Copy number alterations detected by whole-exome and whole-genome sequencing of esophageal adenocarcinoma

Human Genomics

James Y. Dai²  Charles Kooperberg²  Steve Self³  Xibin Sun⁴  Xin Sun¹  Yichen Cheng²  Xiaohong Li²  Xiaoyu Wang³ 

[1] Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China;Public Health Science Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA;Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA;Henan Office for Cancer Research and Control, Henan Cancer Hospital, Zhengzhou, Henan, China

Others  :  1225538
DOI  :  10.1186/s40246-015-0044-0

 received in 2015-06-18, accepted in 2015-08-25,  发布年份 2015

【 摘 要 】

Background

Esophageal adenocarcinoma (EA) is among the leading causes of cancer mortality, especially in developed countries. A high level of somatic copy number alterations (CNAs) accumulates over the decades in the progression from Barrett’s esophagus, the precursor lesion, to EA. Accurate identification of somatic CNAs is essential to understand cancer development. Many studies have been conducted for the detection of CNA in EA using microarrays. Next-generation sequencing (NGS) technologies are believed to have advantages in sensitivity and accuracy to detect CNA, yet no NGS-based CNA detection in EA has been reported.

Results

In this study, we analyzed whole-exome (WES) and whole-genome sequencing (WGS) data for detecting CNA from a published large-scale genomic study of EA. Two specific comparisons were conducted. First, the recurrent CNAs based on WGS and WES data from 145 EA samples were compared to those found in five previous microarray-based studies. We found that the majority of the previously identified regions were also detected in this study. Interestingly, some novel amplifications and deletions were discovered using the NGS data. In particular, SKI and PRKCZ detected in a deletion region are involved in transforming growth factor-β pathway, suggesting the potential utility of novel biomarkers for EA. Second, we compared CNAs detected in WGS and WES data from the same 15 EA samples. No large-scale CNA was identified statistically more frequently by WES or WGS, while more focal-scale CNAs were detected by WGS than by WES.

Conclusions

Our results suggest that NGS can replace microarrays to detect CNA in EA. WGS is superior to WES in that it can offer finer resolution for the detection, though if the interest is on recurrent CNAs, WES can be preferable to WGS for its cost-effectiveness.

【 授权许可】

   
2015 Wang et al.

【 图 表 】

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