大肠癌患者生存相关基因的筛选与网络调控分析

本研究筛选了与大肠癌患者生存期相关的关键基因,以探索这些基因所参与的信号调控网络.在前期研究中,通过对大肠癌相关表达谱数据GSE17538使用显著性分析软件SAM3.01对大肠癌患者生存期相关的基因进行筛选,得到了与大肠癌患者生存期相关的基因235个.对这235个基因进行以下筛选和分析:首先对235个基因进行转录因子结合位点富集分析,筛选含有转录因子结合位点数目大于7个的基因,再将这些基因与大肠癌上调基因集取交集,最后将筛选出的基因进行生存分析及网络调控分析,明确这些基因与大肠癌患者生存期的关系及在大肠癌细胞信号调控网络中所参与的信号网络.通过上述分析筛选出的与大肠癌患者生存期相关,受转录因子调控较多,且在大肠癌中表达上调的基因有6个,分别为STX2,PODXL,KLK6,GRB10,EHBP1和CREB5.这些基因所参与的信号调控网络与大肠癌转移相关信号通路相关.大肠癌患者生存期与大肠癌转移密切相关,生存期相关的6个基因通过调控大肠癌转移相关信号通路影响患者的生存期.     

人类正常胃肠道组织基因表达谱特征的生物信息学分析

目的:筛选人类正常胃肠道组织特异性高表达基因.方法:以公开发表的人类正常组织基因表达数据库资料为研究对象,应用单侧 Student T检验筛选胃、回肠和结肠组织的特异性高表达基因.Ingenuity软件和KEGG分析特异性高表达基因相关的生理功能;Cluster软件分析胃特异性高表达基因谱在胃癌基因数据库中的表达特征.结果:筛选出胃高表达基因196个,回肠高表达基因203个,结肠高表达基因224个,高表达基因的功能与胃肠道的主要生理功能相吻合.筛选出的正常胃肠高表达基因中含有一些癌基因和抑癌基因.系统聚类分析发现胃特异性高表达基因在胃癌数据库的胃正常组织中高表达,而相应的胃癌组织低表达,癌组织和正常组织可以完好聚类分组,并且可以区分中分化和低分化胃癌.结论:人类正常胃、回肠和结肠具有组织特异的与生理功能密切相关的高表达基因群.     

CREB5在大肠癌转移中的调控机制

大肠癌转移过程中所涉及的细胞信号调控网络非常复杂, 寻找调控网络中的关键调控点对阐明大肠癌转移机制以及寻找药物治疗靶点均具有重要意义。研究表明, CREB5 (cAMP responsive element binding protein 5)可能为大肠癌转移相关信号调控网络中的关键基因。文章基于大肠癌表达谱数据, 根据CREB5基因表达值的大小对大肠癌的相关分子事件进行了富集分析, 发现这些分子事件与肿瘤转移密切相关。根据CREB5能够和c-Jun结合成为异二聚体的特点, 联合分析转录因子AP-1结合位点的富集情况, 筛选出在CREB5基因高表达组中表达上调、具有AP-1结合位点、且属于癌症通路的基因16个, 这些基因所构成的分子网络与细胞迁移功能类相关度最高。细胞迁移功能类主要由5个基因——CSF1R、MMP9、PDGFRB、FIGF和IL6所构成, 因此CREB5可能是通过调控这5个关键基因进而促进大肠癌的转移。     

大肠癌组织及癌旁组织中c-myc,COX-2和CD44v6基因表达量差异的检测

目的:通过检测大肠癌组织和癌旁组织中c-myc,COX-2以及CD44v6的表达水平,探讨这三种基因在大肠癌发生和发展中的意义。方法:应用实时荧光定量PCR技术检测了10例大肠癌组织和相应癌旁组织中c-myc,COX-2以及CD44v6基因表达水平的差异,并探讨了各基因在癌组织中的表达水平与大肠癌临床病理指标之间的关系。结果:c-myc,COX-2以及CD44v6在大肠癌组织和癌旁组织中的表达均有非常显著性差异(P<0.01);癌组织中COX-2和CD44v6的表达与淋巴结转移、分化程度及Dukes分期有关(P<0.05)。结论:c-myc,COX-2和CD44v6的异常表达均与大肠癌密切相关,三者从不同方面对大肠癌的发生和发展起到了重要作用,可作为早期诊断和预后的参考指标。     

大肠癌转移相关基因表达调控的生物信息学分析

大肠癌是常见的消化道恶性肿瘤,在中国呈逐年上升的趋势。对大肠癌发生发展转移的研究能够指导临床治疗,对研发新药也有着重要意义。本文通过对表达谱数据进行分析,通过表达谱差异数据进行功能富集,研究了大肠癌转移前的早期原发肿瘤的转录调控特点以及远隔器官转移后的大肠癌的转录调控特点,筛选出了部分能够受到多重调控并在转移后肿瘤组织中高表达的关键基因,通过对这些基因相互作用关系研究,构建出转移后关键基因相互作用调控网络,为大肠癌的治疗提供更多潜在靶点。     

大肠癌组织及癌旁组织中c—myc，COX-2和CD44v6基因表达量差异的检测

目的：通过检测大肠癌组织和癌旁组织中c-myc,COX-2以及CD44v6的表达水平,探讨这三种基因在大肠癌发生和发展中的意义。方法：应用实时荧光定量PCR技术检测了10例大肠癌组织和相应癌旁组织中c-myc,COX-2以及CD44v6基因表达水平的差异,并探讨了各基因在癌纽织中的表达水平与大肠癌临床病理指标之间的关系。结果：c-myc,COX-2以及CD44v6在大肠癌组织和癌旁组织中的表达均有非常显著性差异（P〈0．01）;癌组织中COX-2和CD44v6的表达与淋巴结转移、分化程度及Dukes分期有关（P〈0．05）。结论：c—myc,COX-2和CD44v6的异常表达均与大肠癌密切相关,三者从不同方面对大肠癌的发生和发展起到了重要作用,可作为早期诊断和预后的参考指标。     

胶质母细胞瘤预后相关基因的数据挖掘分析

胶质母细胞瘤（glioblastoma, GBM）是恶性程度最高的颅内恶性肿瘤，目前临床上缺乏有效治疗药物，复发率高且预后差，开发新的抗GBM药物是目前临床上亟待解决的问题。为了筛选与GBM预后密切相关的基因，为寻找新的药物靶点提供线索，采用GEO2R工具从GEO数据库中的269个肿瘤组织和61个正常组织中初步筛选出差异表达基因，然后利用Cluster Profiler数据库进行基因功能富集分析，STRING及Cytoscape进一步筛选出37个差异表达基因，采用GEPIA交互分析对这37个基因在GBM肿瘤组织中的表达进行验证。为了进一步探索这些差异表达基因与患者预后的关系，研究中利用GEPIA工具对TCGA数据库中与患者预后相关的数据进行深入挖掘，最终发现PTTG1、RRM2、E2F7与患者中位生存期呈显著性负相关。研究筛选出的与患者预后密切相关的基因不仅可以为评估患者预后提供参考，同时也为开发新的抗GBM药物提供了潜在的靶点。     

DOK2对胃癌细胞生物学行为的影响及其与胃癌预后的关系

构建重组质粒pc DNA3.1-DOK2并转染胃癌细胞BGC823,采用平板集落形成、CCK8法和软琼脂克隆形成实验检测过表达DOK2基因对BGC823生物学行为的影响,并采用免疫组织化学法检测116例胃癌组织中DOK2蛋白的表达,分析其与胃癌临床病理学特征及预后的关系。结果显示,过表达的DOK2基因对BGC823细胞增殖有显著抑制作用。在所有胃癌组织中,DOK2蛋白低表达占62.93%,且其与胃癌浸润深度、淋巴结转移以及分化程度密切相关;DOK2蛋白的表达、胃癌浸润深度、淋巴结转移、远处转移以及分化程度是影响患者预后生存时间的重要因素。     

