肝细胞癌相关差异基因的生物信息学及预后分析

肝细胞癌是全球癌症相关死亡的主要原因,目前对肝细胞癌的发病机制研究尚不完善,探索肝细胞癌发生、发展相关的分子标志物及其预后具有重要意义。从GEO数据库获得肝细胞癌组织和非癌组织的基因表达阵列数据GSE84402,利用GEO2R筛选差异表达基因;采用DAVID数据库对差异基因进行GO富集分析和KEGG通路分析;通过STRING数据库和Cytoscape软件构建差异表达基因对应的蛋白质相互作用网络,并从网络中筛选出核心基因(hub genes);结合KM plotter数据库的临床信息对hub genes进行预后分析。结果显示:共得到1 307个差异表达基因,其中上调基因741个,下调基因566个,这些差异表达基因主要涉及细胞分裂、细胞周期、DNA复制及物质代谢等生物学过程及生物通路。通过GO、KEGG及蛋白质相互作用网络筛选出BUB1、BUB1B、CCNA2、CCNB1、CCNB2、CDC20、CDK1、MAD2L1、PLK1等9个hub genes,进一步分析发现hub genes均与细胞周期的调控相关,表明细胞周期的调控失常在肝细胞癌的发生、发展过程中具有重要作用。生存分析显示9个hub genes在肝细胞癌患者中均为表达上调的基因,且与患者预后不良相关,这为寻找肝细胞癌患者预后相关生物标志物的研究提供了线索。     

肝细胞癌患者自噬相关基因的预后作用

构建由自噬相关基因组成的预后模型,预测肝细胞癌(HCC)患者的生存预后情况,为其个性化诊疗和临床研究提供依据.利用TCGA数据库中HCC的测序信息与人类自噬数据库联合,筛选差异表达的自噬相关基因,对其进行GO富集与KEGG通路分析;通过单因素与多因素Cox分析筛选与患者生存预后明显相关的风险基因,构建预后风险评分模型;...     

基于生物信息学分析的宫颈鳞状细胞癌预后相关基因的筛选

为了分析宫颈鳞状细胞癌(cervical squamous cell carcinoma, CESC)与正常组织中的差异表达基因(differentially expressed genes, DEGs),鉴定与CESC预后相关的关键基因,从GEO和TCGA数据库下载CESC的基因表达谱数据,利用R软件筛选CESC组织与正常组织中的DEGs,并对这些DEGs开展功能和通路富集分析;然后构建蛋白质-蛋白质相互作用(protein-protein interaction, PPI)网络,筛选出关键(hub)基因;最后对hub基因进行LASSO COX回归及总体生存率(overall survival, OS)分析。研究共筛选出167个DEGs,这些基因主要涉及染色体分离、DNA复制等生物过程,介导染色质结合、G蛋白偶联受体结合等分子功能,富集于染色体区域、纺锤体和MCM复合体。GSEA分析结果显示,富集的通路主要涉及DNA复制和细胞周期信号通路。此外,从PPI网络中筛选出20个hub基因, LASSO COX回归结果显示MAD2L1、ZWINT、RRM2、TTK、CDC6、PBK、TOP2A、KIF11、KIF20A、NCAPG、NUSAP1、CCNB1及CDK1与CESC患者的预后相关; Kaplan-Meier曲线显示, ZWINT、DTL、CCNB1、CDC6、TOP2A、CDK1、PBK、RFC4及NUSAP1的m RNA表达水平与CESC患者生存预后相关。本研究结果表明, ZWINT、CDC6、PBK、TOP2A、NUSAP1、CCNB1和CDK1为CESC的预后关键基因,为阐明CESC的分子机制提供了理论依据。     

多基因模型在肝细胞癌预后中的应用

利用较少分子信息预测肝细胞癌类型对患者的个性化治疗十分关键。探索已知的与肝细胞癌预后相关的信号通路,共发现41个关键基因。随后,运用机器学习的方法对其构建风险预测模型,并在4个肝细胞癌数据集上进行验证。结果显示,该模型能将肝细胞癌患者分成两个预后差异显著的类型:癌症基因图谱(The cancer genome atlas,TCGA)数据集交叉验证的平均log rank P值为0.03;其他测试数据集的log rank P 值分别为0.000 38、0.002 1和0.01。生物信息学分析显示肝细胞癌的预后与细胞周期等信号通路显著相关,并筛选出12个潜在的肝细胞癌分子标志物。研究结果表明,基于41个基因构建的肝细胞癌预后模型具有较好的稳健性和准确的风险预测能力。     

