Genotoxicity Studies Performed in the Ecuadorian Population

Genotoxicity studies in Ecuador have been carried out during the past two decades. The focuses of the research were mainly the area of environmental issues, where the populations have been accidentally exposed to contaminants and the area of occupational exposure of individuals at the workplace. This paper includes studies carried out in the population of the Amazon region, a zone known for its rich biodiversity as well as for the ecological damage caused by oil spills and chemical sprayings whose consequences continue to be controversial. Additionally, we show the results of studies comprised of individuals occupationally exposed to toxic agents in two very different settings: flower plantation workers exposed to pesticide mixtures and X-ray exposure of hospital workers. The results from these studies confirm that genotoxicity studies can help evaluate current conditions and prevent further damage in the populations exposed to contaminants. As such, they are evidence of the need for biomonitoring employers at risk, stricter law enforcement regarding the use of pesticides, and increasingly conscientious oil extraction activities

Alterations and Chromosomal Variants in the Ecuadorian Population

Medical genetics is a field marked by fast progress. Even though it was at one point confined to a group of relatively rare diseases, today it has become a central component in the understanding of disorders and it is the subject of interest for all medical specialties. This paper, shares data on the chromosomal alterations and variations that have been diagnosed in Ecuadorian patients since 1998. A total of 2,636 individual cases have been analyzed by G-banding technique until February 2012. The present work shows this collection of data and the important findings that have appeared throughout these years in hopes that it can contribute to have a deeper understanding of the incidence of chromosomal aberrations and alterations in the Ecuadorian population

Relationship of an hRAD54 gene polymorphism (2290 C/T) in an Ecuadorian population with chronic myelogenous leukemia

The hRAD54 gene is a key member of the RAD52 epistasis group involved in repair of double-strand breaks (DSB) by homologous recombination (HR). Thus, alterations of the normal function of these genes could generate genetic instability, shifting the normal process of the cell cycle, leading the cells to develop into cancer. In this work we analyzed exon 18 of the hRAD54 gene, which has been previously reported by our group to carry a silent polymorphism, 2290 C/T (Ala730Ala), associated to meningiomas. We performed a PCR-SSCP method to detect the polymorphism in 239 samples including leukemia and normal control population. The results revealed that the 2290 C/T polymorphism has frequencies of 0.1 for the leukemia and 0.1 for the control group. These frequencies show no statistical differences. Additionally, we dissected the leukemia group in chronic myelogenous leukemia (CML) and acute lymphoblastic leukemia (ALL) to evaluate the polymorphism. The frequencies found in these subgroups were 0.14 for CML and 0.05 for ALL. We found statistically significant differences between CML patients and the control group (p < 0.05) but we did not find significant differences between ALL and the control group (p > 0.05). These results suggest a possible link between the 2290 C/T polymorphism of the hRAD54 gene and CML

Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis

[Abstract] Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein–protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as MMP2 and MMP9, and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.Instituto Carlos III; PI17/01826Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431G/0

Population history, phylogeography, and conservation genetics of the last Neotropical mega-herbivore, the lowland tapir (Tapirus terrestris)

<p>Abstract</p> <p>Background</p> <p>Understanding the forces that shaped Neotropical diversity is central issue to explain tropical biodiversity and inform conservation action; yet few studies have examined large, widespread species. Lowland tapir (<it>Tapirus terrrestris</it>, Perissodactyla, Tapiridae) is the largest Neotropical herbivore whose ancestors arrived in South America during the Great American Biotic Interchange. A Pleistocene diversification is inferred for the genus <it>Tapirus </it>from the fossil record, but only two species survived the Pleistocene megafauna extinction. Here, we investigate the history of lowland tapir as revealed by variation at the mitochondrial gene Cytochrome <it>b</it>, compare it to the fossil data, and explore mechanisms that could have shaped the observed structure of current populations.</p> <p>Results</p> <p>Separate methodological approaches found mutually exclusive divergence times for lowland tapir, either in the late or in the early Pleistocene, although a late Pleistocene divergence is more in tune with the fossil record. Bayesian analysis favored mountain tapir (<it>T. pinchaque</it>) paraphyly in relation to lowland tapir over reciprocal monophyly, corroborating the inferences from the fossil data these species are sister taxa. A coalescent-based analysis rejected a null hypothesis of allopatric divergence, suggesting a complex history. Based on the geographic distribution of haplotypes we propose (<it>i</it>) a central role for western Amazonia in tapir diversification, with a key role of the ecological gradient along the transition between Andean subcloud forests and Amazon lowland forest, and (<it>ii</it>) that the Amazon river acted as an barrier to gene flow. Finally, the branching patterns and estimates based on nucleotide diversity indicate a population expansion after the Last Glacial Maximum.</p> <p>Conclusions</p> <p>This study is the first examining lowland tapir phylogeography. Climatic events at the end of the Pleistocene, parapatric speciation, divergence along the Andean foothill, and role of the Amazon river, have similarly shaped the history of other taxa. Nevertheless further work with additional samples and loci is needed to improve our initial assessment. From a conservation perspective, we did not find a correspondence between genetic structure in lowland tapir and ecogeographic regions proposed to define conservation priorities in the Neotropics. This discrepancy sheds doubt into this scheme's ability to generate effective conservation planning for vagile species.</p

Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks

[Abstract] Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the prediction of proteins involved in this disease is a trending topic in drug design. This work is proposing accurate prediction classifer for BC proteins using six sets of protein sequence descriptors and 13 machine-learning methods. After using a univariate feature selection for the mix of fve descriptor families, the best classifer was obtained using multilayer perceptron method (artifcial neural network) and 300 features. The performance of the model is demonstrated by the area under the receiver operating characteristics (AUROC) of 0.980±0.0037, and accuracy of 0.936±0.0056 (3-fold cross-validation). Regarding the prediction of 4,504 cancer-associated proteins using this model, the best ranked cancer immunotherapy proteins related to BC were RPS27, SUPT4H1, CLPSL2, POLR2K, RPL38, AKT3, CDK3, RPS20, RASL11A and UBTD1; the best ranked metastasis driver proteins related to BC were S100A9, DDA1, TXN, PRNP, RPS27, S100A14, S100A7, MAPK1, AGR3 and NDUFA13; and the best ranked RNA-binding proteins related to BC were S100A9, TXN, RPS27L, RPS27, RPS27A, RPL38, MRPL54, PPAN, RPS20 and CSRP1. This powerful model predicts several BC-related proteins that should be deeply studied to fnd new biomarkers and better therapeutic targets. Scripts can be downloaded at https://github.com/muntisa/ neural-networks-for-breast-cancer-proteins.This work was supported by a) Universidad UTE (Ecuador), b) the Collaborative Project in Genomic Data Integration (CICLOGEN) PI17/01826 funded by the Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013-2016 and the European Regional Development Funds (FEDER) - “A way to build Europe”; c) the General Directorate of Culture, Education and University Management of Xunta de Galicia ED431D 2017/16 and “Drug Discovery Galician Network” Ref. ED431G/01 and the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23); d) the Spanish Ministry of Economy and Competitiveness for its support through the funding of the unique installation BIOCAI (UNLC08-1E-002, UNLC13-13-3503) and the European Regional Development Funds (FEDER) by the European Union; e) the Consolidation and Structuring of Competitive Research Units - Competitive Reference Groups (ED431C 2018/49), funded by the Ministry of Education, University and Vocational Training of the Xunta de Galicia endowed with EU FEDER funds; f) research grants from Ministry of Economy and Competitiveness, MINECO, Spain (FEDER CTQ2016-74881-P), Basque government (IT1045-16), and kind support of Ikerbasque, Basque Foundation for Science; and, g) Sociedad Latinoamericana de Farmacogenómica y Medicina Personalizada (SOLFAGEM)Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/49Gobierno Vasco; IT1045-1

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

[Abstract] Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic targets, a better understanding of BC molecular processes is required. Here we focused on elucidating the molecular hallmarks of BC heterogeneity and the oncogenic mutations involved in precision medicine that remains poorly defined. To fill this gap, we established an OncoOmics strategy that consists of analyzing genomic alterations, signaling pathways, protein-protein interactome network, protein expression, dependency maps in cell lines and patient-derived xenografts in 230 previously prioritized genes to reveal essential genes in breast cancer. As results, the OncoOmics BC essential genes were rationally filtered to 140. mRNA up-regulation was the most prevalent genomic alteration. The most altered signaling pathways were associated with basal-like and Her2-enriched molecular subtypes. RAC1, AKT1, CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, BCL2, CTNNB1, EGFR, CDK2, GRB2, MED1 and GATA3 were essential genes in at least three OncoOmics approaches. Drugs with the highest amount of clinical trials in phases 3 and 4 were paclitaxel, docetaxel, trastuzumab, tamoxifen and doxorubicin. Lastly, we collected ~3,500 somatic and germline oncogenic variants associated with 50 essential genes, which in turn had therapeutic connectivity with 73 drugs. In conclusion, the OncoOmics strategy reveals essential genes capable of accelerating the development of targeted therapies for precision oncology.Instituto de Salud Carlos III; PI17/0182

Cytogenetic and genomic analysis of a patient with turner syndrome and t(2;12): a case report

Background: Turner syndrome is a genetic disorder that afects women. It is caused by an absent or incomplete X chromosome, which can be presented in mosaicism or not. There are 12 cases of Turner syndrome patients who present structural alterations in autosomal chromosomes. Case presentation: The present case report describes a patient with a reciprocal, maternally inherited translocation between chromosomes 2 and 12 with a mosaicism of X monosomy 45,X,t(2;12)(p13;q24)[95]/46,XX,t(2;12)(p13;q24) [5]. Through genetic mapping arrays, altered genes in the patient were determined within the 23 chromosome pairs. These genes were associated with the patient’s clinical features using a bioinformatics tool Conclusion: To our knowledge, this is the frst case in which a translocation (2;12) is reported in a patient with Turner syndrome and confrmed by conventional cytogenetics, FISH and molecular genetics. Clinical features of our patient are closely related with the loss of one X chromosome, however mild intellectual disability can be likely explained by autosomal genes. The presence of familial translocations was a common fnding, thus emphasizing the need for familiar testing for further genetic counselling

A Quick Guide for Using Microsoft Onenote as an Electronic Laboratory Notebook

[Abstract] Scientific data recording and reporting systems are of a great interest for endorsing reproducibility and transparency practices among the scientific community. Current research generates large datasets that can no longer be documented using paper lab notebooks (PLNs). In this regard, electronic laboratory notebooks (ELNs) could be a promising solution to replace PLNs and promote scientific reproducibility and transparency. We previously analyzed five ELNs and performed two survey-based studies to implement an ELN in a biomedical research institute. Among the ELNs tested, we found that Microsoft OneNote presents numerous features related to ELN best functionalities. In addition, both surveyed groups preferred OneNote over a scientifically designed ELN (PerkinElmer Elements). However, OneNote remains a general note-taking application and has not been designed for scientific purposes. We therefore provide a quick guide to adapt OneNote to an ELN workflow that can also be adjusted to other nonscientific ELNs