TITLE:
Integrated Analysis of the Gene Expression Profiling and Copy Number Aberration of the Ovarian Cancer
AUTHORS:
Xi Liu, Zhongqiang Liu, Wanxin Yu, Ning Zhan, Liangxi Xie, Wenjia Xie, Zongda Zhu, Zhenxiang Deng
KEYWORDS:
Ovarian Cancer, Copy Number Variation, Gene Differential Expression, SAM Method, GISTIC Method
JOURNAL NAME:
Journal of Cancer Therapy,
Vol.12 No.6,
June
28,
2021
ABSTRACT: Objective: DNA copy number alterations and difference
expression are frequently observed in ovarian cancer. The purpose of this way
was to pinpoint gene expression change that was associated with alterations in DNA copy number and could therefore enlighten
some potential oncogenes and stability genes with functional roles in cancers,
and investigated the bioinformatics significance for those correlated genes. Method: We obtained the DNA copy number and
mRNA expression data from the Cancer Genomic Atlas and identified the
most statistically significant copy number alteration regions using the GISTIC.
Then identified the significance genes between the tumor samples within the
copy number alteration regions and analyzed the correlation using a binary
matrix. The selected genes were subjected to bioinformatics analysis using GSEA tool. Results: GISTIC analysis
results showed there were 45 significance copy number amplification
regions in the ovarian cancer, SAM and Fisher’s exact test found there have 40
genes can affect the expression level, which located in the amplification
regions. That means we obtained 40 genes which have a correlation between copy
number amplification and drastic up- and down-expression, which p-value ere overlapped with the several published studies which were focused on the
gene study of tumorigenesis. Conclusion: The use of statistics and
bioinformatics to analyze the microarray data can found an interaction network
involved. The combination of the copy number data and
expression has provided a short list of
candidate genes that are consistent with tumor driving roles. These
would offer new ideas for early diagnosis and treat target of ovarian cancer.