| Summary: | Abstract Background Cervical cancer is a gynecologic cancer type that develops in the cervix, accounting for 8% mortality of all female cancer patients. Infection with specific human papillomavirus (HPV) types is considered the most severe risk factor for cervical cancer. In the context of our socioeconomic conditions, an increasing burden of this disease and high mortality rate prevail in Bangladesh. Although several researches related to the epidemiology, HPV vaccination, and treatment modalities were conducted, researches on the mutation profiles of marker genes in cervical cancer in Bangladesh remain unexplored. Methods In this study, five different genomic regions within the top three most frequently mutated genes (EGFR, KRAS and PIK3CA) in COSMIC database with a key role in the development of cervical cancers were selected to study the mutation frequency in Bangladeshi patients. In silico analysis was done in two steps: nucleotide sequence analysis and its corresponding amino acid analysis. Results DNA from 46 cervical cancer tissue samples were extracted and amplified by PCR, using 1 set of primers designed for EGFR and 2 sets of primers designed for two different regions of both PIK3CA and KRAS gene. In total, 39 mutations were found in 26 patient samples. Eleven different mutations (23.91%), twenty-four different mutations (52.17%) and four mutations (8.7%) were found in amplified EGFR, PIK3CA and KRAS gene fragments, respectively; among which 1 (EGFR) was common in seven patient samples and 2 (PIKCA) were found in more than 1 patient. Our study shows that except for KRAS, the frequency of observed mutations in our patients is higher than those reported earlier in other parts of the world. Most of the exonic mutations were found only in the PIK3CA and EGFR genes. Conclusions The study can be used as a basis to build a mutation database for cervical cancer in Bangladesh with the possibility of targetable oncogenic mutations. Further explorations are needed to establish future diagnostics, personalized medicine decisions, and other pharmaceutical applications for specific cancer subtypes.
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