Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 63-66 |
| Number of pages | 4 |
| Journal | Cancer Genetics and Cytogenetics |
| Volume | 154 |
| Issue number | 1 |
| DOIs | |
| State | Published - Oct 1 2004 |
| Externally published | Yes |
Fingerprint
ASJC Scopus subject areas
- Cancer Research
- Genetics
- Molecular Biology
Cite this
Prediction of chemotherapeutic response in ovarian cancer with DNA microarray expression profiling. / Selvanayagam, Zachariah E.; Cheung, Tak Hong; Wei, Nien; Vittal, Ragini; Kit Lo, Keith Wing; Yeo, Winnie; Kita, Tsunekazu; Ravatn, Roald; Hung Chung, Tony Kwok; Wong, Yick Fu; Chin, Khew Voon.
In: Cancer Genetics and Cytogenetics, Vol. 154, No. 1, 01.10.2004, p. 63-66.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Prediction of chemotherapeutic response in ovarian cancer with DNA microarray expression profiling
AU - Selvanayagam, Zachariah E.
AU - Cheung, Tak Hong
AU - Wei, Nien
AU - Vittal, Ragini
AU - Kit Lo, Keith Wing
AU - Yeo, Winnie
AU - Kita, Tsunekazu
AU - Ravatn, Roald
AU - Hung Chung, Tony Kwok
AU - Wong, Yick Fu
AU - Chin, Khew Voon
PY - 2004/10/1
Y1 - 2004/10/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=4644243615&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4644243615&partnerID=8YFLogxK
U2 - 10.1016/j.cancergencyto.2004.01.024
DO - 10.1016/j.cancergencyto.2004.01.024
M3 - Article
C2 - 15381375
AN - SCOPUS:4644243615
VL - 154
SP - 63
EP - 66
JO - Cancer Genetics and Cytogenetics
JF - Cancer Genetics and Cytogenetics
SN - 0165-4608
IS - 1
ER -