Evidence map›Paper›PMID 26374103›Full record

ArticleHuman genomics2015

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

Xiaoyu Wang, Xiaohong Li, Yichen Cheng, Xin Sun, Xibin Sun, Steve Self, Charles Kooperberg, James Y Dai

Open access · goldAbstract read
In one paragraph

Article in Human genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Emerging Biomarkers for Managing Barrett's Esophagus.Gastrointestinal endoscopy clinics of North America · 2026
    Review
  3. Article
  4. Review
  5. Single-nuclei sequencing of uterine serous carcinoma reveals racial differences in immune signaling.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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  17. Article
  18. Genetic alterations in hepatocellular carcinoma: An update.World journal of gastroenterology · 2016
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Xiaoyu WangVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. xwang234@fredhutch.org.
Xiaohong LiHuman Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. xili@fredhutch.org.
Yichen ChengPublic Health Science Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. ycheng@fredhutch.org.
Xin SunInstitute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China. sunxin@chinacdc.cn.
Xibin SunHenan Office for Cancer Research and Control, Henan Cancer Hospital, Zhengzhou, Henan, China. xbsun21@sina.com.
Steve SelfVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. sself@fredhutch.org.
Charles KooperbergPublic Health Science Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. clk@fredhutch.org.
James Y DaiVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. jdai@fredhutch.org.
Fred Hutch Cancer Center · USHenan Cancer Hospital · CNNational Institute for Occupational Health and Poison Control · CN

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
Use of Biomarkers in Diagnosis, Prognosis, Risk Prediction and Early Detection ofP01CA053996 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI HSU, LI · 1991 to 2015
$9.4M
Statistical inference in genome-wide association and sequencing studiesR01HL114901 · NHLBI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI DAI, JAMES · 2012 to 2015
$1.7M
Adaptive Statistical Methods for Genetic Association StudiesR01HG006124 · NHGRI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2011 to 2014
$1.4M
FHCRC High-Performance Computing ClusterS10OD020069 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPERBERG, CHARLES L · 2015 to 2015
$600k
Genomic studies for understanding etiology of esophageal adenocarcinomaR21CA197502 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI DAI, JAMES · 2015 to 2016
$394k
NCI NIH HHS P01 CA053996NCI NIH HHS P01CA53996NCI NIH HHS P30 CA015704NCI NIH HHS R21 CA197502NHGRI NIH HHS R01 HG006124NHLBI NIH HHS R01 HL114901NHLBI NIH HHS R01HL114901NIH HHS S10 OD020069
6 · The paper itself

Abstract

backgroundEsophageal 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.

resultsIn 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.

conclusionsOur 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.

Indexed as

AdenocarcinomaBarrett EsophagusDNA Copy Number VariationsEsophageal NeoplasmsExomeGenome, HumanHigh-Throughput Nucleotide SequencingHumansNeoplasm ProteinsNeoplasm Proteins

Identifiers

PMID26374103
PMCPMC4570720
OpenAlexW1867723956

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.