Why MUC16 mutations lead to a better prognosis:A study based on The Cancer Genome Atlas gastric cancer cohort

BACKGROUND MUC16,encoding cancer antigen 125,is a frequently mutated gene in gastric cancer.In addition,MUC16 mutations seem to result in a better prognosis in gastric cancer.However,the mechanisms that lead to a better prognosis by MUC16 mutations have not yet been clarified.AIM To delve deeper into the underlying mechanisms that explain why MUC16 mutations signal a better prognosis in gastric cancer.METHODS We used multi-omics data,including mRNA,simple nucleotide variation,copy number variation and methylation data from The Cancer Genome Atlas,to explore the relationship between MUC16 mutations and prognosis.Cox regression and random survival forest algorithms were applied to search for hub genes.Gene set enrichment analysis was used to elucidate the molecular mechanisms.Single-sample gene set enrichment analysis and“EpiDISH”were used to assess immune cells infiltration,and“ESTIMATE”for analysis of the tumor microenvironment.RESULTS Our study found that compared to the wild-type group,the mutation group had a better prognosis.Additional analysis indicated that the MUC16 mutations appear to activate the DNA repair and p53 pathways to act as an anti-tumor agent.We also identified a key gene,NPY1R(neuropeptide Y receptor Y1),which was significantly more highly expressed in the MUC16 mutations group than in the MUC16 wild-type group.The high expression of NPY1R predicted a poorer prognosis,which was also confirmed in a separate Gene Expression Omnibus cohort.Further susceptibility analysis revealed that NPY1R might be a potential drug target for gastric cancer.Furthermore,in the analysis of the tumor microenvironment,we found that immune cells in the mutation group exhibited higher anti-tumor effects.In addition,the tumor mutation burden and cancer stem cells index were also higher in the mutation group than in the wild-type group.CONCLUSION We speculated that the MUC16 mutations might activate the p53 pathway and DNA repair pathway:alternatively,the tumor microenvironment may be involved.

基于The Human Protein Atlas和TCGA数据库分析SmuG1在人卵巢癌中的表达及预后意义

目的通过数据挖掘分析SmuG1在卵巢癌组织中的表达及预后意义。方法 THPA数据库初步探讨SmuG1在人体的分布以及表达, TCGA数据库分析卵巢癌患者SmuG1 mRNA的表达水平与临床病理特征的相关性,通过生存分析探讨SmuG1 mRNA水平与总体生存期的关系,利用Cox比例风险回归模型分析SmuG1是否为患者总体生存期的独立预后影响因子。结果 THPA数据库发现SmuG1是一种细胞内糖基化酶,在全身各类组织及器官中均有表达,TCGA数据库分析发现SmuG1 mRNA水平与卵巢癌的临床分期呈负相关( P =0.024,相关系数 r =-0.5),而与年龄、肿瘤级别、残留肿瘤大小、耐药性等无关( P >0.05)。生存分析发现SmuG1 mRNA水平高的患者比SmuG1 mRNA水平低的患者存活时间更长差异无统计学意义( P =0.035)。Cox比例风险回归模型分析表明SmuG1的表达水平是卵巢癌患者的显著独立预后指标( HR =0.98,95% CI :0.618 97~1.560 583;P =0.009)。结论人卵巢癌组织中SmuG1水平与临床分期呈负相关。SmuG1表达水平高的卵巢癌患者的总体生存期较长,提示SmuG1可能是卵巢癌显著的独立预后指标。

