Analysis of gene expression profiles of gastric normal and cancer tissues by SAGE

In an attempt to understand the molecular bases of gastric cancer progression, we have analyzed the differentially expressed genes in gastric cancer by SAGE. Four SAGE cDNA tag libraries were constructed from two sets of gastric cancer and normal tissues and 241,127 tags were obtained. By comparing the tags from cancer and normal tissues, 414 differentially expressed tags, representing 383 genes, were identified in cancer tissues (p 相似文献   

Identification of differentially expressed genes in human uterine leiomyomas using differential display

INTRODUCTIONUterine leiomyomas (ULs) have been consideredto be of uniceIIular origin[l1. It is one of the mostcommon benign tumors, occurring in 20% to 30% ofwomen[2], accounting for significant morbidity andusually need major surgery[3] which might causesome side effects afterwards[4]. Therefore, to de-velop certain drug treatments instead has been thehope of these patients for a long time. Using alter-native approaches fOr studying patients sufferingfrom leiomyoma in various ethnic gr…     

Comparison of microarray and sage techniques in gene expression analysis of human glioblastoma

To enhance glioblastoma (GB) marker discovery we compared gene expression in GB with human normal brain (NB) by accessing SAGE Genie web site and compared obtained results with published data. Nine GB and five NB SAGE-libraries were analyzed using the Digital Gene Expression Displayer (DGED), the results of DGED were tested by Northern blot analysis and RT-PCR of arbitrary selected genes. Review of available data from the articles on gene expression profiling by microarray-based hybridization showed as few as 35 overlapped genes with increased expression in GB. Some of them were identified in four articles, but most genes in three or even in two investigations. There was found also some differences between SAGE results of GB analysis. Digital Gene Expression Displayer approach revealed 676 genes differentially expressed in GB vs. NB with cut-off ratio: twofold change and P < or = 0.05. Differential expression of selectedgenes obtained by DGED was confirmed by Northern analysis and RT-PCR. Altogether, only 105 of 955 genes presented in published investigations were among the genes obtained by DGED. Comparison of the results obtained by microarrays and SAGE is very complicated because authors present only the most prominent differentially expressed genes. However, even available data give quite poor overlapping of genes revealed by microarrays. Some differences between results obtained by SAGE in different investigations can be explained by high dependence on the statistical methods used. As for now, the best solution to search for molecular tumor markers is to compare all available results and to select only those genes, which significant expression in tumor combined with very low expression in normal tissues was reproduced in several articles. 105 differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of GBs. Some genes, encoded cell surface or extra-cellular proteins may be useful for targeting gliomas with antibody-based therapy.     

Comparative expression analysis of four breast cancer subtypes versus matched normal tissue from the same patients

Gene expression studies have been widely used in an effort to identify signatures that can predict clinical progression of cancer. In this study we focused instead on identifying gene expression differences between breast tumors and adjacent normal tissue, and between different subtypes of tumor classified by clinical marker status. We have collected a set of 20 breast cancer tissues, matched with the adjacent pathologically normal tissue from the same patient. The cancer samples representing each subtype of breast cancer identified by estrogen receptor ER(+/-) and Her2(+/-) status and divided into four subgroups (ER+/Her2+, ER+/Her2-, ER-/Her2+, and ER-/Her2-) were hybridized on Affymetrix HG-133 Plus 2.0 microarrays. By comparing cancer samples with their matched normal controls we have identified 3537 overall differentially expressed genes using data analysis methods from Bioconductor. When we looked at the genes in common of the four subgroups, we found 151 regulated genes, some of them encoding known targets for breast cancer treatment. Unique genes in the four subgroups instead suggested gene regulation dependent on the ER/Her2 markers selection. In conclusion, the results indicate that microarray studies using robust analysis of matched tumor and normal samples from the same patients can be used to identify genes differentially expressed in breast cancer tumor subtypes even when small numbers of samples are considered and can further elucidate molecular features of breast cancer.     

