Signal Peptidase Complex Subunit 1 and Hydroxyacyl-CoA Dehydrogenase Beta Subunit Are Suitable Reference Genes in Human Lungs.

Issac H K Too,Maurice H T Ling

doi:10.5402/2012/790452

Issac H K Too, Maurice H T Ling

Open Access

https://doi.org/10.5402/2012/790452

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Abstract

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.

Highlights

According to American Cancer Society, lung cancer is estimated to account for 27.6% of all cancer-related deaths in America in 2010
Our results showed that different housekeeping genes have indicated diverse gene expression fluctuations within the human lung tissues with the coefficient of variance (CV) values ranging from 0.42 to 2.38
The results showed that Microtubule affinity-regulating kinase 3 (MARK3), TATA-binding protein (TBP), and Phosphoglycerate kinase 1 (PGK1) have the great fluctuations in their gene expression level with the mean CV values of 1.6441, 2.0988, and 2.3760, respectively

Summary

Introduction

According to American Cancer Society, lung cancer is estimated to account for 27.6% of all cancer-related deaths in America in 2010. 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]. 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].

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