%0 Journal Article
%T Signal Peptidase Complex Subunit 1 and Hydroxyacyl-CoA Dehydrogenase Beta Subunit Are Suitable Reference Genes in Human Lungs
%A Issac H. K. Too
%A Maurice H. T. Ling
%J ISRN Bioinformatics
%D 2012
%R 10.5402/2012/790452
%X Lung cancer is a common cancer, and expression profiling can provide an accurate indication to advance the medical intervention. However, this requires the availability of stably expressed genes as reference. Recent studies had shown that genes that are stably expressed in a tissue may not be stably expressed in other tissues suggesting the need to identify stably expressed genes in each tissue for use as reference genes. DNA microarray analysis has been used to identify those reference genes with low fluctuation. Fourteen datasets with different lung conditions were employed in our study. Coefficient of variance, followed by NormFinder, was used to identify stably expressed genes. Our results showed that classical reference genes such as GAPDH and HPRT1 were highly variable; thus, they are unsuitable as reference genes. Signal peptidase complex subunit 1 (SPCS1) and hydroxyacyl-CoA dehydrogenase beta subunit (HADHB), which are involved in fundamental biochemical processes, demonstrated high expression stability suggesting their suitability in human lung cell profiling. 1. Introduction According to American Cancer Society, lung cancer is estimated to account for 27.6% of all cancer-related deaths in America in 2010. In a report surveying cancer occurrence in Singapore from 1968 to 2007 published by National Cancer Centre Singapore, lung cancer is rated as the second and third highest occurrence of cancer in Singaporean men and women, respectively, (http://www.nccs.com.sg/pat/file/Report_1968_2007.pdf). Although lung cancer is preventable at early stage, it is usually diagnosed at advanced stage of disease, which is usually too late for current medical intervention and subsequently causes mortality [1]. Therefore, there is a need to profile gene expressions of lung epithelial cells to advance current treatment modalities. Quantification of gene expressions allows for the analysis of different genes threshold regulation [2]. Profiling of gene expression by the mean of quantitative real-time polymerase chain reaction (qRT-PCR), Northern blot, and DNA microarray analysis [3] allow the study of tumors-related biomarkers regulation and the prognosis of disease stage [4] for lung cancer patient [5]. However, a number of variables, such as selected cell types, mRNA extraction and handling techniques, and analytical quantification approaches [6] may result in different gene expression measurements and affect analysis accuracy [2]. In order to address these variations, normalization that usually involves a group of calibrating genes is employed in many gene
%U http://www.hindawi.com/journals/isrn.bioinformatics/2012/790452/