RESUMEN
Radiotherapy is focused on the tumor but also reaches healthy tissues, causing toxicities that are possibly related to genomic factors. In this context, radiogenomics can help reduce the toxicity, increase the effectiveness of radiotherapy, and personalize treatment. It is important to consider the genomic profiles of populations not yet studied in radiogenomics, such as the indigenous Amazonian population. Thus, our objective was to analyze important genes for radiogenomics, such as ATM, TGFB1, RAD51, AREG, XRCC4, CDK1, MEG3, PRKCE, TANC1, and KDR, in indigenous people and draw a radiogenomic profile of this population. The NextSeq 500® platform was used for sequencing reactions; for differences in the allelic frequency between populations, Fisher's Exact Test was used. We identified 39 variants, 2 of which were high impact: 1 in KDR (rs41452948) and another in XRCC4 (rs1805377). We found four modifying variants not yet described in the literature in PRKCE. We did not find any variants in TANC1-an important gene for personalized medicine in radiotherapy-that were associated with toxicities in previous cohorts, configuring a protective factor for indigenous people. We identified four SNVs (rs664143, rs1801516, rs1870377, rs1800470) that were associated with toxicity in previous studies. Knowing the radiogenomic profile of indigenous people can help personalize their radiotherapy.
RESUMEN
Breast cancer (BCa) is the most common cancer and leading cause of cancer death among women globally. This can be explained by the genetic factor of this disease. This article aims to correlate the epidemiological data, worldwide incidence, and mortality of BCa with the Single-Nucleotide Polymorphisms (SNPs) associated with the susceptibility and severity in different populations. Two hundred and forty genetic variants associated with BCa susceptibility/severity were selected from the literature through Genome-Wide Association Studies (GWAS). The allele frequencies were obtained from the 1000 Genomes Project, and the epidemiological data were obtained from the World Health Organization (WHO). The BCa incidence, mortality rates, and allele frequencies of the variants were evaluated using Pearson's correlation. Our study demonstrated that 11 SNPs (rs3817578, rs4843437, rs3754934, rs61764370, rs780092, rs2290203, rs10411161, rs6001930, rs16886165, rs8051542 and rs4973768) were significantly correlated with the epidemiological data in different ethnic groups. Seven polymorphisms (rs3817578, rs3754934, rs780092, rs2290203, rs10411161, rs6001930 and rs16886165) were inversely correlated with the incidence rate and four polymorphisms (rs4843437, rs61764370, rs8051542 and rs4973768) were directly correlated with the incidence rate. African and South-East Asian populations have a lower risk of developing BCa when evaluated in terms of genetic factors since they possess variants characterized as protective, as their higher incidence is associated with a lower frequency of BCa cases. The genetic variants investigated here are likely to predispose individuals to BCa. The genetic study described here is promising for implementing personalized strategies to screen for breast cancer in diverse populations.
