Expression genomics of cervical cancer: molecular classification and prediction of radiotherapy response by DNA microarray.
OBJECTIVE
The incidence and mortality rates of cervical cancer are declining in the United States; however, worldwide, cervical cancer is still one of the leading causes of death in women, second only to breast cancer. This disparity is at least partially explained by the absence of or comparatively ineffective screening programs in the developing world. Recent advances in expression genomics have enabled the use of DNA microarray to profile gene expression of various cancers. These expression profiles may be suitable for molecular classification and prediction of disease outcome and treatment response. We envision that expression genomics applied in cervical cancer may provide a more rational approach to the classification and treatment of the disease.


METHODS
In this report, we examined the expression profiles of cervical cancer compared with normal cervical tissues in DNA microarrays that contained approximately 11,000 features that correspond to either human transcripts with known function or anonymous expressed sequence tags.


RESULTS
Our results showed that normal cervical tissues were completely segregated from the cancer samples using about 40 genes whose expressions were significantly different between these specimens. In addition, clinical stage IB and stage IIB tumors could also be classified based on their signature expression patterns. Most importantly, some of the tumor samples were further stratified into two major groups based on their response to radiotherapy, and we were able to predict the response of these patients to radiotherapy from their expression profiles.


CONCLUSIONS
Gene expression profiling by DNA microarray may be used for further molecular classification of disease stages and prediction of treatment response in cervical cancer.
Wong
Yick Fu
YF
Department of Obstetrics and Gynecology, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, People's Republic of China.
Selvanayagam
Zachariah E
ZE
Wei
Nien
N
Porter
Joseph
J
Vittal
Ragini
R
Hu
Rong
R
Lin
Yong
Y
Liao
Jason
J
Shih
Joe Weichung
JW
Cheung
Tak Hong
TH
Lo
Keith Wing Kit
KW
Yim
So Fan
SF
Yip
Shing Kai
SK
Ngong
Danny Tse
DT
Siu
Nelson
N
Chan
Loucia Kit Ying
LK
Chan
Chun Sing
CS
Kong
Tony
T
Kutlina
Elena
E
McKinnon
Randall D
RD
Denhardt
David T
DT
Chin
Khew-Voon
KV
Chung
Tony Kwok Hung
TK
D002584:Cervix Uteri / Q000166:cytology; D005260:Female; D006801:Humans; D009367:Neoplasm Staging; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012016:Reference Values; D016896:Treatment Outcome; D002583:Uterine Cervical Neoplasms / Q000145:classification* / Q000235:genetics* / Q000473:pathology / Q000532:radiotherapy