基于数据挖掘分析PTGER3在肠型胃癌中的表达及临床意义

目的:探讨PTGER3在肠型胃癌中的表达及临床意义。方法:从GEO数据库的GSE29272数据集中下载58对肠型胃癌组织和癌旁组织的基因表达谱数据,筛选出差异表达基因,并利用DAVID数据库进行基因的功能富集分析。采用WGCNA软件对差异表达基因进行权重基因共表达网络分析,以挖掘出肠型胃癌发生发展过程中的关键调控基因。分析关键调控基因表达水平与肠型胃癌预后的相关性,并在Kaplan-Meier Plotter数据库中验证其预后意义。结果:共获得393个差异表达基因,DAVID 功能富集分析显示它们主要涉及ECM受体相互作用、p53信号通路、PI3K-Akt信号通路和癌症信号通路等。PTGER3是癌症信号通路上的一个重要成员,在肠型胃癌组织中的表达明显上调。差异基因的共表达网络分析发现PTGER3是模块枢纽基因,与胃癌的发生发展关系密切。GSE29272数据集和Kaplan-Meier Plotter数据库的生存分析均显示PTGER3高表达与预后不良显著相关（P=0.034;P<0.001）。结论:PTGER3表达上调可能参与了肠型胃癌的发生发展,而且其高表达提示患者预后不良。     

Integrated Bioinformatics Analysis Identifies Crucial Biochemical Processes Shared between Pancreatitis and Pancreatic Ductal Adenocarcinoma

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy associated with rapid progression and an abysmal prognosis. Previous research has shown that chronic pancreatitis can significantly increase the risk of developing PDAC. The overarching hypothesis is that some of the biological processes disrupted during the inflammatory stage tend to show significant dysregulation, even in cancer. This might explain why chronic inflammation increases the risk of carcinogenesis and uncontrolled proliferation. Here, we try to pinpoint such complex processes by comparing the expression profiles of pancreatitis and PDAC tissues. Methods: We analyzed a total of six gene expression datasets retrieved from the EMBL-EBI ArrayExpress and NCBI GEO databases, which included 306 PDAC, 68 pancreatitis and 172 normal pancreatic samples. The disrupted genes identified were used to perform downstream analysis for ontology, interaction, enriched pathways, potential druggability, promoter methylation, and the associated prognostic value. Further, we performed expression analysis based on gender, patient’s drinking habit, race, and pancreatitis status. Results: Our study identified 45 genes with altered expression levels shared between PDAC and pancreatitis. Over-representation analysis revealed that protein digestion and absorption, ECM-receptor interaction, PI3k-Akt signaling, and proteoglycans in cancer pathways as significantly enriched. Module analysis identified 15 hub genes, of which 14 were found to be in the druggable genome category. Conclusion: In summary, we have identified critical genes and various biochemical processes disrupted at a molecular level. These results can provide valuable insights into certain events leading to carcinogenesis, and therefore help identify novel therapeutic targets to improve PDAC treatment in the future.     

Whole genome expression profiling of advance stage papillary serous ovarian cancer reveals activated pathways

Ovarian cancer is the most lethal type of gynecologic cancer in the Western world. The high case fatality rate is due in part because most ovarian cancer patients present with advanced stage disease which is essentially incurable. In order to obtain a whole genome assessment of aberrant gene expression in advanced ovarian cancer, we used oligonucleotide microarrays comprising over 40,000 features to profile 37 advanced stage papillary serous primary carcinomas. We identified 1191 genes that were significantly (P < 0.001) differentially regulated between the ovarian cancer specimens and normal ovarian surface epithelium. The microarray data were validated using real time RT-PCR on 14 randomly selected differentially regulated genes. The list of differentially expressed genes includes ones that are involved in cell growth, differentiation, adhesion, apoptosis and migration. In addition, numerous genes whose function remains to be elucidated were also identified. The microarray data were imported into PathwayAssist software to identify signaling pathways involved in ovarian cancer tumorigenesis. Based on our expression results, a signaling pathway associated with tumor cell migration, spread and invasion was identified as being activated in advanced ovarian cancer. The data generated in this study represent a comprehensive list of genes aberrantly expressed in serous papillary ovarian adenocarcinoma and may be useful for the identification of potentially new and novel markers and therapeutic targets for ovarian cancer.     