Systematic analysis of DNA polymerases as therapeutic targets in pan-cancers

Introduction:DNA polymerases are crucial for maintaining genome stability and influencing tumorigenesis.However,the clinical implications of DNA polymerases in tumorigenesis and their potential as anti-cancer therapy targets are not well understood.Methods:We conducted a systematic analysis using TCGA Pan-Cancer Atlas data and Gene Set Cancer Analysis results to examine the expression profiles of 15 DNA polymerases(POLYs)and their clinical correlations.We also evaluated the prognostic value of POLYs by analyzing their expression levels in relation to overall survival time(OS)using Kaplan-Meier survival curves.Additionally,we investigated the correlations between POLY expression and immune cells,DNA damage repair(DDR)pathways,and ubiquitination.Drug sensitivity analysis was performed to assess the relationship between POLY expression and drug response.Results:Our analysis revealed that 14 out of 15 POLYs exhibited significantly distinct expression patterns between tumor and normal samples across most cancer types,except for DNA nucleotidylexotransferase(DNTT).Specifically,POLD1 and POLE showed elevated expression in almost all cancers,while POLQ exhibited high expression levels in all cancer types.Some POLYs showed heightened expression in specific cancer subtypes,while others exhibited low expression.Kaplan-Meier survival curves demonstrated significant prognostic value of POLYs in multiple cancers,including PAAD,KIRC,and ACC.Cox analysis further validated these findings.Alteration patterns of POLYs varied significantly among different cancer types and were associated with poorer survival outcomes.Significant correlations were observed between the expression of POLY members and immune cells,DDR pathways,and ubiquitination.Drug sensitivity analysis indicated an inverse relationship between POLY expression and drug response.Conclusion:Our comprehensive study highlights the significant role of POLYs in cancer development and identifies them as promising prognostic and immunological biomarkers for various cancer types.Additionally,targeting POLYs therapeutically holds promise for tumor immunotherapy.

Targeted therapies in metastatic gastric cancer: Current knowledge and future perspectives

Gastric cancer(GC)represents a leading cause of cancer related morbidity and mortality worldwide accounting for more than 1 million of newly diagnosed cases and thousands of deaths every year.In the last decade,the development of targeted therapies and the optimization of already available chemotherapeutic drugs has expanded the available treatment options for advanced GC and granted better survival expectations to the patients.At the same time,global efforts have been undertaken to investigate in detail the genomic and epigenomic heterogeneity of this disease,resulting in the identification of new specific and sensitive predictive and prognostic biomarkers and in innovative molecular classifications based on gene expression profiling.Nonetheless,several randomized studies aimed at exploring new innovative agents,such as immune checkpoint inhibitors,failed to demonstrate clinically meaningful survival advantages.Therefore,it is essential to further improve the molecular characterization of GC subgroups in order to provide researchers and medical oncologists with new tools for patients’selection and stratification in future clinical development programs and subsequent trials.The aim of the present manuscript is to provide a global overview of the recent molecular classifications from The Cancer Genome Atlas and the Asian Cancer Research Group and to present key promising developments in the field of immunotherapy and targeted therapies in metastatic GC.

Emerging molecular classifications and therapeutic implications for gastric cancer

Gastric cancer(GC) is a highly aggressive and life-threatening malignancy.Even with radical surgical removal and front-line chemotherapy,more than half of GCs locally relapse and metastasize at a distant site.The dismal outcomes reflect the ineffectiveness of a one-size fits-all approach for a highly heterogeneous disease with diverse etiological causes and complex molecular underpinnings.The recent comprehensive genomic and molecular profiling has led to our deepened understanding of GC.The emerging molecular classification schemes based on the genetic,epigenetic,and molecular signatures are providing great promise for the development of more effective therapeutic strategies in a more personalized and precise manner.To this end,the Cancer Genome Atlas(TCGA) research network conducted a comprehensive molecular evaluation of primary GCs and proposed a new molecular classification dividing GCs into four subtypes:Epstein-Barr virus-associated tumors,microsatellite unstable tumors,genomically stable tumors,and tumors with chromosomal instability.This review primarily focuses on the TCGA molecular classification of GCs and discusses the implications on novel targeted therapy strategies.We believe that these fundamental findings will support the future application of targeted therapies and will guide our efforts to develop more efficacious drugs to treat human GCs.

