Tumor cells often exhibit an altered metabolic phenotype. However, it is unclear as to when this switch takes place in ovarian cancer, and the potential for these changes to serve as therapeutic targets in clinical prevention and intervention trials. We used our recently developed and characterized mouse ovarian surface epithelial (MOSE) cancer progression model to study metabolic changes in distinct disease stages. As ovarian cancer progresses, complete oxidation of glucose and fatty acids were significantly decreased, concurrent with increases in lactate excretion and (3)H-deoxyglucose uptake by the late-stage cancer cells, shifting the cells towards a more glycolytic phenotype. These changes were accompanied by decreases in TCA flux but an increase in citrate synthase activity, providing substrates for de novo fatty acid and cholesterol synthesis. Also, uncoupled maximal respiration rates in mitochondria decreased as cancer progressed. Treatment of the MOSE cells with 1.5 μM sphingosine, a bioactive sphingolipid metabolite, decreased citrate synthase activity, increased TCA flux, decreased cholesterol synthesis and glycolysis. Together, our data confirm metabolic changes during ovarian cancer progression, indicate a stage specificity of these changes, and suggest that multiple events in cellular metabolism are targeted by exogenous sphingosine which may be critical for future prevention trials.
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http://dx.doi.org/10.1016/j.yexcr.2013.02.017 | DOI Listing |
Front Oncol
January 2025
Gynecologic Oncology Section, Stephenson Cancer Center, Obstetrics and Gynecology Department, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Background/objectives: Patients with ovarian cancer commonly experience metastases and recurrences, which contribute to high mortality. Our objective was to better understand ovarian cancer metastasis and identify candidate biomarkers and drug targets for predicting and preventing ovarian cancer recurrence.
Methods: Transcripts of 770 cancer-associated genes were compared in cells collected from ascitic fluid versus resected tumors of an ES-2 orthotopic ovarian cancer mouse model.
Front Nutr
January 2025
Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Background: Few studies have explored the link between nutritional status and prognosis in patients with epithelial ovarian cancer (EOC), and existing findings are controversial. Thus, this study aimed to explore the effects of pre-treatment nutrition-related indicators on the prognosis of patients with newly diagnosed EOC.
Methods: In this ambispective cohort study, 1,020 patients with EOC diagnosed by pathology examination were enrolled and followed-up until December 31, 2023.
BMJ Oncol
November 2024
Department of Computer Science, Durham University, Durham, UK.
Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.
View Article and Find Full Text PDFObjective: Early detection of ovarian cancer can improve patient outcomes; however, screening tests can yield false-positive results, leading to unnecessary surgical interventions. This systematic review explores the prevalence of false-positive ovarian cancer screenings and subsequent unnecessary surgical interventions.
Methods And Analysis: Five databases were searched in March 2023 and again in March 2024, encompassing primary literature published between 2003 and 2024.
BMJ Oncol
May 2024
Medical Oncology Department, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Transgender and gender-diverse (TGD) individuals face an elevated risk of cancer in comparison with the general population. This increased risk is primarily attributed to an imbalanced exposure to modifiable risk factors and a limited adherence to cancer screening programmes, stemming from historical social and economic marginalisation. Consequently, these factors contribute to poorer clinical outcomes in terms of cancer diagnosis and mortality.
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