Background: Our recent study showed that tetrathiomolybdate (TM), a drug to treat copper overload disorders, can sensitize drug-resistant endometrial cancer cells to reactive oxygen species (ROS)-generating anticancer drug doxorubicin. To expand these findings in the present study we explore TM efficacy in combination with a spectrum of ROS-generating anticancer drugs including mitomycin C, fenretinide, 5-fluorouracil and doxorubicin in ovarian cancer cells as a model system.
Methods: The effects of TM alone or in combination with doxorubicin, mitomycin C, fenretinide, or 5-fluorouracil were evaluated using a sulforhodamine B assay. Flow cytometry was used to detect the induction of apoptosis and ROS generation. Immunoblot analysis was carried out to investigate changes in signaling pathways.
Results: TM potentiated doxorubicin-induced cytotoxicity and modulated key regulators of apoptosis (PARP, caspases, JNK and p38 MAPK) in SKOV-3 and A2780 ovarian cancer cell lines. These effects were linked to the increased production of ROS, as shown in SKOV-3 cells. ROS scavenging by ascorbic acid blocked the sensitization of cells by TM. TM also sensitized SKOV-3 to mitomycin C, fenretinide, and 5-fluorouracil. The increased cytotoxicity of these drugs in combination with TM was correlated with the activity of ROS, loss of a pro-survival factor (e.g. XIAP) and the appearance of a pro-apoptotic marker (e.g. PARP cleavage).
Conclusions: Our data show that TM increases the efficacy of various anticancer drugs in ovarian cancer cells in a ROS-dependent manner.
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http://dx.doi.org/10.1186/1471-2407-12-147 | DOI Listing |
Biometrics
January 2025
Department of Biostatistics, University of Michigan at Ann Arbor, Ann Arbor, MI 48109, United States.
Graphical models are powerful tools to investigate complex dependency structures in high-throughput datasets. However, most existing graphical models make one of two canonical assumptions: (i) a homogeneous graph with a common network for all subjects or (ii) an assumption of normality, especially in the context of Gaussian graphical models. Both assumptions are restrictive and can fail to hold in certain applications such as proteomic networks in cancer.
View Article and Find Full Text PDFJ Thorac Oncol
January 2025
Department of General Internal Medicine and Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Hypothesis: To evaluate how comorbidities affect mortality benefits of lung cancer screening (LCS) with low-dose computed-tomography (LDCT).
Methods: We developed a comorbidity index (PLCO-ci) using LCS-eligible participants' data from the Prostate Lung Colorectal and Ovarian (PLCO) trial (training set) and the National Lung Screening Trial (NLST) (validation set). PLCO-ci predicts 5-year non-lung cancer (LC) mortality using a regularized Cox model; with performance evaluated by the area under the ROC curve (ROC).
Med Image Anal
January 2025
Nuffield Department of Medicine, University of Oxford, Oxford, UK; Department of Engineering Science, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Oxford, UK. Electronic address:
Predicting disease-related molecular traits from histomorphology brings great opportunities for precision medicine. Despite the rich information present in histopathological images, extracting fine-grained molecular features from standard whole slide images (WSI) is non-trivial. The task is further complicated by the lack of annotations for subtyping and contextual histomorphological features that might span multiple scales.
View Article and Find Full Text PDFPhytomedicine
January 2025
School of Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China. Electronic address:
Background: Melittin, a major peptide component of bee venom, has demonstrated promising anti-cancer activity across various preclinical cell models, making it a potential candidate for cancer therapy. However, its molecular mechanisms, particularly in ovarian cancer, remain largely unexplored. Ovarian cancer is a life-threatening gynecological malignancy with poor clinical outcomes and limited treatment options.
View Article and Find Full Text PDFEur Radiol
January 2025
Department of Radiology, Montpellier Research Center Institute, PINKCC Laboratory, Montpellier, France.
Objective: To provide up-to-date European Society of Urogenital Radiology (ESUR) guidelines for staging and follow-up of patients with ovarian cancer (OC).
Methods: Twenty-one experts, members of the female pelvis imaging ESUR subcommittee from 19 institutions, replied to 2 rounds of questionnaires regarding imaging techniques and structured reporting used for pre-treatment evaluation of OC patients. The results of the survey were presented to the other authors during the group's annual meeting.
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