed database, Springer database, HighWire database, and so on. Results Aerobic glycolysis (Warburg effect) was regarded as the most important characteristics of energy metabolism in tumor cells. lncRNA could regulate many key progressions involved energy metabolism in tumor cells, such as glucose metabolism, lipid metabolism, and glutamine metabolism, resulting in accelerated uptake of glucose, decomposition of glutamine, and formation of lipid. Conclusions The functions and mechanisms of energy metabolism in tumor cells regulated by lncRNA are entirely unclear. The role of lncRNA played in cancer needs to be understood, which may contribute to new tumor biomarker detection and effective treatment strategies.