Weighted Gene Co-expression Network Analysis of Gene Modules for the Prognosis of Esophageal Cancer

Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.

Nine-long non-coding ribonucleic acid signature can improve the survival prediction of colorectal cancer

BACKGROUND Investigating molecular biomarkers that accurately predict prognosis is of considerable clinical significance.Accumulating evidence suggests that long noncoding ribonucleic acids(lncRNAs)are frequently aberrantly expressed in colorectal cancer(CRC).AIM To elucidate the prognostic function of multiple lncRNAs serving as biomarkers in CRC.METHODS We performed lncRNA expression profiling using the lncRNA mining approach in large CRC cohorts from The Cancer Genome Atlas(TCGA)database.Receiver operating characteristic analysis was performed to identify the optimal cutoff point at which patients could be classified into the high-risk or low-risk groups.Based on the Cox coefficient of the individual lncRNAs,we identified a ninelncRNA signature that was associated with the survival of CRC patients in the training set(n=175).The prognostic value of this nine-lncRNA signature was validated in the testing set(n=174)and TCGA set(n=349).The prognostic models,consisting of these nine CRC-specific lncRNAs,performed well for risk stratification in the testing set and TCGA set.Time-dependent receiver operating characteristic analysis indicated that this predictive model had good performance.RESULTS Multivariate Cox regression and stratification analysis demonstrated that this nine-lncRNA signature was independent of other clinical features in predicting overall survival.Functional enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology terms further indicated that these nine prognostic lncRNAs were closely associated with carcinogenesis-associated pathways and biological functions in CRC.CONCLUSION A nine-lncRNA expression signature was identified and validated that could improve the prognosis prediction of CRC,thereby providing potential prognostic biomarkers and efficient therapeutic targets for patients with CRC.

Advances in molecular,genetic and immune signatures of gastric cancer:Are we ready to apply them in our patients' decision making?

In the last few years we have witnessed a vast expansion of our knowledge regarding the molecular and genetic profile of gastric cancer.The molecular subtypes described have shed light on the pathogenesis of the disease,thus prompting the development of new therapeutic strategies and favoring a more individualized approach for treatment.Most of the clinical trials for so called targeted therapies could be considered,at best,partially successful.In addition,checkpoint inhibitors ha-ve recently been added to our armamentarium in later stages of the disease,and combinations with chemotherapy and targeted agents are currently under development.In view of the rapid advances of molecular oncology,a new challenge for the clinical oncologist arises: The appropriate patient selection for each new therapy,which can be made possible only through the implementation of predictive biomarkers in our therapy decision making.

Eight hub genes as potential biomarkers for breast cancer diagnosis and prognosis:A TCGA-based study

BACKGROUND Breast cancer(BC)is the most common malignant tumor in women.AIM To investigate BC-associated hub genes to obtain a better understanding of BC tumorigenesis.METHODS In total,1203 BC samples were downloaded from The Cancer Genome Atlas database,which included 113 normal samples and 1090 tumor samples.The limma package of R software was used to analyze the differentially expressed genes(DEGs)in tumor tissues compared with normal tissues.The cluster Profiler package was used to perform Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis of upregulated and downregulated genes.Univariate Cox regression was conducted to explore the DEGs with statistical significance.Protein-protein interaction(PPI)network analysis was employed to investigate the hub genes using the CytoHubba plug-in of Cytoscape software.Survival analyses of the hub genes were carried out using the Kaplan-Meier method.The expression level of these hub genes was validated in the Gene Expression Profiling Interactive Analysis database and Human Protein Atlas database.RESULTS A total of 1317 DEGs(fold change>2;P<0.01)were confirmed through bioinformatics analysis,which included 744 upregulated and 573 downregulated genes in BC samples.KEGG enrichment analysis indicated that the upregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,cell cycle,and the p53 signaling pathway(P<0.01);and the downregulated genes were mainly enriched in the cytokine-cytokine receptor interaction,peroxisome proliferator-activated receptor signaling pathway,and AMP-activated protein kinase signaling pathway(P<0.01).CONCLUSION In view of the results of PPI analysis,which were verified by survival and expression analyses,we conclude that MAD2L1,PLK1,SAA1,CCNB1,SHCBP1,KIF4A,ANLN,and ERCC6L may act as biomarkers for the diagnosis and prognosis in BC patients.

