Computational Dissection of the Ovarian Cancer Genome: Integrative Analysis of Mutations and Signaling Pathways

Emmanuel Ifeanyi Obeagu

doi:10.22270/ajdhs.v6i2.157

Authors

Emmanuel Ifeanyi Obeagu Division of Haematology, Department of Biomedical and Laboratory Science, Africa University, Zimbabwe. https://orcid.org/0000-0002-4538-0161

DOI:

https://doi.org/10.22270/ajdhs.v6i2.157

Keywords:

Ovarian cancer genomics, Bioinformatics, Somatic mutations, Signaling pathways, Precision oncology

Abstract

Ovarian cancer remains one of the most lethal gynecologic malignancies, driven by profound genomic instability, molecular heterogeneity, and frequent therapeutic resistance. The rapid expansion of high-throughput sequencing technologies has generated large-scale genomic datasets that require advanced computational approaches for meaningful biological interpretation. This narrative review examines current bioinformatics strategies used to dissect the ovarian cancer genome, with a focus on integrative analyses of somatic mutations and dysregulated signaling pathways. We discuss computational methods for mutation profiling, copy number and structural variant analysis, pathway enrichment, and network-based modeling, as well as emerging multi-omics and machine learning frameworks. Particular emphasis is placed on key oncogenic pathways implicated in ovarian cancer pathogenesis, including DNA damage response, PI3K/AKT/mTOR, RAS/MAPK, and immune-related signaling networks. Finally, we highlight ongoing challenges related to tumor heterogeneity, clonal evolution, data integration, and clinical translation. Integrative computational dissection of ovarian cancer genomics provides a critical foundation for biomarker discovery, therapeutic stratification, and the advancement of precision oncology.

Keywords: Ovarian cancer genomics; Bioinformatics; Somatic mutations; Signaling pathways; Precision oncology

Author Biography

Emmanuel Ifeanyi Obeagu , Division of Haematology, Department of Biomedical and Laboratory Science, Africa University, Zimbabwe.

Division of Haematology, Department of Biomedical and Laboratory Science, Africa University, Zimbabwe.

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