Exploration of gene expression profiles and immune microenvironment between high and low tumor mutation burden groups in prostate cancer

BackgroundTumor mutation burden (TMB) has been established as a biomarker for response to immune therapy and prognosis in various cancers. However, the association between TMB and prognosis of prostate cancer (PCa) remains unclear. This study aimed to investigate the impact of TMB in biochemical recurrence (BCR) and the immune microenvironment in high and low TMB groups.MethodsMutation data, gene expression, clinicopathological information were downloaded from The Cancer Genome Atlas (TCGA). Mutation types and TMB values were identified. All samples were divided into high and low TMB groups with median TMB value as the cutoff point. The BCR-free survival rates, Differentially expressed genes (DEGs) and immune cells infiltrations in different TMB groups were identified.ResultsThe most common variant type and SNV were single nucleotide polymorphism and C > T. respectively. High TMB level was significantly associated with older age, positive lymph node, higher International Society of Urological Pathology (ISUP) grade, advanced stage and poor BCR-free survival. 132 DEGs were identified and involved in receptor ligand activity and hormone activity. High expression of six core genes UBE2C, PLK1, CDC20, BUB1, CDK1 and HJURP were associated with worse BCR-free survival. The analysis of immune cells infiltration revealed that the amount of activated CD4⁺ memory T cells was significantly different in high and low TMB groups.ConclusionsThe current study comprehensively described the summary of mutation and TMB related DEGs in PCa. TMB was associated with BCR-free survival and the infiltration of activated CD4⁺ memory T cells in the immune microenvironment.     

Animal model and bioinformatics analyses suggest the TIMP1/MMP9 axis as a potential biomarker in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is a common malignant tumor of the head and neck. However, the molecular mechanism underlying its development and progression is yet unclear. Genes that are differentially expressed, that is, differentially expressed genes (DEGs), between normal and diseased tissues are believed to be involved in disease development and progression. To identify the DEGs in OSCC and explore their role in occurrence and progression, we established a Chinese hamster OSCC model, determined the DEG, screened the identified DEGs, and performed Gene Ontology (GO) and KEGG enrichment analyses. A protein–protein interaction (PPI) network was generated to screen potential candidate genes. We then analyzed the expression, tumor stage and prognosis of candidate genes using the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, we verified the candidate DEGs by quantitative real-time PCR and Gene Expression Omnibus analysis. The results showed 194 significantly DEGs, 140 enriched GO terms, and 8 KEGG pathways, which suggested that OSCC was closely related to the immune system, cell migration, and extracellular matrix. GEPIA and PPI network analysis revealed that SPP1, TNC, and ACTA1 were significantly related to tumor staging; SPP1, tissue inhibitors of matrix metallopeptidases (MMPs) 1 (TIMP1), and ACTA1 were closely related to prognosis. The scores for the top five highest degree genes were close, and the TIMP1/MMP9 axis appeared to be at the center of the PPI network, indicating that expression changes in the TIMP1/MMP9 axis and related genes may be involved in tumor invasion and metastasis. These findings provide novel insights into the mechanism of oral cancer.     

Analysis of susceptibility genes and myocardial infarction risk correlation of ischemic cardiomyopathy based on bioinformatics

BackgroundThe present study was to investigated differential expressed genes (GEGs) in ischemic cardiomyopathy (ICM), and to construct regulation networks, and to study the correlation between myocardial infarction risk.MethodsData sets were downloaded from the Gene Expression Omnibus (GEO) to screen out messenger RNA (mRNA) and long non-coding RNA (lncRNA) differentially expressed between ICM samples and normal samples. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Differentially expressed mRNA and lncRNA were analyzed, and bioinformatics methods were used to predict and analyze microRNA (miRNA), and a competing endogenous RNA (Hub gene) regulatory network was constructed. Using the Limma software package in R language, DEGs of ICM were screened with non-heart failure donors as the control group under the conditions that the differential expression ratio was not less than 2 times, and the corrected P value was <0.05. The ClusterProfiler software package was used for GO enrichment analysis and KEGG enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) 11.0 online database was used to screen key genes for protein-protein interaction (PPI) network analysis.ResultsThe GO function analysis and KEGG pathway analysis showed that the DEGs were significantly enriched in metabolic pathways, oxidative phosphorylation, extracellular matrix receptor interactions, and other pathways, and were closely related to fibrosis, collagen catabolic process, and inflammatory response function, and a Hub gene regulatory network related to ICM lncRNA was constructed. Bioinformatics methods were used to effectively analyze the DEGs of ICM, and the Hub gene regulatory network of ICM was successfully constructed.ConclusionsThis study identified a certain risk correlation between ICM susceptibility genes and myocardial infarction.     

