Obtaining estimates for the ages of all the protein-coding genes and most of the ontology-identified noncoding genes of the human genome,assigned to 19 phylostrata

Following Liebeskind et al [1], we have attempted to find consensus ages for the protein-coding and the noncoding genes of the human genome, using publicly-available ortholog databases. For each database separately, we determined its age estimate for the genes it listed, determining this by identifying the earliest ortholog for the gene in question. We assigned these ages to 1 of the 19 major phylostrata defined by Domazet-Loso and Tautz [2], 2 of which were further subdivided. From these various estimates, we found the modal value if 1 was present, defining this as the consensus age for the gene. For the genes where no consensus value could be found, we recorded the median value of the age estimates across the databases interrogated. We present a resource that lists the age, as so defined, of every one of the 19,660 protein-coding genes and of 5,981 of the 16,528 non–protein-coding genes of the human genome, the age being the time when the gene was accreted to the evolving human genome. We calculate the number of genes that accreted to the genome, epoch by epoch, and consider the rate at which they accreted.     

The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website

The discovery of mutations in cancer genes has advanced our understanding of cancer. These results are dispersed across the scientific literature and with the availability of the human genome sequence will continue to accrue. The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website have been developed to store somatic mutation data in a single location and display the data and other information related to human cancer. To populate this resource, data has currently been extracted from reports in the scientific literature for somatic mutations in four genes, BRAF, HRAS, KRAS2 and NRAS. At present, the database holds information on 66 634 samples and reports a total of 10 647 mutations. Through the web pages, these data can be queried, displayed as figures or tables and exported in a number of formats. COSMIC is an ongoing project that will continue to curate somatic mutation data and release it through the website.     

COSMIC 2005

The Catalogue Of Somatic Mutations In Cancer (COSMIC) database and web site was developed to preserve somatic mutation data and share it with the community. Over the past 25 years, approximately 350 cancer genes have been identified, of which 311 are somatically mutated. COSMIC has been expanded and now holds data previously reported in the scientific literature for 28 known cancer genes. In addition, there is data from the systematic sequencing of 518 protein kinase genes. The total gene count in COSMIC stands at 538; 25 have a mutation frequency above 5% in one or more tumour type, no mutations were found in 333 genes and 180 are rarely mutated with frequencies <5% in any tumour set. The COSMIC web site has been expanded to give more views and summaries of the data and provide faster query routes and downloads. In addition, there is a new section describing mutations found through a screen of known cancer genes in 728 cancer cell lines including the NCI-60 set of cancer cell lines.     

Distinct hepatitis B virus integration patterns in hepatocellular carcinoma and adjacent normal liver tissue

Infection by the hepatitis B virus (HBV) is one of the main etiologies of hepatocellular carcinoma (HCC). During chronic infection, HBV DNA can integrate into the human genome, and this has been postulated as a possible mechanism of HBV‐induced HCC. In this study we used 2199 HBV integration sites from Dr.VIS v2.0 and mapped them to the human genome (hg19) to obtain viral integration sites (VIS) related to protein‐coding and non‐protein‐coding genes. In total, we found 1,377 and 767 VIS within close proximity to protein coding genes and noncoding genes, respectively. Genes affected more than two times included 23.1% of protein‐coding genes and 24.7% of long noncoding RNAs (lncRNA). Only 4.8% of VIS were shared between HCC and non‐tumor tissues. HBV integrations were more common in chromosomes 5, 8, 10, and 19 in HCC tissue and chromosomes 1 and 2 in non‐tumorous tissue. The number of integration sites on each chromosome correlated with the number of fragile sites in non‐tumorous tissue but not in HCC tissue. Functional enrichment analysis of the protein‐coding genes containing or in close proximity to HBV integration sites in HCC tissue showed an enrichment of cancer related gene ontology terms. Additionally, the most frequently associated lncRNA genes were related to telomere maintenance, protein modification processes, and chromosome localization. Thus, HBV may have preferred integration sites in the human genome that serve a critical role in HCC development. These results show that HCC treatment may benefit from the development of next generation anti‐viral therapies.     

