Advanced search
1 file | 248.53 KB

Predicting the clinical behavior of ovarian cancer from gene expression profiles

Author
Organization
Abstract
We investigated whether prognostic information is reflected in the expression patterns of ovarian carcinoma samples. RNA obtained from seven FIGO stage I without recurrence, seven platin-sensitive advanced-stage (III or IV), and six platin-resistant advanced-stage ovarian tumors was hybridized on a complementary DNA microarray with 21,372 spotted clones. The results revealed that a considerable number of genes exhibit nonaccidental differential expression between the different tumor classes. Principal component analysis reflected the differences between the three tumor classes and their order of transition. Using a leave-one-out approach together with least squares support vector machines, we obtained an estimated classification test accuracy of 100% for the distinction between stage I and advanced-stage disease and 76.92% for the distinction between platin-resistant versus platin-sensitive disease in FIGO stage III/IV. These results indicate that gene expression patterns could be useful in clinical management of ovarian cancer.
Keywords
platin resistance, MICROARRAY DATA, ovarian cancer, microarrays, clinical, FIGO stage, CLASSIFICATION, MARKERS

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 248.53 KB

Citation

Please use this url to cite or link to this publication:

Chicago
De Smet, F, NL Pochet, K Engelen, T Van Gorp, P Van Hummelen, Kathleen Marchal, F Amant, D Timmerman, BL De Moor, and IB Vergote. 2006. “Predicting the Clinical Behavior of Ovarian Cancer from Gene Expression Profiles.” International Journal of Gynecological Cancer 16 (suppl. 1): 147–151.
APA
De Smet, F, Pochet, N., Engelen, K., Van Gorp, T., Van Hummelen, P., Marchal, K., Amant, F., et al. (2006). Predicting the clinical behavior of ovarian cancer from gene expression profiles. INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER, 16(suppl. 1), 147–151.
Vancouver
1.
De Smet F, Pochet N, Engelen K, Van Gorp T, Van Hummelen P, Marchal K, et al. Predicting the clinical behavior of ovarian cancer from gene expression profiles. INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER. 2006;16(suppl. 1):147–51.
MLA
De Smet, F, NL Pochet, K Engelen, et al. “Predicting the Clinical Behavior of Ovarian Cancer from Gene Expression Profiles.” INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER 16.suppl. 1 (2006): 147–151. Print.
@article{3186799,
  abstract     = {We investigated whether prognostic information is reflected in the expression patterns of ovarian carcinoma samples. RNA obtained from seven FIGO stage I without recurrence, seven platin-sensitive advanced-stage (III or IV), and six platin-resistant advanced-stage ovarian tumors was hybridized on a complementary DNA microarray with 21,372 spotted clones. The results revealed that a considerable number of genes exhibit nonaccidental differential expression between the different tumor classes. Principal component analysis reflected the differences between the three tumor classes and their order of transition. Using a leave-one-out approach together with least squares support vector machines, we obtained an estimated classification test accuracy of 100\% for the distinction between stage I and advanced-stage disease and 76.92\% for the distinction between platin-resistant versus platin-sensitive disease in FIGO stage III/IV. These results indicate that gene expression patterns could be useful in clinical management of ovarian cancer.},
  author       = {De Smet, F and Pochet, NL and Engelen, K and Van Gorp, T and Van Hummelen, P and Marchal, Kathleen and Amant, F and Timmerman, D and De Moor, BL and Vergote, IB},
  issn         = {1048-891X},
  journal      = {INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER},
  language     = {eng},
  number       = {suppl. 1},
  pages        = {147--151},
  title        = {Predicting the clinical behavior of ovarian cancer from gene expression profiles},
  url          = {http://dx.doi.org/10.1111/j.1525-1438.2006.00321.x},
  volume       = {16},
  year         = {2006},
}

Altmetric
View in Altmetric
Web of Science
Times cited: