ObjectiveTo investigate the effect of LOC103693069 on hypoxic apoptosis of bone marrow mesenchymal stem cells (BMSCs). Methods BMSCs from 1-week-old Sprague Dawley rat bone marrow were isolated, cultured, and passaged by the whole bone marrow adherent culture method. After identification of adipogenic, chondrogenic, and osteogenic differentiation, the 3rd generation cells were treated with hypoxia under 5%O2, 1%O2, and anaerobic conditions. After 48 hours, the cell viability, apoptosis, and apoptosis-related proteins [hypoxia inducible factor 1α (HIF-1α), Caspase-3, B cell lymphoma/leukemia 2 (Bcl-2)] expressions were detected, and normal BMSCs were used as controls. Based on the research results, the concentration group with the most obvious apoptosis was selected and used for subsequent experiments. After 48 hours of hypoxia treatment, BMSCs were taken and analyzed by gene chip and real-time fluorescence quantitative PCR (qRT-PCR) to screen the most significantly down-regulated gene and construct their high-expression, low-expression, and negative control lentiviruses; BMSCs were transfected with the different lentiviruses, respectively. After qRT-PCR detection confirmed that the transfection was successful, the BMSCs were treated with hypoxia for 48 hours to observe the cell viability and the expressions of apoptosis-related proteins. ResultsAfter cell viability, apoptosis, and apoptosis-related proteins were detected, cell apoptosis was the most significant under anaerobic conditions after 48 hours. The above indicators were significantly different from other groups (P<0.05), and this group was used for treatment conditions for subsequent experiments. Gene chip analysis showed that after 48 hours of hypoxia treatment, AC125847.1, LOC102547753, AABR07017208.2, and LOC103693069 were significantly down-regulated in BMSCs, and the expressions of LOC103693069 was the most significant down-regulation detected by qRT-PCR (P<0.05). It was selected to construct lentivirus and transfect BMSCs. Afterwards, qRT-PCR detection showed the successful transfection into the cells. After hypoxia treatment, the apoptosis rate and the expressions of apoptosis-related proteins of BMSCs overexpressed by the gene were significantly reduced (P<0.05). Conclusion LOC103693069 can relieve the hypoxic apoptosis of BMSCs.
Objective To investigate the role of long non-coding RNA metastasis-associated in colon cancer 1-antisense RNA （MACC1-AS1）in cisplatin resistant gastric cancer and its possible mechanism. Methods Human gastric cancer cell line BGC823 and cisplatin resistant gastric cancer cell line (BGC823/DDP) were selected as the research objects. BGC823/DDP cells were transfected and divided into negative control group (si-NC group, transfected with si-NC empty plasmid) and MACC1-AS1 gene silencing group (si-MACC1-AS1 group, transfected with si-MACC1-AS1 plasmid). The BGC823 cells were transfected and divided into positive control group (pcDNA-NC group, transfected with pcDNA-NC empty plasmid) and MACC1-AS1 gene overexpression group (pcDNA-MACC1-AS1 group, transfected with pcDNA-MACC1-AS1 plasmid). MTT was used to detect the inhibition and 50% inhibition concentration (IC50). Flow cytometry was used to detect apoptosis. Real-time fluorescence quantitative PCR was used to detect the mRNA expression levels of MACC1-AS1, B-lymphoma-2 gene (Bcl-2), Bcl-2 related X gene (Bax), mammalian target of rapamycin (mTOR), phosphorylated mTOR (p-mTOR), protein kinase B (AKT), and phosphorylated AKT (p-AKT). Western blot was used to detect the protein expression levels of Bax, Bcl-2, p-mTOR, mTOR, AKT, and p-AKT. Results The relative expression level of MACC1-AS1 mRNA in BGC823/DDP cells was higher than that in BGC823 gastric cancer cells (P<0.01). The relative expression level of MACC1-AS1 mRNA in the si-MACC1-AS1 group cells was lower than that in the si-NC group cells (P<0.01). The relative expression level of MACC1-AS1 mRNA in the pcDNA-MACC1-AS1 group cells was higher than that in the pcDNA-NC group cells (P<0.01). The cell growth inhibition rate and IC50 of the si-MACC1-AS1 group were higher than those of the si-NC group (P<0.01). The cell growth inhibition rate and IC50 of the pcDNA-MACC1-AS1 group were lower than those of the pcDNA-NC group (P<0.01). The mRNA and protein relative expression levels of Bcl-2, p-AKT/AKT and p-mTOR/mTOR in the pcDNA-MACC1-AS1 group were significantly higher than those in the pcDNA-NC group (P<0.01). The relative expression levels of Bax protein and mRNA in the pcDNA-MACC1-AS1 group were significantly lower than those in the pcDNA-NC group (P<0.01). The apoptosis rate of the pcDNA-MACC1-AS1 group was significantly lower than that of the pcDNA-NC group (P<0.01). The mRNA and protein relative expression levels of Bcl-2, p-AKT/AKT and p-mTOR/mTOR in the si-MACC1-AS1 group were significantly lower than those in the si-NC group (P<0.01). The relative expression levels of Bax protein and mRNA in the si-MACC1-AS1 group were significantly higher than those in the si-NC group (P<0.01). The apoptosis rate of the si-MACC1-AS1 group was significantly higher than that of the si-NC group (P<0.01). Conclusions MACC1-AS1 highly expresses in cisplatin resistant gastric cancer cells. Overexpression of MACC1-AS1 regulates AKT/mTOR pathway mediated apoptosis and enhances cisplatin resistance of gastric cancer cells.