利用组织微阵列研究ACVRL1在鼻咽癌中的表达及临床意义

ACVRL1基因又名活化素受体样激酶l(activin receptor-like kinase-1, ALK1),与2型遗传性出血性毛细血管扩张性疾病(HHT2)密切相关.通过制作含896个组织点阵的鼻咽癌组织微阵列.结合原位杂交法检测ACVRL1在鼻咽癌组织中的mRNA表达,建立ACVRL1基因在鼻咽癌组织中的原位表达谱,分析ACVRL1mRNA的表达与鼻咽癌临床病理特征关系,并分析其与鼻咽癌颈部淋巴结转移的关系.结果发现ACVRL1mRNA在鼻咽癌组织中的表达与相应非癌组织相比,有显著性差异(P<0.05);ACVRL1mRNA的表达与临床分期无显著相关性(P>0.05);与颈部淋巴结有无转移存在显著性差异(P<0.05);但与EBV VCA-IgA血清滴度没有显著相关性(P>0.05).灵敏度、特异度、阳性预测值和阴性预测值等指标综合评估ACVRL1基因作为鼻咽癌颈部淋巴结转移分子标志物的有效性.这些结果表明ACVRL1基因在鼻咽癌组织中表达下调,与颈部淋巴结转移密切相关,可作为鼻咽癌颈部淋巴结是否转移的候选分子标志物.     

铜死亡相关LncRNA预测胃癌的预后及免疫反应

基于生物信息学分析构建预后相关的预测模型,探讨铜死亡相关LncRNA与胃癌（GC）在免疫和预后方面的关系。从癌症基因组图谱（TCGA）数据库下载胃癌患者的RNA测序和临床数据,基于共表达分析筛选出铜死亡相关LncRNA,通过LASSO回归和多因素Cox回归分析构建出与胃癌预后密切相关的铜死亡相关LncRNA风险预测模型,并计算所有胃癌患者样本的风险评分。通过Kaplan-Meier生存分析、回归分析和受试者工作特征（ROC）曲线等证实模型的预后预测性能,并分析风险评分与通路富集分析、免疫浸润细胞、免疫检查点基因、体细胞基因突变及抗癌药物敏感性的相关性。差异表达分析结果表明,LncRNA HAGLR在肿瘤组织中的表达上调。通过实时荧光定量PCR(qRT-PCR)检测LncRNA HAGLR在69例行根治性手术胃癌患者的癌组织及癌旁组织的表达。结果表明,相比于癌旁组织,胃癌组织中HAGLR表达上调,且与肿瘤大小、浸润深度、肿瘤TNM分期、分化程度及淋巴结转移成明显相关性（P<0.05）。本研究构建的铜死亡相关LncRNA预后模型具有较高的预测价值,并且与免疫细胞浸润异质性明显相关,在...     

Stem cell gene Girdin: a potential early liver metastasis predictor of colorectal cancer

The objective of this study is to investigate the liver's metastasis-related genes and the relationship between Girdin protein expression and clinical and pathological characteristics and prognosis in colorectal cancer. The differential expression of genes between tumor cells from cases with liver metastasis and those from cases without liver metastasis were detected using an RT(2) Profiler? PCR Array. The expression of the stem cell gene Girdin was analyzed using immunohistochemistry staining. Subsequently, the relationship between Girdin and clinicopathological parameters of colorectal cancer was determined. The Girdin protein was verified as a gene related to liver metastasis and was expressed positively in 161 (37.01 %) of the 435 cases examined. The expression of Girdin protein was related to histological grade and distant metastasis (P = 0.007 and 0.007, respectively). After analyzing survival rates, cases with highly expressed Girdin protein were shown to attain a significantly higher rate of liver metastasis and poorer postoperative, disease-specific survival than those with no or low expressed Girdin protein (P = 0.001). In the Cox regression test, the depth of tumor invasion, histological grade, duke's stage, distant metastasis, and the Girdin protein were detected as an independent prognostic factor (0.020, 0.032, 0.001, 0.001, and 0.010, respectively). The Girdin protein may be a potential new early liver metastasis biomarker of colorectal cancer.     

生物信息学分析筛选结直肠癌靶基因及评估预后价值

为寻找与结直肠癌发展和预后相关的潜在关键基因及信号通路.从美国国立信息中心NCBI的GEO数据库获得结直肠癌基因表达数据集GSE106582,通过PCA对样本进行分组,利用GEO2R进行综合分析,筛选结直肠癌与癌旁对照组的差异表达基因;通过DAVID在线工具对差异表达基因进行GO本体分析和KEGG通路富集分析,初步分析...     