Molecular basis of the differences between normal and tumor tissues of gastric cancer

To be able to describe the differences between the normal and tumor tissues of gastric cancer at a molecular level would be essential in the study of the disease. We investigated the gene expression pattern in the two types of tissues from gastric cancer by performing expression profiling of 86 tissues on 17K complementary DNA microarrays. To select for the differentially expressed genes, class prediction algorithm was employed. For predictor selection, samples were first divided into a training (n=58), and a test set (n=28). A group of 894 genes was selected by a t-test in a training set, which was used for cross-validation in the training set and class (normal or tumor) prediction in the test set. Smaller groups of 894 genes were individually tested for their ability to correctly predict the normal or tumor samples based on gene expression pattern. The expression ratios of the 5 genes chosen from microarray data can be validated by real time RT-PCR over 6 tissue samples, resulting in a high level of correlation, individually or combined. When a representative predictor set of 92 genes was examined, pathways of 'focal adhesion' (with gene components of THBS2, PDGFD, MAPK1, COL1A2, COL6A3), 'ECM-receptor interaction' pathway (THBS2, COL1A2, COL6A3, FN1) and 'TGF-beta signaling' (THBS2, MAPK1, INHBA) represent some of the main differences between normal and tumor of gastric cancer at a molecular level.     

Discovery of EST-SSRs in lung cancer: tagged ESTs with SSRs lead to differential amino acid and protein expression patterns in cancerous tissues

Tandem repeats are found in both coding and non-coding sequences of higher organisms. These sequences can be used in cancer genetics and diagnosis to unravel the genetic basis of tumor formation and progression. In this study, a possible relationship between SSR distributions and lung cancer was studied by comparative analysis of EST-SSRs in normal and lung cancerous tissues. While the EST-SSR distribution was similar between tumorous tissues, this distribution was different between normal and tumorous tissues. Trinucleotides tandem repeats were highly different; the number of trinucleotides in ESTs of lung cancer was 3 times higher than normal tissue. Significant negative correlation between normal and cancerous tissue showed that cancerous tissue generates different types of trinucleotides. GGC and CGC were the more frequent expressed trinucleotides in cancerous tissue, but these SSRs were not expressed in normal tissue. Similar to the EST level, the expression pattern of EST-SSRs-derived amino acids was significantly different between normal and cancerous tissues. Arg, Pro, Ser, Gly, and Lys were the most abundant amino acids in cancerous tissues, and Leu, Cys, Phe, and His were significantly more abundant in normal tissues than in cancerous tissues. Next, the putative functions of triplet SSR-containing genes were analyzed. In cancerous tissue, EST-SSRs produce different types of proteins. Chromodomain helicase DNA binding proteins were one of the major protein products of EST-SSRs in the cancerous library, while these proteins were not produced from EST-SSRs in normal tissue. For the first time, the findings of this study confirmed that EST-SSRs in normal lung tissues are different than in unhealthy tissues, and tagged ESTs with SSRs cause remarkable differences in amino acid and protein expression patterns in cancerous tissue. We suggest that EST-SSRs and EST-SSRs differentially expressed in cancerous tissue may be suitable candidate markers for lung cancer diagnosis and prediction.     

胃癌组织中肿瘤相关成纤维细胞与正常成纤维细胞之间转录组学研究及验证

胃癌组织中肿瘤相关成纤维细胞(carcinoma associated fibroblasts, CAFs)是胃癌微环境的重要成分,主要来源于正常成纤维细胞(normal fibroblasts, NFs)的活化,对胃癌的发生发展有重要作用,但是两者之间的基因表达差异并不完全清楚。本研究选取从人胃癌组织中分离获得的CAFs及NFs 各3组,进行转录组学研究,筛选出3组细胞中交集且差异倍数较大的基因12个,用Omicsbean在线工具对差异基因进行Gene Ontology (GO)功能及KEGG通路富集,构建蛋白质相互作用调控网络;最后用RT-qPCR验证CAFs和NFs中差异基因的表达。结果显示,筛选出的12个差异表达基因主要参与NF-κB信号、炎症、细胞黏附、细胞表面受体和细胞因子等功能,上述功能均与肿瘤的发生发展密切相关。RT-qPCR检测发现,与NFs相比,CAFs中BCL2A1、NKX3-2、CXCL12、TNFAIP3、FOS、CDH4及CLDN1表达上调;ATF3、CYFIP2、CCL11、KLF2及GDF15基因表达下调,差异均具有统计学意义(P＜0.05)。结果提示,胃癌CAFs与NFs中存在肿瘤相关的差异表达基因,这些差异基因可能在胃癌微环境中发挥重要作用。     

