최정균 교수

Mitotic cell division increases tumour mutation burden and copy number load, predictive markers of the clinical benefit of immunotherapy. Cell division correlates also with genomic demethylation involving methylation loss in late-replicating partial methylation domains. Here we find that immunomodulatory pathway genes are concentrated in these domains and transcriptionally repressed in demethylated tumours with CpG island promoter hypermethylation. Global methylation loss correlated with immune

We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as 'effect size', a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The statistical significance was determined by a permutation test extended to multiple datasets. It was shown

We collected 10 published gene expression datasets from cancers of 13 different tissues and constructed 2 distinct coexpression networks: a tumor network and normal network. Comparison of the two networks showed that cancer affected many coexpression relationships. Functional changes such as alteration in energy metabolism, promotion of cell growth and enhanced immune activity were accompanied with coexpression changes. Coregulation of collagen genes that may control invasion and metastatic spre

Human promoters containing a CpG island tend to remain nucleosome-free as well as methylation-free. In contrast, exons demonstrate a high degree of methylation and nucleosome occupancy. Exonic DNA methylation seems to function together with exonic nucleosomes and H3K36me3 for the proper splicing of transcripts with different expression levels.

A statistical method for combining multiple microarray studies has been previously developed by the authors. Here, we present the application of the method to our hepatocellular carcinoma (HCC) data and report new findings on gene expression changes accompanying HCC. From the cross-verification result of our studies and that of published studies, we found that single microarray analysis might lead to false findings. To avoid those pitfalls of single-set analyses, we employed our effect size meth

Insomnia is reported to chronically affect 10∼15% of the adult population. However, very little is known about the genetics and metabolism of insomnia. Here we surveyed 10,038 Korean subjects whose genotypes have been previously profiled on a genome-wide scale. About 16.5% reported insomnia and displayed distinct metabolic changes reflecting an increase in insulin secretion, a higher risk of diabetes, and disrupted calcium signaling. Insomnia-associated genotypic differences were highly concentr

Phenotypic discordance between monozygotic twins, such as a difference in disease susceptibility, implicates the role of the environment in determining phenotype. To assess genomewide environmental effects on "gene expression phenotype," we employed a published microarray data set for twins. We found that variations in expression phenotypes between monozygotic twins have biases in their chromosomal locations. They also showed a strong inverse correlation with gene density. Genomic regions of low

Non-self epitopes, whether originated from foreign substances or somatic mutations, trigger immune responses when presented by major histocompatibility complex (MHC) molecules and recognized by T cells. Identification of immunogenically active neoepitopes has significant implications in cancer and virus medicine. However, current methods are mostly limited to predicting physical binding of mutant peptides and MHCs. We previously developed a deep-learning based model, DeepNeo, to identify immunog