Identification of genes with a correlation between copy number and expression in gastric cancer
- Equal contributors
1 State Key Laboratory of Medical Genomics and Shanghai Institute of Hematology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
2 Department of Pathology, Ninth People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
3 Department of Oncology, Gongli Hospital, Shanghai, China
4 National Engineering Center for Biochip at Shanghai, Shanghai, China
BMC Medical Genomics 2012, 5:14 doi:10.1186/1755-8794-5-14Published: 4 May 2012
To elucidate gene expression associated with copy number changes, we performed a genome-wide copy number and expression microarray analysis of 25 pairs of gastric tissues.
We applied laser capture microdissection (LCM) to obtain samples for microarray experiments and profiled DNA copy number and gene expression using 244K CGH Microarray and Human Exon 1.0 ST Microarray.
Obviously, gain at 8q was detected at the highest frequency (70%) and 20q at the second (63%). We also identified molecular genetic divergences for different TNM-stages or histological subtypes of gastric cancers. Interestingly, the C20orf11 amplification and gain at 20q13.33 almost separated moderately differentiated (MD) gastric cancers from poorly differentiated (PD) type. A set of 163 genes showing the correlations between gene copy number and expression was selected and the identified genes were able to discriminate matched adjacent noncancerous samples from gastric cancer samples in an unsupervised two-way hierarchical clustering. Quantitative RT-PCR analysis for 4 genes (C20orf11, XPO5, PUF60, and PLOD3) of the 163 genes validated the microarray results. Notably, some candidate genes (MCM4 and YWHAZ) and its adjacent genes such as PRKDC, UBE2V2, ANKRD46, ZNF706, and GRHL2, were concordantly deregulated by genomic aberrations.
Taken together, our results reveal diverse chromosomal region alterations for different TNM-stages or histological subtypes of gastric cancers, which is helpful in researching clinicopathological classification, and highlight several interesting genes as potential biomarkers for gastric cancer.