转录组分析松茸多糖诱导T细胞增殖的分子机制

目的转录组分析松茸多糖(TMP-A)诱导T细胞增殖的分子机制。方法分别用TMP-A(10μg/mL)、LPS(10μg/mL)处理T细胞24 h,采用RNA-seq测序技术对T细胞进行测序并进行生物信息学分析。结果空白对照组、TMP-A组和LPS阳性对照组分别得到46 574 489、50 259 600、57 439 600条Clean reads,对应的总大小分别为6.99、7.54、8.62 G。线粒体色素C氧化酶基因家族、钙网蛋白基因等是TMP-A组的超高表达基因,在T细胞增殖过程中细胞运动、蛋白质合成及线粒体代谢增强,且氧化磷酸化所产生的能量是T细胞增殖过程的主要能量来源。TMP-A组相比于空白对照组有485个基因差异表达,其中上调的基因482个,下调的基因3个,主要与离子转运和系统过程,外周和质膜以及分子功能中转运活性有关;且通路涉及神经活性配体-受体相互作用、Ras信号途径、MAPK信号途径等。结论 T细胞在TMP-A作用下的生物代谢发生差异,离子转运、质膜、转运活性相关基因是TMP-A诱导T细胞增殖的关键基因,且Ras-Raf-Erk-MAPK信号通路是TMP-A诱导T...     

Clinical and prognostic value of chaperonin containing T-complex 1 subunit 3 in hepatocellular carcinoma: A Study based on microarray and RNA-sequencing with 4272 cases

Liver cancer is one of the few tumors with a steadily increasing morbidity and mortality; hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. We combined the expression profiles of Chaperonin Containing T-complex 1 Subunit 3 (CCT3) in HCC tissues based on microarray and RNA-sequencing data. The CCT3 expression levels were extracted and examined based on 421 samples from The Cancer Genome Atlas (TCGA) (HCC, n?=?371; non-HCC, n?=?50) and 3851 samples from 31 microarray or RNA-sequencing datasets (HCC, n?=?1975; non-tumor?=?1876). We used a variety of meta-analytic methods, including SMD forest maps, sensitivity analysis, subgroup analysis and sROC curves, to confirm the final results. Meanwhile, database-derived immunohistochemistry data was used for validation. We also further explained the potential mechanism of CCT3 in HCC through signal pathway analyses and PPI network construction with the CCT3 co-expressed genes. The mRNA and protein expression of CCT3 in HCC tissues were higher than in non-HCC tissues. The expression of CCT3 differed between groups when grouped according to clinicopathological parameters, such as race, family history, and histological grade. The results of standardised mean difference (SMD) forest map and summary receiver operating characteristic (sROC) curve revealed that CCT3 was highly expressed in HCC tissues and had a high ability to distinguish between cancer tissues and non-cancer tissues. The main form of CCT3 gene alteration in HCC was mRNA up-regulation and amplification (23%), and the most common mutation type was missense. The mRNA expression of CCT3 in HCC was negatively correlated with DNA methylation. According to the Kyoto Encyclopedia of Genes and Genomes pathway analysis, CCT3 can influence HCC occurrence and development through cell cycle and DNA replication pathways. In summary, this study carries out the staging and prognostic analysis of HCC. It suggests that CCT3 might play an important part in the tumorigenesis and progression of HCC and may have a certain prognostic value in HCC. Moreover, CCT3 might represent a promising biomarker for HCC.     

