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This study explores predicting chromosome instability in cancer using gene expression data and location information. It delves into the mechanisms of cell cycle regulation and the manifestation of chromosome instability in cancer cells as a key distinguishing feature. The research aims to detect gene expression patterns associated with chromosome instability through clustering samples and testing membership similarity. The methodology involves visualizing expression data onto chromosomes with location annotations for comprehensive analysis.
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Predicting chromosome instability in cancer using gene expression data and location information Bioinformatics for Genomic Medicine 2006 04-24 Do Kyoon Kim
Introduction • Microarray data • High throughput data contains many information • Integration of data & knowledge • Better outcome?
Introduction • Chromosome instability in cancer • 세포 내 유전체의 안정성은 유전체 복제(replication)와 분열(mitosis)의 각 단계들이 상호 의존적인 연속과정으로 순차적으로 조절되어 유지 • 세포주기의 조절에는 사이클린, 사이클린 의존성 키나아제 등의 단백질 활성화 효소에 의해서 조절되어 지는데 이러한 조절 기능에 이상이 생기면 정상세포가 암 세포화 될 수 있다고 알려져 있음 • 암세포에서는 세포의 핵을 구성하는 염색체의 불안정성 (chromosome instability)이 나타나는데 이는 암세포와 정상세포를 구별 하는 중요한 특징의 하나임
Problem definition • Detect gene expression pattern by chromosome instability in cancer using microarray gene expression data and location information (genes within the chromosomal region) • Add additional function to the ChromoViz for visualization if possible
Method • Clustering each samples by number of chromosome unit - Chromosome unit: genes in user defined distance on chromosome Normal patient A cancer B cancer C cancer
Method 2. Test membership similarity between chromosome unit and cluster using hypergeometric distribution Normal patient A cancer B cancer C cancer 1 2 1 2 1 2 3 1 2 4 3 4 3 4 4 3
Method 3. Compare to each graphs or visualize expression data onto chromosome with associated annotation of location information
