Objective To identify and isolate the variant gene associated with gastric adenocarcinoma and clone the fragment of variant gene.Methods By arbitrarily primer polymerase chain reaction (AP-PCR), DNA samples from 5 matched gastric adenocarcinoma and non-tumor gastric tissues were analysed. Results The produced AP-PCR profiles were different in each matched gastric adenocarcinoma and non-tumor gastric tissue. One differentiated amplified DNA fragments PW2.2 from a matched gastric adenocarcinoma were cloned. The result of Southern blot hybridization with PW2.2 as a probe showing that this fragment was also found in some other gastric adenocarcinoma samples. Conclusion AP-PCR fingerprinting assay can be used to identify and clone the variant genes associated with gastric adenocarcinoma.
To evaluate the differential expression profiles of the lncRNAs, miRNAs, mRNAs and ceRNAs, and their implication in the prognosis in clear cell renal cell carcinoma (CCRCC), the large sample genomics analysis technologies were used in this study. The RNA and miRNA sequencing data of CCRCC were obtained from The Cancer Genome Atlas (TCGA) database, and R software was used for gene expression analysis and survival analysis. Cytoscape software was used to construct the ceRNA network. The results showed that a total of 1 570 lncRNAs, 54 miRNAs, and 17 mRNAs were differentially expressed in CCRCC, and most of their expression levels were up-regulated (false discovery rate < 0.01 and absolute log fold change > 2). The ceRNA regulatory network showed the interaction between 89 differentially expressed lncRNAs and 9 differentially expressed miRNAs. Further survival analysis revealed that 38 lncRNAs (including COL18A1-AS1, TCL6, LINC00475, UCA1, WT1-AS, HOTTIP, PVT1, etc.) and 2 miRNAs (including miR-21 and miR-155) were correlated with the overall survival time of CCRCC (P < 0.05). Together, this study provided us several new evidences for the targeted therapy and prognosis assessment of CCRCC.
ObjectiveTo explore the single locus mutation that related to hepatitis B virus (HBV) co-infection by means of genome-wide association study (GWAS) in Chinese Han patients with pulmonary tuberculosis (TB).MethodsA total of 946 patients with pulmonary TB enrolled between March 2013 and March 2018 were genotyped by Illumina Human Omni Express gene chip. After quality control, 389 972 single nucleotide polymorphisms (SNPs) of 703 patients with single TB infection and 53 patients with TB-HBV co-infection were included in the follow-up association analysis.ResultsThe SNP with the strongest statistical correlation signal was rs118122819 (P=2.923×10−12, odds ratio=7.933) located on chromosome 8p23.1. Other potential susceptibility genes included CDH4 (rs73309833), MARCH1 (rs3797020), and DNER (rs13393112), etc. In addition, a strong linkage imbalance between rs118122819 and rs4840365 (D’=0.88, r2=0.76) was found, while rs4840365 was located in the MFHAS1 gene region.ConclusionsThis study provides evidence for the presence of susceptibility gene locus for HBV co-infection in pulmonary TB patients, and provides important clues for the mechanism research, disease prevention, and treatment of co-infection. But these associations must be replicated and validated in larger studies.
The severe acute respiratory syndrome coronavirus 2 is characterized by a long incubation period, strong infectivity and general susceptibility to the population. At present, there are no specific medicines that can treat coronavirus disease 2019. In order to increase the understanding of the molecular biology of severe acute respiratory syndrome coronavirus 2 and try to find effective treatments, we used SnapGene Viewer to analyze the genomic sequences of five strains of severe acute respiratory syndrome coronavirus 2 that published by National Genomics Data Center. The results showed that the genome length of this virus was about 29.8 kb and twelve open reading frames were predicted, and five nucleotide change sites were found in the open reading frames. In addition, we analyzed drugs used during the outbreak of severe acute respiratory syndrome, current drugs for the treatment of coronavirus disease 2019 and other possible drugs, to find some possible medicines with clinical treatment effects.
ObjectiveTo compare the function and action pathways of VEGFA, VEGFB and VEGFC in VEGF family of mouse eye.MethodsUsing the BXD mouse gene data in Genenetwork database as template to compare and study the similarities and differences of VEGFA, VEGFB and VEGFC molecular pathways or potential functions in the whole genome expression spectrum of BXD recombinant mouse inbred line population, with multiple analytical methods and statistical strategies were used, such as gene expression level, target genes comparison, top genes comparison associated to target genes, expression Quantitative Trait Loci (eQTL).ResultsMatrix comparison showed strong positive correlation between two probes of VEGFC (r=0.732, P＜0.01), weak correlation between VEGFA 1420909 and VEGFC 1440739, VEGFA 1451959 and VEGFC 1451803, VEGFC 1419417959 and VEGFC 1439766, VEGFC 1451803 and VEGFC 1439766 (P＜0.05); there was no correlation between VEGFA 1420909 and four other genes except VEGFC 1440739, VEGFA 1451959 and VEGFC 1440739, VEGFB 1451803 and VEGFA 1420909/VEGFC 1419417/VEGFC 1440739 (P ＞0.05). In the comparative analysis of the relevant Top50 genes of each VEGF gene, most of the genes in BXD mouse were not significantly correlated with VEGFA, VEGFB and VEGFC except for the weak association of individual related genes. The results of eQTL analysis showed that each probe of VEGF gene was located on different chromosomes.ConclusionsThe expression levels and positive and negative correlations of VEGFA, VEGFB and VEGFC were different in the VEGF family of mouse eye, suggesting that these genes may play their role through different pathways.
Objective To analyze the expression of H2A histone family, member X (H2AFX) gene in lung adenocarcinoma and its influence on prognosis. Methods We analyzed the expression level of H2AFX gene in the tumor tissues (497 cases) and normal adjacent tissues (54 cases) of lung adenocarcinoma patients via The Cancer Genome Atlas. The patients were divided into high expression group and low expression group according to the expression level of H2AFX gene in lung adenocarcinoma samples. The relationship between H2AFX and clinicopathological features of patients was analyzed through logistic regression. Kaplan-Meier survival curve and log-rank test were used to study the correlation between H2AFX expression and the prognosis of lung adenocarcinoma patients. Univariate and multiple Cox regression analyses were performed to determine the prognostic significance of H2AFX expression in lung adenocarcinoma patients. The research also covered H2AFX-related pathways of genes in the development of lung adenocarcinoma with gene set enrichment analysis (GSEA). Results The H2AFX expression was higher in lung adenocarcinoma tissues than that in normal adjacent tissues (P<0.001). Besides, it was significantly correlated with age (P<0.001), T staging (P=0.007), and N staging (P=0.010), but had little to do with M staging or gender (P>0.05). Kaplan-Meier survival curve and log-rank test showed that the survival rate of patients with high H2AFX expression was vastly lower than that of patients with low H2AFX expression (P<0.001). Multiple Cox regression analysis demonstrated that H2AFX could be an independent prognostic factor for lung adenocarcinoma [hazard ratio=1.41, 95% confidence interval (1.11, 1.78), P=0.004]. The results of GSEA displayed that H2AFX was involved in cell cycle, homologous recombination, DNA replication, base excision and repair, spliceosome, mismatch repair, p53 signaling pathway, nucleotide excision and repair, RNA degradation, RNA polymerase, and other pathways. Conclusions The expression of H2AFX gene is high in lung adenocarcinoma, and closely connected to the prognosis, occurrence, and evolution of lung adenocarcinoma. This gene can be one of the new molecular markers and therapeutic targets for lung adenocarcinoma.
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.