Molecular Profile of Variants Potentially Associated with Severe Forms of COVID-19 in Amazonian Indigenous Populations.

Coronavirus disease 2019 (COVID-19) is an infection caused by SARS-CoV-2. Genome-wide association studies (GWASs) have suggested a strong association of genetic factors with the severity of the disease. However, many of these studies have been completed in European populations, and little is known about the genetic variability of indigenous peoples' underlying infection by SARS-CoV-2. The objective of the study is to investigate genetic variants present in the genes AQP3, ARHGAP27, ELF5L, IFNAR2, LIMD1, OAS1 and UPK1A, selected due to their association with the severity of COVID-19, in a sample of indigenous people from the Brazilian Amazon in order to describe potential new and already studied variants. We performed the complete sequencing of the exome of 64 healthy indigenous people from the Brazilian Amazon. The allele frequency data of the population were compared with data from other continental populations. A total of 66 variants present in the seven genes studied were identified, including a variant with a high impact on the ARHGAP27 gene (rs201721078) and three new variants located in the Amazon Indigenous populations (INDG) present in the AQP3, IFNAR2 and LIMD1 genes, with low, moderate and modifier impact, respectively.

Molecular Profile of Variants in CDH1, TP53, PSCA, PRKAA1, and TTN Genes Related to Gastric Cancer Susceptibility in Amazonian Indigenous Populations.

Gastric Cancer is a disease associated with environmental and genetic changes, becoming one of the most prevalent cancers around the world and with a high incidence in Brazil. However, despite being a highly studied neoplastic type, few efforts are aimed at populations with a unique background and genetic profile, such as the indigenous peoples of the Brazilian Amazon. Our study characterized the molecular profile of five genes associated with the risk of developing gastric cancer by sequencing the complete exome of 64 indigenous individuals belonging to 12 different indigenous populations in the Amazon. The analysis of the five genes found a total of 207 variants, of which 15 are new in our indigenous population, and among these are two with predicted high impact, present in the TTN and CDH1 genes. In addition, at least 20 variants showed a significant difference in the indigenous population in comparison with other world populations, and three are already associatively related to some type of cancer. Our study reaffirms the unique genetic profile of the indigenous population of the Brazilian Amazon and allows us to contribute to the conception of early diagnosis of complex diseases such as cancer, improving the quality of life of individuals potentially suffering from the disease.

Epidemiological-molecular profile of variants associated with type 2 diabetes mellitus in indigenous populations from the Brazilian Amazon.

AIMS: While lifestyle factors are strongly associated with Type 2 diabetes (T2DM), genetic characteristics also play a role. However, much of the research on T2DM genetics focuses on European and Asian populations, leaving underrepresented groups, such as indigenous populations with high diabetes prevalence, understudied. METHODS: We characterized the molecular profile of 10 genes involved in T2DM risk through complete exome sequencing of 64 indigenous individuals belonging to 12 different Amazonian ethnic groups. RESULTS: The analysis revealed 157 variants, including four exclusive variants in the indigenous population located in the NOTCH2 and WFS1 genes with a modifier or moderate impact on protein effectiveness. Furthermore, a high impact variant in NOTCH2 was also found. Additionally, the frequency of 10 variants in the indigenous group showed significant differences when compared to other global populations that were evaluated. CONCLUSION: Our study identified 4 novel variants associated with T2DM in the NOTCH2 and WFS1 genes in the Amazonian indigenous populations we studied. In addition, a variant with a high predicted impact in NOTCH2 was also observed. These findings represent a valuable starting point for conducting further association and functional studies, which could help to improve our understanding of the unique characteristics of this population.

Incidence of Hereditary Gastric Cancer May Be Much Higher than Reported.

