medRxivGenetic & Genomic MedicinePreprint
Utilizing a Variant Prioritization Approach to Explore Genetic Variants in Cervical Cancer Cases among Malawian Women
Samuel D. GwayiiD, Tamiwe TomokaiD, Emile Rugamika ChimusaiD, Yuri D. FedoriwiD, Benjamin KumwendaiD
Abstract
IntroductionCervical cancer (CC) represents a neoplastic transformation of the cervical epithelium. CC is the third most common cancer type in Malawi. In 2018, the estimated cervical cancer mortality rate was 51.5 deaths per 100,000 women per year among Malawian women. Although recent burden association and meta-analysis studies have identified candidate cervical cancer susceptibility variants in Malawian women, they did not establish the functional significance of individual variants. AimThis study aimed to identify germline genetic variants most likely to contribute to cervical cancer susceptibility among Malawian women. MethodologyWhole blood samples were collected from 20 newly diagnosed cervical cancer patients at the Malawi National Cancer Treatment Centre between October and December 2023, and whole genome sequencing was performed. Variants were annotated via VEP and prioritized by ClinVar pathogenic status, Condel (SIFT and PolyPhen2) and minor allele frequency (MAF [≤] 0.1) in the 1000 Genomes project and GenomAD databases. Genes containing the prioritized variants were annotated using the DAVID tool. ResultsWe identified five known pathogenic variants in the ROS1 gene among Malawian cervical cancer patients. We also identified 51 moderate impact variants, 64.7% of which were located in known genes associated with CC, including ADRB1, APOBEC3B, FAT1, IL12RB1, DST, EXO1 and FGFRL1 genes. Discussion and ConclusionThe presence of known pathogenic variants in the ROS1 gene, which is associated with a high recurring rate of CC, as well as the identified moderate impact variants in other genes associated with CC, provide novel insights into the genetic landscape of cervical cancer in Malawi and highlight potentially functional variants that warrant further investigation.
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 0
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