Purpose: This study examined the gene copy number change events at chromosome 20 in gastric cancer, and their possible relationship with recurrence using cDNA microarray-based comparative genomic hybridization.
Experimental Design: Thirty pairs of gastric tumor and normal gastric tissues were used in the cDNA microarray-based comparative genomic hybridization. The cDNA microarrays containing 17,000 sequence-verified human gene probes were used in a direct comparison design, where genomic DNAs from the normal and tumor tissues were labeled with fluorescent dyes Cy3 and Cy5, respectively, and cohybridized. Genes with log(2) (Cy5/Cy3) > or = 0.58 in at least one case were selected as the amplified genes. In order to search for the association between gene copy number changes and the recurrence status, patients were grouped according to their recurrence status. Gene selection between the two groups was done, and each patient was given a score based on the sum of the selected genes' ratios. Logistic regression analysis was carried out in order to determine if the score of a group of patients was correlated with a recurrence.
Results: A group of genes including NCOA6, CYP24A1, PTPN1, and ZNF217 was amplified in gastric cancer. Another group of 39 genes, whose sum of copy number change levels was significantly associated with a poor prognosis for recurrence, was selected (P < 0.05).
Conclusion: Ninety-six amplified genes at chromosome 20 of gastric cancer are reported. A scoring system based on gene copy changes at chromosome 20 can provide an independent patient grouping system that can distinguish patient recurrence status and survival.
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Copy number variants (CNVs) are prevalent in both diploid and haploid genomes, with the latter containing a single copy of each gene. Studying CNVs in genomes from single or few cells is significantly advancing our knowledge in human disorders and disease susceptibility. Low-input including low-cell and single-cell sequencing data for haploid and diploid organisms generally displays shallow and highly non-uniform read counts resulting from the whole genome amplification steps that introduce amplification biases.
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