Gene expression changes in cervical squamous cell carcinoma after initiation of chemoradiation and correlation with clinical outcome

PURPOSE: The purpose of this study was to investigate early gene expression changes after chemoradiation in a human solid tumor, allowing identification of chemoradiation-induced gene expression changes in the tumor as well as the tumor microenvironment. In addition we aimed to identify a gene expression profile that was associated with clinical outcome. METHODS AND MATERIALS: Microarray experiments were performed on cervical cancer specimens obtained before and 48 h after chemoradiation from 12 patients with Stage IB2 to IIIB squamous cell carcinoma of the cervix treated between April 2001 and August 2002. RESULTS: A total of 262 genes were identified that were significantly changed after chemoradiation. Genes involved in DNA repair were identified including DDB2, ERCC4, GADD45A, and XPC. In addition, significantly regulated cell-to-cell signaling pathways included insulin-like growth factor-1 (IGF-1), interferon, and vascular endothelial growth factor signaling. At a median follow-up of 41 months, 5 of 12 patients had experienced either local or distant failure. Supervised clustering analysis identified a 58-gene set from the pretreatment samples that were differentially expressed between patients with and without recurrence. Genes involved in integrin signaling and apoptosis pathways were identified in this gene set. Immortalization-upregulated protein (IMUP), IGF-2, and ARHD had particularly marked differences in expression between patients with and without recurrence. CONCLUSIONS: Genetic profiling identified genes regulated by chemoradiation including DNA damage and cell-to-cell signaling pathways. Genes associated with recurrence were identified that will require validation in an independent patient data set to determine whether the 58-gene set associated with clinical outcome could be useful as a prognostic assay.     

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.     

The impact of genomics in understanding human melanoma progression and metastasis

BACKGROUND: Recent technological advances in the analysis of the human genome have opened the door to improving our primitive understanding of the gene expression patterns in cancer. For the first time, we have an overview of the complexities of tumorigenesis and metastatic progression of cancer. The examination of the phenotypic and (epi)genetic changes in cutaneous melanoma has identified several genes deemed central to the development and progression of melanoma. METHODS: A review of the recent literature was performed to determine the role of array-based high-throughput gene expression analysis in understanding the specific genes involved as well as the pathways and the comparative gene expression patterns of primary and metastatic melanoma. RESULTS: Most studies utilizing gene microarray analysis and other whole genome approaches reveal a wide array of genes and expression patterns in human melanoma. Furthermore, several of the same genes have been found in comparative studies, with some studies attempting correlation with clinical outcome. Several genes have been identified as potential prognostic markers of tumor progression and overall clinical outcome. CONCLUSIONS: High-throughput gene expression analysis has had a major impact in melanoma research. Several gene expression platforms have provided insight into the gene expression patterns in melanoma. Such data will provide the foundations for the future development of prognostic markers and improved targeted therapies for patients with melanoma.     

Impact of DNA amplification on gene expression patterns in breast cancer

Genetic changes underlie tumor progression and may lead to cancer-specific expression of critical genes. Over 1100 publications have described the use of comparative genomic hybridization (CGH) to analyze the pattern of copy number alterations in cancer, but very few of the genes affected are known. Here, we performed high-resolution CGH analysis on cDNA microarrays in breast cancer and directly compared copy number and mRNA expression levels of 13,824 genes to quantitate the impact of genomic changes on gene expression. We identified and mapped the boundaries of 24 independent amplicons, ranging in size from 0.2 to 12 Mb. Throughout the genome, both high- and low-level copy number changes had a substantial impact on gene expression, with 44% of the highly amplified genes showing overexpression and 10.5% of the highly overexpressed genes being amplified. Statistical analysis with random permutation tests identified 270 genes whose expression levels across 14 samples were systematically attributable to gene amplification. These included most previously described amplified genes in breast cancer and many novel targets for genomic alterations, including the HOXB7 gene, the presence of which in a novel amplicon at 17q21.3 was validated in 10.2% of primary breast cancers and associated with poor patient prognosis. In conclusion, CGH on cDNA microarrays revealed hundreds of novel genes whose overexpression is attributable to gene amplification. These genes may provide insights to the clonal evolution and progression of breast cancer and highlight promising therapeutic targets.     

