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KRAS mutations linked with cancer. Flavonoids were docked against KRAS G12C and G12D receptors. Abyssinone III, alpha naphthoflavone, beta naphthoflavone, abyssinone I, abyssinone II and beta naphthoflavone, genistin, daidzin showed good docking scores against KRAS G12C and G12D receptors, respectively. The MD simulation data revealed that Rg, RMSD, RMSF, and SASA values were within acceptable limits. Alpha and beta naphthoflavone showed good binding energies with KRAS G12C and G12D receptors. DFT and MEP analysis highlighted the nucleophilic and electrophilic zones of best-docked flavonoids. A novel avenue for the control of KRAS G12C and G12D mutations is made possible by flavonoids.
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http://dx.doi.org/10.1080/10286020.2024.2343821 | DOI Listing |
Crit Rev Oncol Hematol
September 2025
Unit of Cancer Genetics, Institute of Genetic & Biomedical Research (IRGB), National Research Council (CNR), Traversa La Crucca n. 3, 07100, Sassari, Italy; Immuno-Oncology & Targeted Cancer Biotherapies, University of Sassari, Viale San Pietro 43, 07100, Sassari, Italy. Electronic address: gpalmier
Mutations in the KRAS gene are prominent oncogenic drivers in non-small cell lung cancer (NSCLC), with multiple pathophysiological, clinical and prognostic implications. Although historically considered an "undruggable" target, recent research led to the development of specific KRAS-G12C inhibitors, like sotorasib and adagrasib which are currently approved for clinical use in patients affected by advanced NSCLC. However, the clinical utility of these drugs is often limited by resistance development through several biological mechanisms, including additional KRAS mutations, activation of compensatory pathways and metabolic reprogramming.
View Article and Find Full Text PDFESMO Open
September 2025
Unit of Oncological Gynecology, Women's Children's and Public Health Department, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy; Università Cattolica del Sacro Cuore, Rome, Italy. Electronic address: https://twitter.com/camillanero.
Background: The No Specific Molecular Profile (NSMP) subtype accounts for ∼30%-40% of endometrial cancer (EC), comprising a heterogeneous group of EC.
Patients And Methods: The primary outcome of this study was the prevalence of actionable genomic alterations in NSMP EC, classified according to the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets (ESCAT). Oncogenic and likely oncogenic alterations, pathways, and co-mutation patterns were reported.
J Phys Chem B
September 2025
State Key Laboratory of Porous Materials for Separation and Conversion, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai 200433, China.
Ras is a node protein in the classic tumor signaling pathway known as RAS-RAF-MEK. Mutations in Ras are reported to occur in approximately 19% of human cancers. Among them, the G12D mutation is one of the most prevalent mutations found in Ras.
View Article and Find Full Text PDFExpert Opin Biol Ther
September 2025
Department of Medical Oncology, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
Introduction: Metastatic colorectal cancer (mCRC) remains a leading cause of cancer mortality worldwide, with limited long-term survival despite therapeutic advances. The increasing understanding of its molecular heterogeneity has paved the way for precision medicine approaches aiming to optimize treatment efficacy and reduce unnecessary toxicity.
Areas Covered: This review provides an in-depth analysis of the current and emerging molecular targets in mCRC, including RAS, BRAF, HER2, and microsatellite instability.
Despite promising results in using deep learning to infer genetic features from histological whole-slide images (WSIs), no prior studies have specifically applied these methods to lung adenocarcinomas from subjects who have never smoked tobacco (NS-LUAD) - a molecularly and histologically distinct subset of lung cancer. Existing models have focused on LUAD from predominantly smoker populations, with limited molecular scope and variable performance. Here, we propose a customized deep convolutional neural network based on ResNet50 architecture, optimized for multilabel classification for NS-LUAD, enabling simultaneous prediction of 16 molecular alterations from a single H&E-stained WSI.
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