Genes and SNPs Associated with Non-hereditary and Hereditary Colorectal Cancer

Background: Colorectal cancer is the third most common cancer in both men and women in the world andthe second leading cause of cancer-related deaths. The incidence of colorectal cancer has increased in Iran inthe past three decades and is now considered as a serious problem for our society. This cancer has two typeshereditary and non-hereditary, 80% of cases being the latter. Considering that the relationship between SNPswith diseases is a concern, many researchers believed that they offer valuable markers for identifying genesresponsible for susceptibility to common diseases. In some cases, they are direct causes of human disease. OneSNP can increase risk of cancer, but when considering the rate of overlap and frequency of DNA repair pathways,it might be expected that SNP alone cannot affect the final result of cancer, although several SNPs together canexert a significant influence. Therefore identification of these SNPs is very important. The most important lociwhich include mutations are: MLH1, MSH2, PMS2, APC, MUTYH, SMAD7, STK11, XRCC3, DNMT1, MTHFR,Exo1, XRCC1 and VDR. Presence of SNPs in these genes decreases or increases risk of colorectal cancer. Materialsand Methods: In this article we reviewed the Genes and SNPs associated with non-hereditary and hereditary ofcolorectal cancer that recently were reported from candidate gene y, meta-analysis and GWAS studies. Results:As with other cancers, colorectal cancer is associated with SNPs in gene loci. Generally, by exploring SNPs, itis feasible to predict the risk of developing colorectal cancer and thus establishing proper preventive measures.Conclusions: SNPs of genes associated with colorectal cancer can be used as a marker SNP panel as a potentialtool for improving cancer diagnosis and treatment planning.     

Emerging links between epigenetic alterations and dysregulation of noncoding RNAs in cancer

Epigenetic changes, including DNA methylation and histone modification, play key roles in the dysregulation of tumor-related genes, thereby affecting numerous cellular processes, including cell proliferation, cell adhesion, apoptosis, and metastasis. In recent years, numerous studies have shown that noncoding RNAs (ncRNAs) are key players in the initiation and progression of cancer and epigenetic mechanisms are deeply involved in their dysregulation. Indeed, the growing list of microRNA (miRNA) genes aberrantly methylated in cancer suggests that a large number of miRNAs exert tumor-suppressive or oncogenic effects. In addition, it now appears that long ncRNAs may be causally related to epigenetic dysregulation of critical genes in cancer. Dissection of the relationships between ncRNAs and epigenetic alterations may lead to the development of novel approaches to the diagnosis and treatment of cancer.     

How different are luminal A and basal breast cancers?

Heterogeneity of breast cancer makes its evolution difficult to predict, and its treatment far from being optimal. At least 5 main molecular subtypes exist. Two major subtypes are luminal A and basal subtypes, which have opposite features, notably survival. To characterize these 2 subtypes better, with the hope of better understanding their different biology and clinical outcome, we have profiled a series of 138 tumours (80 luminal A and 58 basal) using Affymetrix whole‐genome DNA microarrays. We have identified 5,621 probe sets as differentially expressed between the 2 subtypes in our series. These differences were validated in 6 independent public series (more than 600 tumours) profiled using different DNA microarrays platforms. Analysis of functions and pathways related to these probe sets, and the extent of the observed differences, confirmed that the 2 subtypes represent very distinct entities. Genes associated with proliferation, cell cycle, cell motility, angiogenesis, and NFkB signalling were overexpressed in basal tumours. Genes involved in fatty acid metabolism, TGFB signalling, and oestrogen receptor (ER) signalling were overexpressed in luminal A samples. Half of the genes overexpressed in luminal tumours contained ER‐binding sites. The number of differentially expressed genes was as high as the set of genes discriminating 2 cancers of different anatomical origin (breast and colon) or discriminating acute myeloid and lymphoid leukaemia. We provide a comprehensive list of genes/pathways that define potential diagnostic, prognostic and therapeutic targets for these 2 subtypes, which should be treated differently given the profound differences observed at the molecular level. © 2008 Wiley‐Liss, Inc.     

Metastasis Suppression in Prostate Cancer

Due to a lack of effective treatments, the development of metastases remains the most lethal aspect of prostate cancer. In order to help overcome this problem there has been an ongoing effort to develop strategies for early intervention. This includes the development of strategies that allow histologic lesions and disseminated cells that are highly likely to cause metastatic disease to be distinguished from those that are not, as well as therapeutic approaches to specifically target bone metastases. Such approaches will be expedited by the identification of genes and signaling cascades that regulate metastatic growth. Genes that specifically suppress metastasis are strong candidates for these studies. This review will focus on metastasis-suppressor genes that have been identified functionally, particularly those found to play a role in prostate cancer, and discuss how the identification and study of these genes has influenced our overall understanding of the metastatic process.     

