Zang X.,Integrated Cancer Research Center |
Jones C.M.,Integrated Cancer Research Center |
Long T.Q.,Integrated Cancer Research Center |
Monge M.E.,Integrated Cancer Research Center |
And 9 more authors.
Journal of Proteome Research | Year: 2014
Prostate cancer (PCa) is the second leading cause of cancer-related mortality in men. The prevalent diagnosis method is based on the serum prostate-specific antigen (PSA) screening test, which suffers from low specificity, overdiagnosis, and overtreatment. In this work, untargeted metabolomic profiling of age-matched serum samples from prostate cancer patients and healthy individuals was performed using ultraperformance liquid chromatography coupled to high-resolution tandem mass spectrometry (UPLC-MS/MS) and machine learning methods. A metabolite-based in vitro diagnostic multivariate index assay (IVDMIA) was developed to predict the presence of PCa in serum samples with high classification sensitivity, specificity, and accuracy. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent PSA test. Within the discriminant panel, 31 metabolites were identified by MS and MS/MS, with 10 further confirmed chromatographically by standards. Numerous discriminant metabolites were mapped in the steroid hormone biosynthesis pathway. The identification of fatty acids, amino acids, lysophospholipids, and bile acids provided further insights into the metabolic alterations associated with the disease. With additional work, the results presented here show great potential toward implementation in clinical settings. © 2014 American Chemical Society.
PubMed | Integrated Cancer Research Center
Type: | Journal: Scientific reports | Year: 2016
A functionalized nanohydrogel siRNA delivery system and a mouse model of serous ovarian cancer were used to test predictions from previous cell line studies that knockdown of EGFR (epidermal growth factor receptor) may be of clinical significance in the treatment of epithelial tumors especially with respect to the enhancement of platinum based therapies. Our results support these predictions and suggest that targeted delivery of EGFR siRNA may be an effective strategy for the treatment of ovarian and other epithelial tumors associated with elevated levels of EGFR and especially those demonstrating resistance to platinum-based therapies.