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Ovarian cancer stem cells: Can targeted therapy lead to improved progression-free survival?

ABSTRACT: Despite significant effort and research funds, epithelial ovarian cancer remains a very deadly disease. There are no effective screening methods that discover early stage disease; the majority of patients are diagnosed with advanced disease. Treatment modalities consist primarily of radical debulking surgery followed by taxane and platinum-based chemotherapy. Newer therapies including limited targeted agents and intraperitoneal delivery of chemotherapeutic drugs have improved disease-free intervals, but failed to yield long-lasting cures in most patients. Chemotherapeutic resistance, particularly in the recurrent setting, plagues the disease. Targeting the pathways and mechanisms behind the development of chemoresistance in ovarian cancer could lead to significant improvement in patient outcomes. In many malignancies, including blood and other solid tumors, there is a subgroup of tumor cells, separate from the bulk population, called cancer stem cells (CSCs). These CSCs are thought to be the cause of metastasis, recurrence and resistance. However, to date, ovarian CSCs have been difficult to identify, isolate, and target. It is felt by many investigators that finding a putative ovarian CSC and a chemotherapeutic agent to target it could be the key to a cure for this deadly disease. This review will focus on recent advances in this arena and discuss some of the controversies surrounding the concept.

SUBMITTER: Walters Haygood CL

PROVIDER: S-EPMC4172672 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Ovarian cancer stem cells: Can targeted therapy lead to improved progression-free survival?

Walters Haygood Christen L CL Arend Rebecca C RC Straughn J Michael JM Buchsbaum Donald J DJ

World journal of stem cells 20140901 4

Despite significant effort and research funds, epithelial ovarian cancer remains a very deadly disease. There are no effective screening methods that discover early stage disease; the majority of patients are diagnosed with advanced disease. Treatment modalities consist primarily of radical debulking surgery followed by taxane and platinum-based chemotherapy. Newer therapies including limited targeted agents and intraperitoneal delivery of chemotherapeutic drugs have improved disease-free interv ...[more]

PMID: 25258665

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Project description:To identify and evaluate the prognostic ability of progression-free survival-related profile for advanced-stage ovarian cancer, advanced-stage serous ovarian cancer tissues from 110 patients who received primary surgery and a platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays of more than 40,000 transcripts. We first selected 88 genes by a univariate Cox proportional hazard analysis (p<0.01) and next optimized regression coefficients by ridge regression model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p,0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). In multivariable analysis, our prognostic index was independently associated with progression-free survival times compared to other clinical factors (p<0.001). Furthermore, the prognostic ability of our prognostic index was validated in external, publicly available dataset (n = 87), and was proved in multivariate analysis (p = 0.0032). These results suggest that disease progression or recurrence of advanced-stage serous ovarian cancer can be predicted by gene expression profile. The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.

Dataset Information

Ovarian cancer stem cells: Can targeted therapy lead to improved progression-free survival?

Publications

Ovarian cancer stem cells: Can targeted therapy lead to improved progression-free survival?

Similar Datasets

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