Identification of Biomarkers Related to the Efficacy of Radiotherapy in Pancreatic Cancer.

BACKGROUND/AIM: Pancreatic cancer (PC) has one of the highest mortality rates, with an overall five-year survival rate of only 7%. When diagnosed, PC is limited to the pancreas in only 20% of patients, whereas in 50% it has already metastasized. This is due to its late diagnosis, which makes the treatments used, such as radiotherapy, difficult, and reduces survival rates. Therefore, the importance of this study in detecting genes that may become possible biomarkers for this type of tumor, especially regarding the human secretome, is highlighted. These genes participate in pathways that are responsible for tumor migration and resistance to therapies, along with other important factors. MATERIALS AND METHODS: To achieve these goals, the following online tools and platforms have been expanded to discover and validate these biomarkers: The Human Protein Atlas database, the Xena Browser platform, Gene Expression Omnibus, the EnrichR platform and the Kaplan-Meier Plotter platform. RESULTS: Our study adopted a methodology that allows the identification of potential biomarkers related to the effectiveness of radiotherapy in PC. Inflammatory pathways were predominantly enriched, related to the regulation of biological processes, primarily in cytokine-derived proteins, which are responsible for tumor progression and other processes that contribute to the development of the disease. CONCLUSION: Radiotherapy treatment demonstrated greater efficacy when used in conjunction with other forms of therapy since it decreased the expression of essential genes involved in several inflammatory pathways linked to tumor progression.

Immunogenetics of HLA-B: SNP, allele, and haplotype diversity in populations from different continents and ancestry backgrounds.

HLA-B is among the most variable gene in the human genome. This gene encodes a key molecule for antigen presentation to CD8+ T lymphocytes and NK cell modulation. Despite the myriad of studies evaluating its coding region (with an emphasis on exons 2 and 3), few studies evaluated introns and regulatory sequences in real population samples. Thus, HLA-B variability is probably underestimated. We applied a bioinformatics pipeline tailored for HLA genes on 5347 samples from 80 different populations, which includes more than 1000 admixed Brazilians, to evaluate the HLA-B variability (SNPs, indels, MNPs, alleles, and haplotypes) in exons, introns, and regulatory regions. We observed 610 variable sites throughout HLA-B; the most frequent variants are shared worldwide. However, the haplotype distribution is geographically structured. We detected 920 full-length haplotypes (exons, introns, and untranslated regions) encoding 239 different protein sequences. HLA-B gene diversity is higher in admixed populations and Europeans while lower in African ancestry individuals. Each HLA-B allele group is associated with specific promoter sequences. This HLA-B variation resource may improve HLA imputation accuracy and disease-association studies and provide evolutionary insights regarding HLA-B genetic diversity in human populations.

Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil.

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.