基于TCGA研究左右半结肠癌基因表达差异及苦参-大血藤-半枝莲作用机制

【目的】探讨左半结肠癌与右半结肠癌的基因表达差异及大肠癌核心药对苦参-大血藤-半枝莲作用于左右半结肠癌的机制差异。【方法】下载134例左半结肠癌及194例右半结肠癌患者癌症基因组图谱(TCGA)的转录组数据,应用R软件实现2组差异基因分析及京都基因与基因组百科全书(KEGG)通路富集分析;通过BATMAN-TCM数据库获取苦参-大血藤-半枝莲药对的活性成分及靶点,基于左右半结肠癌差异基因,分别进行药对-左/右半结肠癌KEGG富集分析、蛋白质互作(PPI)网络构建,比较药对治疗左、右半结肠癌富集的生物信号通路差异及关键靶点差异。【结果】左半结肠癌与右半结肠癌相对于正常癌旁组织共同的差异表达基因共6051个,左半结肠癌特异性的差异表达基因共1958个,右半结肠癌特异性的差异表达基因共1739个;左半结肠癌特异性KEGG富集通路14条,右半结肠癌特异性KEGG富集通路23条。苦参-大血藤-半枝莲药对活性化合物共85个,对应的靶点合计469个,药对-左半结肠癌靶点富集于10条KEGG信号通路,关键靶点为DRD2、CACNA1C、HTR3A、COMT、TH,药对-右半结肠癌靶点富集于1条KEGG信号通路,核心靶点为HTR3A、DRD2、TH、AGT、GRIN2B。【结论】左半结肠癌与右半结肠癌存在基因表达差异:左半结肠癌与免疫功能异常、AMPK信号通路异常等机制有关,右半结肠癌与中性粒细胞外陷阱形成、酒精中毒、Hippo信号通路异常等机制有关。除调控细胞周期及必需氨基酸代谢等机制外,苦参-大血藤-半枝莲药对对调节左半结肠癌肠道内分泌功能、抑制右半结肠癌炎症反应具有特异性作用,亦可能对结肠癌患者具有情绪调控作用。

基于TCGA数据库构建肝细胞癌双硫死亡相关基因(DRGs)预后风险模型及评价

目的基于癌症基因组图谱(the cancer genome atlas,TCGA)数据库构建肝细胞癌(hepatocellular carcinoma,HCC)双硫死亡相关基因(disulfidptosis-related genes,DRGs)预后风险模型及评价。方法通过生物信息学方法分析TCGA数据库中371例HCC样本及50例癌旁样本中15个DRGs的表达情况,并进行基因本体(gene ontology,GO)功能注释和京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)富集分析、Kaplan-Meier(KM)生存分析;通过单因素COX回归分析筛选出有统计学意义的DRGs,通过LASSO回归分析及多因素COX回归分析筛选出关键DRGs构建预后风险模型,并根据风险评分将HCC患者分为高风险组和低风险组,制作KM生存曲线和时间依赖的受试者工作特征(receiver operator characteristic,ROC)曲线进行验证评价。结果与癌旁样本相比,HCC样本15个DRGs中FLNA,MYH9,TLN1,ACTB,MYL6,CAPZB,DSTN,ACTN4,SLC7A11,INF2,CD2AP,PDLIM1和FLNB均表达上调,且差异具有统计学意义(t=1793~6310,均P<0.001);经GO功能注释和KEGG富集分析显示,DRGs主要与肌动蛋白细胞骨架和细胞黏附相关的生物过程或途径密切相关。经KM生存分析结果显示,SLC7A11,INF2,CD2AP,MYL6,ACTB高表达组生存率低于低表达组[HR=1.46(1.03~2.07)~1.93(1.36~2.75),均P<0.05]。通过单因素COX回归分析、LASSO分析及多因素COX回归分析构建预后风险模型riskscore=(0.247×SLC7A11)+(0.289×INF2)+(0.076×CD2AP)+(0.06×MYL6);计算样本的风险评分,风险评分越高,预后不良的HCC患者人数越多;KM生存分析显示高风险组的总生存率比低风险组低;1,3,5年的AUC值分别为0.709,0.661和0.648;通过多因素COX回归分析表明SLC7A11[HR=1.832(1.274~2.636),P=0.001]是独立的预后危险因素。结论四个DRGs构建的预后风险模型在预测HCC患者预后情况有一定的作用。