Hereditary gastric cancers (HGCs) are supposed to be rare and difficult to identify. Nonetheless, many cases of young patients with gastric cancer (GC) fulfill the clinical criteria for considering this diagnosis but do not present the defined pathogenic mutations necessary to meet a formal diagnosis of HGC. Moreover, GC in young people is a challenging medical situation due to the usual aggressiveness of such cases and the potential risk for their relatives when related to a germline variant. Aiming to identify additional germline alterations that might contribute to the early onset of GC, a complete exome sequence of blood samples from 95 GC patients under 50 and 94 blood samples from non-cancer patients was performed and compared in this study. The number of identified germline mutations in GC patients was found to be much higher than that from individuals without a cancer diagnosis. Specifically, the number of high functional impact mutations, including those affecting genes involved in medical diseases, cancer hallmark genes, and DNA replication and repair processes, was much higher, strengthening the hypothesis of the potential causal role of such mutations in hereditary cancers. Conversely, classically related HGC mutations were not found and the number of mutations in genes in the CDH1 pathway was not found to be relevant among the young GC patients, reinforcing the hypothesis that existing alternative germline contributions favor the early onset of GC. The LILRB1 gene variants, absent in the world's cancer datasets but present in high frequencies among the studied GC patients, may represent essential cancer variants specific to the Amerindian ancestry's contributions. Identifying non-reported GC variants, potentially originating from under-studied populations, may pave the way for additional discoveries and translations to clinical interventions for GC management. The newly proposed approaches may reduce the discrepancy between clinically suspected and molecularly proven hereditary GC and shed light on similar inconsistencies among other cancer types. Additionally, the results of this study may support the development of new blood tests for evaluating cancer risk that can be used in clinical practice, helping physicians make decisions about strategies for surveillance and risk-reduction interventions.

Pharmacogenomic Profile of Amazonian Amerindians.

Given the role of pharmacogenomics in the large variability observed in drug efficacy/safety, an assessment about the pharmacogenomic profile of patients prior to drug prescription or dose adjustment is paramount to improve adherence to treatment and prevent adverse drug reaction events. A population commonly underrepresented in pharmacogenomic studies is the Native American populations, which have a unique genetic profile due to a long process of geographic isolation and other genetic and evolutionary processes. Here, we describe the pharmacogenetic variability of Native American populations regarding 160 pharmacogenes involved in absorption, distribution, metabolism, and excretion processes and biological pathways of different therapies. Data were obtained through complete exome sequencing of individuals from 12 different Amerindian groups of the Brazilian Amazon. The study reports a total of 3311 variants; of this, 167 are exclusive to Amerindian populations, and 1183 are located in coding regions. Among these new variants, we found non-synonymous coding variants in the DPYD and the IFNL4 genes and variants with high allelic frequencies in intronic regions of the MTHFR, TYMS, GSTT1, and CYP2D6 genes. Additionally, 332 variants with either high or moderate (disruptive or non-disruptive impact in protein effectiveness, respectively) significance were found with a minimum of 1% frequency in the Amazonian Amerindian population. The data reported here serve as scientific basis for future design of specific treatment protocols for Amazonian Amerindian populations as well as for populations admixed with them, such as the Northern Brazilian population.

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.

Family-based whole-exome sequencing identifies rare variants potentially related to cutaneous melanoma predisposition in Brazilian melanoma-prone families.

Genetic predisposition accounts for nearly 10% of all melanoma cases and has been associated with a dozen moderate- to high-penetrance genes, including CDKN2A, CDK4, POT1 and BAP1. However, in most melanoma-prone families, the genetic etiology of cancer predisposition remains undetermined. The goal of this study was to identify rare genomic variants associated with cutaneous melanoma susceptibility in melanoma-prone families. Whole-exome sequencing was performed in 2 affected individuals of 5 melanoma-prone families negative for mutations in CDKN2A and CDK4, the major cutaneous melanoma risk genes. A total of 288 rare coding variants shared by the affected relatives of each family were identified, including 7 loss-of-function variants. By performing in silico analyses of gene function, biological pathways, and variant pathogenicity prediction, we underscored the putative role of several genes for melanoma risk, including previously described genes such as MYO7A and WRN, as well as new putative candidates, such as SERPINB4, HRNR, and NOP10. In conclusion, our data revealed rare germline variants in melanoma-prone families contributing with a novel set of potential candidate genes to be further investigated in future studies.

Chemical Inhibition of Apurinic-Apyrimidinic Endonuclease 1 Redox and DNA Repair Functions Affects the Inflammatory Response via Different but Overlapping Mechanisms.

