Cancer platinum resistance detection and sensitization method

The phosphorylation status of the BAD protein is a determinant of ovarian cancer cell responsiveness to platinum chemotherapy. Indirect manipulation of BAD phosphorylation status influences cisplatin sensitivity. BAD phosphorylation represents a biomarker that predicts platinum sensitivity and is a therapeutic target to increase platinum sensitivity. The methods employ phospho-specific antibody against a particular amino acid residue or site. Phospho-specific protein characterization methods include immunohistochemical (IHC), flow cytometric, immunofluorescent, capture-and-detection, or reversed phase assay

Prevalence of viral DNA in high-grade serous epithelial ovarian cancer and correlation with clinical outcomes.

IntroductionCurrently 11 infectious agents are classified as carcinogenic but the role of infectious agents on outcomes of epithelial ovarian cancer is largely unknown.ObjectiveTo explore the association between infectious agents and ovarian cancer, we investigated the prevalence of viral DNA in primary ovarian cancer tumors and its association with clinical outcomes.MethodsArchived tumors from 98 patients diagnosed with high-grade serous epithelial ovarian cancer were collected between 1/1/1994 and 12/31/2010. After DNA extraction, Luminex technology was utilized to identify polymerase chain reaction-amplified viral DNA for 113 specific viruses. Demographic data and disease characteristics were summarized using descriptive statistics. We used logistic regression and Cox proportional hazards model to assess associations between tumor viral status and disease outcome and between tumor viral presence and overall survival (OS), respectively.ResultsForty-six cases (45.9%) contained at least one virus. Six highly prevalent viruses were associated with clinical outcomes and considered viruses of interest (VOI; Epstein-Barr virus 1, Merkel cell polyomavirus, human herpes virus 6b, and human papillomaviruses 4, 16, and 23). Factors independently associated with OS were presence of VOI (HR 4.11, P = 0.0001) and platinum sensitivity (HR 0.21, PConclusionsThe presence of a VOI was significantly associated with a lower OS. These findings may have implications for clinical management of ovarian cancer but require additional studies

Detectable Lipidomes and Metabolomes by Different Plasma Exosome Isolation Methods in Healthy Controls and Patients with Advanced Prostate and Lung Cancer

Circulating exosomes in the blood are promising tools for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multi-omic profiles in patients with non-small cell lung cancer (NSCLC), castration-resistant prostate cancer (CRPC), and healthy controls, and developed an algorithm to quantify exosome enrichment. Plasma exosomes were isolated from CRPC (n = 10), NSCLC (n = 14), and healthy controls (n = 10) using three different methods: size exclusion chromatography (SEC), lectin binding, and T-cell immunoglobulin domain and mucin domain-containing protein 4 (TIM4) binding. Molecular profiles were determined by mass spectrometry of extracted exosome fractions. Enrichment analysis of uniquely detected molecules was performed for each method with MetaboAnalyst. The exosome enrichment index (EEI) scores methods based on top differential molecules between patient groups. The lipidomic analysis detected 949 lipids using exosomes from SEC, followed by 246 from lectin binding and 226 from TIM4 binding. The detectable metabolites showed SEC identifying 191 while lectin binding and TIM4 binding identified 100 and 107, respectively. When comparing uniquely detected molecules, different methods showed preferential enrichment of different sets of molecules with SEC enriching the greatest diversity. Compared to controls, SEC identified 28 lipids showing significant difference in NSCLC, while only 1 metabolite in NSCLC and 5 metabolites in CRPC were considered statistically significant (FDR < 0.1). Neither lectin-binding- nor TIM4-binding-derived exosome lipids or metabolites demonstrated significant differences between patient groups. We observed the highest EEI from SEC in lipids (NSCLC: 871.33) which was also noted in metabolites. These results support that the size exclusion method of exosome extraction implemented by SBI captures more heterogeneous exosome populations. In contrast, lectin-binding and TIM4-binding methods bind surface glycans or phosphatidylserine moieties of the exosomes. Overall, these findings suggest that specific isolation methods select subpopulations which may significantly impact cancer biomarker discovery

Detectable Lipidomes and Metabolomes by Different Plasma Exosome Isolation Methods in Healthy Controls and Patients with Advanced Prostate and Lung Cancer

Circulating exosomes in the blood are promising tools for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multi-omic profiles in patients with non-small cell lung cancer (NSCLC), castration-resistant prostate cancer (CRPC), and healthy controls, and developed an algorithm to quantify exosome enrichment. Plasma exosomes were isolated from CRPC (n = 10), NSCLC (n = 14), and healthy controls (n = 10) using three different methods: size exclusion chromatography (SEC), lectin binding, and T-cell immunoglobulin domain and mucin domain-containing protein 4 (TIM4) binding. Molecular profiles were determined by mass spectrometry of extracted exosome fractions. Enrichment analysis of uniquely detected molecules was performed for each method with MetaboAnalyst. The exosome enrichment index (EEI) scores methods based on top differential molecules between patient groups. The lipidomic analysis detected 949 lipids using exosomes from SEC, followed by 246 from lectin binding and 226 from TIM4 binding. The detectable metabolites showed SEC identifying 191 while lectin binding and TIM4 binding identified 100 and 107, respectively. When comparing uniquely detected molecules, different methods showed preferential enrichment of different sets of molecules with SEC enriching the greatest diversity. Compared to controls, SEC identified 28 lipids showing significant difference in NSCLC, while only 1 metabolite in NSCLC and 5 metabolites in CRPC were considered statistically significant (FDR < 0.1). Neither lectin-binding- nor TIM4-binding-derived exosome lipids or metabolites demonstrated significant differences between patient groups. We observed the highest EEI from SEC in lipids (NSCLC: 871.33) which was also noted in metabolites. These results support that the size exclusion method of exosome extraction implemented by SBI captures more heterogeneous exosome populations. In contrast, lectin-binding and TIM4-binding methods bind surface glycans or phosphatidylserine moieties of the exosomes. Overall, these findings suggest that specific isolation methods select subpopulations which may significantly impact cancer biomarker discovery