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Gastric cancer and esophageal cancer are the second and sixth leading causes of cancer-related death worldwide. Multiple genomic alterations underlying gastric cancer and esophageal squamous cell carcinoma (ESCC) have been identified, but the full spectrum of genomic structural variations and mutations have yet to be uncovered. Here, we report the results of whole-genome sequencing of 30 samples comprising tumor and blood from 15 patients, four of whom presented with ESCC, seven with gastric cardia adenocarcinoma (GCA), and four with gastric noncardia adenocarcinoma. Analyses revealed that an A>C mutation was common in GCA, and in addition to the preferential nucleotide sequence of A located 5 prime to the mutation as noted in previous studies, we found enrichment of T in the 5 prime base. The A>C mutations in GCA suggested that oxidation of guanine may be a potential mechanism underlying cancer mutagenesis. Furthermore, we identified genes with mutations in gastric cancer and ESCC, including well-known cancer genes, TP53, JAK3, BRCA2, FGF2, FBXW7, MSH3, PTCH, NF1, ERBB2, and CHEK2, and potentially novel cancer-associated genes, KISS1R, AMH, MNX1, WNK2, and PRKRIR Finally, we identified recurrent chromosome alterations in at least 30% of tumors in genes, including MACROD2, FHIT, and PARK2 that were often intragenic deletions. These structural alterations were validated using the The Cancer Genome Atlas dataset. Our studies provide new insights into understanding the genomic landscape, genome instability, and mutation profile underlying gastric cancer and ESCC development. Cancer Res; 76(7); 1714-23. ©2016 AACR., (©2016 American Association for Cancer Research.)

Genomic instability plays an important role in most human cancers. To characterize genomic instability in esophageal squamous cell carcinoma (ESCC), we examined loss of heterozygosity (LOH), copy number (CN) loss, CN gain, and gene expression using the Affymetrix GeneChip Human Mapping 500K (n = 30 cases) and Human U133A (n = 17 cases) arrays in ESCC cases from a high-risk region of China. We found that genomic instability measures varied widely among cases and separated them into two groups: a high-frequency instability group (two-thirds of all cases with one or more instability category of > or =10%) and a low-frequency instability group (one-third of cases with instability of <10%). Genomic instability also varied widely across chromosomal arms, with the highest frequency of LOH on 9p (33% of informative single nucleotide polymorphisms), CN loss on 3p (33%), and CN gain on 3q (48%). Twenty-two LOH regions were identified: four on 9p, seven on 9q, four on 13q, two on 17p, and five on 17q. Three CN loss regions-3p12.3, 4p15.1, and 9p21.3-were detected. Twelve CN gain regions were found, including six on 3q, one on 7q, four on 8q, and one on 11q. One of the most gene-rich of these CN gain regions was 11q13.1-13.4, where 26 genes also had RNA expression data available. CN gain was significantly correlated with increased RNA expression in over 80% of these genes. Our findings show the potential utility of combining CN analysis and gene expression data to identify genes involved in esophageal carcinogenesis.

Whole genome association studies of complex human diseases represent a new paradigm in the postgenomic era. In this study, we report application of the Affymetrix, Inc. (Santa Clara, CA) high-density single nucleotide polymorphism (SNP) array containing 11,555 SNPs in a pilot case-control study of esophageal squamous cell carcinoma (ESCC) that included the analysis of germ line samples from 50 ESCC patients and 50 matched controls. The average genotyping call rate for the 100 samples analyzed was 96%. Using the generalized linear model (GLM) with adjustment for potential confounders and multiple comparisons, we identified 37 SNPs associated with disease, assuming a recessive mode of transmission; similarly, 48 SNPs were identified assuming a dominant mode and 53 SNPs in a continuous mode. When the 37 SNPs identified from the GLM recessive mode were used in a principal components analysis, the first principal component correctly predicted 46 of 50 cases and 47 of 50 controls. Among all the SNPs selected from GLMs for the three modes of transmission, 39 could be mapped to 1 of 33 genes. Many of these genes are involved in various cancers, including GASC1, shown previously to be amplified in ESCCs, and EPHB1 and PIK3C3. In conclusion, we have shown the feasibility of the Affymetrix 10K SNP array in genome-wide association studies of common cancers and identified new candidate loci to study in ESCC.

Tumor and matched normal tissue from 19 esophageal squamous cell carcinoma patients from a high-risk area of China were analyzed with 7680 gene cDNA microarrays. Forty-one genes were differentially expressed (P < 0.001; >/==" BORDER="0">2-fold change) between tumor and matched normal samples (13 overexpressed and 28 underexpressed). Hierarchical clustering showed consistent molecular profiles across patients. Multidimensional scaling plots visually distinguished cases by family history status, which was confirmed statistically using a global permutation test (P = 0.007); we then identified 152 genes of which the expression differed in tumors from family history positive versus negative cases (55 overexpressed and 97 underexpressed at P < 0.001). These data indicate that molecular profiles in esophageal squamous cell carcinoma are highly consistent and that expression patterns in familial cases differ from those in sporadic cases.