The presence of oxidized DNA lesions, such as 7,8-dihydro-8-oxoguanine (8-oxoG) and apurinic/apyrimidinic sites (AP sites), has been described as epigenetic signals that are involved in gene expression control. In mammals, Apurinic-apyrimidinic endonuclease 1/Redox factor-1 (APE1/Ref-1) is the main AP endonuclease of the base excision repair (BER) pathway and is involved in active demethylation processes. In addition, APE1/Ref-1, through its redox function, regulates several transcriptional factors. However, the transcriptional control targets of each APE1 function are not completely known. In this study, a transcriptomic approach was used to investigate the effects of chemical inhibition of APE1/Ref-1 redox or DNA repair functions by E3330 or methoxyamine (MX) in an inflammatory cellular model. Under lipopolysaccharide (LPS) stimulation, both E3330 and MX reduced the expression of some cytokines and chemokines. Interestingly, E3330 treatment reduced cell viability after 48 h of the treatment. Genes related to inflammatory response and mitochondrial processes were downregulated in both treatments. In the E3330 treatment, RNA processing and ribosome biogenesis genes were downregulated, while they were upregulated in the MX treatment. Furthermore, in the E3330 treatment, the cellular stress response was the main upregulated process, while the cellular macromolecule metabolic process was observed in MX-upregulated genes. Nuclear respiratory factor 1 (NRF1) was predicted to be a master regulator of the downregulated genes in both treatments, while the ETS transcription factor ELK1 (ELK1) was predicted to be a master regulator only for E3330 treatment. Decreased expression of ELK1 and its target genes and a reduced 28S/18S ratio were observed, suggesting impaired rRNA processing. In addition, both redox and repair functions can affect the expression of NRF1 and GABPA target genes. The master regulators predicted for upregulated genes were YY1 and FLI1 for the E3330 and MX treatments, respectively. In summary, the chemical inhibition of APE1/Ref-1 affects gene expression regulated mainly by transcriptional factors of the ETS family, showing partial overlap of APE1 redox and DNA repair functions, suggesting that these activities are not entirely independent. This work provides a new perspective on the interaction between APE1 redox and DNA repair activity in inflammatory response modulation and transcription.

Cyclic alternation of quiet and active sleep states in the octopus.

Previous observations suggest the existence of 'Active sleep' in cephalopods. To investigate in detail the behavioral structure of cephalopod sleep, we video-recorded four adult specimens of Octopus insularis and quantified their distinct states and transitions. Changes in skin color and texture and movements of eyes and mantle were assessed using automated image processing tools, and arousal threshold was measured using sensory stimulation. Two distinct states unresponsive to stimulation occurred in tandem. The first was a 'Quiet sleep' state with uniformly pale skin, closed pupils, and long episode durations (median 415.2 s). The second was an 'Active sleep' state with dynamic skin patterns of color and texture, rapid eye movements, and short episode durations (median 40.8 s). 'Active sleep' was periodic (60% of recurrences between 26 and 39 min) and occurred mostly after 'Quiet sleep' (82% of transitions). These results suggest that cephalopods have an ultradian sleep cycle analogous to that of amniotes.

The Shared Use of Extended Phenotypes Increases the Fitness of Simulated Populations.

Extended phenotypes are manifestations of genes that occur outside of the organism that possess those genes. In spite of their widespread occurrence, the role of extended phenotypes in evolutionary biology is still a matter of debate. Here, we explore the indirect effects of extended phenotypes, especially their shared use, in the fitness of simulated individuals and populations. A computer simulation platform was developed in which different populations were compared regarding their ability to produce, use, and share extended phenotypes. Our results show that populations that produce and share extended phenotypes outrun populations that only produce them. A specific parameter in the simulations, a bonus for sharing extended phenotypes among conspecifics, has a more significant impact in defining which population will prevail. All these findings strongly support the view, postulated by the extended fitness hypothesis (EFH) that extended phenotypes play a significant role at the population level and their shared use increases population fitness. Our simulation platform is available at https://github.com/guilherme-araujo/gsop-dist.

Exome Sequencing of Native Populations From the Amazon Reveals Patterns on the Peopling of South America.

Studies on the peopling of South America have been limited by the paucity of sequence data from Native Americans, especially from the east part of the Amazon region. Here, we investigate the whole exome variation from 58 Native American individuals (eight different populations) from the Amazon region and draw insights into the peopling of South America. By using the sequence data generated here together with data from the public domain, we confirmed a strong genetic distinction between Andean and Amazonian populations. By testing distinct demographic models, our analysis supports a scenario of South America occupation that involves migrations along the Pacific and Atlantic coasts. Occupation of the southeast part of South America would involve migrations from the north, rather than from the west of the continent.

