Transcription profiling of ovarium cancer samples from patients with tumors of different stages, sensitivity to platinum chemotherapy and with no disease recurrence, recurrence or progression to evaluate models of clinical behaviour

ABSTRACT: Ovarian cancer is the leading cause of death in gynaecological malignancies in women. However, currently there are no clinical or pathologic parameters available that can reliably predict clinical outcome. In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict disease stage with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). In the current study we prospectively evaluate models, built on the pilot data set, on a set of 49 new patients. Principal component analysis

INSTRUMENT(S): Generation III Scanner

ORGANISM(S): Homo sapiens

SUBMITTER: Paul Van Hummelen 

PROVIDER: E-MEXP-995 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress