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Decoding Ewing sarcoma: from <i>EWSR1::FLI1</i> translocation to advanced diagnostic approaches.

November 5, 2026pubmed logopapers

Authors

Maurya A,Minal SP,Kumar S,Ramani N,Yadav SC

Affiliations (3)

  • Electron Microscope Facility,Department of Anatomy, All India Institute of Medical Sciences, New Delhi, India.
  • Special Centre for Nano Science, Jawaharlal Nehru University, New Delhi, India.
  • Radiation Biology and Health Sciences Division, Bhabha Atomic Research Centre, Mumbai, India.

Abstract

This review discusses Ewing sarcoma and its diagnostic approaches, highlighting emerging high-throughput technologies that address current diagnostic limitations by enabling rapid, accurate, and personalized diagnostic strategies. Diagnostic approaches for Ewing sarcoma encompass conventional imaging modalities, including X-ray, Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET), together with histopathological and molecular techniques such as Immunohistochemistry (IHC), Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR), Fluorescence in Situ Hybridization (FISH), as well as advanced modalities like liquid biopsy, Next-Generation Sequencing (NGS), nano-diagnostic methods, and Artificial Intelligence (AI)-driven analytical tools. Together, these enable earlier and more accurate detection, molecular profiling, personalized medicine, and precision-guided clinical decision-making. Emerging diagnostic technologies offer new opportunities to improve the detection and molecular characterization of Ewing sarcoma through earlier diagnosis, comprehensive genomic profiling, and personalized medicine. Although NGS, liquid biopsy, and AI have demonstrated significant potential for precision diagnostics, their clinical implementation remains limited by high costs, restricted accessibility, and the need for standardized protocols and clinical validation. Continued technological refinement, integration into routine practice, and access will help overcome existing barriers, strengthen precision diagnostics, improve patient outcomes, and support personalized medicine.

Topics

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