利用TCGA和GEPIA2公共数据库分析ACSM3与卵巢癌预后的关系

目的 研究肿瘤基因图谱(TCGA)数据库中酰基辅酶A合成酶中链家族成员3(ACSM3)在357例卵巢癌患者中的表达量及其与患者生存状况的关系。方法 对TCGA数据库中357例卵巢癌患者的ACSM3表达量及其与生存情况的关系进行分析,寻找其共表达基因并进行基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)富集分析。结果 多因素Cox回归分析进一步表明,ACSM3是卵巢癌患者预后的影响因素,其共表达基因富集分析结果与炎症应答和肿瘤中基因异常转录相关。结论 ACSM3的表达对卵巢癌患者的预后具有重要的意义,高表达预后较好。ACSM3可以成为指导临床医师评估卵巢癌患者预后的重要指标。

The expression significance of RACGAP1 gene in hepatocellular carcinoma and its prognostic effect were analyzed based on TCGA database

Objective:To explore the expression and clinical significance of RACGAP1 gene in hepatocellular carcinoma.Methods:Data about RACGAP1 gene and clinic pathological data in liver cancer were retrieved from The Cancer Genome Atlas(TCGA).The relationship between the expression of RACGAP1 gene and clinic pathological parameters,and prognosis were analyzed by R 2.15.3 software.The association between RACGAP1 gene expression and prognosis of liver cancer patients was analyzed by Kaplan-Meier survival function analysis and Cox regression analysis.Results:TCGA database was used to collect 235 cases of liver cancer with clinical pathological parameters and their corresponding RACGAP1 expression levels.After the incomplete cases and those with no detailed pathological parameters were excluded,and it was found that RACGAP1 was highly expressed in liver cancer tissues.Meanwhile,the expression of RACGAP1 in patients with liver cancer in the TCGA tumor database was further analyzed with the matching clinical data parameters.The expression level of RACGAP1 was significantly correlated with the pathological grade and T stage of liver cancer patients(all P<0.05),but was not significantly correlated with American Joint Committee on Cancer(AJCC)pathological stage and gender(P>0.05).There was a significant correlation between RACGAP1 expression level and overall survival(OS)in patients with liver cancer(P<0.05),and the overall survival time of patients with low expression was better than that of patients with high expression(P<0.05).Cox regression was used to analyze the correlation between T stage,M stage,N stage and RACGAP1 expression in patients with hepatocellular carcinoma(HCC),and RACGAP1 became an independent prognostic factor in patients with HCC(P<0.05).Conclusion:Based on the tumor-related gene information in the public database TCGA,RACGAP1 gene is highly expressed in liver cancer tissues and becomes an independent prognostic factor of liver cancer,which is expected to become an important therapeutic target of drug therapy for liver cancer.

Identification and validation of a new prognostic signature based on cancer-associated fibroblast-driven genes in breast cancer

BACKGROUND Breast cancer(BC),a leading malignant disease,affects women all over the world.Cancer associated fibroblasts(CAFs)stimulate epithelial-mesenchymal transition,and induce chemoresistance and immunosuppression.AIM To establish a CAFs-associated prognostic signature to improve BC patient out-come estimation.METHODS We retrieved the transcript profile and clinical data of 1072 BC samples from The Cancer Genome Atlas(TCGA)databases,and 3661 BC samples from the The Gene Expression Omnibus.CAFs and immune cell infiltrations were quantified using CIBERSORT algorithm.CAF-associated gene identification was done by weighted gene co-expression network analysis.A CAF risk signature was established via univariate,least absolute shrinkage and selection operator regression,and mul-tivariate Cox regression analyses.The receiver operating characteristic(ROC)and Kaplan-Meier curves were employed to evaluate the predictability of the model.Subsequently,a nomogram was developed with the risk score and patient clinical signature.Using Spearman's correlations analysis,the relationship between CAF risk score and gene set enrichment scores were examined.Patient samples were collected to validate gene expression by quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS Employing an 8-gene(IL18,MYD88,GLIPR1,TNN,BHLHE41,DNAJB5,FKBP14,and XG)signature,we attemp-ted to estimate BC patient prognosis.Based on our analysis,high-risk patients exhibited worse outcomes than low-risk patients.Multivariate analysis revealed the risk score as an independent indicator of BC patient prognosis.ROC analysis exhibited satisfactory nomogram predictability.The area under the curve showed 0.805 at 3 years,and 0.801 at 5 years in the TCGA cohort.We also demonstrated that a reduced CAF risk score was strongly associated with enhanced chemotherapeutic outcomes.CAF risk score was significantly correlated with most hallmark gene sets.Finally,the prognostic signature were further validated by qRT-PCR.CONCLUSION We introduced a newly-discovered CAFs-associated gene signature,which can be employed to estimate BC patient outcomes conveniently and accurately.

基于TCGA数据库分析乳腺癌组织RBP7 mRNA表达与肿瘤免疫细胞浸润及预后的相关性

目的通过生物信息学的方法探讨视黄醇结合蛋白7(retinol binding protein 7,RBP7)在乳腺癌中的作用。方法使用R语言基于癌症基因组图谱(the cancer genome atlas,TCGA)数据库和人类蛋白质图谱(the human protein atlas,HPA)数据库探索基因RBP7在乳腺癌组织中的差异表达。通过Kaplan-Meier生存分析和受试者工作特征(receiver operating characteristic,ROC)曲线,评估RBP7与乳腺癌临床数据的关系。基于TCGA数据库分析RBP7高低表达分组与不同肿瘤浸润免疫细胞(tumor-infiltrating immune cells,TIICs)的相关性。基因组富集分析(gene set enrichment analysis,GSEA)评估RBP7在与表型相关度排序的基因表中的分布趋势。结果与癌旁组织相比,乳腺癌中RBP7 mRNA表达水平下调,该分子表达在细胞核中。ROC曲线分析显示RBP7诊断乳腺癌的曲线下面积(area under curve,AUC)是0.943(95%CI:0.926~0.960),RBP7的最佳截断值是6.29,敏感度和特异度分别为82.32%,93.69%。Kaplan-Meier生存分析显示RBP7低表达与乳腺癌患者的总生存率相关(HR=0.68,95%CI:0.49~0.93,P=0.017),RBP7是乳腺癌发生的独立危险因素。Spearman相关性揭示RBP7与乳腺癌中pDC细胞和NK细胞呈正相关(r=0.290,0.253,均P<0.05),与Th2细胞呈负相关(r=-0.217,P<0.05)。GSEA表明RBP7富集在脂肪生成、核糖体、肽配体结合受体、钙信号途径等通路中(均P<0.001)。结论RBP7影响乳腺癌的发生发展,可能成为乳腺癌潜在生物标志物和治疗靶点。