Integrating expression‐related SNPs into genome‐wide gene‐ and pathway‐based analyses identified novel lung cancer susceptibility genes

Traditional pathway analysis map single nucleotide polymorphisms (SNPs) to genes according to physical position, which lacks sufficient biological bases. Here, we incorporated genetics of gene expression into gene‐ and pathway‐based analysis to identify genes and pathways associated with lung cancer risk. We identified expression‐related SNPs (eSNPs) in lung tissues and integrated these eSNPs into three lung cancer genome‐wide association studies (GWASs), including 12,843 lung cancer cases and 12,639 controls. We used SKAT‐C for gene‐based analysis, and conditional analysis to identify independent eSNPs of each gene. ARTP algorithm was used for pathway analysis. A total of 374,382 eSNPs in the GWAS datasets survived quality control, which were mapped to 5,084 genes and 2,752 pathways. In the gene‐based analysis, nine genes showed significant associations with lung cancer risk. Among them, TP63 (3q28), RP11‐650L12.2 (15q25.1) and CHRNA5 (15q25.1) were located in known lung cancer susceptibility loci. We also validated two newly identified susceptibility loci (RNASET2 and AL133458.1 in 6q27, and MPZL3 in 11q23.3). Besides, DVL3 (3q27.1), RP11‐522I20.3 (9q21.32) and CCDC116 (22q11.21) were identified as novel lung cancer susceptibility genes. Pathway analysis showed that pathways involved in protein structure, the Notch signaling pathway and the nicotinic acetylcholine receptor‐related pathways were associated with lung cancer risk. Combing eSNPs, gene‐ and pathway‐based analysis identifies novel lung cancer susceptibility genes, which serves as a powerful approach to decipher biological mechanisms underlying GWAS findings.     

前列腺癌诊断/预后和耐药分子标志物的筛选及其临床意义

目的：基于已发表的芯片数据通过生物信息学方法筛选差异表达基因,以发现前列腺癌诊断/预后和耐药相关分子标志物。方法：筛选GEO数据库中已发表的前列腺癌mRNA芯片数据GSE6956和前列腺癌细胞多烯紫杉醇耐药mRNA芯片数据GSE33455进行差异表达分析;通过生物学功能注释、基因通路富集分析、蛋白质相互作用网络（protein-protein interaction,PPI）分析等生物信息学方法发现和识别与差异表达基因相关的生物学功能和信号通路;比对TCGA数据库,验证差异表达基因在前列腺癌组织及癌旁组织中的表达,并通过Kaplan-Meier分析差异表达基因对前列腺癌患者生存率的影响;用qPCR方法验证差异表达基因在前列腺癌细胞株PC3及多烯紫杉醇耐药细胞PC3-DTX中的表达情况。结果：共筛选出227个在前列腺癌和前列腺癌多烯紫杉醇耐药细胞芯片数据中共同差异表达基因。差异表达基因主要富集到了癌症相关通路（Lysosome、Sphingolipid、FoxO、Acute myeloid leukemia）,并主要参与细胞黏附、自噬和胞内蛋白转运等生物学过程。构建PPI网络选取18个连接度最高的基因作为Hub基因。Hub基因和共同差异表达基因中,上调基因CITED2、LRP12和RPL17-C18orf32与前列腺癌患者的不良预后显著相关。qPCR验证显示CITED2在多烯紫杉醇耐药细胞PC3-DTX中高表达。结论：通过生物信息学方法筛选出在前列腺癌组织和耐药细胞中共同差异表达,且与前列腺癌患者的不良预后密切相关的基因,为前列腺癌诊断/预后和耐药分子标志物的研究提供了新的思路。     

