Involvement of erbB4 and tumor marker genes in renal carcinoma regulatory network

BackgroundRenal carcinoma is a common urologic tumor, and there is no ideal tumor marker for clinical diagnosis except for imaging diagnosis. This study aims to screen the serum tumor markers closely related with the benign and malignant of renal carcinoma out and chart out the regulatory network that involves renal carcinoma-related genes.MethodsBased on 96 pathologically diagnosed renal cancer patients, factors strongly linked to renal carcinoma character were selected using Fisher discriminant analysis. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized to manipulate function annotation of erbB4 and the selected genes and pathway analysis.ResultsFour essential tumor markers CYFRA21-1, CA125, VHL and HIF-1β were successfully screened out. Using GO and KEGG databases, the regulatory network of renal cancer cell escaping apoptosis was charted out on the basis of erbB4 signaling pathway.ConclusionSerum tumor marker genes play a certain part in the genesis and development of renal carcinoma. We preliminarily illustrated the molecular mechanism of these markers to predict tumor, laying a foundation for further exploration in renal carcinoma.     

Establishment of optimal regulatory network of colorectal cancer based on p42.3 protein

Objective: to establish regulatory network of colorectal cancer involving p42.3 protein and to provide theoretical evidence for deep functional exploration of p42.3 protein in the onset and development of colorectal cancer. Methods: with protein similarity algorithm, reference protein set of p42.3 cell apoptosis was built according to structural features of p42.3. GO and KEGG databases were used to establish regulatory network of tumor cell apoptosis involving p42.3; meanwhile, the largest possible working pathway that involves p42.3 protein was screened out based on Bayesian network theory. Besides, GO and KEGG were used to build regulatory network on early diagnosis gene markers for colorectal cancer including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, at the same time, a regulatory network of colorectal cancer cell apoptosis which involves p42.3 was established. Results: cell apoptotic regulatory network that p42.3 participates in primarily consists of Bcl-2 family genes and the largest possible pathway is p42.3 → FKBP → Bcl-2 centered as FKBP protein. Combined with colorectal cancer regulatory network that involves early diagnosis gene markers, it can be predicted that p42.3 is most likely to regulate the colorectal cancer cell apoptosis through FKBP → Bcl-2 → Bax → caspase-9 → caspase-3 pathway. Conclusion: the colorectal cancer apoptosis network based on p42.3 established in the study provides theoretical evidence for deep exploration of p42.3 regulatory mechanism and molecular targeting treatment of colorectal cancer.     

肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析

目的比较肾透明细胞癌Caki-1细胞系与正常肾上皮细胞系ASE-5063中的差异表达基因（DEGs）,寻找潜在的肾透明细胞癌特异性分子标志物。 方法利用GEO数据库自带的GEO2R在线分析工具分析基因芯片GSE78179,将筛选出的DEGs分别导入Metascape、STRING以及Cytoscape进行综合分析并筛选出核心基因。最后使用FunRich等软件对筛选出的核心基因进行GO和KEGG富集分析。 结果共筛选出562个DEGs,其中上调基因345个,下调基因217个。进一步使用MCODE筛选出36个关键基因,GO功能分析发现这些基因与细胞粘附分子活性、趋化因子活性、细胞通讯和信号转导等密切相关;KEGG通路富集结果则表明差异基因主要集中在趋化因子信号通路、TNF信号通路以及NF-κB信号通路等多种与肿瘤相关的通路上。 结论运用生物信息学方法筛选出肾透明细胞癌Caki-1细胞系中DEGs,其中数个核心基因广泛参与多种肿瘤的病理进程,但尚未在肾透明细胞癌有相关研究报道,提示其可能是治疗肾透明细胞癌的潜在靶点。     

COPD 差异表达基因的生物信息学分析及在LUSC样本中的表达

为确定慢性阻塞性肺病(COPD)的分子标记物及COPD与肺鳞状细胞癌(LUSC)共存的差异表达基因,探寻COPD合并肺癌的预测因子,发现新的治疗靶点。本研究采用生物信息学方法,从GEO数据库中筛选3套基因芯片数据集,挖掘COPD患者小气道上皮细胞(SAEC)的差异表达基因(DEG)以及潜在的生物标记物,并通过基因本体(GO)、京都基因与基因组百科全书(KEGG)富集分析预测DEGs的功能及参与的代谢途径。继而对DEGs构建PPI网络,使用Cytoscape软件筛选子模块和Hub基因,并将Hub基因通过TCGA数据库分析其在LUSC中的差异表达情况及差异基因间的相关性。结果共获得52个上调基因和24个下调基因,代谢通路主要集中在细胞色素P450对外源物质的代谢、化学致癌、花生四烯酸代谢及甲状腺激素合成四条途径上,通过Cytoscape软件从PPI网络中筛选得到2个功能模块和10个Hub基因,进一步验证发现其中5个基因在TCGA数据库中的LUSC样本中同样差异表达。由此推测SPP1、ALDH3A1、SPRR3、KRT6A和SPRR1B 可能为COPD 分子标记物及COPD与LUSC共存的DEGs,从而为研究COPD和LUSC的发病机制及二者潜在关系奠定良好的基础。     

