Genomics for Clinical Practice in Oncology

Abstract

Customizing the right drug for the right patient on the basis of the results of the patient's genomic analysis promises to improve quality of life and reduce the burden of disease cost. Technologies such as microarray, next-generation sequencing and scanning for sequence variation, combined with clinical factors, will establish genetic variants responsible for susceptibility to disease and its progression. In oncology, whole-genome expression data is being used to identify tumor subtypes of conditions, such as acute myeloid leukemia, or Burkitt's lymphoma from diffuse B cell lymphomas, as well as prognostic biomarkers, for example in early-stage non-small-cell lung cancer and also to determine the sensitivity and response to chemotherapeutic drugs. Moreover, disease monitoring has been in use for gene expression analysis in peripheral blood mononuclear cells to predict graft rejection in solid organ transplantation. Several clinical and research-based studies have already established the enormous potential of genomics in cardiovascular, neurological, organ transplantation and other disease-related areas. This chapter also focuses on the effects of genomics in the transition from conventional, ‘one-size-fits-all’ medicine towards the new paradigm of personalized medicine.