肝细胞癌高表达基因cDNA文库的构建及生物信息学分析

目的:构建肝细胞癌的高表达基因cDNA文库并进行相应的生物信息学分析。方法:应用抑制性消减杂交(SSH)技术,以7对肝癌组织和癌旁组织为实验材料,构建肝癌高表达基因的cDNA文库;使用BioEdit、BLAST和EGAD等软件进行生物信息学分析。结果:获得1450个白色阳性克隆,经PCR扩增后均有100～1000bb的插入片段,经杂交验证选取125个克隆进行测序;经BLAST、EGAD等生物信息学工具分析获得基因83个,其中细胞分裂相关基因5个,参与细胞信号转导或通讯的基因5个,参与细胞结构或运动的基因7个,细胞或器官防御相关基因11个,参与细胞内基因转录或蛋白表达的基因22个,代谢相关基因18个,另有15个未归类基因。结论:利用SSH技术可构建肝细胞癌组织差异表达基因的消减cDNA文库,为进一步深入探讨肝癌的诊断、治疗和预后评估等提供更多的分子指标。     

肝细胞癌根治性切除术后预后因素分析

目的:探讨影响肝细胞癌患者根治性术后预后相关因素。方法:回顾性分析2004年1月1日至2009年12月31日245例我院行根治性切除术的肝细胞癌患者,采用Kaplan-Meier法和Cox比例风险模型分析临床资料、手术过程、病理特征与预后的关系。结果:多因素分析结果显示术前AFP水平、术中出血量、TNM分期是影响无进展生存时间和总生存时间的独立风险因素。术前AFP水平越高、术中出血量越大、TNM分期越晚则患者无进展生存时间及总生存时间明显缩短。此外,患者出现肿瘤组织局部坏死、门静脉癌栓,则总生存时间明显缩短。结论:术前AFP水平、术中出血量、TNM分期是外科根治性切除术后肝细胞癌患者复发及死亡的相关因素,对于临床医师判断预后及延长术后生存时间具有重要的临床意义。     

一种新的泛素化-铁死亡相关基因特征用于肝细胞癌患者预后分析

本研究通过筛选泛素化-铁死亡相关基因构建肝细胞癌(hepatocellular carcinoma, HCC)预后模型,并探究泛素化-铁死亡相关基因对HCC预后的影响。使用R包DESeq2对TCGA-LIHC数据集进行差异分析,获取HCC差异表达基因(HCC＿DEGs)。将HCC＿DEGs、泛素化相关基因(ubiquitination related genes, URGs)和铁死亡差异表达基因(ferroptosis＿differentially expressed genes, FERR＿EDGs)取交集获得泛素化和铁死亡相关基因(UBFE＿EDGs),将UBFE＿EDGs依次进行LASSO回归分析、单因素Cox回归分析和多因素Cox回归分析以筛选出最佳独立预后基因用于构建HCC预后模型(ubiquitination and ferroptosis-related prognostic model, UBFE)。由生存曲线、 ROC曲线和校正曲线评估UBFE的预测准确性。单因素Cox回归分析、多因素Cox回归分析评估UBFE风险评分是否为HCC的预后独立危险因素,并构建列线图模型。...     

肺腺癌预后相关miRNA生物信息学筛选及其临床意义

目的：探讨肺腺癌预后相关miRNA组学特征及其临床意义。方法：应用癌症基因组图谱（TCGA）数据库,检索人肺腺癌miRNA表达谱数据,进行差异分析,再利用Cox风险回归模型筛选预后相关miRNA;利用mirwalk分析平台,对筛选出的miRNA进行靶向调控基因预测、KEGG功能富集分析,最后,预测出预后相关miRNA的功能。结果：共筛选肺腺癌差异miRNA46个,其中,上调19个、下调27个;通过Cox生存分析筛选到预后相关miRNA有6个,即hsa-mir-21、hsa-mir-142、hsa-mir-200a高表达,hsa-mir-101、hsa-let-7c、hsa-mir-378e低表达,其中hsa-mir-21、hsa-mir-378e与肺腺癌患者不良预后有关,生存期显著缩短（P<0.05,AUC=0.618）。KEGG分析上述预后相关miRNA靶向调控基因与免疫反应通路、miRNA与癌症通路、代谢通路等有关。结论：hsa-mir-21、hsa-mir-378e与肺腺癌预后不良有关,未来经进一步临床验证有可能作为肺腺癌预后相关的分子标记物。     

急性髓性白血病预后免疫相关基因的生物信息学分析

急性髓性白血病(acute myeloid leukemia,AML)是一种造血干细胞的恶性克隆性疾病,复发率高,预后差,临床缺乏准确而稳健的预后标志物.本研究旨在构建一个免疫相关基因(immune-related genes,IRGs)的拟合模型来预测AML患者的预后.首先,从TCGA中下载AML样本的基因表达谱数据...     

