The Meta-analysis of Breast Cancer Microarray Studies - Literature review Example

Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggests patterns for coordinate regulation” David D Smith, Pål Sætrom, Ola Snøve Jr, Cathryn Lundberg, Guillermo E Rivas, Carlotta Glackin and Garrett P Larson. Published: 28 January 2008. BMC Bioinformatics 2008, 9:63 Meta-analysis is a statistical technique encompassing an amalgamation of the work carried out or the research performed its review and summary. Meta-analysis encompasses primary studies of the meta-data that is entered in the data-base and then the hypothesis is tested. It is a way that helps to direct the study in the direction to assure how it is going to be of help. Thus meta-analysis combines the entire research carried out in one topic and then interprets the results with advantages and disadvantages. The present meta-analysis is also an amalgamation of various interventions and has shown the impact of independent variable and also the strength of relationship between the variables. This meta-analysis has taken the advantage of molecular profiling in order to classify and to establish the prognosis on the basis of genetic marks of tumors. This meta-analysis was performed as breast cancer is one of the most widely studied malignancies in the present epoch of genomics. The meta-analysis provides the promising results in co-relating the gene expression with the disease prognosis, the repeated occurrence of the disease, the metastatic potential of the breast cancer, the kind of therapeutic response as well as various biological aspects of the breast cancer. It is evident that the meta-analysis could have also taken into consideration the entire spectrum of breast cancer, various pathways that lead to the formation of oncogenic cells and therefore require utmost care in bioinformatic analysis of the complete gene expression profiling. The meta-analysis performed in the article discussed here encompasses alterations in microRNA (miRNA) associated with tumor suppressor gene leading to metastasis. It is manifested that it is directly related to the poor prognosis of breast cancer. Moreover it shows that deregulation of miRNAs is one of the major factors contributing in defining the etiology of cancer. The meta-analysis also signify that the stability of various transcripts do have direct influence on the cell physiology and cellular machinery. Although meta-analysis lacks in providing a complete picture about the various sub-types of breast cancer and do not establish any kind of co-relation with the breast cancer pathogenesis especially the role of HER2. The meta-analysis took into consideration only ER+ and ER- tumor types and did not take into account the estrogen and progesterone receptor levels. The meta-analysis does not provide the picture about the stage of the tumor that was studied, the intensity of vascular invasion in the tumor cells and the degree of cell proliferation. The meta-analysis provides the analytic data of expression level of miRNAs as suppressors. These suppressors are known to have a negative impact on the tumor suppressor genes and therefore they inhibit the expression of tumor elevating genes. Research analysis states the role of these tumor promoting genes as they are down-regulated in breast cancer. The meta-analysis provides a clear picture about the miRNAs and their involvement in activating oncogenes in breast tumor formation. The analysis has opened a new paradigm of research to explore various miRNAs which are potentially imperative in the tumor formation. It is known that some of the miRNAs have potential role in establishing themselves as biomarkers of breast cancer and do play important role in the diagnosis and prognosis of the disease. It is important to understand that appropriate prognosis is desired in any case of cancer, with time breast cancer was studied to a greater extent and many prognosis models have been established. The meta-analysis does not provide a statistical analysis about the prognosis. The meta-analysis did not consider all the genes which are established as the biomarkers in the establishing the prognosis of the breast cancer. Although with the advent of microarray technology many new cancer genes are set as the genetic biomarkers. It is necessary that the meta-analysis must incorporate the appropriate application of all the genes involved in the breast cancer and serve as the genetic markers for the formation of tumors. This could be due to the expression of great number of genes in the microarray process with a less number of genes being classified or due to the redundancies of the data leading to poor prognosis. However various reports establish the utility of microarray experiment in generating the data for establishing the prognosis but still conventional clinical markers are being used in the prognosis of the cancer treatment. The meta-analysis does not consider the importance of BRC-1 and BRC-2. These are essential markers for establishing the prognosis of the breast cancer and therefore form a wide range of application in the prognosis of breast cancer. The present meta-analysis lacks in highlighting the importance and does not provide appropriate information in this aspect and therefore the meta-analysis is disadvantageous in this regard. The study carried out in this meta-analysis is related to gene expression of breast cancer (BrCa) tumors. This meta-analysis is identified to study dysregulated genes in the datasets. These samples are collected from various patients and breast tumor datasets are generated on cDNA or oligonucleotide arrays. In the present meta-analysis 9 published microarray studies were included those with estrogen receptor positive (ER+) BrCa tumor cases and estrogen receptor negative (ER-) BrCa tumor cases from Oncomine database. In this study a meta-analysis was performed to identify those genes which are unanimously up or down regulated in both the cases of ER+ and ER- tumor states. Further in order to study the relatedness of gene that were expressed, proximal promoter sequence or 3’UTR of the top ranked genes that were expressed were studied. To carry out the study a combination of transcription factor binding sites (TFBS), promoter, 3’UTR motifs and microRNA were analyzed. The study concludes the facts that most of the over expressed genes identified were seen before also but many new gene expressions were also reported. In ER- tumors most of the genes were initially identified but this meta-analysis could analyze a collection of cis-acting target sites which are known to play an imperative role in differential gene expression in both the sets ER+/ ER- breast cancer tumors. The background of the study encompasses an understanding towards variation in gene expression which is essential for the classification of breast tumors. A unified set of genes for the implication of profile was lacking and therefore prognostic sets were developed with a unified gene profile that is capable of predicting the jeopardy of reoccurrence and therapeutic answer is highly beneficial. The extent of expression is also a parameter to assess the basis of malignancy. The present meta-analysis encompasses summarizing and synthesizing studies. This includes experiments to ascertain the common regulatory themes and cis-elements for the observed patterns of gene expression. Some of the studies performed co-expression networks in Drosophila gene networks, based on some kind of similarity and co-localization of TFBS with cis-regulatory modules (CRM). This also suggests the phylogenetic conservation of genes during the process of evolution. Along with TFBS, the phylogenetic motifs identify new cis- acting signals modulating transcription. When compared, phylogenetic cis-element and known sequence, relatedness of modulators can be observed and therefore an understanding is generated to rank the genes as over- and under- expressed gene sets. The results procured in the meta-analysis display that forty-six percent of unique probes mapped many-to-one unique UniGene IDs. Providing the mean as 12.7 where as median as1. They procured the following meta-analysis results. Breast Cancer Gene Expression Datasets used in Meta-Analysis Author Journal Array Type, N Probes Sample N ER+ Sample N ER- Other Relevant Clinical Criteria Wang, Y. et al. Lancet [73] Affy, 22283 209 77 DFS 5 Yr Zhao, H. et al. Mol Biol Cell [80] cDNA, 27276 24 11 PR Status, Grade, HER2, LN Status Sotiriou, C. et al. PNAS [81] cDNA, 7549 65 34 LN Status, Chemo/Radio/Horm Tx, 5 Yr OS Ma, X. et al. PNAS [82] cDNA, 1940 18 5 PR, Grade, HER2, Grade, Histology Van de Vijver, M. et al. NEJM [83] cDNA, 23130 226 69 DFS 5 Yr, LN Status, T/M Stage Gruvberger, S. et al. Ca Res [84] cDNA, 3369 28 30 Sorlie, T. et al. PNAS [2] cDNA, 7937 56 18 DFS 5 Yr, LN Status, M Stage West, M. et al. PNAS [85] Affy, 6718 25 24 Perou, C. et al. PNAS [1] cDNA, 8838 26 9 Before/After Chemo, Histology, Grade DFS, Disease Free Survival; Pr, Progesterone status; LN, Lymph node status; OS, overall survival. Smith et al. BMC Bioinformatics 2008 9:63   doi:10.1186/1471-2105-9-63 According to the meta-analysis performed; microRNAs that were used in the study encompasses (21- 23 nucleotides). These are non-coding RNAs and they identify their complementary target sequences in mRNAs and tell about the translational repression or RNA degradation. The analysis utilized the findings that depicts that microRNAs do play imperative roles in cancer and dysregulation of these miRNAs is considered to be the pathological feature that displays estrogen or progesterone receptor status as well as the stage of tumor in breast cancer. These miRNAs target 3’UTRs with short sequence to complement the short nucleotides in the miRNAs at 5’ region. The meta-analysis identified sets of genes that differentiate expressions of ER+ and ER- tumors. It was also assessed that a few of them do possess common cis-regulatory motifs for co-regulation. It is this site that is inexplicably upregulated in both ER+ and ER- tumors. Some of the genes may contain common cis-regulatory motifs and therefore they are co-regulated suggesting that there is some common pathway for their expression. TFBS, CTTTGA, the binding sites for lymphoid enhancer binding factor (LEF1), suggesting the role of LEF1 I tumerogenesis. The LEF1 binding site CTTTGA is the most imperative binding site in the Wnt signaling pathway required for cell-to-cell adhesion and also in the development of mammary glands and therefore it is postulated to have some role in cancer too. When Wnt binds with frizzled protein degradation of β- catenin is prevented this is then transported to nucleus to bind with the transcription factors of TCF/ LEF family including TCF8. If the signaling pathway is altered or any kind of alteration occurs in β- catenin then it results in colorectal and lymphoblastic tumors. It is now reported that if mutation occurs in Wnt pathway genes then it causes β- catenin stabilization and activation of LEF/ TCF- induced transcription. Therefore this meta-analysis suggests that mutation in Wnt signaling pathway contribute to breast cancer. However, the results of this analysis do not point out the role played by other pathways and their expression in the microarray studies especially the BCL-1 and BCL-2. The meta-analysis does report that estrogen receptor binding site (TGACCTTG) is over-enriched and state that estrogen play an important role on genes in ER+ over expression in tumors. It is reported that differences in ER binding sites do exist in gene sets which may reside at distance and are upstream. The analysis indicates that E2F binding site (GCGCSAA) is ranked among top 5 motifs and they were found in over expressed ER- tumors (8 out of 147) and in over expressed ER+ tumors (0 out of 138). It is established prior to this analysis the role of E2F in tumor generation but the analysis did not report so. However, it is reported that the presence of E2F in genes over expressed in ER-BrCa tumors indicates its role in tumor generation as it activates some of the target genes playing imperative role in cell cycle control. A limitation is mentioned in this analysis that in a few cases motif count alone may not be considered to be a good predictor due to positional bias. For some positional bias has got some role to play. The analysis does not imply the role of various other factors playing role in the designation of ER+ and ER- breast tumors. However the results are quite convincing about the meta-analysis performed in the present study and role of genes mentioned in the analysis. The meta-analysis however is totally focused on the fact to identify genes which are expressed in ER+ and ER- breast tumors. It also correlates the significance of these genes in the development of tumors. The analysis co-relate the established three genes ESR1, GATA3 and SLC39A6 overlap with the 1% ER+ upregulated genes. The meta-analysis is also useful for the prognosis. The analysis establish that overlap of 23 genes out of top 5% ER- upregulated tumors through a set of 69 genes representing overexpression in additional 12 types of undifferentiated cancers, this was identified via meta-profiling and are known to activate cancer. The list encompasses genes shown to be concerned in the undifferentiated phenotype. They comprise the MELK kinase for mammalian embryogenesis, the apoptosis inhibitor BIRC5, and multiple genes implicated in cell cycle control (CCNA2, MCM6 and FOXM1). When screening was performed, proximal promoter along with 3UTR domains of the meta-analysis studied TFBS, displayed phylogenetically conserved motifs, while miRNAs differ in pervasiveness between ER+ upregulated versus ER- upregulated genes. The analysis state that, ER- genes had significantly shorter 3UTRs than ER+ genes, evidently short 3UTRs are common for miRNA anti-targets, suggesting that dissimilar mechanisms control groups of ER+ and ER- genes; that is, ER+ genes may be miRNA targets whereas ER- genes may be anti-targets. Dependable with this proposition, ER+ genes have appreciably more reputed miRNA target sites than predicted by 3UTR length alone, whereas ER- genes have considerably less reputed miRNA target sites than anticipated by 3UTR length alone. Anti-target genes are usually concerned with the basis cellular processes signifying the role of these genes in the cell-cycle are appreciably overrepresented in the ER- genes. It is therefore suggested that keeping this analysis as basis a new paradigm has paved the way for further studies related to larger sequence domains upstream or target genes and recommends further basic presentation and differentiation in marking abundance between these gene sets. The study signify that the phylogenetic motifs were small ( Read More