血清肿瘤标志物CEA、CA199及CA153联合检测对肺癌的诊断价值

目的：评价血清CEA、CA199及CA153联合检测对肺癌诊断及分期的临床价值。方法：用化学发光分析法测定144例不同类型及分期的肺癌患者、92例肺良性疾病患者及76例健康体检者血清CEA、CA199及CA153水平的变化。结果：肺癌组血清CEA、CA199及CA153水平均高于正常对照组及肺良性疾病患者,有显著性差异,且TNM分期越晚,其水平越高;3项肿瘤标志联合检测可提高敏感性及准确性。结论：CEA、CA199及CA153联合检测可以为肺癌的诊断及分期提供有价值的实验室依据。     

miR-29a靶基因预测及其相关生物信息学分析

目的:通过对miR-29a进行靶基因预测及相关生物信息学分析,为miR-29a靶基因的实验验证提供数据支持,以期为深入研究miR-29a的生物学功能和调控机制提供理论指导。方法:利用PubMed检索miR-29a相关文章,通过miRBase在线工具分析miR-29a序列。应用TargetScan及miRNAda两种计算方法预测miR-29a靶基因并取其交集作为分析的基因集合,分别进行基因本体(gene ontology,GO)中的分子功能和生物学过程以及KEGG(Kyoto Encyclopedia of Genes and Genomes)生物通路富集分析。结果:(1)miR-29a序列在多物种间具有高度保守性。(2)两种方法预测miR-29a靶基因交集共191个。(3)miR-29a靶基因GO分子功能集中于转录因子活性、DNA结合和钙离子结合等(P0.05);miR-29a靶基因GO生物学过程集中于调控转录、细胞粘附、细胞增殖与凋亡等(P0.05);KEGG生物通路主要富集于PI3K-AKT信号通路、JAK-STAT信号通路、T细胞受体信号通路和胰岛素信号通路等信号转导通路,以及肺小细胞癌和子宫内膜癌等疾病通路(P0.05)。结论:miR-29a可能通过参与多个靶基因信号通路的调控,在机体的多种生理病理过程中发挥重要作用,是一个颇有研究价值的生物学靶标。     

LncRNA HSPC324 plays role in lung development and tumorigenesis

Lung cancer is a leading cause of cancer-related death in the world. Therefore, identifying the genes and molecular pathways involved in lung development and tumorigenesis can help us improve the therapeutic strategies of lung cancer. Accumulating evidence confirms that long noncoding RNAs, as a novel layer of regulatory RNA molecules, play an important role in various aspects of the cells. Here, using available high throughput gene expression data, we identified an lncRNA (HSPC324) with high expression level in lung tissue that is distinctly expressed in lung tumor tissues relative to normal. Using GO enrichment and KEGG pathway analyses, we further analyzed the functions and pathways involving the HSPC324-correlated genes. Ectopic expression of lncRNA HSPC324 significantly inhibited proliferation, cell cycle and migration; on the other hand, increased apoptosis and ROS production in lung adenocarcinoma cells. Overall, this study introduces HSPC324 as a new player in the development of lung cancer.     

Prognostic value of metabolic genes in lung adenocarcinoma via integrative analyses

BackgroundLung adenocarcinoma (LUAD) is the most common malignant lung tumor. Metabolic pathway reprogramming is an important hallmark of physiologic changes in cancers. However, the mechanisms through which these metabolic genes and pathways function in LUAD as well as their prognostic values have not been fully established.MethodsFour publicly available datasets from GEO and TCGA were used to identify differentially expressed genes (DEGs) in LUAD, which were then subjected to GO and KEGG pathway enrichment analysis. Associations between metabolic gene expressions with overall survival, tumor stage, TP53 mutation status, and infiltrated immune cells were investigated. Protein-protein interactions were evaluated using GeneMANIA and Metascape.ResultsBy integrating four public datasets, 247 DEGs were identified in LUAD. These DEGs were significantly enriched in regulation of chromosome segregation, centromeric region, and histone kinase activity GO terms, as well as in cell cycle, p53 signaling pathway, metabolic pathways, and other KEGG pathways. Elevated expressions of ten metabolic genes in LUAD were significantly associated with poor survival outcomes. These metabolic genes were highly expressed in more advanced tumor stage and TP53 mutated patients. Moreover, expression levels were significantly correlated with tumor-infiltrating immune cells. PPI interaction analysis revealed that the top 20 genes interacting with each metabolic gene were significantly enriched in DNA replication, response to radiation, and central carbon metabolism in cancer.ConclusionThis study elucidates on molecular changes in metabolic genes in LUAD, which may inform the development of genetically oriented diagnostic approaches and effective treatment options.     

