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Structural Variations of the 3D Genome Architecture in Cervical Cancer Development.

ABSTRACT: Human papillomavirus (HPV) integration is the major contributor to cervical cancer (CC) development by inducing structural variations (SVs) in the human genome. SVs are directly associated with the three-dimensional (3D) genome structure leading to cancer development. The detection of SVs is not a trivial task, and several genome-wide techniques have greatly helped in the identification of SVs in the cancerous genome. However, in cervical cancer, precise prediction of SVs mainly translocations and their effects on 3D-genome and gene expression still need to be explored. Here, we have used high-throughput chromosome conformation capture (Hi-C) data of cervical cancer to detect the SVs, especially the translocations, and validated it through whole-genome sequencing (WGS) data. We found that the cervical cancer 3D-genome architecture rearranges itself as compared to that in the normal tissue, and 24% of the total genome switches their A/B compartments. Moreover, translocation detection from Hi-C data showed the presence of high-resolution t(4;7) (q13.1; q31.32) and t(1;16) (q21.2; q22.1) translocations, which disrupted the expression of the genes located at and nearby positions. Enrichment analysis suggested that the disrupted genes were mainly involved in controlling cervical cancer-related pathways. In summary, we detect the novel SVs through Hi-C data and unfold the association among genome-reorganization, translocations, and gene expression regulation. The results help understand the underlying pathogenicity mechanism of SVs in cervical cancer development and identify the targeted therapeutics against cervical cancer.

SUBMITTER: Adeel MM

PROVIDER: S-EPMC8344058 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Craniosynostosis refers to a condition during early development in which one or more of the fibrous sutures of the skull prematurely fuse by turning into bone, which produces recognizable patterns of cranial shape malformations depending on which suture(s) are affected. In addition to cases with isolated cranial dysmorphologies, craniosynostosis appears in syndromes that include skeletal features of the eyes, nose, palate, hands, and feet as well as impairment of vision, hearing, and intellectual development. Approximately 85% of the cases are nonsyndromic sporadic and emerge after de novo structural genome rearrangements or single nucleotide variation, while the remainders consist of syndromic cases following mendelian inheritance. By karyotyping, genome wide linkage, and CNV analyses as well as by whole exome and whole genome sequencing, numerous candidate genes for craniosynostosis belonging to the FGF, Wnt, BMP, Ras/ERK, ephrin, hedgehog, STAT, and retinoic acid signaling pathways have been identified. Many of the craniosynostosis-related candidate genes form a functional network based upon protein-protein or protein-DNA interactions. Depending on which node of this craniosynostosis-related network is affected by a gene mutation or a change in gene expression pattern, a distinct craniosynostosis syndrome or set of phenotypes ensues. Structural variations may alter the dosage of one or several genes or disrupt the genomic architecture of genes and their regulatory elements within topologically associated chromatin domains. These may exert dominant effects by either haploinsufficiency, dominant negative partial loss of function, gain of function, epistatic interaction, or alteration of levels and patterns of gene expression during development. Molecular mechanisms of dominant modes of action of these mutations may include loss of one or several binding sites for cognate protein partners or transcription factor binding sequences. Such losses affect interactions within functional networks governing development and consequently result in phenotypes such as craniosynostosis. Many of the novel variants identified by genome wide CNV analyses, whole exome and whole genome sequencing are incorporated in recently developed diagnostic algorithms for craniosynostosis.

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Structural Variations of the 3D Genome Architecture in Cervical Cancer Development.

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