Abstract
Esophageal adenocarcinoma (EAC) is highly mutated and molecularly heterogeneous. The number of cell lines available for study is limited and their genome has been only partially characterized. The availability of an accurate annotation of their mutational landscape is crucial for accurate experimental design and correct interpretation of genotype-phenotype findings. We performed high coverage, paired end whole genome sequencing on eight EAC cell lines-ESO26, ESO51, FLO-1, JH-EsoAd1, OACM5.1 C, OACP4 C, OE33, SK-GT-4-all verified against original patient material, and one esophageal high grade dysplasia cell line, CP-D. We have made available the aligned sequence data and report single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number alterations, identified by comparison with the human reference genome and known single nucleotide polymorphisms (SNPs). We compare these putative mutations to mutations found in primary tissue EAC samples, to inform the use of these cell lines as a model of EAC.
Highlights
Esophageal adenocarcinoma (EAC), including cancers of the gastro-esophageal junction, represent a substantial health concern in Western countries due to its increasing incidence and poor prognosis
In addition to point mutations there are widespread copy number alterations with evidence of catastrophic events such as chromothripsis and bridge fusion breakages in about one-third of cases (Nones et al, 2014)
An accurate annotation of the mutational landscape of available EAC cell lines is crucial for optimal experimental design, interpretation of genotype-phenotype data and to analyse drug sensitivities
Summary
Esophageal adenocarcinoma (EAC), including cancers of the gastro-esophageal junction, represent a substantial health concern in Western countries due to its increasing incidence and poor prognosis. There are no widely accepted animal models for EAC and a limited number of cell lines are all that are available for in vitro functional studies. Recent genome-wide sequencing projects have shown that EAC is one of the most highly mutated solid cancers with a high degree of heterogeneity (Dulak et al, 2013; Weaver et al, 2014). An accurate annotation of the mutational landscape of available EAC cell lines is crucial for optimal experimental design, interpretation of genotype-phenotype data and to analyse drug sensitivities. We performed high-coverage paired-end whole genome sequencing and aligned the sequence data to the human reference genome in order to detect single nucleotide variants, indels and copy number alterations
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