Gonghong Wei, Ph.D.

Professor，Faculty of Biochemistry and Molecular Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland

卫功宏

Integromic analysis of the mechanisms underlying cancer predisposition and progression

Developing New Quantitative Imaging Markers to Assist Cancer Risk and Prognosis Assessment

Looking into the order of DNA sequences in the human genomes between any two individuals could reveal hardly any differences. Nevertheless, genome sequence variation including single nucleotide polymorphism (SNP) does occur in the population, and may have profound effects on an individual's risk of developing diseases such as cancer. Thus, how human genetic variants cause cancer and its progression is in general one of the most compelling puzzles and questions in genome medicine. Genome-wide association studies (GWAS) have to date identified a substantial number of SNPs associated with predisposition to various diseases, including prostate cancer (PCa). However, the biological mechanisms and phenotypic effects of these SNPs remain poorly defined, in particular for noncoding genomic variants, thereby hindering the translation of GWAS discoveries to the clinic for disease prediction, diagnosis and prognosis. Here I will present our recent study, using integrated genomics, bioinformatics and molecular approach, and the data of prostate tissue-relevant expression quantitative trait loci (eQTL), histone modification marked gene regulatory elements (epigenome), and the set of genome-wide binding sites of transcription factors (TF cistrome), to systems investigate thus far discovered PCa predisposition loci. Through dissecting PCa regulatory genome including TF cistromes and the epigenomes with epigenetic marks H3K4me1 and H3K27ac, we find that the PCa risk SNPs and especially potential causal eQTL SNPs (eSNPs) are markedly enriched in PCa-specific regulatory genomic region. Intriguingly, these SNPs are more likely to be locating at multiple TF chromatin binding sites and (super-) enhancers, thereby altering the binding of TFs to chromatin and leading to gene misregulation. In addition, I will highlight that we have identified over one hundred eQTL genes that may drive PCa progression and possess clinically translational values in PCa risk prediction and prognosis.