基于TCGA数据库角蛋白家族基因对肺腺癌病人预后的预测价值

目的:探讨角蛋白(KRT)家族基因对肺腺癌(LUAD)病人预后的预测价值。方法:RNA测序数据来自LUAD肿瘤和配对正常组织的癌症基因组图谱(TCGA)数据库。采用多变量COX比例风险回归分析评估KRT家族成员基因的预后价值。分析筛选变量以构建风险评分,时间相关ROC曲线评估预测结果。采用使用Nomogram评估个体化预后风险。结果:从差异表达基因中筛选出14个在LUAD肿瘤及癌旁组织中存在显著失衡的KRT基因。ROC曲线分析证实,该14个KRT基因可以作为LUAD诊断的潜在诊断标志物。6个KRT基因与肺癌预后相关,结果显示KRT8和KRT6A是影响LUAD预后的独立危险因素。结论:KRT8和KRT6A可作为LUAD的预后指标,KRT8和KRT6A高表达表明LUAD病人的预后较差。

基于TCGA数据库探究SERPINA5在前列腺癌中的表达及临床意义

目的:研究前列腺癌中关键基因的差异化表达,为前列腺癌的诊疗提供新的生物治疗靶点和理论依据。方法:从美国癌症基因组图谱(TCGA)中下载前列腺癌的相关基因数据,利用R软件筛选出在前列腺癌组织和癌旁组织中差异化表达的基因,并进行富集分析。利用STRING 11.0构建差异基因所表达蛋白的互作网络图,并通过Cytoscape_v3.7.1进一步筛选Hub基因,通过Oncomine数据库对Hub基因在前列腺癌中的表达进行验证得到关键基因,随后利用R软件对关键基因与临床数据进行统计分析,最终利用在线工具GEPIA对关键基因进行生存分析。结果:总共得到551个样本(其中癌旁组织样本52个,癌组织样本499个),筛选后得到463个差异基因,其中呈现上调趋势的基因共265个,下调198个。富集分析后发现这些基因主要富集在顶体反应的调节、三酰甘油代谢过程,PPAR信号通路等,进一步筛选后得到10个Hub基因,与Oncomine数据库联合验证后得到关键基因SERPINA5,进行临床分析发现前列腺癌病人的SERPINA5的表达水平与肿瘤分化程度、TNM分期以及无病生存率有关(P<0.05),而与年龄、人种以及总生存率的差异无关(P>0.05)。结论:前列腺癌中存在大量差异基因可能对疾病的发生发展起到影响作用,其中SERPINA5也许可以作为前列腺癌早期筛查标志物或治疗的生物靶点,为前列腺癌的预防与治疗带来新的方案以及研究方向。

基于TCGA数据分析NEK2基因在恶性胸膜间皮瘤中的表达及预后意义

目的 分析永不有丝分裂基因A相关激酶2(NEK2)基因在恶性胸膜间皮瘤(MPM)中的表达及预后意义。方法 下载癌症基因组图谱(TCGA)数据库MPM基因表达数据、临床病理数据和生存状态数据;使用perl软件和R语言的limma、timeROC等程序包作NEK2基因在MPM中的差异分析、临床病理相关性分析、COX单因素和多因素分析以及基因富集分析,并绘制ROC曲线;利用TIMER2.0数据库分析MPM中NEK2表达与常见的免疫细胞浸润的相关性。选取12例MPM组织和6例非MPM胸膜组织,通过RT-qPCR的方法验证NEK2基因在MPM与非瘤组织中的表达情况。结果 与正常肺组织相比,NEK2在MPM组织中高表达(P<0.001)。NEK2基因mRNA表达量与MPM淋巴结分期具有显著相关性(P<0.05);NEK2高表达与MPM患者预后不良相关(P<0.001);NEK2基因表达与MPM中B淋巴细胞、巨噬细胞、树突状细胞浸润水平呈正相关(P<0.05),并在细胞周期、DNA复制、剪接体、mRNA监测等通路显著富集。在收集到的病例样本中,与非MPM胸膜组织相比,NEK2基因在MPM组织中的表达量显著增高(P<0.01)。结论 NEK2在MPM组织中高表达,且NEK2在MPM中高表达提示预后不良,可能成为治疗MPM的潜在靶点。