基于生物信息学分析的子宫内膜异位症miRNA-mRNA调控网络的初步构建*

目的 用生物信息学分析方法初步构建子宫内膜异位症miRNA-mRNA的调控网络,探索其在子宫内膜异位症中的分子调控机制。方法 从GEO下载数据集GSE7305,使用R语言软件对其进行差异表达基因分析。使用DAVID在线网站对获得的差异表达基因进行基因功能和KEGG信号通路富集分析。通过HMDD v3.0精准查询与子宫内膜异位症相关且经过验证（≥2次）的miRNA,并使用miRwalk 2.0数据库预测其靶基因。将预测的靶基因和GSE7305中的差异表达基因求得交集,获得miRNA和mRNA相互作用关系对。在Cytoscape v3.6.1中绘制miRNA-mRNA调控网络图,并运用CytoHubba插件进行核心mRNA及miRNA的筛选,构建相应的子网络。结果 从GSE7305中共获得655个差异表达基因,其主要富集于补体信号通路、p53信号通路、细胞黏附相关信号通路中。成功构建子宫内膜异位症miRNA-mRNA分子调控网络,并筛选出核心mRNA和miRNA： hsa-miR-20a-5p、hsa-miR-141-3p、hsa-miR-200b-3p、hsa-miR-449b-3p属于高频下调表达的miRNA,且均可靶向作用于GATA6;高频上调表达的hsa-miR-125-5p可同时作用于PGR、ESR1,并下调两者表达水平。结论 通过基因芯片分析和数据库挖掘方法构建miRNA-mRNA调控网络,为研究子宫内膜异位症发病机制、探索联合miRNA及其靶基因作为临床诊断标志物提供可靠的研究方向。     

卵巢癌发生发展关键基因的生物信息学筛选

目的 筛选影响卵巢癌发生发展的关键基因,并分析其作用机制.方法 利用高通量基因表达(GEO)数据库、癌症基因图谱(TCGA)数据库及KMplot数据库筛选卵巢癌关键基因,分析其与患者临床病理学特征的关系,同时使用GESA进行信号通路聚类分析,并使用TIMER数据库确定与之密切相关的基因,通过STRING数据库绘制互作网...     

Regulatory network analysis of hypertension and hypotension microarray data from mouse model

We aimed to identify the potential genes related to blood pressure regulation and screen target genes for high blood pressure (BPH) and low blood pressure (BPL) treatment. The GSE19817 microarray dataset, which included the aorta, liver, heart, and kidney samples from BPH, BPL, and normotensive mice, was downloaded from the Gene Expression Omnibus. Principal component analysis (PCA) was performed based on the entire expression profile. Differentially expressed genes (DEGs) were screened, followed by pathway enrichment analysis. Finally, gene regulatory networks were constructed based on BPH-related and BPL-related DEGs in the aorta, liver, heart, and kidney samples. As a result, DEGs were screened within their respective tissues due to high heterogeneity of different tissues. Totally, 2,726 BPH-related DEGs and 2,472 BPL-related DEGs were screened, which were mainly enriched in pathways such as immune response. The topology data of gene regulatory networks constructed by DEGs in the heart, kidney, and liver were similar than that in aorta. Finally, among BPH-related DEGs, Sept6 and Pigx were found in the top 10 differentially regulated DEGs by comparing the BPH-related DEGs of the aorta with the DEGs of the other 3 tissues in the regulatory network. Although among the top 10 differentially regulated BPL-related DEGs, no common differentially regulated DEGs were found, Wif1, Urb2, and Gtf2ird1 were found among the top ten DEGs in the three tissues other than the kidney tissue. Sept6 and Pigx might participate in the pathogenesis of BPH, whereas Gtf2ird1, Urb2, and Wif1 might be critical target genes for BPL treatment.