The Search for Secreted Proteins in Prostate Cancer by the Escherichia coli Ampicillin Secretion Trap: Expression of NBL1 Is Highly Restricted to the Prostate and Is Related to Cancer Progression

Aims: Genes expressed only in cancer tissue or specific organs will be useful molecular markers. To identify genes that encode secreted proteins present in prostate cancer (PCa), we generated Escherichia coli ampicillin secretion trap (CAST) libraries from PCa and normal prostate (NP). Methods and Results: We identified 15 candidate genes that encode secreted proteins present in PCa and NP. Quantitative RT-PCR analysis revealed that MSMB, NBL1 and AZGP1 were expressed with much higher specificity in PCa and NP than in 14 other kinds of normal tissue. We focused on NBL1, which was originally identified as a putative tumor suppressor gene. Western blot analysis revealed that NBL1 protein was highly expressed in both cell lysate and culture media of the DU145 PCa cell line. Immunohistochemical analysis showed that NBL1 expression was highly detected in and restricted to NP and PCa and was significantly down-regulated in PCa. NBL1 expression was significantly reduced according to the tumor stage, Gleason grade and preoperative prostate-specific antigen (PSA) value. Conclusion: NBL1 is a secreted protein that is highly restricted to the prostate. Underexpression of NBL1 correlated with PCa progression. NBL1 might be a candidate tumor marker for PCa in addition to PSA.     

Identification of key biomarkers for thyroid cancer by integrative gene expression profiles

Thyroid cancer is a frequently diagnosed malignancy and the incidence has been increased rapidly in recent years. Despite the favorable prognosis of most thyroid cancer patients, advanced patients with metastasis and recurrence still have poor prognosis. Therefore, the molecular mechanisms of progression and targeted biomarkers were investigated for developing effective targets for treating thyroid cancer. Eight chip datasets from the gene expression omnibus database were selected and the inSilicoDb and inSilicoMerging R/Bioconductor packages were used to integrate and normalize them across platforms. After merging the eight gene expression omnibus datasets, we obtained one dataset that contained the expression profiles of 319 samples (188 tumor samples plus 131 normal thyroid tissue samples). After screening, we identified 594 significantly differentially expressed genes (277 up-regulated genes plus 317 down-regulated genes) between the tumor and normal tissue samples. The differentially expressed genes exhibited enrichment in multiple signaling pathways, such as p53 signaling. By building a protein–protein interaction network and module analysis, we confirmed seven hub genes, and they were all differentially expressed at all the clinical stages of thyroid cancer. A diagnostic seven-gene signature was established using a logistic regression model with the area under the receiver operating characteristic curve (AUC) of 0.967. Seven robust candidate biomarkers predictive of thyroid cancer were identified, and the obtained seven-gene signature may serve as a useful marker for thyroid cancer diagnosis and prognosis.     