Large-scale serial analysis of gene expression reveals genes differentially expressed in ovarian cancer

Difficulties in the detection, diagnosis, and treatment of ovarian cancer result in an overall low survival rate of women with this disease. A better understanding of the pathways involved in ovarian tumorigenesis will likely provide new targets for early and effective intervention. Here, we have used serial analysis of gene expression (SAGE) to generate global gene expression profiles from various ovarian cell lines and tissues, including primary cancers, ovarian surface epithelia cells, and cystadenoma cells. The profiles were used to compare overall patterns of gene expression and to identify differentially expressed genes. We have sequenced a total of 385,000 tags, yielding >56,000 genes expressed in 10 different libraries derived from ovarian tissues. In general, ovarian cancer cell lines showed relatively high levels of similarity to libraries from other cancer cell lines, regardless of the tissue of origin (ovarian or colon), indicating that these lines had lost many of their tissue-specific expression patterns. In contrast, immortalized ovarian surface epithelia and ovarian cystadenoma cells showed much higher similarity to primary ovarian carcinomas than to primary colon carcinomas. Primary tissue specimens therefore appeared to be a better model for gene expression analyses. Using the expression profiles described above and stringent selection criteria, we have identified a number of genes highly differentially expressed between nontransformed ovarian epithelia and ovarian carcinomas. Some of the genes identified are already known to be overexpressed in ovarian cancer, but several represent novel candidates. Many of the genes up-regulated in ovarian cancer represent surface or secreted proteins such as claudin-3 and -4, HE4, mucin-1, epithelial cellular adhesion molecule, and mesothelin. Interestingly, both apolipoprotein E (ApoE) and ApoJ, two proteins involved in lipid homeostasis, are among the genes highly up-regulated in ovarian cancer. Selected serial analysis of gene expression results were further validated through immunohistochemical analysis of ApoJ, claudin-3, claudin-4, and epithelial cellular adhesion molecule in archival material. These experiments provided additional evidence of the relevance of our findings in vivo. The publicly available expression data reported here should stimulate and aid further research in the field of ovarian cancer.     

A novel gammaretroviral shuttle vector insertional mutagenesis screen identifies SHARPIN as a breast cancer metastasis gene and prognostic biomarker

Breast cancer (BC) is the second leading cause of malignancy among U.S. women. Metastasis results in a poor prognosis and increased mortality, but the molecular mechanisms by which metastatic tumors occur are not well understood. Identifying the genes that drive the metastatic process could provide targets for improved therapy and biomarkers to improve BC patient outcomes. Using a forward mutagenesis screen, BC cells mutagenized with a replication-incompetent gammaretroviral vector (γRV) were xenotransplanted into the mammary fat pad of immunodeficient mice. In this approach the vector provirus dysregulates nearby genes, providing a selective advantage to transduced cells to form metastases. Metastatic tumors were analyzed for proviral integration sites to identify nearby candidate metastasis genes. The γRV has a transgene cassette that allows for rescue in bacteria and rapid identification of vector integration sites. Using this approach, we identified the previously described metastasis gene WWTR1 (TAZ), and three other novel candidate metastasis genes including SHARPIN. SHARPIN was independently validated in vivo as a BC metastasis gene. Analysis of patient data showed that SHARPIN expression predicts metastasis-free survival after adjuvant therapy. Our approach has broad potential to identify genes involved in oncogenic processes for BC and other cancers. We show here it can identify both known (WWTR1) and novel (SHARPIN) BC metastasis genes.     

