Prediction of chemotherapeutic response in ovarian cancer with DNA microarray expression profiling.
Ovarian carcinoma is a leading cause of gynecologic cancer death in women. Despite treatment, a large number of women with ovarian cancer eventually relapse and die of the disease. Hence, recurrent ovarian cancer continues to be a therapeutic dilemma, possibly a result of the emergence of drug resistance during relapse. Recent advances in expression genomics enable global transcript analysis that leads to molecular classification of cancers and prediction of outcome and treatment response. We did a cDNA microarray examination of the expression profiles of eight primary ovarian cancers stratified into two groups based on their chemotherapeutic response. We applied a voice-speech-pattern recognition algorithm for microarray data analysis and were able to model and predict the response of these patients to chemotherapy from their expression profiles. Hence, gene expression profiling by means of DNA microarray may be applied diagnostically for predicting treatment response in ovarian cancer.
Selvanayagam
Zachariah E
ZE
Department of Pediatrics, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New Jersey, New Brunswick, NJ, USA.
Cheung
Tak Hong
TH
Wei
Nien
N
Vittal
Ragini
R
Lo
Keith Wing Kit
KW
Yeo
Winnie
W
Kita
Tsunekazu
T
Ravatn
Roald
R
Chung
Tony Kwok Hung
TK
Wong
Yick Fu
YF
Chin
Khew-Voon
KV
D000328:Adult; D000368:Aged; D019008:Drug Resistance, Neoplasm / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D010051:Ovarian Neoplasms / Q000188:drug therapy* / Q000235:genetics*; D010363:Pattern Recognition, Automated