Discovery of core gene families associated with liver metastasis in colorectal cancer and regulatory roles in tumor cell immune infiltration

In this study, we aimed to uncover genes that drive the pathogenesis of liver metastasis in colorectal cancer (CRC), and identify effective genes that could serve as potential therapeutic targets for treating with colorectal liver metastasis patients based on two GEO datasets. Several bioinformatics approaches were implemented. First, differential expression analysis screened out key differentially expressed genes (DEGs) across the two GEO datasets. Based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we identified the enrichment functions and pathways of the DEGs that were associated with liver metastasis in CRC. Second, immune infiltration analysis identified key immune signature gene sets associated with CRC liver metastasis, among which two key immune gene families (CD and CCL) identified as key DEGs were filtered by protein-protein interaction (PPI) network. Some of the members in these gene families were associated with disease free survival (DFS) or overall survival (OS) in two subtypes of CRC, namely COAD and READ. Finally, functional enrichment analysis of the two gene families and their neighboring genes revealed that they were closely associated with cytokine, leukocyte proliferation and chemotaxis. These results are valuable in comprehending the pathogenesis of liver metastasis in CRC, and are of seminal importance in understanding the role of immune tumor infiltration in CRC. Our study also identified potentially effective therapeutic targets for liver metastasis in CRC including CCL20, CCL24 and CD70.     

SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles

Although metastasis is the principal cause of death cause for colorectal cancer (CRC) patients, the molecular mechanisms underlying CRC metastasis are still not fully understood. In an attempt to identify metastasis-related genes in CRC, we obtained gene expression profiles of 55 early stage primary CRCs, 56 late stage primary CRCs, and 34 metastatic CRCs from the expression project in Oncology (http://www.intgen.org/expo/). We developed a novel gene selection algorithm (SVM-T-RFE), which extends support vector machine recursive feature elimination (SVM-RFE) algorithm by incorporating T-statistic. We achieved highest classification accuracy (100%) with smaller gene subsets (10 and 6, respectively), when classifying between early and late stage primary CRCs, as well as between metastatic CRCs and late stage primary CRCs. We also compared the performance of SVM-T-RFE and SVM-RFE gene selection algorithms on another large-scale CRC dataset and the five public microarray datasets. SVM-T-RFE bestowed SVM-RFE algorithm in identifying more differentially expressed genes, and achieving highest prediction accuracy using equal or smaller number of selected genes. A fraction of selected genes have been reported to be associated with CRC development or metastasis.     

应用结直肠癌基因检测指导术后化疗

为了探讨结直肠癌基因检测在术后化疗中的应用价值,本研究于2015年2月至2017年2月期间,选取在我院行结直肠癌根治术患者102例,根据患者选取的治疗方案,分为观察组(n=47)和对照组(n=55)。其中观察组根据术后肿瘤组织基因检测结果给予化疗方案,对照组直接选用FOLFOX4方案,随访观察两组无进展生存期和总生存期。研究发现,观察组检测到1例Nras基因突变,3例Braf基因突变,19例Kras基因突变,2例Pik3ca基因突变;Kras基因突变与肿瘤部位和分化程度有关(p<0.05);观察组中位无进展生存期为23个月,明显长于对照组的17个月,差异比较具有统计学意义(p<0.05);观察组中位总生存期为31个月,明显长于对照组的25个月,差异比较具有统计学意义(p<0.05);观察组和对照组Ⅲ～Ⅳ级肝肾损害、骨髓抑制和胃肠道反应比例比较差异无统计学意义(p>0.05)。研究表明结直肠癌基因检测指导术后化疗,可以提高患者无进展生存期和总生存期,具有较好的应用价值。     

