A Resampling-Based Meta-Analysis For Detection Of Differential Gene Expression In Breast Cancer
| العنوان: | A Resampling-Based Meta-Analysis For Detection Of Differential Gene Expression In Breast Cancer |
|---|---|
| المؤلفون: | Betül Bozkurt, Isik G. Yulug, Gülüşan Ergül, Bala Gur-Dedeoglu, Ozlen Konu, Serkan Kir, Ahmet Rasit Ozturk |
| المصدر: | BMC Genomics BMC Cancer, Vol 8, Iss 1, p 396 (2008) BMC Cancer |
| بيانات النشر: | Aperta, 2008. |
| سنة النشر: | 2008 |
| مصطلحات موضوعية: | Ductal Carcinomas, Real time polymerase chain reaction, Metastasis, Breast cancer, 0302 clinical medicine, Binding protein, Databases, Genetic, Lung carcinoma, skin and connective tissue diseases, Cancer genetics, Oligonucleotide Array Sequence Analysis, Gene expression regulation, Regulation of gene expression, 0303 health sciences, Microarray Data, Secreted frizzled related protein 1, protein GSPT1, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Gene expression profiling, Reproducibility, 3. Good health, Gene Expression Regulation, Neoplastic, Genetic algorithm, Oncology, 030220 oncology & carcinogenesis, Reverse transcription polymerase chain reaction, Human, Protein PRNP, Activating transcription factor 3, Clinical article, Genetic database, Protein ADAMTS1, lcsh:RC254-282, Article, Statistics, Nonparametric, 03 medical and health sciences, Genetics, Information retrieval, Validation process, Humans, Tumors, Microarray analysis techniques, Protein COX6C, Protein ID4, Gene expression regulation, Neoplastic, Vasculotropin receptor 1, E-cadherin, medicine.disease, RNA extraction, Carcinoma, Lobular, Protein SPTBN1, Gene identification, Protein FN1, Pathway, Reproducibility of results, Cancer Research, Unclassified drug, Oligonucleotide array sequence analysis, Bioinformatics, Information processing, Protein NME1, Breast, Transcription factor Maf, Patterns, Reverse transcriptase polymerase chain reaction, Profiles, Intraductal carcinoma, Reverse Transcriptase Polymerase Chain Reaction, Carcinoma, Ductal, Breast, Classification, Securin, Nonparametric test, Invasive lobular carcinoma, Protein IGFBP6, Paget nipple disease, Female, DNA microarray, Research Article, Breast tumor, Breast Neoplasms, Protein GSN, Biology, Lobular Carcinoma, medicine, Human tissue, Protein Rad21, 030304 developmental biology, Sample size, Reproducibility of Results, Cancer, Metabolism, Genetic variability, Controlled study, Meta analysis |
| الوصف: | BackgroundAccuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.MethodsA resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis.ResultsThe two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results.ConclusionThe proposed meta-analysis approach has the ability to detect a set of differentially expressed genes with the least amount of within-group variability, thus providing highly stable gene lists for class prediction. Increased statistical power and stringent filtering criteria used in the present study also make identification of novel candidate genes possible and may provide further insight to improve our understanding of breast cancer development. |
| وصف الملف: | application/pdf |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::467a1319300844e8da19f852aecfd6b9Test https://aperta.ulakbim.gov.tr/record/41529Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....467a1319300844e8da19f852aecfd6b9 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |