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| http://dx.doi.org/10.1097/CM9.0000000000003136 | DOI Listing |
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Long-term Survival Case of SCLC Transformation After Osimertinib Resistance in EGFR-mutant NSCLC: Benefits from Chemo-immunotherapy Combined with Anti-angiogenic Therapy Followed by Osimertinib Rechallenge.
Cancer Lett
January 2025
Department of Medical Thoracic Oncology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer(IBMC),Chinese Academy of Sciences, Hangzhou, Zhejiang, China. Electronic address:
Enhancing Treatment Decisions for Advanced Non-Small Cell Lung Cancer with Epidermal Growth Factor Receptor Mutations: A Reinforcement Learning Approach.
Cancers (Basel)
January 2025
Department of Medical Oncology, Faculty of Medicine, İstinye University, İstanbul 34010, Turkey.
Background: Although higher-generation TKIs are associated with improved progression-free survival in advanced NSCLC patients with EGFR mutations, the optimal selection of TKI treatment remains uncertain. To address this gap, we developed a web application powered by a reinforcement learning (RL) algorithm to assist in guiding initial TKI treatment decisions.
Methods: Clinical and mutational data from advanced NSCLC patients were retrospectively collected from 14 medical centers.
Teliso-V and osimertinib: the METamorphosis of EGFR-mutant lung cancer?
Ann Oncol
January 2025
Department of Medical Oncology, National Cancer Centre Singapore, Duke-NUS Oncology Academic Clinical Programme, Singapore.
Glioma Image-Level and Slide-Level Gene Predictor (GLISP) for Molecular Diagnosis and Predicting Genetic Events of Adult Diffuse Glioma.
Bioengineering (Basel)
December 2024
Department of Pathology, University of Yamanashi, Yamanashi 409-3898, Japan.
The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: , , mutations, promoter mutations, homozygous deletion (CHD), amplification (amp), 7 gain/10 loss (7+/10-), 1p/19q co-deletion, and promoter methylation.
View Article and Find Full Text PDFExploiting YES1-driven EGFR expression improves the efficacy of EGFR inhibitors.
Mol Cancer Res
January 2025
Cleveland Clinic, Cleveland, OH, United States.
Epidermal growth factor receptor (EGFR) is a highly expressed driver of many cancers, yet the utility of EGFR inhibitors is limited to cancers that harbor sensitizing mutations in the EGFR gene due to dose limiting toxicities. Rather than conventionally blocking the kinase activity of EGFR, we sought to reduce its transcription as an alternative approach to broaden the therapeutic window for EGFR inhibitors targeting wildtype or mutant EGFR. We found that YES1 is highly expressed in triple negative breast cancer (TNBC) and drives cell growth by elevating EGFR levels.
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