STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS

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Year : 2026 | Volume : 04 | 01 | Page :
    By

    Dr. Atul Khajuria,

  • Ashish Kumar,

  1. Dean, Faculty of Allied & Healthcare Sciences Rayat Bahra Professional University, Hoshiarpur, Punjab
  2. Assistant Professor, Faculty of Allied & Healthcare Sciences Rayat Bahra Professional University, Hoshiarpur, Punjab

Abstract

Structural genomic alterations, including copy number variations (CNVs) and structural variants (SVs), play a central role in cancer initiation and progression. These alterations extend beyond gene dosage effects and interact dynamically with epigenomic mechanisms such as DNA methylation, histone modifications, and three-dimensional chromatin organization. Recent pan-cancer studies have demonstrated that CNV burden and SV signatures reflect key oncogenic processes including chromothripsis, homologous recombination deficiency, enhancer hijacking, and extrachromosomal DNA (ecDNA) amplification. These mechanisms alter transcriptional regulation through chromatin remodeling, neo-topologically associating domain formation, and enhancer-promoter interactions. Integration of multi-omics datasets, including CNV, SV, methylation, and transcriptomic data, has enabled identification of robust molecular subtypes with distinct clinical outcomes, immune microenvironments, and therapeutic responses. These integrated signatures outperform traditional single-layer biomarkers in prognostic prediction and treatment stratification. Furthermore, structural–epigenomic interactions provide insights into tumor heterogeneity, resistance mechanisms, and disease evolution. Clinical implementation of such integrative models can enhance personalized treatment strategies and improve survival outcomes. In conclusion, structural–epigenomic integration represents a transformative approach in oncology, offering improved prognostic accuracy and guiding precision medicine. Future research should focus on translating these findings into clinically applicable tools and validating them across diverse populations.

Keywords: Copy number variation, Structural variants, Epigenomics, Cancer prognosis, Multi-omics integration

How to cite this article:
Dr. Atul Khajuria, Ashish Kumar. STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS. International Journal of Cell Biology and Cellular Functions. 2026; 04(01):-.
How to cite this URL:
Dr. Atul Khajuria, Ashish Kumar. STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS. International Journal of Cell Biology and Cellular Functions. 2026; 04(01):-. Available from: https://journals.stmjournals.com/ijcbcf/article=2026/view=239267


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Ahead of Print Subscription Review Article
Volume 04
01
Received 21/03/2026
Accepted 25/03/2026
Published 25/03/2026
Publication Time 4 Days
55

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