XPA deficiency affects the ubiquitin-proteasome system function.

Xeroderma pigmentosum complementation group A (XPA), is defective in xeroderma pigmentosum patients, causing pre-disposition to skin cancer and neurological abnormalities, which is not well understood. Here, we analyzed the XPA-deficient cells transcriptional profile under oxidative stress. The imbalance in of ubiquitin-proteasome system (UPS) gene expression was observed in XPA-deficient cells and the involvement of nuclear factor erythroid 2-related factor-2 (NFE2L2) was indicated. Co-immunoprecipitation assays showed the interaction between XPA, apurinic-apyrimidinic endonuclease 1 (APE1) and NFE2L2 proteins. Decreased NFE2L2 protein expression and proteasome activity was also observed in XPA-deficient cells. The data suggest the involvement of the growth arrest and DNA-damage-inducible beta (GADD45ß) in NFE2L2 functions. Similar results were obtained in xpa-1 (RNAi) Caenorhabditis elegans suggesting the conservation of XPA and NFE2L2 interactions. In conclusion, stress response activation occurs in XPA-deficient cells under oxidative stress; however, these cells fail to activate the UPS cytoprotective response, which may contribute to XPA patient's phenotypes.

Assessment of somatic mutations in urine and plasma of Wilms tumor patients.

Tumor DNA has been detected in body fluids of cancer patients. Somatic tumor mutations are being used as biomarkers in body fluids to monitor chemotherapy response as a minimally invasive tool. In this study, we evaluated the potential of tracking somatic mutations in free DNA of plasma and urine collected from Wilms tumor (WT) patients for monitoring treatment response. Wilms tumor is a pediatric renal tumor resulting from cell differentiation errors during nephrogenesis. Its mutational repertoire is not completely defined. Thus, for identifying somatic mutations from tumor tissue DNA, we screened matched tumor/leukocyte DNAs using either a panel containing 16 WT-associated genes or whole-exome sequencing (WES). The identified somatic tumor mutations were tracked in urine and plasma DNA collected before, during and after treatment. At least one somatic mutation was identified in five out of six WT tissue samples analyzed. Somatic mutations were detected in body fluids before treatment in all five patients (three patients in urine, three in plasma, and one in both body fluids). In all patients, a decrease of the variant allele fraction of somatic mutations was observed in body fluids during neoadjuvant chemotherapy. Interestingly, the persistence of somatic mutations in body fluids was in accordance with clinical parameters. For one patient who progressed to death, it persisted in high levels in serial body fluid samples during treatment. For three patients without disease progression, somatic mutations were not consistently detected in samples throughout monitoring. For one patient with bilateral disease, a somatic mutation was detected at low levels with no support of clinical manifestation. Our results demonstrated the potential of tracking somatic mutations in urine and plasma DNA as a minimally invasive tool for monitoring WT patients. Additional investigation is needed to check the clinical value of insistent somatic mutations in body fluids.

Distribution and linkage disequilibrium of the enhancer SNP rs5758550 among Latin American populations: influence of continental ancestry.