Construction of a mitochondrial-associated protein DRP1 and a lung cancer-associated protein Erbb4 combined regulatory network

ObjectiveThis research was to establish a mitochondrial-related Drp1 gene and a lung cancer-related Erbb4 gene to participate in the regulatory network of lung cancer cell apoptosis, and to provide theoretical support for mitochondria to participate in tumor regulation.MethodThe GO and KEGG methods were used to construct the regulatory networks of lung cancer related Drp1 and Erbb4 proteins that involved in the apoptosis of tumor cells, and to combine with the Bayesian network theory to screen out the largest possible action path acting on this network; The information about Drp1 in Oncomine database was collected, and the data in current database were analyzed twice. The role of Drp1 in lung cancer was meta-analyzed.ResultA regulatory network of Drp1 and Erbb4 involved in the apoptosis of tumor cells was successfully constructed; the optimal pathway was optimized using Bayesian theory; a total of 446 different types of research results were collected in the Oncomine database, of which there were 18 studies with statistical differences in Drp1 expression, 13 studies with increased Drp1’s expression, and 5 studies with decreased expression. Compared with the control group, Drp1 was expressed in lung cancer tissues highly (P < 0.05).ConclusionEstablishment and optimization of mitochondrial-related Drp1 and tumor-related Erbb4 genes involved in the regulation of apoptosis of cancer cells. It was proposed that Drp1 was expressed in lung cancer tissues highly through in-depth excavation of tumor-associated gene information in the Oncomine gene chip database.     

基于蛋白互作网络识别非小细胞肺癌相关基因功能模块

本研究对非小细胞肺癌(non-small cell lung carcinoma,NSCLC)基因表达数据进行差异表达分析,并与蛋白质相互作用网络(PPIN)数据进行整合,进一步利用Heinz搜索算法识别NSCLC相关的基因功能模块,并对模块中的基因进行功能(GO term)和通路(KEGG)富集分析,旨在探究肺癌发病分子机制。蛋白互作网络分析得到一个包含96个基因和117个相互作用的功能模块,以及8个对NSCLC的发生和发展起到关键作用候选基因标志物。富集分析结果表明,这些基因主要富集于基因转录催化及染色质调控等生物学过程,并在基础转录因子、黏着连接、细胞周期、Wnt信号通路及HTLV-Ⅰ感染等生物学通路中发挥重要作用。本研究对非小细胞肺癌相关的基因和生物学通路进行预测,可用于肺癌的早期诊断和早期治疗,以降低肺癌死亡率。     

Identifying breast cancer subtypes associated modules and biomarkers by integrated bioinformatics analysis

Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the breast cancer subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment show that the blue module genes engaged in cell cycle, DNA replication, p53 signaling pathway, and pathway in cancer. According to the connectivity analysis and survival analysis, 8 out of 96 hub genes were filtered and have shown the highest expression in basal-like breast cancer. Furthermore, the hub genes were validated by the external datasets and quantitative real-time PCR (qRT-PCR). In summary, hub genes of Cyclin E1 (CCNE1), Centromere Protein N (CENPN), Checkpoint kinase 1 (CHEK1), Polo-like kinase 1 (PLK1), DNA replication and sister chromatid cohesion 1 (DSCC1), Family with sequence similarity 64, member A (FAM64A), Ubiquitin Conjugating Enzyme E2 C (UBE2C) and Ubiquitin Conjugating Enzyme E2 T (UBE2T) may serve as the prognostic markers for different subtypes of breast cancer.     