Epigenetic perturbations and cancer: innovative therapeutic strategies against cancer

A complex system of molecular milestones ensures labelling of the genome, driving its organization and functions. These milestones correspond to particular marks associated to active and repressed genes, as well as to non-coding regions or those containing repetitive sequences. Most of these marks are chemical modifications of DNA, corresponding to cytosine methylation, or various posttranslational modifications of histones, the proteins which package the genome. These chemical modifications of DNA or histones are reversible and are catalysed and removed by enzymatic activities associated with factors ensuring critical cellular functions. Indeed, these enzymes are directly connected with signalling pathways, sensing extra- and intracellular environments. Altogether these mechanisms globally control the expression status of genes in each cell, meaning that certain genes are kept active, while most of the genome remains silent. Subtle metabolic changes or intra and extracellular modifications, by altering the marking associated to genes, can have long-term consequences on their expression status. Genes coding for essential regulators of cellular proliferation and differentiation could be among these genes, such as tumor suppressor genes for instance. Hence the knowledge of all these so-called "epigenetic" mechanisms will shed new light on the environmental impact on the control of gene expression and associated diseases, including malignant transformation. The understanding of these mechanisms will also pave the way for innovative therapeutic strategies to fight cancer. This review is aiming to give an overview to the reader of the relevance of epigenetic mechanisms for the understanding and treatment of cancer.     

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.     

miRNAs and their potential for use against cancer and other diseases

miRNAs are 19-24 nucleotide long noncoding RNAs found in almost all genetically dissected species, including viruses, plants, nematodes, flies, fish, mice and humans. Rapid advances have been made in understanding their physiological functions, while abnormal patterns of miRNA expression have been found in many disease states, most notably human cancer. It is now clear that miRNAs represent a class of genes with a great potential for use in diagnosis, prognosis and therapy. In this review we will focus on the discoveries that elucidate their crucial role in mammalian diseases, particularly in cancer, and propose that miRNA-based gene therapy might become the potential technology of choice in a wide range of human diseases including cancer.     

Differential expression profiling of head and neck squamous cell carcinoma (HNSCC)

Head and neck squamous cell carcinoma (HNSCC) is the fifth most common cancer in men with an incidence of about 780000 new cases per year worldwide and a poor rate of survival. There is a need for a better understanding of HNSCC, for the development of rational targeted interventions and to define new prognostic or diagnostic markers. To address these needs, we performed a large-scale differential display comparison of hypopharyngeal HNSCCs against histologically normal tissue from the same patients. We have identified 70 genes that exhibit a striking difference in expression between tumours and normal tissues. There is only a limited overlap with other HNSCC gene expression studies that have used other techniques and more heterogeneous tumour samples. Our results provide new insights into the understanding of HNSCC. At the genome level, a series of differentially expressed genes cluster at 12p12-13 and 1q21, two hotspots of genome disruption. The known genes share functional relationships in keratinocyte differentiation, angiogenesis, immunology, detoxification, and cell surface receptors. Of particular interest are the 13 'unknown' genes that exist only in EST, theoretical cDNA and protein databases, or as chromosomal locations. The differentially expressed genes that we have identified are potential new markers and therapeutic targets.     

基于生信分析筛选胆囊癌关键基因#br# 及相关通路的研究#br#

目的通过生信分析筛选胆囊癌治疗的关键基因及癌症相关通路,挖掘胆囊癌患者的差异基因,预测胆囊癌的潜在治疗靶点。方法对GEO数据库中获得的芯片数据进行差异基因（DEGs）分析。选取NCBI 基因表达综合数据库(GEO)中的基因表达芯片 “GSE76633 ”和 “GSE74048”,利用GEO2R在线分析工具对胆囊癌样本和正常胆囊样本中的差异基因进行筛选。在DAVID和KOBAS上对差异基因进行生物过程（GO）分析和通路富集（KEGG）分析。使用蛋白质 蛋白质相互作用（PPI）分析数据库STRING构建靶点互作（PPI）网络模型。结果该研究共筛选了197个差异基因（P<005,|Log2FC|>2）,其中有33个上调基因,164个下调基因。这些基因主要参与了代谢过程的调节,脂肪酸β 氧化、氧化 还原过程等GO生物过程。主要调控代谢途径,甘氨酸、丝氨酸和苏氨酸代谢,缬氨酸亮氨酸和异亮氨酸降解,抗生素的生物合成等。结论该研究利用生物信息学筛选出胆囊癌中的差异基因及相关通路,帮助理解其分子机制及在胆囊癌发病机制和发生、发展过程中的作用,为寻找胆囊癌新的治疗靶点提供思路。