结直肠癌患者血清GDF-15、G-CSF水平与临床病理特征及预后的关系

摘要 目的：探究结直肠癌血清生长分化因子-15（GDF-15）、粒细胞集落刺激因子（G-CSF）水平与患者临床病理参数、预后的关系,并分析其对结直肠癌的诊断价值。方法：采集结直肠癌患者、结直肠腺瘤患者及健康体检志愿者的血清样本,酶联免疫吸附测定（ELISA）实验检测血清GDF-15、G-CSF;分析结直肠癌患者血清GDF-15、G-CSF水平与患者临床病理参数的关系;Kaplan Meier生存曲线分析血清GDF-15、G-CSF水平与患者预后的关系;受试者工作特征曲线（ROC）分析血清GDF-15、G-CSF水平对结直肠癌的诊断价值。结果：结直肠癌患者血清GDF-15、G-CSF水平高于结直肠腺瘤患者及健康体检志愿者（均P<0.05）;血清GDF-15水平与肿瘤直径、分化程度、远处转移及TNM分期相关（均P<0.05）;血清G-CSF水平与肿瘤分化程度、远处转移及TNM分期相关（均P<0.05）;Kaplan Meier生存曲线结果显示,血清GDF-15低表达、G-CSF低表达患者的术后5年总生存率及中位生存时间均分别高于血清GDF-15高表达、G-CSF高表达患者（均P<0.05）;ROC分析结果表明,血清GDF-15、G-CSF有较好的诊断结直肠癌的价值,血清GDF-15、G-CSF联合应用的敏感度、特异度分别为0.876、0.863。结论：结直肠癌患者血清GDF-15、G-CSF水平升高,且均与患者病情恶性进展、不良预后相关;血清GDF-15、G-CSF是诊断结直肠癌的潜在指标。     

Combining bioinformatics techniques to explore the molecular mechanisms involved in pancreatic cancer metastasis and prognosis

This article aims to explore the underlying molecular mechanisms and prognosis‐related genes in pancreatic cancer metastasis. Pancreatic cancer metastasis‐related gene chip data were downloaded from GENE EXPRESSION OMNIBUS(GEO)database. Differentially expressed genes were screened after R‐package pre‐treatment. Functional annotations and related signalling pathways were analysed using DAVID software. GEPIA (Gene Expression Profiling Interactive Analysis) was used to perform prognostic analysis, and differential genes associated with prognosis were screened and validated using data from GEO. We screened 40 healthy patients, 40 primary pancreatic cancer and 40 metastatic pancreatic cancer patients, collected serum, designed primers and used qPCR to test the expression of prognosis‐related genes in each group. 109 differentially expressed genes related with pancreatic cancer metastasis were screened, of which 49 were up‐regulated and 60 were down‐regulated. Functional annotation and pathway analysis revealed differentially expressed genes were mainly concentrated in protein activation cascade, extracellular matrix construction, decomposition, etc In the biological process, it is mainly involved in signalling pathways such as PPAR, PI3K‐Akt and ECM receptor interaction. Prognostic analysis showed the expression levels of four genes were significantly correlated with the overall survival time of patients with pancreatic cancer, namely SCG5, CRYBA2, CPE and CHGB. qPCR experiments showed the expression of these four genes was decreased in both the primary pancreatic cancer group and the metastatic pancreatic cancer group, and the latter was more significantly reduced. Pancreatic cancer metastasis is closely related to the activation of PPAR pathway, PI3K‐Akt pathway and ECM receptor interaction. SCG5, CRYBA2, CPE and CHGB genes are associated with the prognosis of pancreatic cancer, and their low expression suggests a poor prognosis.     

结直肠癌COX-2表达及其与临床病理特征的相关性分析

目的:探讨结直肠癌环氧化酶-2(cyclooxygenase-2,COX-2)的表达及其与临床病理特征的相关性。方法:选择2017年8月～2019年6月在本院外科手术诊治的结直肠癌患者60例,取所有患者的病灶组织标本与癌旁组织标本,采用PCR与免疫组化法检测COX-2 mRNA与蛋白表达情况,分析其与患者的临床病理特征的相关性。结果:直肠癌组织COX-2 mRNA与蛋白表达阳性率分别为63.3%和55.0%,显著高于癌旁组织的20.0%和16.7%(P0.05)。随着结直肠癌的病理分期及分化程度的增加、淋巴结转移的发生,直肠癌组织的COX-2 mRNA、蛋白表达阳性率显著升高(P0.05)。Spearman等级相关分析显示直肠癌组织的COX-2 mRNA、蛋白表达阳性率与临床分期、组织学分化与淋巴结转移都存在显著相关性(P0.05)。Cox模型多因素分析显示临床分期、组织学分化与淋巴结转移都是影响COX-2蛋白表达的主要因素(P0.05)。结论:结直肠癌COX-2的mRNA与蛋白都呈现高表达,与患者的临床分期、组织学分化与淋巴结转移显著相关。