Non-coding RNAs in cancer initiation and progression and as novel biomarkers

Cancer represents a complex group of heterogeneous diseases. While many cancers share fundamental biological processes (hallmarks of cancer) necessary for their development and progression, cancers also distinguish themselves by their dependence on distinct oncogenic pathways. Over the last decade, targeted therapies have been introduced to the clinic with variable success. In truth, single targeted therapies may be successful in only a subset of malignancies but insufficient to address malignancies that often rely on multiple pathways, thus evading single targeted agents. Investigators have recently identified potentially functional components of the human genome that were previously thought to have no biological function. This discovery has added to the already established complexity of gene regulation in the pathogenesis of cancer. Non-coding RNAs represent key regulators of gene expression. Improved knowledge of their biogenesis and function may in turn lead to a better understanding of the heterogeneity of malignancies and eventually be leveraged as diagnostic, prognostic and therapeutic targets. MicroRNAs (miRNAs or miRs) for example, have the capacity for the regulation of multiple genes and thus redirection or reprogramming of biological pathways. However, several other members of the non-coding RNA family may be of equal biological relevance. In this review, we provide a perspective on emerging concepts in the clinical application of miRNA and other non-coding RNAs as biomarkers in cancer with an eye on the eventual integration of both miRNA and other non-coding RNA biology into our understanding of cancer pathogenesis and treatment.     

Characterization of novel and complex genomic aberrations in glioblastoma using a 32K BAC array

Glioblastomas (GBs) are malignant CNS tumors often associated with devastating symptoms. Patients with GB have a very poor prognosis, and despite treatment, most of them die within 12 months from diagnosis. Several pathways, such as the RAS, tumor protein 53 (TP53), and phosphoinositide kinase 3 (PIK3) pathways, as well as the cell cycle control pathway, have been identified to be disrupted in this tumor. However, emerging data suggest that these aberrations represent only a fraction of the genetic changes involved in gliomagenesis. In this study, we have applied a 32K clone-based genomic array, covering 99% of the current assembly of the human genome, to the detailed genetic profiling of a set of 78 GBs. Complex patterns of aberrations, including high and narrow copy number amplicons, as well as a number of homozygously deleted loci, were identified. Amplicons that varied both in number (three on average) and in size (1.4 Mb on average) were frequently detected (81% of the samples). The loci encompassed not only previously reported oncogenes (EGFR, PDGFRA, MDM2, and CDK4) but also numerous novel oncogenes as GRB10, MKLN1, PPARGC1A, HGF, NAV3, CNTN1, SYT1, and ADAMTSL3. BNC2, PTPLAD2, and PTPRE, on the other hand, represent novel candidate tumor suppressor genes encompassed within homozygously deleted loci. Many of these genes are already linked to several forms of cancer; others represent new candidate genes that may serve as prognostic markers or even as therapeutic targets in the future. The large individual variation observed between the samples demonstrates the underlying complexity of the disease and strengthens the demand for an individualized therapy based on the genetic profile of the patient.     

Novel molecular targets regulated by tumor suppressors microRNA-1 and microRNA-133a in bladder cancer

Our expression signatures of human cancer including bladder cancer (BC) revealed that the expression of microRNA-1 (miR-1) and microRNA-133a (miR-133a) is significantly reduced in cancer cells. In the human genome, miR-1 and miR-133a are located on the same chromosomal region (miR-1-2 and miR-133a-1 on 18q11.2, and miR-1-1 and miR-133a-2 on 20q13.33) called cluster. In this study, we identified the novel molecular targets commonly regulated by miR-1 and miR-133a in BC. Genome-wide molecular target search and luciferase reporter assays showed that prothymosin-α (PTMA) and purine nucleoside phosphorylase (PNP) are directly regulated by miR-1 and miR-133a. Silencing of these two genes significantly inhibited cell proliferation and invasion, and increased apoptosis in BC cells. Immunohistochemistry showed that PTMA expression levels were significantly higher in BC compared to normal bladder epitheliums. PTMA and PNP were identified as new target genes regulated by the miR-1 and miR-133a cluster in BC. These genes may function as oncogenes contributing to cell proliferation and invasion in BC. Tumor suppressive miR-1 and miR-133a-mediated novel molecular targets may provide new insights into the potential mechanisms of BC oncogenesis.     

microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer

microRNA expression profiling plays an emerging role in cancer classification and identification of therapeutic strategies. In this study, we have evaluated the benefits of a joint microRNA-mRNA analysis in breast cancer. Matched mRNA and microRNA global expression profiling was conducted in a well-annotated cohort of 207 cases with complete 10-year follow-up. Penalized Cox regression including microRNA expression, mRNA expression, and clinical covariates was used to identify microRNAs associated with distant relapse-free survival (DRFS) that provide independent prognostic information, and are not simply surrogates of previously identified prognostic covariates. Penalized regression was chosen to prevent overfitting. Furthermore, microRNA-mRNA relationships were explored by global expression analysis, and exploited to validate results in several published cohorts (n = 592 with DRFS, n = 1,050 with recurrence-free survival). Four microRNAs were independently associated with DRFS in estrogen receptor (ER)-positive (3 novel and 1 known; miR-128a) and 6 in ER-negative (5 novel and 1 known; miR-210) cases. Of the latter, miR-342, -27b, and -150 were prognostic also in triple receptor-negative tumors. Coordinated expression of predicted target genes and prognostic microRNAs strengthened these results, most significantly for miR-210, -128a, and -27b, whose targets were prognostic in meta-analysis of several cohorts. In addition, miR-210 and -128a showed coordinated expression with their cognate pri-microRNAs, which were themselves prognostic in independent cohorts. Our integrated microRNA-mRNA global profiling approach has identified microRNAs independently associated with prognosis in breast cancer. Furthermore, it has validated known and predicted microRNA-target interactions, and elucidated their association with key pathways that could represent novel therapeutic targets.     

CDC25A, VAV1, TP73, BRCA1 and ZAP70 gene overexpression correlates with radiation response in colorectal cancer

Radiotherapy is increasingly used in adjuvant approaches for colorectal cancer (CRC) to reduce local recurrence and improve survival. However, the principal limitation is the large variability in response among different individuals due to tumor heterogeneity. In the present study, we compared gene expression profiles between radiosensitive and radioresistant colorectal cancer cell lines to identify radiation-related molecules that can be used to evaluate the effects of radiation. The CRC cell line SW620 was irradiated with a high-energy photo beam. Following radiation treatment, RNA was extracted from non-irradiated and irradiated cells, respectively, and gene expression analysis was performed by oligonucleotide microarray and the DAVID bioinformatics method. To further confirm the results, an additional 4 CRC cell lines, COLO205, T84, HCT116, SW480 and SW403 were purchased from ATCC. The radiosensitivities of each were determined by the survival fraction at 2 Gray (SF2) of the surviving cells using the ATPLite assay, and the gene expression profiles after irradiation among the radiosensitive and radioresistant cell lines were analyzed by membrane arrays. The relationships between gene expression and patient clinicopathological features were also analyzed using membrane arrays and RT-PCR. The results from oligonucleotide microarray analysis show that 1601 genes were up-regulated (gene expression ratio of post- to pre-radiation treatment>2). By bioinformatic database analysis, 30 up-regulated genes were identified as involved in DNA damage response pathways, immune response pathways and the complement and coagulation cascades pathway. Fifteen genes showed differential gene expression profiles between radiosensitive (HCT116 and SW620) and radioresistant CRC cell lines (SW403 and SW480). In 110 CRC tissues, we detected five genes CDC25A, VAV1, TP73, BRCA1 and ZAP70 from 15 overexpressed genes that significantly related to prognostic factors (tumor size, advanced stage, invasive depth, lymph node metastasis and differentiation). These findings suggest that CDC25A, VAV1, TP73, BRCA1 and ZAP70 may be novel markers for predicting the effectiveness of radiotherapy in CRC patients.