6 research outputs found

    Genotype and phenotype landscape of MEN2 in 554 medullary thyroid cancer patients: the BrasMEN study

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    Multiple endocrine neoplasia type 2 (MEN2) is an autosomal dominant genetic disease caused by RET gene germline mutations that is characterized by medullary thyroid carcinoma (MTC) associated with other endocrine tumors. Several reports have demonstrated that the RET mutation profile may vary according to the geographical area. In this study, we collected clinical and molecular data from 554 patients with surgically confirmed MTC from 176 families with MEN2 in 18 different Brazili an centers to compare the type and prevalence of RET mutations with those from other countries. The most frequent mutations, classified by the number of families affected, occur in codon 634, exon 11 (76 families), followed by codon 918, exon 16 (34 families: 26 with M918T and 8 with M918V) and codon 804, exon 14 (22 families: 15 with V804M and 7 with V804L). When compared with other major published series from Europe, there are several similarities and some differences. While the mutations in codons C618, C620, C630, E768 and S891 present a similar prevalence, some mutations have a lower prevalence in Brazil, and others are found mainly in Brazil (G533C and M918V). These results reflect the singular proportion of European, Amerindian and African ancestries in the Brazilian mosaic genome83289298CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DO RIO GRANDE DO SUL - FAPERGSSem informaçãoSem informação2006/60402-1; 2010/51547-1; 2013/01476-9; 2014/06570-6; 2009/50575-4; 2010/51546-5; 2012/21942-116/2551-0000482-

