Ovarian cancer is a highly invasive and metastatic disease with a poor prognosis if diagnosed at an advanced stage, which is often the case. Recent studies argue that ovarian cancer cells that have undergone epithelial-to-mesenchymal transition (EMT) acquire aggressive malignant properties, but the relevant molecular mechanisms in this setting are not well-understood. Here, we report findings from an siRNA screen that identified the homeobox transcription factor ALX1 as a novel regulator of EMT. RNA interference-mediated attenuation of ALX1 expression restored E-cadherin expression and cell-cell junction formation in ovarian cancer cells, suppressing cell invasion, anchorage-independent growth, and tumor formation. Conversely, enforced expression of ALX1 in ovarian cancer cells or nontumorigenic epithelial cells induced EMT. We found that ALX1 upregulated expression of the key EMT regulator Snail (SNAI1) and that it mediated EMT activation and cell invasion by ALX1. Our results define the ALX1/Snail axis as a novel EMT pathway that mediates cancer invasion.
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http://dx.doi.org/10.1158/0008-5472.CAN-12-2377 | 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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