%0 Journal Article
%T Sex-Specific Genomic Biomarkers for Individualized Treatment of Life-Threatening Diseases
%A Hojin Moon
%A Karen L. Lopez
%A Grace I. Lin
%A James J. Chen
%J Disease Markers
%D 2013
%R 10.1155/2013/393020
%X Numerous studies have demonstrated sex differences in drug reactions to the same drug treatment, steering away from the traditional view of one-size-fits-all medicine. A premise of this study is that the sex of a patient influences difference in disease characteristics and risk factors. In this study, we intend to exploit and to obtain better sex-specific biomarkers from gene-expression data. We propose a procedure to isolate a set of important genes as sex-specific genomic biomarkers, which may enable more effective patient treatment. A set of sex-specific genes is obtained by a variable importance ranking using a combination of cross-validation methods. The proposed procedure is applied to three gene-expression datasets. 1. Introduction Personalized medicine is defined by the use of genomic signatures of patients to assign effective therapies in order to achieve the best medical outcomes for individual patients, thus improving public health. Despite the variety of clinical, morphological, and molecular parameters used to classify human malignancies, patients receiving the same diagnosis can have markedly different clinical courses and treatment responses. Since there is no simple way to determine who will have an adverse reaction, the current system of ¡°one-size-fits-all-¡± diagnoses is simply not good enough. An increasing number of studies have demonstrated sex differences in drug reactions to the same drug treatment. Migeon [1] implied that males and females responded differently to drug treatments and that sex plays a key role in cancer. In addition, females are historically less studied subjects due to the complication of estrous cycle, and therefore such studies would further benefit women¡¯s health and promote public health. Recent advancements in biotechnology have accelerated the search for molecular biomarkers useful in the diagnosis and treatment of disease. Molecular biomarkers of disease risk and status are critical to an accurate treatment by identifying patients most likely to benefit from particular drugs or experience adverse reactions. Because medicine is always practiced on individuals rather than populations, the goal is to change the assignment of therapies from a population-based approach to an individualized approach. Gene-expression data can be used to identify patients with a good disease prognosis, thereby preventing some patients from unnecessary therapies and toxicity. For example, gene-expression profiling was used to predict clinical outcomes in pediatric patients with acute myeloid leukemia and to find genes whose aberrant
%U http://www.hindawi.com/journals/dm/2013/393020/