宫颈腺癌发生相关蛋白的蛋白质组学初步研究

目的：为了研究宫颈腺癌和正常宫颈组织的差异表达蛋白,为宫颈腺癌的发生和早期诊断提供有意义的生物标志物。方法：以正常宫颈组织和宫颈腺癌组织为研究对象,提取组织总蛋白,依次进行二维凝胶电泳,凝胶图象分析,基质辅助激光解吸附／离子化飞行时间质谱及生物信息学分析。Western Blot方法验证部分蛋白表达情况。结果：建立了宫颈腺癌和正常宫颈组织的二维电泳图谱,进行质谱和生物信息学分析比较鉴定宫颈腺癌和正常宫颈组织差异表达蛋白7个,与正常宫颈组织比较,宫颈腺癌表达降低的蛋白有3个,包括抑制素（inhibin-beta）,PTEN,乳铁蛋白（lactoferrin）;宫颈腺癌表达升高的蛋白有4个,包括谷胱甘肽S-转移酶（GSTT1＊0）,Homeodomain—interacting protein kinase2（HIPK2）,CD44v5,galectin-7。Western Blot方法检测结果显示inhibin-beta和PTEN在宫颈腺癌中表达变化情况与蛋白质组学结果一致。结论：宫颈腺癌和正常宫颈组织存在差异表达蛋白,这些差异表达蛋白可能是宫颈腺癌发生相关蛋白,可能作为宫颈腺癌早期诊断的标志物。     

Isolation of diallyl trisulfide inducible differentially expressed genes in human gastric cancer cells by modified cDNA representational difference analysis

Extensive epidemiologic studies indicated protective effects of consumption of garlic on reducing human gastric cancer (HGC) incidence. Diallyl trisulfide (DATS), a critical organic allyl sulfur component of garlic, was reported to have chemopreventive effects in inhibiting tumor process. We used DATS to treat HGC cell line BGC823 cells, and showed that DATS induces G1/S arrest and apoptosis in BGC823 cells demonstrated by a flow cytometric analysis. To further isolate DATS inducible differentially expressed genes in BGC823 cells, we combined a highly specific subtractive hybridization of cDNA representational difference analysis (cDNA RDA) with a sensitive bidirectional radioactive detection of mRNA differential display (mRNA DD) to develop a subtractive hybridization differential display (SHDD) method. This modified method adopted a first round of bidirectional subtractive hybridization between two sample cDNAs and a second round of bidirectional subtractive hybridization between the two resultant first-round difference products. Bidirectional subtractive hybridizations magnified the differences between the two sample cDNAs and favored isolating mRNA species with very small expression differences. We employed the SHDD method to detect DATS inducible differentially expressed genes in BGC823 cells. A total of 14 cDNA fragments (11 upregulated and 3 downregulated by DATS treatment) were isolated and confirmed by reverse Northern blot analysis. Our data show that SHDD is a powerful technique for identifying differentially expressed mRNA species between two sample cDNAs and provide useful cellular and molecular information for understanding the effects of garlic against human gastric cancer.     

Comparison of microarray and SAGE techniques in gene expression analysis of human glioblastoma

To enhance glioblastoma (GB) marker discovery, we compared gene expression in GB with human normal brain (NB) by accessing the SAGE Genie web site and compared the results with published data. Nine GB and five NB SAGE libraries were analyzed using the Digital Gene Expression Displayer (DGED); the results of DGED were tested by Northern blot analysis and RT-PCR of arbitrarily selected genes. Review of available data from the articles on gene expression profiling by microarray-based hybridization showed as few as 35 overlapped genes with increased expression in GB. Some of them were identified in four articles, but most genes were identified in three or even in two investigations. Some differences were also found between SAGE results of GB analysis. The Digital Gene Expression Displayer approach revealed 676 genes differentially expressed in GB vs. NB with cutoff ratio: twofold change and P ≤ 05. Differential expression of selected genes obtained by DGED was confirmed by Northern analysis and RT-PCR. Altogether, only 105 of 955 genes presented in published investigations were among the genes obtained by DGED. Comparison of the results obtained by microarrays and SAGE is very complicated because the authors present only the most prominent differentially expressed genes. However, even available data give quite poor overlapping of genes revealed by microarrays. Some differences between results obtained by SAGE in different investigations can be explained by high dependence on the statistical methods used. As for now, the best solution to search for molecular tumor markers is to compare all available results and to select only those genes where significant expression in tumors combined with very low expression in normal tissues was reproduced in several articles. One hundred five differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of GBs. Some genes, encoded cell surface or extracellular proteins may be useful for targeting gliomas with antibody-based therapy. The text was submitted by the authors in English.