肺腺癌诊断标志物筛选及免疫细胞浸润分析

用生物信息学方法筛选肺腺癌(Lung adenocarcinoma,LUAD)的诊断生物标志物,并分析肺腺癌中免疫细胞浸润情况。从GEO和TCGA数据库下载肺腺癌的表达数据集,利用R软件筛选肺腺癌与正常肺组织间的差异表达基因(DEGs),使用DAVID网站对DEGs进行GO及KEGG富集分析,使用STRING及Cytoscape等工具对DEGs构建蛋白相互作用网络并筛选hub基因;利用Kaplan-Meier法对DEGs进行生存分析,并对hub基因进行ROC分析筛选诊断生物标志物,利用GSEA预测有预后价值的基因参与的信号通路;并用Cibersort软件反卷积算法分析肺腺癌中免疫细胞浸润情况。共得到肺腺癌的234个DEGs,这些基因主要参与信号转导、物质代谢、免疫反应等相关信号通路;构建PPI网络筛选出的20个hub基因中8个存在预后价值(CCNA2、DLGAP5、HMMR、MMP1、MMP9、MMP13、SPP1、TOP2A),ROC分析中DLGAP5、SPP1值分别是0.703、0.706;DLGAP5、SPP1基因表达水平与肺腺癌组织浆细胞、未活化的CD4⁺记忆细胞、调节T细胞、巨噬细胞M0、M1、M2及中性粒细胞浸润密切相关(P＜0.05)。肺腺癌中DLGAP5、SPP1具有较高诊断价值且参与肺腺癌组织免疫细胞浸润;DLGAP5、SPP1基因可作为肺腺癌诊断的生物标志物,可为肺腺癌的靶向治疗研究提供新思路。     

IgA 肾病患者与膜性肾病患者外周血单核细胞mRNA分析

为了寻找诊断、鉴别IgA肾病(IgAN)和膜性肾病(MN)的血液特异性标记物,利用公共数据库中的IgAN和MN患者的外周血单核细胞(PBMCs)的转录组表达谱数据集识别特异性生物标记物,为诊断和鉴别提供简便、可靠的依据补充。从公共基因表达数据库(GEO)下载IgAN患者组(n=15)和MN患者组(n=8)芯片数据集,筛选前250个差异表达基因(DEGs)。通过分析筛选关键基因和途径,进行基因本体(GO)富集分析、京都基因与基因组百科全书(KEGG)通路分析和蛋白质与蛋白质相互作用关系(PPI)分析等进一步了解DEGs。通过分析共发现75个显著DEGs,其中73个上调基因,2个下调基因。GO富集分析的生物学过程(BP)主要包括蛋白质转运、内溶酶体到溶酶体转运、趋化因子介导的信号通路作用等。显著富集差异表达基因KEGG通路分析包括Endocytosis和Hepatitis B的相关信号通路。PPI筛选出EPS15、STAT4、CCL2、SUN2、SEC24C、SEC31A、GOLGB1、F2R,RAB12和PTK2B等关键基因。成功筛选出核心差异表达基因,为IgAN和MN的诊断和鉴别提供简便、可靠的依据补充,甚至提供治疗的新靶点。     

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer and optimal selection of traditional Chinese medicine target

The paper aimed to screen out genetic markers applicable to early diagnosis for colorectal cancer and establish apoptotic regulatory network model for colorectal cancer, and to analyze the current situation of traditional Chinese medicine (TCM) target, thereby providing theoretical evidence for early diagnosis and targeted therapy of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers that are applied to early diagnosis of colorectal cancer were searched and performed comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. KEGG analysis was employed to establish apoptotic regulatory network model based on screened genetic markers, and optimization was conducted on TCM targets. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, P53, APC, DCC and PTEN, among which DCC has the highest diagnostic efficiency. Apoptotic regulatory network was built by KEGG analysis. Currently, it was reported that TCM has regulatory function on gene locus in apoptotic regulatory network. The apoptotic regulatory model of colorectal cancer established in this study provides theoretical evidence for early diagnosis and TCM targeted therapy of colorectal cancer in clinic.     

长丝萝中的两个抗肿瘤活性成分的分离鉴定及对抑癌基因变化的验证

以长丝萝Dolichousnea longissima中分离得到的体外细胞毒活性较强的两个苯骈呋喃类化合物为实验材料,采用Affymetrix全表达谱基因芯片、GO分类、Pathway分析和实时荧光定量PCR技术对2种化合物处理前后的肝癌细胞株HepG2的差异表达基因进行分析和验证。结果表明,(Z)-2-乙酰基-5,5-二[2-(7-乙酰基-4,6-二羟基-3,5-二甲基苯骈呋喃基)]-4-羟基-2,4-戊二烯-1-醛筛选出明显变化的基因728个,其中上调基因有246个,下调基因有482个。PATHWAY分析与肿瘤相关的信号通路有细胞周期信号通路、内吞作用信号通路、癌细胞中信号通路、前列腺癌信号通路、p53信号通路、结肠直肠癌信号通路。GO分类显示差异基因共参与266个BP分类、68个CC分类和43个MF分类。4-[3-(7-乙酰基-4,6-二羟基-3,5-二甲基-2-氧代-2,3-二氢苯骈呋喃基)]-4-[2-(7-乙酰基-4,6-二羟基-3,5-二甲基苯骈呋喃基)]-3-氧代丁酸乙酯筛选出明显变化的基因112个,其中上调基因有8个,下调基因有104个。PATHWAY分析与肿瘤相关的信号通路有细胞周期信号通路、内吞作用信号通路。GO分类显示差异基因共参与109个BP分类、48个CC分类和15个MF分类。因此,以上两个苯骈呋喃类化合物均主要通过影响细胞周期信号通路和内吞作用信号通路使抑癌基因发生变化。     