OBJECTIVES: A single nucleotide polymorphism (SNP), rs5758550, in a critical enhancer region downstream of the CYP2D6 promoter was proposed to modulate CYP2D6 activity, depending on its linkage disequilibrium (LD) with the common CYP2D6 SNP, rs16947. We examined the influence of individual biogeographical ancestry on the frequency distribution of rs5758550 and its LD with rs16947 in Latin American populations. We then inferred the impact of rs5758550 on the predictive accuracy of CYP2D6 metabolizer status based on CYP2D6 haplotypes. METHODS: The study cohorts consisted of the Admixed American (AMR) superpopulation of the 1000 Genomes Project (n = 347) plus an admixed Brazilian (BR) cohort (N = 224). Individual proportions of Native, African and European ancestry estimated by ADMIXTURE analysis, were used to design four sub-cohorts, in which one of the three ancestral roots predominated largely (>6 fold) over the other two: AMR-NAT and AMR-EUR, comprised 80 AMR individuals each, with >70% Native or >70% European ancestry, BR-EUR and BR-AFR comprised Brazilians with >90% European (n = 80) or >70% African ancestry (n = 64), respectively. CYP2D6 haplotypes were inferred based on 10 commonly reported CYPD6 variants with or without addition of the enhancer rs5758550 SNP, pairwise LD was assessed by the R parameter, and activity scores were used to infer CYP2D6 metabolizer status. RESULTS: Minor allele frequency (MAF) of all CYP2D6 SNPs, except the rare (<0.02) rs5030656 and rs35742688, differed significantly across sub-cohorts, whereas no difference was observed for rs5758550. The R values for LD between rs5758550 and rs16947 ranged from 0.15 (BR-AFR) to 0.85 (AMR-NAT), with intermediate values in the predominantly European sub-cohorts (0.34-0.67). As a consequence, distribution of CYP2D6 haplotypes containing the rs16947 SNP plus rs5758550 wild-type (A) or variant (G) allele differed markedly across sub-cohorts. Comparison of the CYP2D6 activity scores assigned to the wild-type (CYP2D6*1) and the rs16947-containing haplotypes with or without inclusion of rs5758550, showed that knowledge of the rs5758550 genotype has negligible impact on predicted CYP2D6 phenotypes in AMR-EUR and AMR-NAT, but affects prediction in 10.7 and 21.6% of BR-EUR and BR-AFR individuals, respectively. CONCLUSION: Collectively, the present results reveal potential pharmacogenomic (PGx) implications of the population diversity in Latin America, affecting a major drug-metabolizing pathway. Thus, the influence of enhancer rs5758550 on assignment of CYP2D6 metabolic phenotypes varies markedly, according to the individual proportions of Native, European and African ancestry. This conclusion reinforces the notion that extrapolation of PGx data across the heterogeneous Latin American is risky, if not inappropriate.

neoANT-HILL: an integrated tool for identification of potential neoantigens.

BACKGROUND: Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. RESULTS: We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity. CONCLUSION: neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available through github at https://github.com/neoanthill/neoANT-HILL.

Analysis of the microarray gene expression for breast cancer progression after the application modified logistic regression.

Methods based around statistics and linear algebra have been increasingly used in attempts to address emerging questions in microarray literature. Microarray technology is a long-used tool in the global analysis of gene expression, allowing for the simultaneous investigation of hundreds or thousands of genes in a sample. It is characterized by a low sample size and a large feature number created a non-square matrix, and by the incomplete rank, that can generate countless more solution in classifiers. To avoid the problem of the 'curse of dimensionality' many authors have performed feature selection or reduced the size of data matrix. In this work, we introduce a new logistic regression-based model to classify breast cancer tumor samples based on microarray expression data, including all features of gene expression and without reducing the microarray data matrix. If the user still deems it necessary to perform feature reduction, it can be done after the application of the methodology, still maintaining a good classification. This methodology allowed the correct classification of breast cancer sample data sets from Gene Expression Omnibus (GEO) data series GSE65194, GSE20711, and GSE25055, which contain the microarray data of said breast cancer samples. Classification had a minimum performance of 80% (sensitivity and specificity), and explored all possible data combinations, including breast cancer subtypes. This methodology highlighted genes not yet studied in breast cancer, some of which have been observed in Gene Regulatory Networks (GRNs). In this work we examine the patterns and features of a GRN composed of transcription factors (TFs) in MCF-7 breast cancer cell lines, providing valuable information regarding breast cancer. In particular, some genes whose αi ∗ associated parameter values revealed extreme positive and negative values, and, as such, can be identified as breast cancer prediction genes. We indicate that the PKN2, MKL1, MED23, CUL5 and GLI genes demonstrate a tumor suppressor profile, and that the MTR, ITGA2B, TELO2, MRPL9, MTTL1, WIPI1, KLHL20, PI4KB, FOLR1 and SHC1 genes demonstrate an oncogenic profile. We propose that these may serve as potential breast cancer prediction genes, and should be prioritized for further clinical studies on breast cancer. This new model allows for the assignment of values to the αi ∗ parameters associated with gene expression. It was noted that some αi ∗ parameters are associated with genes previously described as breast cancer biomarkers, as well as other genes not yet studied in relation to this disease.

