Bioinformatics for cancer management in the post-genome era.

Human cancer is caused by multiple factors, such as genetic predisposition, chronic persistent inflammation, environmental factors, life style, and aging. Dysregulated proliferation, dysregulated adhesion, resistance to apoptosis, resistance to senescence, and resistance to anti-cancer drugs are features of cancer cells. Accumulation of multiple epigenetic changes and genetic alterations of cancer-associated genes during multi-stage carcinogenesis results in more malignant phenotypes. Post-genome science is characterized by omics data related to genome, transcriptome, proteome, metabolome, interactome, and epigenome as well as by high-throughput technology, such as whole-genome tiling oligonucleotide array, array CGH with 32,433 overlapping BAC clones, transcriptome microarray, mass spectrometry, tissue-based expression array, and cell-based transfection array. Benchtop oncology supplies Desktop oncology with large amounts of omics data produced by high-throughput technology. Desktop oncology establishes knowledge on cancer-related biomarkers, such as predisposition markers, diagnostic markers, prognostic markers, and therapeutic markers, by using bioinformatics and human intelligence of experts for data mining and text mining. Bedside oncology applies the knowledge established by Desktop oncology to determine therapeutics for cancer patients. Antibody drugs (Trastuzumab/Herceptin, Cetuximab/Erbitux, Bevacizumab/Avastin, et cetera), small molecule inhibitors for tyrosine kinases (Gefitinib/Iressa, Erlotinib/Tarceva, Imatinib/Gleevec, et cetera), conventional cytotoxic drugs, and anti-hormonal drugs are used for cancer chemotherapy. Biomarker monitoring contributes to therapeutic optional choice and drug dosage determination for cancer patients. Knowledge on biomarkers is feedforwarded from desktop to bedside in the translational research, and then biomarker monitoring is feedbacked from bedside to desktop in the reverse translational research. Desktop oncology is indispensable for cancer research in the post-genome era. Combination of genetic screening for cancer predisposition in the general population and precise selection of therapeutic options during cancer management could contribute to the realization of personalized prevention and to dramatically improve the prognosis of cancer patients in the future.