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REVIEW article

Front. Genome Ed.

Sec. Genome Editing in Cancer and Immunology

Volume 7 - 2025 | doi: 10.3389/fgeed.2025.1565387

This article is part of the Research Topic Insights in Genome Editing in Cancer and Immunology 2024 View all articles

Unraveling the Future of Genomics: CRISPR, Single-Cell Omics, and the Applications in Cancer and Immunology

Provisionally accepted
A Vipin Menon A Vipin Menon 1,2Bicna Song Bicna Song 1,2Lumen Chao Lumen Chao 1,2Diksha Sriram Diksha Sriram 3Pamela Chasky Pamela Chasky 1,4Ishnoor Bakshi Ishnoor Bakshi 3Jane Ulianova Jane Ulianova 1,2Wei Li Wei Li 1,2*
  • 1 Center for Genetic Medicine Research, Children’s National Hospital, Washington D.C., District of Columbia, United States
  • 2 Department of Genomics and Precision Medicine, George Washington University, Washington, D.C., District of Columbia, United States
  • 3 George Washington University, Washington, D.C., District of Columbia, United States
  • 4 Integrated Biomedical Sciences (IBS) Program, George Washington University, Washington, D.C., District of Columbia, United States

The final, formatted version of the article will be published soon.

    The CRISPR system has transformed many research areas, including cancer and immunology, by providing a simple yet effective genome editing system. Its simplicity has facilitated large-scale experiments to assess gene functionality across diverse biological contexts, generating extensive datasets that boosted the development of computational methods and machine learning/artificial intelligence applications. Integrating CRISPR with single-cell technologies has further advanced our understanding of genome function and its role in many biological processes, providing unprecedented insights into human biology and disease mechanisms. This powerful combination has accelerated AI-driven analyses, enhancing disease diagnostics, risk prediction, and therapeutic innovations. This review provides a comprehensive overview of CRISPR-based genome editing systems, highlighting their advancements, current progress, challenges, and future opportunities, especially in cancer and immunology.

    Keywords: Cas9, Cas9-variants, base-editors, prime-editors, machine learning, deep learning, Therapeutics, clinical research

    Received: 23 Jan 2025; Accepted: 26 Mar 2025.

    Copyright: © 2025 Menon, Song, Chao, Sriram, Chasky, Bakshi, Ulianova and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Wei Li, Center for Genetic Medicine Research, Children’s National Hospital, Washington D.C., 20010, District of Columbia, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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