Essential Saccharomyces cerevisiae genome instability suppressing genes identify potential human tumor suppressors.

Gross Chromosomal Rearrangements (GCRs) play an important role in human diseases, including cancer. Although most of the nonessential Genome Instability Suppressing (GIS) genes in Saccharomyces cerevisiae are known, the essential genes in which mutations can cause increased GCR rates are not well understood. Here 2 S. cerevisiae GCR assays were used to screen a targeted collection of temperature-sensitive mutants to identify mutations that caused increased GCR rates. This identified 94 essential GIS (eGIS) genes in which mutations cause increased GCR rates and 38 candidate eGIS genes that encode eGIS1 protein-interacting or family member proteins. Analysis of TCGA data using the human genes predicted to encode the proteins and protein complexes implicated by the S. cerevisiae eGIS genes revealed a significant enrichment of mutations affecting predicted human eGIS genes in 10 of the 16 cancers analyzed.

Influence of BRCA1 Germline Mutations in the Somatic Mutational Burden of Triple-Negative Breast Cancer.

The majority of the hereditary triple-negative breast cancers (TNBCs) are associated with BRCA1 germline mutations. Nevertheless, the understanding of the role of BRCA1 deficiency in the TNBC tumorigenesis is poor. In this sense, we performed whole-exome sequencing of triplet samples (leucocyte, tumor, and normal-adjacent breast tissue) for 10 cases of early-onset TNBC, including 5 hereditary (with BRCA1 germline pathogenic mutation) and 5 sporadic (with no BRCA1 or BRCA2 germline pathogenic mutations), for assessing the somatic mutation repertoire. Protein-affecting somatic mutations were identified for both mammary tissues, and Ingenuity Pathway Analysis was used to investigate gene interactions. BRCA1 and RAD51C somatic promoter methylation in tumor samples was also investigated by bisulfite sequencing. Sporadic tumors had higher proportion of driver mutations (≥25% allele frequency) than BRCA1 hereditary tumors, whereas no difference was detected in the normal breast samples. Distinct gene networks were obtained from the driver genes in each group. The Cancer Genome Atlas data analysis of TNBC classified as hereditary and sporadic reinforced our findings. The data presented here indicate that in the absence of BRCA1 germline mutations, a higher number of driver mutations are required for tumor development and that different defective processes are operating in the tumorigenesis of hereditary and sporadic TNBC in young women.

On the Impact of the Pangenome and Annotation Discrepancies While Building Protein Sequence Databases for Bacteria Proteogenomics.

In proteomics, peptide information within mass spectrometry (MS) data from a specific organism sample is routinely matched against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or genetically poorly characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for 10 different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bordetella pertussis generated very complex databases even having low pangenomic complexity. We further tested database performance by using MS data from eight clinical strains from M. tuberculosis, and from two published datasets from Staphylococcus aureus. We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.

A comprehensive analysis of core polyadenylation sequences and regulation by microRNAs in a set of cancer predisposition genes.

Two core polyadenylation elements (CPE) located in the 3' untranslated region of eukaryotic pre-mRNAs play an essential role in their processing: the polyadenylation signal (PAS) AAUAAA and the cleavage site (CS), preferentially a CA dinucleotide. Herein, we characterized PAS and CS sequences in a set of cancer predisposition genes (CPGs) and performed an in silico investigation of microRNAs (miRNAs) regulation to identify potential tumor-suppressive and oncogenic miRNAs. NCBI and alternative polyadenylation databases were queried to characterize CPE sequences in 117 CPGs, including 81 and 17 known tumor suppressor genes and oncogenes, respectively. miRNA-mediated regulation analysis was performed using predicted and validated data sources. Based on NCBI analyses, we did not find an established PAS in 21 CPGs, and verified that the majority of PAS already described (74.4%) had the canonical sequence AAUAAA. Interestingly, "AA" dinucleotide was the most common CS (37.5%) associated with this set of genes. Approximately 90% of CPGs exhibited evidence of alternative polyadenylation (more than one functional PAS). Finally, the mir-192 family was significantly overrepresented as regulator of tumor suppressor genes (P < 0.01), which suggests a potential oncogenic function. Overall, this study provides a landscape of CPE in CPGs, which might be useful in development of future molecular analyses covering these frequently neglected regulatory sequences.