Non-coding RNA (ncRNA) is a newly discovered functional RNA different from messenger RNA, which can participate in the regulation of tumor occurrence and development. Studies have shown that ncRNA can participate in the regulation of radiotherapy response to gastric cancer, and its mechanism may be related to its influence on DNA damage repair, gastric cancer cell stemness, apoptosis, and activation of epidermal growth factor receptor signal pathway. This article summarizes the mechanism of ncRNA regulating the response of gastric cancer to radiotherapy, and looks forward to the potential clinical application of ncRNA in the resistance of gastric cancer to radiotherapy.
ObjectiveTo investigate the key long non-coding RNAs (lncRNAs) and transcription factors (TFs) in idiopathic pulmonary fibrosis (IPF) by Bioinformatics analysis.MethodsBioinformatics analysis of three gene expression profiles from the Gene Expression Omnibus dataset (GSE2052, GSE44723, and GSE24206), including 42 IPF and 21 normal lung tissues, was performed in this study. Subsequently, differentially expressed genes (DEGs) were filtered, and key genes involved in signaling pathways and the DEG-associated protein-protein interaction network (PPI) were further analyzed. The filtered genes expression was determined by real-time quantitative polymerase chain reaction analysis.ResultsA total of 8483 aberrantly expressed genes were screened, and 29 overlapping genes were identified among these three datasets. A significant enrichment analysis of DEG-associated functions and pathways was further performed. A total of 18 modules were obtained from the DEG PPI network, and most of the modules were involved in polyubiquitination, Golgi vesicle transport, endocytosis and so on. The key genes were obtained through hypergeometric testing, and most of the corresponding genes were closely associated with ubiquitin-mediated proteolysis, the spliceosome, and the cell cycle. These differential expressed genes, such as lncMALAT1, E2F1 and YBX1, were detected in the peripheral blood of IPF patients when compared with those normal control subjects.ConclusionlncMALAT1, E2F1 and YBX1 might be possible regulators for the pathogenesis of idiopathic pulmonary fibrosis.
ObjectiveTo investigate relationship of long non-coding RNA FoxP4-AS1 expression with lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC).MethodsReal time fluorescent quantitative polymerase chain reaction was used to detect the expression level of FoxP4-AS1 in 52 cases of PTC tissues and corresponding adjacent tissues, PTC cells (TPC-1, B-CPAP, K1), and normal thyroid follicular epithelial cells (Nthy-ori3-1). Univariate and multivariate analysis were used to identify the influencing factors of LNM in PTC. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of influencing factors of LNM in PTC.ResultsThe expression level of FoxP4-AS1 in the PTC tissues was significantly decreased as compared with the corresponding adjacent tissues (t=7.898, P<0.001), which in the different cells had statistical difference (F=29.866, P<0.001): expression levels in the TPC-1 and K1 cells were lower than Nthy-ori3-1 cells (P<0.05) and in the B-CPAP cells and Nthy-ori3-1 cells had no statistical difference (P>0.05) by multiple comparisons. Univariate analysis showed that the extraglandular invasion (χ2=4.205, P=0.040)and low expression of FoxP4-AS1 (χ2=7.144, P=0.008) were the influencing factors of LNM in PTC. Binary logistic regression analysis showed that extraglandular invasion [OR=9.455, 95%CI (1.120, 79.835), P=0.039] and low expression ofFoxP4-AS1[OR=5.437, 95%CI (1.488, 19.873), P=0.010] were risk factors for LNM of PTC. The area under the ROC curve ofFoxP4-AS1,extraglandular invasion alone, and combination of the two were 0.679, 0.656, and 0.785, respectively.ConclusionsFoxP4-AS1 is down-regulated in PTC. Low level of FoxP4-AS1 is a risk factor for LNM of PTC. Combined detection of expression level of FoxP4-AS1 and extraglandular invasion has a high predictive value for LNM of PTC.