2010 Reviewers for Biotechnic & Histochemistry

Pancreatic cancer is characterized by aggressive growth and resistance to treatment. Identification of unique biomarkers for diagnosis and prognosis is important for treatment of this disease. We investigated the expression patterns of mucin 1 (MUC1), mucin 2 (MUC2) and cytokeratin 17 (CK17) in both normal tissues and metastatic adenocarcinomas using immunohistochemistry (IHC). We have shown that MUC1 (pan-epithelial membrane mucin), MUC2 (intestinal-type secretory mucin) and CK17 can be used as a panel of markers to distinguish collectively pancreatobiliary carcinoma from other primary site carcinomas. Tumors originating in the pancreatobiliary system showed an expression pattern of MUC1 (+), MUC2 (?) and CK17 (+). By contrast, tumors arising from the colorectal region were MUC1 (?), MUC2 (+) and CK17 (?), while tumors originating from non-pancreatobiliary system tissue expressed a MUC1 (+), MUC2 (?) and CK17 (?) profile. More importantly, the MUC1 (+), MUC2 (?) and CK17 (+) result showed greater sensitivity than CA19-9 by IHC, which is the currently accepted and widely used pancreatic tumor marker for diagnosing pancreatic cancer. Thirteen of 51 cases (25%) of pancreatobiliary adenocarcinomas with the pattern MUC1 (+), MUC2 (?) and CK17 (+) showed no immunoreactivity for CA19-9, while 34/51 (67%) cases having MUC1 (+), MUC2 (?) and CK17 (+) were correlated with positive CA19-9 staining. Our data support using an antibody panel of MUC1, MUC2 and CK17 to enhance current methods for pancreatic cancer diagnosis by identifying specifically the primary tissue of origin.     

Critical roles of mucin-1 in sensitivity of lung cancer cells to tumor necrosis factor-alpha and dexamethasone

Lung cancer is the leading cause of death from cancer. Mucins are glycoproteins with high molecular weight, responsible for cell growth, differentiation, and signaling, and were proposed to be correlated with gene heterogeneity of lung cancer. Here, we report aberrant expression of mucin genes and tumor necrosis factor receptors in lung adenocarcinoma tissues compared with normal tissues in GEO datasets. Mucin-1 (MUC1) gene was selected and considered as the target gene; furthermore, the expression pattern of adenocarcinomic cells (A549, H1650, or H1299 cells) was validated under the stimulation with tumor necrosis factor-alpha (TNFα) or dexamethasone (DEX), separately. MUC1 gene interference was done to A549 cells to show its role in sensitivity of lung cancer cells to TNFα and DEX. Results of our experiments indicate that MUC1 may regulate the influence of inflammatory mediators in effects of glucocorticoids (GCs), as a regulatory target to improve therapeutics. It shows the potential effect of MUC1 and GCs in lung adenocarcinoma (LADC), which may help in LADC treatment in the future.     

Hormonal regulation of MUC1 expression.

Several circulating mucinous markers, including CA 15.3, MCA, CA 459, CASA, and Truquant BR, are secreted products of the polymorphic MUC1 gene, and are used as diagnostic tools in patients with breast cancer. In clinical practice the measurement of the levels of these markers in the blood can give important information on the tumor's response to treatment and its biological behavior during disease monitoring. Since the marker levels reflect the activity of the tumor, it is important to know all factors influencing the production/secretion and the blood concentrations of MUC1 mucin. Recent findings suggest that MUC1 gene expression is regulated by steroid hormones and other substances present in the serum. Such observations are very important not only because of their biological significance but also for their clinical implications, as one approach to breast cancer therapy is based on chemical hormone manipulation. Nevertheless, we have preliminarily demonstrated that endocrine treatment in breast cancer patients does not influence the circulating CA 15.3 serum levels, so changes in marker levels are related only to the clinical evolution of the tumor.