肾透明细胞癌预后相关miRNAs的生物信息学分析

目的寻找可作为肾透明细胞癌（ccRCC）生物标志物的miRNA,以及ccRCC与正常组织间miRNA差异表达情况。 方法利用TCGA数据库下载ccRCC中miRNA表达数据,分析肿瘤与正常组织间差异表达miRNA。使用Kaplan-Meier曲线对患者进行生存分析,筛选出表达情况与临床预后相关的miRNA。通过生物信息学对miRNA的靶基因进行预测,然后运用FunRich软件和ClueGO对靶基因进行GO和KEGG富集分析。 结果通过TCGA数据库分析发现,ccRCC较正常组织差异表达miRNA共54个,其中上调33个,下调21个。通过生存分析发现hsa-miR-21和hsa-miR-155与患者预后相关,P≤0.05。进一步通过Perl软件在Targetscan、miRDB、miRTarBase、miRPath这四个数据库中预测miRNA靶基因并将结果取交集,共发现129个靶基因。GO和KEGG分析结果表明,这些靶基因主要与转录因子活性、信号转导以及FoxO、TNF等信号通路密切相关。 结论通过生物信息学分析发现了ccRCC与正常组织的差异表达miRNA;其中hsa-miR-21和hsa-miR-155与患者总体生存率相关,并通过调控靶基因参与相关的信号通路进而影响ccRCC的发生发展进程,提示hsa-miR-21和hsa-miR-155可能是ccRCC潜在的生物标志物。     

Prognostic evaluation and immune infiltration analysis of five bioinformatic selected genes in hepatocellular carcinoma

Despite the development in hepatocellular carcinoma (HCC) treatment in recent years, the therapeutic outcome of HCC remains unfavourable. This study examines the prognosis of HCC from a genetic level using clinical databases and single-cell data to identify genes with a high prognostic value. Three up-regulated genes (UBE2S, PTTG1, and CDC20) and two down-regulated genes (SOCS2 and DNASE1L3) in HCC tissues were identified. Various analyses confirmed its correlation with tumour stage (p < 0.01) and patient survival time (log-rank p < 0.001). Immune analysis, single-cell analysis, and gene set enrichment analysis (GSEA) were employed to provide insight on how they affect cancer progression, and we observed a close relation between these genes and tumour immune infiltration. Eventually, we constructed a risk score system that risk score = (0.0465) × UBE2S + (0.1851) × CDC20 + (−0.0461) × DNASE1L3 + (−0.2279) × SOCS2 (5-year area under curve = 0.706). The risk score system may serve as an effective novel prognostic system for HCC patients. This study might provide novel ideas for prognostic or therapeutic biomarkers for HCC.     

High CCNB2 expression correlates with poor prognosis in hepatocellular carcinoma

Cyclin B2 (CCNB2), a member of the cyclin protein family, has a key role in the progression of G2/M transition. However, the clinical value of CCNB2 in hepatocellular carcinoma (HCC) is still unknown. The aim of our study is to identify the role of CCNB2 in HCC patients. Immunohistochemical analysis using tissue microarray (TMA) was employed to evaluate the expression of CCNB2 in HCC and the correlation between CCNB2 expression and clinicopathological features in HCC patients. The relationship between CCNB2 expression and the prognosis of HCC patients was analyzed using Oncomine and Kaplan-Meier Plotter online resources. High CCNB2 cytoplasmic expression was observed in 77.22% of patients with HCC, which was related to differentiation (P<0.001), tumor diameter (P=0.025), and hepatitis B virus infection (P=0.008). High CCNB2 nuclear expression was seen among 43.43% of cases, which was associated with differentiation (P=0.001). CCNB2 levels were inversely proportional to patient prognosis. The study suggests that CCNB2 expression could be an effective prognostic biomarker for HCC.     