Extracellular matrix (ECM) has been implicated in tumor progress and chemosensitivity. Ovarian cancer brings a great threat to the health of women with a significant feature of high mortality and poor prognosis. However, the potential significance of matrix stiffness in the pattern of long non-coding RNAs (lncRNAs) expression and ovarian cancer drug sensitivity is still largely unkown. Here, based on RNA-seq data of ovarian cancer cell cultured on substrates with different stiffness, we found that a great amount of lncRNAs were upregulated in stiff group, whereas SNHG8 was significantly downregulated, which was further verified in ovarian cancer cells cultured on polydimethylsiloxane (PDMS) hydrogel. Knockdown of SNHG8 led to an impaired efficiency of homologous repair, and decreased cellular sensitivity to both etoposide and cisplatin. Meanwhile, the results of the GEPIA analysis indicated that the expression of SNHG8 was significantly decreased in ovarian cancer tissues, which was negatively correlated with the overall survival of patients with ovarian cancer. In conclusion, matrix stiffening related lncRNA SNHG8 is closely related to chemosensitivity and prognosis of ovarian cancer, which might be a novel molecular marker for chemotherapy drug instruction and prognosis prediction.
ObjectiveTo summarize the research progress of long non-coding RNA (lncRNA) in the regulation of malignant biological behavior of gallbladder cancer so as to provide references for its related research.MethodThe relevant literatures about studies of lncRNA in gallbladder cancer in recent years were reviewed.ResultsThe recent studies had shown that 19 lncRNAs associated with gallbladder cancer had played the important roles in regulating tumor cell proliferation, migration, invasion, apoptosis, “sponge” miRNAs, chemoresistance, and tumor metastasis. Among them, most lncRNAs tended to have carcinogenic properties, only a few had anticarcinogenic effect. Although the research suggested the mechanism and role of lncRNA to promote or inhibit the occurrence and development of gallbladder cancer, the current research on its mechanism was still limited. In addition, some lncRNAs were found to be specifically expressed in the serum of patients with gallbladder cancer, so which were expected to become biomarkers for tumor diagnosis and prognosis.ConclusionslncRNAs associated with gallbladder cancer have carcinogenic or anticarcinogenic effect, or chemoresistance. They play potential roles in diagnosis, prognosis, and (or) treatment of tumors, but molecular mechanisms of their effects are still limited.
Long non-coding RNA (lncRNA) is a type of nucleic acid sequence that exceeds 200 nucleotides in length and cannot encode any complete protein. In recent years, its important regulatory role in various pathophysiological processes has been gradually clarified, however, few studies have reported its role in carcinogenic virus infection. This article summarizes the currently known lncRNAs abnormally expressed in hepatitis B virus-induced hepatocellular carcinoma, and focuses on the mechanisms of lncRNAs regulating the occurrence and development of hepatitis B virus-related hepatocellular carcinoma such as controlling virus replication and host immunity, cell cycle and proliferation, invasion and metastasis, autophagy and apoptosis of liver cancer cells, hoping to provide a theoretical basis for the molecular targeted therapy of hepatocellular carcinoma.
Calcific aortic valve disease has been the most common heart valve disorder in western world, accompanying with the increase of morbidity in our country year by year. Several molecules and mechanisms are involved in the progression of aortic valve calcification, which intensify the complexity of this pathological process. It is known that inflammation, a key factor in many diseases, has its own role in the development of aortic valve calcification. It has been demonstrated that inflammation, one of the most important participants in this disorder, which may accelerate the local lesions in aortic valve via promoting the expression of osteogenic differentiation of associated factors or decreasing the level of protective molecules. Dyslipidemia is a traditional risk factor of cardiovascular events. However, it may induce or enhance the inflammatory response whereby facilitates the calcific lesions in aortic valve. Recently, several researches have illustrated that non-coding RNAs, a stimulative factor in the progression of malignant tumor, might play a role in the development of aortic valve calcification. MiRNA and lncRNA, the non-coding RNAs which regulate the expression of genes involved in inflammatory and osteogenic differentiation, are undeniable regulators of aortic valve calcification.
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.