Previous studies on the genetic causes of ovarian cancer have focused on comparing allelic imbalance in tumour and normal tissues. Thomassen et al present the first documented report using genome-wide gene expression data to investigate the chromosomal position of regions corresponding to early recurrence of ovarian cancer.
Global gene expression data from 833 ovarian cancer patients were collected. Three of the four data sets were used to identify genomic regions involved in survival. The fourth data set was used as an independent data set for validation. This study used Gene Set Enrichment Analysis to rank chromosomal regions in relation to their association with ovarian cancer survival. Over-representation analysis was used to identify loci with imbalanced expression in tumours from short-term survivors compared to long-term survivors. 1-4 consecutive cytogenic bands were identified; these corresponded to regions of increased expression, occurring at 5q12-14 and a very large region of chromosome 7 with the strongest signal at 7p15-13. Reduced expression was identified at 4q26-32, 6p12-q15, 9p21-q32, and 11p14-11. Region scores summarizing the expressional level of a certain region was calculated by Kaplan-myer plots and analyzed for their association to ovarian cancer survival. These six identified alterations all worsened prognosis in short term survivors. Thus it was deduced that each of the regions contained one or a few metastasis inducing or suppressing genes that are causal for the spreading of ovarian cancer and decreased sensitivity of tumours to treatment.
Although the exact causal genes weren’t identified, the impact of the identified regions on alterations on biological processes was investigated. Pathway analysis of expression patterns associated with high mutational region score identified upregulation of 4 growth factor pathways: epidermal growth factor (EGF), platelet-derived growth factor (PDGF), insulin-like growth factor 1 (IGF1), and Thrombopoietin. Three of these; EGF, PDGR, and IGF1 have been linked with tumourigenesis, progression, angiogenesis, metastasis and survival in solid tumours.
This study is an example of the genomic study of informational challenge number 2 with defects in the ‘readout’ of the genome in the correct order, time and amount (S Degnan, 2009). With further research, measuring DNA copy number in identified regions combined with clinical data will be important for the evaluation of the prognosis of ovarian cancer patients.
References:
Article: Thomassen Mads, Jochumsen Kirsten M, Mogensen Ole , Qihua Tan, Torben A. Kruse, (2009), Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival, Journal of Genes, Chromosomes and Cancer DOI:10.1002/gcc.20676
Fig: Dark stains indicating gene mutations in ovarian cancer cells. (Credit: Georgia Tech/Ovarian Cancer Institute)
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