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EWSR1 fusions are highly promiscuous and are associated with unique malignancies, clinical phenotypes, and molecular subtypes. However, rare fusion partners (RFP) of EWSR1 has not been well described. Here, we conducted a cross-sectional, retrospective study of 1,140 unique tumors harboring EWSR1 fusions. We identified 64 unique fusion partners. RFPs were identified more often in adults than children. Alterations in cell cycle control and DNA damage response genes as driving the differences between fusion partners. Potentially clinically actionable genomic variants were more prevalent in tumors harboring RFP than common fusions. While the data presented here is limited, tumors harboring RFP of EWSR1 may represent molecularly distinct entities and may benefit from further molecular testing to identify targeted therapeutic options.
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http://dx.doi.org/10.1016/j.tranon.2023.101795 | DOI Listing |
Nat Rev Clin Oncol
September 2025
German Cancer Consortium (DKTK), Partner Site Essen, Essen, Germany.
Targeted radionuclide therapy (TRT) is a cutting-edge treatment approach in oncology that combines the molecular precision of targeted agents with the effect of radiotherapy to selectively deliver cytotoxic radiation to cancer cells. Research efforts from the past few decades have led to a diverse molecular landscape of TRT and have provided lessons for further rational development of targeted radiopharmaceuticals and expansion of the clinical applications of this treatment modality. In this Review, we discuss TRT in the context of therapeutic approaches currently available in oncology, describe the broad range of established and emerging targets for TRT including innovative approaches to exploit vulnerabilities presented by the tumour microenvironment, and address the challenges for clinical translation and molecular optimization.
View Article and Find Full Text PDFVirchows Arch
September 2025
Ningbo Clinical Pathology Diagnosis Center, #685 Huancheng North Road, Ningbo, Zhejiang, 315000, China.
The spindle cell variant of papillary thyroid carcinoma (PTC) is exceptionally rare and poses significant diagnostic challenges due to its morphological overlap with other spindle cell lesions of the thyroid. We report a novel case of spindle cell variant PTC in a 66-year-old woman presenting with a TI-RADS 4 thyroid nodule, initially classified as Bethesda III on fine-needle aspiration. Histopathological examination revealed a biphasic tumor composed predominantly of bland spindle cells arranged in solid sheets and fascicles, admixed with entrapped thyroid follicles.
View Article and Find Full Text PDFExp Hematol
September 2025
Tsuruoka Metabolomics Laboratory, National Cancer Center, Tsuruoka, Yamagata 997-0052, Japan. Electronic address:
Gene rearrangements of the human MLL gene (also known as KMT2A) generate multiple fusion oncoproteins which cause leukemia with poor prognosis. MLL is an epigenetic regulator that reads and writes epigenetic information and has an evolutionarily conserved role maintaining expression of Homeotic (HOX) genes during embryonic development. Most MLL gene rearrangements found in leukemia generate a constitutively active version of the wild-type protein, which causes overexpression of HOX and other genes and leukemic transformation of normal hematopoietic progenitors.
View Article and Find Full Text PDFJ Thorac Oncol
July 2025
Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Introduction: TNM staging systems create prognostic categories by anatomic extent of disease. Whether therapeutically important molecular alterations in NSCLC augment the prognostic information of TNM staging is unclear. To study this, we analyzed molecular data from the ninth edition of the lung cancer staging system.
View Article and Find Full Text PDFBiosaf Health
August 2025
Faculty of Innovation Engineering, Macau University of Science and Technology, 999078, Macao Special Administrative Region of China.
Understanding human-virus protein-protein interactions is critical for studying molecular mechanisms driving viral infection, immune evasion, and propagation, thereby informing strategies for public health. Here, we introduce a novel multimodal deep learning framework that integrates high-confidence experimental datasets to systematically predict putative interactions between human and viral proteins. Our approach incorporates two complementary tasks: binary classification for interaction prediction and conditional sequence generation to identify interacting protein partners.
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