Chemotherapy eliminates the bulk of the tumor but it leaves a core of cancer cells with high capacity for repair and renewal. The molecular properties identified in these cells may explain some of the unique characteristics of CSCs that control self-renewal and drive metastasis. The identification and cloning of human OCSCs can aid in the development of better therapeutic approaches for ovarian cancer patients.

Evidence suggests that an inflammatory profile of cytokines and chemokines persisting at a particular site would lead to the development of a chronic disease. Recent studies implicate bacterial infection as one possible link between inflammation and carcinogenesis; however, the crucial molecular pathways involved remain unknown. We hypothesized that one possible upstream signaling pathway leading to inflammation in carcinogenesis may be mediated by Toll-like receptors (TLR). We describe for the first time an adaptive mechanism acquired by ovarian cancer cells that allows them to promote a proinflammatory environment and develop chemoresistance. We propose that the TLR-4-MyD88 signaling pathway may be a risk factor for developing cancer and may represent a novel target for the development of biomodulators. Our work explains how bacterial products, such as lipopolysaccharide, can promote, directly from the tumor, the production of proinflammatory cytokines and the enhancement of tumor survival. In addition, we provide new evidence that links TLR-4 signaling, inflammation, and chemoresistance in ovarian cancer cells. (Cancer Res 2006; 66(7): 3859-68)

Early diagnosis of epithelial ovarian cancer (EOC) would significantly decrease the morbidity and mortality from this disease but is difficult in the absence of physical symptoms. Here, we report a blood test, based on the simultaneous quantization of four analytes (leptin, prolactin, osteopontin, and insulin-like growth factor-II), that can discriminate between disease-free and EOC patients, including patients diagnosed with stage I and II disease, with high efficiency (95%). Microarray analysis was used initially to determine the levels of 169 proteins in serum from 28 healthy women, 18 women newly diagnosed with EOC, and 40 women with recurrent disease. Evaluation of proteins that showed significant differences in expression between controls and cancer patients by ELISA assays yielded the four analytes. These four proteins then were evaluated in a blind cross-validation study by using an additional 106 healthy females and 100 patients with EOC (24 stage I͞II and 76 stage III͞IV). Upon sample decoding, the results were analyzed by using three different classification algorithms and a binary code methodology. The four-analyte test was further validated in a blind binary code study by using 40 additional serum samples from normal and EOC cancer patients. No single protein could completely distinguish the cancer group from the healthy controls. However, the combination of the four analytes exhibited the following: sensitivity 95%, positive predictive value (PPV) 95%, specificity 95%, and negative predictive value (NPV) 94%, a considerable improvement on current methodology.insulin-like growth factor-II ͉ leptin ͉ osteopontin ͉ prolactin E pithelial ovarian cancer (EOC) is the fourth leading cause of cancer-related death in women in the U.S. and the leading cause of gynecologic cancer death. EOC is characterized by few early symptoms, presentation at an advanced stage, and poor survival. Despite being one tenth as common as breast cancer, EOC is three times more lethal. This year Ϸ22,220 women will be newly diagnosed with ovarian cancer, and 16,210 will die from the disease (1). The high mortality rate is due to the difficulties with the early detection of ovarian cancer. Indeed, Ϸ80% of patients are diagnosed with advanced staged disease. In patients who are diagnosed with early disease (stage I or II), the 5-yr survival ranges from 60% to 90%, depending on the degree of tumor differentiation (2, 3). In patients with advanced disease, 80-90% will initially respond to chemotherapy, but Ͻ10-15% will remain in permanent remission (4). Although advances in treatment have led to an improved 5-yr survival rate approaching 45%, overall survival has not been enhanced (2, 5).Two alternative strategies have been reported for early detection by using serum biomarkers. One approach is the analysis of serum samples by mass spectrometry to find proteins or protein fragments of unknown identity that detect the presence͞absence of cancer (6-8). Alternatively, analysis of the presence͞absence͞abundance of known proteins͞peptides ...

Purpose: Early detection would significantly decrease the mortality rate of ovarian cancer. In this study, we characterize and validate the combination of six serum biomarkers that discriminate between disease-free and ovarian cancer patients with high efficiency. Experimental Design: We analyzed 362 healthy controls and 156 newly diagnosed ovarian cancer patients. Concentrations of leptin, prolactin, osteopontin, insulin-like growth factor II, macrophage inhibitory factor, and CA-125 were determined using a multiplex, bead-based, immunoassay system. All six markers were evaluated in a training set (181 samples from the control group and 113 samples from OC patients) and a test set (181sample control group and 43 ovarian cancer). Results: Multiplex and ELISA exhibited the same pattern of expression for all the biomarkers. None of the biomarkers by themselves were good enough to differentiate healthy versus cancer cells. However, the combination of the six markers provided a better differentiation than CA-125. Four models with <2% classification error in training sets all had significant improvement (sensitivity 84%-98% at specificity 95%) over CA-125 (sensitivity 72% at specificity 95%) in the test set. The chosen model correctly classified 221out of 224 specimens in the test set, with a classification accuracy of 98.7%. Conclusions: We describe the first blood biomarker test with a sensitivity of 95.3% and a specificity of 99.4% for the detection of ovarian cancer. Six markers provided a significant improvement over CA-125 alone for ovarian cancer detection. Validation was performed with a blinded cohort. This novel multiplex platform has the potential for efficient screening in patients who are at high risk for ovarian cancer.