A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer
نویسندگان
چکیده
BACKGROUND The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. METHODS Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). RESULTS Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2-p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. CONCLUSIONS The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP.
منابع مشابه
Classification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest
Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and smal...
متن کاملFeature Selection and Classification of Microarray Gene Expression Data of Ovarian Carcinoma Patients using Weighted Voting Support Vector Machine
We can reach by DNA microarray gene expression to such wealth of information with thousands of variables (genes). Analysis of this information can show genetic reasons of disease and tumor differences. In this study we try to reduce high-dimensional data by statistical method to select valuable genes with high impact as biomarkers and then classify ovarian tumor based on gene expression data of...
متن کاملPrediction of blood cancer using leukemia gene expression data and sparsity-based gene selection methods
Background: DNA microarray is a useful technology that simultaneously assesses the expression of thousands of genes. It can be utilized for the detection of cancer types and cancer biomarkers. This study aimed to predict blood cancer using leukemia gene expression data and a robust ℓ2,p-norm sparsity-based gene selection method. Materials and Methods: In this descriptive study, the microarray ...
متن کاملIdentification of diagnostic biomarkers by bioinformatics analysis in the inflamed and non-inflamed intestinal mucosa in Crohn\'s disease patients
Background: Crohn's disease (CD) is a type of inflammatory bowel disease (IBD) which despite the unknown details is generally related to genetic, immune system, and environmental factors. In this study, we identify transcriptional signatures in patients with CD and then explain the potential molecular mechanisms in inflamed and non-inflamed intestinal mucosa in these patients. Materials and Me...
متن کاملmiR-4284 and miR-4484 as Putative Biomarkers for Diffuse Large B-Cell Lymphoma
Diffuse large B-cell lymphoma is the most common type of non-Hodgkin lymphoma. MicroRNAs (miRNAs) are endogenous small RNA, which can regulate gene expression at the post-transcriptional level. MiRNA profiling has shown a great potential as novel diagnostic and prognostic biomarkers. The present study was performed at the Nemazee Teaching Hospital (Shiraz, Iran) from 2011 to 2013.The aim of thi...
متن کامل