Genomic Variants and Worldwide Epidemiology of Breast Cancer: A Genome-Wide Association Studies Correlation Analysis

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.

Impact of pri-let-7a-1 rs10739971 for Gastric Cancer Predisposition in an Amazon Region

Gastric cancer (GC) is the fifth most common type of cancer and the fourth leading cause of cancer death. In Brazil, GC has a high incidence and mortality rates, and it is highly variable by region. The Amazon region has significant rising rates among all Brazil regions. Only very few studies have evaluated the association between genetic variants and the risk of gastric cancer in the Brazilian Amazon population. Therefore, this study aimed to investigate associations between single nucleotide polymorphisms of miRNA processing genes and the risk for GC in this population. Potentially functional single nucleotide polymorphisms from miRNA processing genes were genotyped in 159 cases and 193 healthy controls by QuantStudio Real Time PCR. According to our findings, the genotype GG of the variant rs10739971 presents a lower risk to the development of GC in comparison to the remaining genotypes (p = 0.000016; OR = 0.055; 95% CI = 0.015-0.206). This is the first study to report the association of pri-let-7a-1 rs10739971 with GC in the Brazilian Amazon population, which is a highly mixed population with a unique genetic constitution that is different from other populations that are studied in the vast majority of scientific research.

Mucin (MUC) Family Influence on Acute Lymphoblastic Leukemia in Cancer and Non-Cancer Native American Populations from the Brazilian Amazon

The mucin (MUC) family includes several genes aberrantly expressed in multiple carcinomas and mediates diverse pathways essentials for oncogenesis, in both solid and hematological malignancies. Acute Lymphoblastic Leukemia (ALL) can have its course influenced by genetic variants, and it seems more frequent in the Amerindian population, which has been understudied. Therefore, the present work aimed to investigate the MUC family exome in Amerindian individuals from the Brazilian Amazon, in a sample containing healthy Native Americans (NAMs) and indigenous subjects with ALL, comparing the frequency of polymorphisms between these two groups. The population was composed of 64 Amerindians from the Brazilian Amazon, from 12 different isolated tribes, five of whom were diagnosed with ALL. We analyzed 16 genes from the MUC family and found a total of 1858 variants. We compared the frequency of each variant in the ALL vs. NAM group, which led to 77 variants with a significant difference and, among these, we excluded those with a low impact, resulting in 63 variants, which were distributed in nine genes, concentrated especially in MUC 19 (n = 30) and MUC 3A (n = 18). Finally, 11 new variants were found in the NAM population. This is the first work with a sample of native Americans with cancer, a population which is susceptible to ALL, but remains understudied. The MUC family seems to have an influence on the development of ALL in the Amerindian population and especially MUC19 and MUC3A are shown as possible hotspots. In addition, the 11 new variants found point to the need to have their clinical impact analyzed.

Correlation between Genomic Variants and Worldwide Epidemiology of Prostate Cancer

Prostate cancer (PCa) incidence and mortality vary across territories and populations. This can be explained by the genetic factor of this disease. This article aims to correlate the epidemiological data, worldwide incidence, and mortality of PCa with single-nucleotide polymorphisms (SNPs) associated with the susceptibility and severity of this neoplasm in different populations. Eighty-four genetic variants associated with prostate cancer susceptibility were selected from the literature through genome association studies (GWAS). Allele frequencies were obtained from the 1000 Genomes Project, and epidemiological data were obtained from Surveillance, Epidemiology, and End Results (SEER). The PCa incidence, mortality rates, and allele frequencies of variants were evaluated by Pearson’s correlation. Our study demonstrated that 12 SNPs (rs2961144, rs1048169, rs7000448, rs4430796, rs2066827, rs12500426, rs6983267, rs11649743, rs2075110, rs114798100, rs855723, and rs2075109) were correlated with epidemiological data in different ethnic groups. Ten SNPs (rs2961144, rs1048169, rs7000448, rs4430796, rs2066827, rs12500426, rs11649743, rs2075110, rs114798100, and rs2075109) were positively correlated with the mortality rate. Seven SNPs (rs1048169, rs2961144, rs7000448, rs4430796, rs2066827, rs12500426, and rs114798100) were positively correlated with incidence. Positive correlations of incidence and mortality rates were more frequent in the African population. The genetic variants investigated here are likely to predispose to PCa and could play a role in its progression and aggressiveness. This genetic study demonstrated here is promising for implementing personalized strategies to screen for prostate cancer in diverse populations.

MUC family influence on acute lymphoblastic leukemia in Native American populations from Brazilian Amazon

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Background: The MUC family includes several genes previously associated with carcinogenesis and it is associated with solid neoplasms such as those of the gastrointestinal tract. As far as we are aware, there are no studies relating MUC genes to acute lymphoblastic leukemia (ALL), and this type of cancer is more frequent in the Amerindian population, which has been understudied. Therefore, the present work aimed to investigate the MUC family exome in Amerindian individuals from Brazilian Amazon, in a sample containing healthy Native Americans (NAM) and indigenous with ALL, comparing the frequency of polymorphisms between these two groups. Methods: The population was formed by 64 Amerindians from the Brazilian Amazon from 12 different ethnic groups, 5 of whom were diagnosed with ALL. We analyzed 16 genes from the MUC family (MUC1, MUC2, MUC3A, MUC4, MUC5AC, MUC5B, MUC6, MUC7, MUC12, MUC13, MUC15, MUC16, MUC17, MUC19, MUC20, MUC21) and found a total of 1858 variants. Results: After the quality filter, only 743 variants remained. Among them, we compared the frequency of each polymorphism in the LLA vs NAM group, which led to 77 variants with a significant difference, and, among these, we excluded those with LOW impact, resulting in 63. The 63 polymorphisms were distributed in 9 genes, concentrated especially in MUC 19 (n = 30) and MUC 3A (n = 18). Finally, 11 new variants were found in the NAM population. Conclusions: This is the first work with a sample of native americans with cancer, a population which is susceptible to ALL, but remains understudied. The MUC family seems to have an influence on the development of ALL in the Amerindian population, and especially MUC19 and MUC3A are shown as possible hotspots. In addition, the 11 new variants found point to the need to have their clinical impact analyzed. Keywords: MUC family; ALL; Susceptibility; Native American Populations; Brazil.

The Genomic Profile Associated with Risk of Severe Forms of COVID-19 in Amazonian Native American Populations

Genetic factors associated with COVID-19 disease outcomes are poorly understood. This study aimed to associate genetic variants in the SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6, XCR1, and ABO genes with the risk of severe forms of COVID-19 in Amazonian Native Americans, and to compare the frequencies with continental populations. The study population was composed of 64 Amerindians from the Amazon region of northern Brazil. The difference in frequencies between the populations was analyzed using Fisher’s exact test, and the results were significant when p ≤ 0.05. We investigated 64 polymorphisms in 7 genes; we studied 47 genetic variants that were new or had impact predictions of high, moderate, or modifier. We identified 15 polymorphisms with moderate impact prediction in 4 genes (ABO, CXCR6, FYCO1, and SLC6A20). Among the variants analyzed, 18 showed significant differences in allele frequency in the NAM population when compared to others. We reported two new genetic variants with modifier impact in the Amazonian population that could be studied to validate the possible associations with COVID-19 outcomes. The genomic profile of Amazonian Native Americans may be associated with protection from severe forms of COVID-19. This work provides genomic data that may help forthcoming studies to improve COVID-19 outcomes.