Title :
Microarray therapeutic index: A novel method to combine molecular and clinical data from cancer patients
Author :
Sungchul Ji ; Cheng, Lin ; Szafran, W. ; Carmona, Rhadames
Author_Institution :
Dept. of Pharmacology & Toxicology, Rutgers Univ., Piscataway, NJ, USA
Abstract :
A new method has been developed that enables combining the microarray and clinical data (e.g., survival months) of cancer patients in order to calculate what is here referred to as the individualized therapeutic index (ITI). The prerequisite for calculating ITI includes (i) the measurement of the microarray (or micro) therapeutic index, mTI, defined here for the first time, and (ii) the conversion of mTI into ITI through filtering off those genes whose transcript dynamics cause deviations of points from the regression line of the survival months vs. mTI (SmTI) plot. The ability to measure ITI values of drugs opens up new opportunities to improve drug discovery research (i.e., theragnostics) and personalized medicine.
Keywords :
DNA; RNA; biomedical measurement; cancer; drugs; genetics; lab-on-a-chip; molecular biophysics; regression analysis; cancer; clinical data; drug discovery research; gene filtering off; individualized therapeutic index; microarray data; microarray therapeutic index; molecular data; personalized medicine; regression line; Bioinformatics; Biomedical measurements; Conferences; Drugs; Filtering; Indexes; RNA; RNA differential expression; RNA expression profiles; drug success rate; genotype-phenotype coupling; individualized therapeutic index; micro therapeutic index; personalized medicine; theragnostics;
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4673-2746-6
Electronic_ISBN :
978-1-4673-2744-2
DOI :
10.1109/BIBMW.2012.6470284