基于TCGA数据分析TRIM45基因在乳腺癌中的表达特征及生物学功能

目的基于GDC TCGA Breast Cancer(BRCA)的数据,评估TRIM45(Tripartite Motif Family 45)在乳腺癌中的表达、预后价值及其与临床病理的相关性,揭示TRIM45在乳腺癌中的生物学功能及可能的作用机制。方法采用R软件对GDC TCGA Breast Cancer(BRCA)数据进行生信分析,研究TRIM45在乳腺癌中的表达及其与临床病理的关系。采用Kaplan-Meier法评估TRIM45对乳腺癌预后的影响。应用KEGG基因集进行GSEA(Gene Set Enrichment Analysis)基因富集分析,采用Spearman相关性分析筛选TRIM45相关作用基因。结果TRIM45在乳腺癌临床样本中的表达高于癌旁组织(P<0.001);Kaplan-Meier生存分析显示TRIM45高表达患者的总生存期高于TRIM45低表达者(P<0.05);TRIM45在乳腺癌中的表达与T分期、TNM分期、分子分型及病理类型相关联(P<0.05);GSEA富集分析结果显示TRIM45在KEGG_PATHWAYS_IN_CANCER信号通路中发挥重要的生物学作用,Spearman相关性分析筛选出TRIM45与STK36、IKBKB、GLI3具有正相关关系(P<0.001),与HIF1A具有负相关关系(P<0.001)。结论TRIM45在乳腺癌中的表达与T分期、TNM分期、分子分型及病理类型相关联;TRIM45可能通过调控STK36、IKBKB、GLI3和HIF1A在乳腺癌发生发展中发挥重要作用。

基于TCGA数据库分析SSBP1基因在肝细胞癌中的表达及预后

目的利用癌症基因组图谱(TCGA)数据库研究SSBP1基因在肝细胞癌(HCC)组织中的表达情况,并探讨SSBP1基因表达量与患者临床病理特征及预后的相关性。方法基于TCGA数据库提取374例HCC组织及50例正常肝组织中SSBP1基因表达量数据、患者的临床病理参数资料,利用R 4.1.2分析SSBP1在HCC中的表达情况及其与HCC患者的临床病理特征和预后的相关性,通过基于基因表达水平值的交互式分析平台(GEPIA)数据库和R 4.1.2联合分析SSBP1在HCC各临床病理分期间的表达差异,利用TIMER数据库分析SSBP1表达与免疫细胞浸润的相关性,通过R软件pROC程序包制作ROC生存曲线评估SSBP1表达量对HCC的诊断效果。结果TCGA数据库分析表明,无论是配对样本还是非配对样本,SSBP1 mRNA在HCC组织中的表达水平均高于正常肝组织(P均<0.001),且表达水平与性别和M分期有关(P均<0.05),与年龄、T分期、AJCC分期等无关(P均>0.05)。进一步进行单因素和多因素Cox回归分析发现,SSBP1高表达是影响HCC患者总生存期(OS)的独立危险因素(HR=1.713,P=0.016)。免疫细胞浸润分析发现,HCC组织中SSBP1表达与幼稚B细胞浸润水平呈负相关,而与记忆B细胞和巨噬细胞呈正相关(|r|>0.2,P均<0.05)。ROC曲线分析显示,SSBP1 mRNA表达水平对HCC的早期诊断和预后均具有良好的评估价值(AUC>0.50)。结论SSBP1 mRNA在HCC中的表达增高,且高表达是预后不良的独立危险因素,同时SSBP1对HCC具有良好的诊断价值,可成为HCC患者预后判断一种潜在的分子标志物以及免疫治疗的潜在靶点。