Down-regulation of RBP4 indicates a poor prognosis and correlates with immune cell infiltration in hepatocellular carcinoma

Recent research has indicated that metabolically related genes play crucial roles in the pathogenesis of hepatocellular carcinoma (HCC). We evaluated the associations between novel biomarkers and retinol-binding protein 4 (RBP4) for predicting clinical HCC outcomes, hub-related genes, pathway regulation, and immune cells infiltration. Bioinformatic analyses based on data from The Cancer Genome Atlas were performed using online analysis tools. RBP4 expression was low in HCC and was also down-regulated in pan-cancers compared with normal tissues. RBP4 expression was also significantly different based on age (41–60 years old versus 61–80 years old), and low RBP4 expression levels were associated with advanced tumor stages and grades. Higher RBP4 expression was associated with better overall survival time in HCC patients, and we identified a deletion-mutation rate of 1.4% in RBP4. We also identified ten co-expressed genes most related to RBP4 and explored the relationships between six hub genes (APOB, FGA, FGG, SERPINC1, APOA1, and F2) involved in RBP4 regulation. A pathway enrichment analysis for RBP4 indicated complement and coagulation cascades, metabolic pathways, antibiotic biosynthesis pathways, peroxisome proliferator-activated receptor signaling pathways, and pyruvate metabolism pathways. These results suggest that RBP4 may be a novel biomarker for HCC prognosis, and an indicator of low immune response to the disease.     

Overexpression of SSR2 promotes proliferation of liver cancer cells and predicts prognosis of patients with hepatocellular carcinoma

Signal Sequence Receptor Subunit 2 (SSR2) is a key endoplasmic reticulum gene involved in protein folding and processing. Previous studies found that it was upregulated in several cancers, but its precise role in hepatocellular carcinoma (HCC) remains unclear. To have a better understanding of this gene in HCC, we examined the expression of SSR2 in HCC tissues by analysing The Cancer Genome Atlas (TCGA) data and immunohistochemistry. We also assessed the association between SSR2 expression and clinicopathological characteristics of HCC patients and patient survival. Potential function of SSR2 was predicted through GSEA and protein–protein interaction analysis. MTT, flowcytometry, transwell and a nude mice xenograft model were employed to investigate the biological functions in vivo and in vitro. The results showed that the expression of SSR2 was significantly increased in HCC tissues, and SSR2 expression was associated with several clinical characteristics. In addition, patients with higher SSR2 expression had poorer survival. Enrichment analysis suggested that SSR2 was probably involved in biological process or signalling pathways related to G2/M checkpoint, passive transmembrane transporter activity, ATF2_S_UP. V1_UP and ncRNA metabolic process. Further experimental study showed that SSR2 knockdown inhibited cell proliferation, migration and invasion ability and promoted apoptosis and cell cycle arrest in vitro. Moreover, downregulation of SSR2 also repressed the growth of HepG2 cells in vivo. In conclusion, our study suggests that SSR2 may act as an oncogene in HCC.     

Musashi2 predicts poor prognosis and invasion in hepatocellular carcinoma by driving epithelial–mesenchymal transition

The high incidence of recurrence and the poor prognosis of hepatocellular carcinoma (HCC) necessitate the discovery of new predictive markers of HCC invasion and prognosis. In this study, we evaluated the expression pattern of two members of a novel oncogene family, Musashi1 (MSI1) and Musashi2 (MSI2) in 40 normal hepatic tissue specimens, 149 HCC specimens and their adjacent non‐tumourous tissues. We observed that MSI1 and MSI2 were significantly up‐regulated in HCC tissues. High expression levels of MSI1 and MSI2 were detectable in 37.6% (56/149) and 49.0% (73/149) of the HCC specimens, respectively, but were rarely detected in adjacent non‐tumourous tissues and were never detected in normal hepatic tissue specimens. Nevertheless, only high expression of MSI2 correlated with poor prognosis. In addition, MSI2 up‐regulation correlated with clinicopathological parameters representative of highly invasive HCC. Further study indicated that MSI2 might enhance invasion of HCC by inducing epithelial–mesenchymal transition (EMT). Knockdown of MSI2 significantly decreased the invasion of HCC cells and changed the expression pattern of EMT markers. Moreover, immunohistochemistry assays of 149 HCC tissue specimens further confirmed this correlation. Taken together, the results of our study demonstrated that MSI2 correlates with EMT and has the potential to be a new predictive biomarker of HCC prognosis and invasion to help guide diagnosis and treatment of post‐operative HCC patients.