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Published on: January 12, 2020
Identification of candidate growth promoting genes in ovarian cancer through integrated copy number and expression
Manasa Ramakrishna1, Louise H Williams, Samantha E Boyle
1VBCRC Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia.
Abstract:
Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (> 40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r > or =0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2.
Insights
This study identifies key genes involved in ovarian cancer by analyzing genomic rearrangements and expression data. Findings reveal novel potential drivers for ovarian cancer, aiding in diagnostics and therapeutics.
Area of Science:
- Genomics
- Cancer Biology
- Molecular Oncology
Background:
- Ovarian cancer exhibits complex genomic rearrangements, but driver genes are largely unknown.
- Identifying these genes is crucial for understanding disease etiology and developing new treatments.
Purpose of the Study:
- To identify genes targeted by genomic alterations in epithelial ovarian carcinomas.
- To correlate copy number variations with gene expression levels.
Main Methods:
- Integrated high-resolution, genome-wide copy number and expression data from 68 primary ovarian carcinomas.
- Analyzed regions of frequent copy number amplification and their correlation with gene expression.
Main Results:
- Frequent copy number gains observed on chromosomes 3, 7, 8, and 20 in over 40% of samples.
- Identified 32 protein-coding genes with strong positive correlation between copy number and expression in amplified regions.
- Validated known ovarian cancer genes (e.g., ERBB2) and discovered novel candidates (e.g., MYNN, PUF60, TPX2).
Conclusions:
- Genomic alterations in specific chromosomal regions are common in ovarian cancer.
- Integrative analysis successfully identified potential novel driver genes, including MYNN, PUF60, and TPX2.
- These findings offer insights into ovarian cancer pathogenesis and potential therapeutic targets.
