Cytogenomics in cancer

Citogenómica en cáncer

Published 2026-02-17

Resumen gráfico Citogenómica en cáncer
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Yunis Hazbun LK, Vásquez Rodriguez MY, Yunis JJ. Cytogenomics in cancer. Rev. colomb. hematol. oncol. [Internet]. 2026 Feb. 17 [cited 2026 Feb. 18];13(1-Supl):53-71. https://doi.org/10.51643/22562915.849

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Vol. 13 No. 1-Supl (2026): Biología molecular tumoral: de la básica a la clínica
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Yunis Hazbun LK, Vásquez Rodriguez MY, Yunis JJ. Cytogenomics in cancer. Rev. colomb. hematol. oncol. [Internet]. 2026 Feb. 17 [cited 2026 Feb. 18];13(1-Supl):53-71. https://doi.org/10.51643/22562915.849
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https://doi.org/10.51643/22562915.849
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Luz Karime Yunis Hazbun
Servicios Médicos Yunis Turbay - Instituto de Genética, Bogotá, Colombia
Roles:  
https://orcid.org/0000-0003-3365-5196
Mike Yeferson Vásquez Rodriguez
Servicios Médicos Yunis Turbay – Instituto de Genética, Bogotá, Colombia
Roles:  
Juan José Yunis
Servicios Médicos Yunis Turbay – Instituto de Genética, Bogotá, Colombia
Roles:  
https://orcid.org/0000-0001-7688-9094
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Luz Karime Yunis Hazbun ,

Médica (MD), Magister en Genética Humana (MS), Doctora en Oncología (PhD). Directora médica de área.

Mike Yeferson Vásquez Rodriguez,

Biólogo, BS, analista de laboratorio análisis y desarrollo

Juan José Yunis,

MD, MSc. Servicios Médicos Yunis Turbay – Instituto de Genética.

Introduction: cytogenomics integrates classical cytogenetics with advanced genomic tools to identify structural genome alterations, reshaping cancer diagnosis and treatment within precision medicine.

Methods: a narrative review was conducted using 57 sources from 2010 to 2025, retrieved from PubMed, Scopus, Web of Science, and Google Scholar. Included materials were original articles, reviews, clinical guidelines, and technical documents. Keywords included cytogenomics, cancer, NGS, OGM, precision medicine, multi-omics, and artificial intelligence.

Results: techniques such as karyotyping, FISH, MLPA, microarrays, NGS, and optical genome mapping enable high-resolution detection of clinically relevant genomic alterations. Integration with artificial intelligence improves analytic accuracy. Multiomic strategies enhance tumor profiling and discovery of novel therapeutic targets. Clinical guidelines and international initiatives support clinical adoption.

Conclusions: cytogenomics, strengthened by AI and multi-omics, is transforming the clinical management of cancer. Despite technological and ethical challenges, its role in personalized oncology continues to expand.

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