    XAF1 as a modifier of p53 function and cancer susceptibility

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    Cancer risk is highly variable in carriers of the common TP53-R337H founder allele, possibly due to the influence of modifier genes. Whole-genome sequencing identified a variant in the tumor suppressor XAF1 (E134*/Glu134Ter/rs146752602) in a subset of R337H carriers. Haplotype-defining variants were verified in 203 patients with cancer, 582 relatives, and 42,438 newborns. The compound mutant haplotype was enriched in patients with cancer, conferring risk for sarcoma (P = 0.003) and subsequent malignancies (P = 0.006). Functional analyses demonstrated that wild-type XAF1 enhances transactivation of wild-type and hypomorphic TP53 variants, whereas XAF1-E134* is markedly attenuated in this activity. We propose that cosegregation of XAF1-E134* and TP53-R337H mutations leads to a more aggressive cancer phenotype than TP53-R337H alone, with implications for genetic counseling and clinical management of hypomorphic TP53 mutant carriers.Fil: Pinto, Emilia M.. St. Jude Children's Research Hospital; Estados UnidosFil: Figueiredo, Bonald C.. Instituto de Pesquisa PelĂ© Pequeno Principe; BrasilFil: Chen, Wenan. St. Jude Children's Research Hospital; Estados UnidosFil: Galvao, Henrique C.R.. Hospital de CĂąncer de Barretos; BrasilFil: Formiga, Maria Nirvana. A.c.camargo Cancer Center; BrasilFil: Fragoso, Maria Candida B.V.. Universidade de Sao Paulo; BrasilFil: Ashton Prolla, Patricia. Universidade Federal do Rio Grande do Sul; BrasilFil: Ribeiro, Enilze M.S.F.. Universidade Federal do ParanĂĄ; BrasilFil: Felix, Gabriela. Universidade Federal da Bahia; BrasilFil: Costa, Tatiana E.B.. Hospital Infantil Joana de Gusmao; BrasilFil: Savage, Sharon A.. National Cancer Institute; Estados UnidosFil: Yeager, Meredith. National Cancer Institute; Estados UnidosFil: Palmero, Edenir I.. Hospital de CĂąncer de Barretos; BrasilFil: Volc, Sahlua. Hospital de CĂąncer de Barretos; BrasilFil: Salvador, Hector. Hospital Sant Joan de Deu Barcelona; EspañaFil: Fuster Soler, Jose Luis. Hospital ClĂ­nico Universitario Virgen de la Arrixaca; EspañaFil: Lavarino, Cinzia. Hospital Sant Joan de Deu Barcelona; EspañaFil: Chantada, Guillermo Luis. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentina. St. Jude Children's Research Hospital; Estados UnidosFil: Vaur, Dominique. Comprehensive Cancer Center François Baclesse; FranciaFil: Odone Filho, Vicente. Universidade de Sao Paulo; BrasilFil: BrugiĂšres, Laurence. Institut de Cancerologie Gustave Roussy; FranciaFil: Else, Tobias. University of Michigan; Estados UnidosFil: Stoffel, Elena M.. University of Michigan; Estados UnidosFil: Maxwell, Kara N.. University of Pennsylvania; Estados UnidosFil: Achatz, Maria Isabel. Hospital Sirio-libanĂȘs; BrasilFil: Kowalski, Luis. A.c.camargo Cancer Center; BrasilFil: De Andrade, Kelvin C.. National Cancer Institute; Estados UnidosFil: Pappo, Alberto. St. Jude Children's Research Hospital; Estados UnidosFil: Letouze, Eric. Centre de Recherche Des Cordeliers; FranciaFil: Latronico, Ana Claudia. Universidade de Sao Paulo; BrasilFil: Mendonca, Berenice B.. Universidade de Sao Paulo; BrasilFil: Almeida, Madson Q.. Universidade de Sao Paulo; BrasilFil: Brondani, Vania B.. Universidade de Sao Paulo; BrasilFil: Bittar, Camila M.. Universidade Federal do Rio Grande do Sul; BrasilFil: Soares, Emerson W.S.. Hospital Do CĂąncer de Cascavel; BrasilFil: Mathias, Carolina. Universidade Federal do ParanĂĄ; BrasilFil: Ramos, Cintia R.N.. Hospital de CĂąncer de Barretos; BrasilFil: Machado, Moara. National Cancer Institute; Estados UnidosFil: Zhou, Weiyin. National Cancer Institute; Estados UnidosFil: Jones, Kristine. National Cancer Institute; Estados UnidosFil: Vogt, Aurelie. National Cancer Institute; Estados UnidosFil: Klincha, Payal P.. National Cancer Institute; Estados UnidosFil: Santiago, Karina M.. A.c.camargo Cancer Center; BrasilFil: Komechen, Heloisa. Instituto de Pesquisa PelĂ© Pequeno Principe; BrasilFil: Paraizo, Mariana M.. Instituto de Pesquisa PelĂ© Pequeno Principe; BrasilFil: Parise, Ivy Z.S.. Instituto de Pesquisa PelĂ© Pequeno Principe; BrasilFil: Hamilton, Kayla V.. St. Jude Children's Research Hospital; Estados UnidosFil: Wang, Jinling. St. Jude Children's Research Hospital; Estados UnidosFil: Rampersaud, Evadnie. St. Jude Children's Research Hospital; Estados UnidosFil: Clay, Michael R.. St. Jude Children's Research Hospital; Estados UnidosFil: Murphy, Andrew J.. St. Jude Children's Research Hospital; Estados UnidosFil: Lalli, Enzo. Institut de Pharmacologie MolĂ©culaire et Cellulaire; FranciaFil: Nichols, Kim E.. St. Jude Children's Research Hospital; Estados UnidosFil: Ribeiro, Raul C.. St. Jude Children's Research Hospital; Estados UnidosFil: Rodriguez-Galindo, Carlos. St. Jude Children's Research Hospital; Estados UnidosFil: Korbonits, Marta. Queen Mary University of London; Reino UnidoFil: Zhang, Jinghui. St. Jude Children's Research Hospital; Estados UnidosFil: Thomas, Mark G.. Colegio Universitario de Londres; Reino UnidoFil: Connelly, Jon P.. St. Jude Children's Research Hospital; Estados UnidosFil: Pruett-Miller, Shondra. St. Jude Children's Research Hospital; Estados UnidosFil: Diekmann, Yoan. Colegio Universitario de Londres; Reino UnidoFil: Neale, Geoffrey. St. Jude Children's Research Hospital; Estados UnidosFil: Wu, Gang. St. Jude Children's Research Hospital; Estados UnidosFil: Zambetti, Gerard P.. St. Jude Children's Research Hospital; Estados Unido

    Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

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    The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

    Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

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    Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe

    Enteric methane mitigation strategies for ruminant livestock systems in the Latin America and Caribbean region: a meta-analysis.

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    Abstract: Latin America and Caribbean (LAC) is a developing region characterized for its importance for global food security,producing 23 and 11% of the global beef and milk production, respectively. The region?s ruminant livestock sector however, is under scrutiny on environmental grounds due to its large contribution to enteric methane (CH4) emissions and influence on global climate change. Thus, the identification of effective CH4 mitigation strategies which do not compromise animal performance is urgently needed, especially in context of the Sustainable Development Goals (SDG) defined in the Paris Agreement of the United Nations. Therefore, the objectives of the current study were to: 1) collate a database of individual sheep, beef and dairy cattle records from enteric CH4 emission studies conducted in the LAC region, and 2) perform a meta-analysis to identify feasible enteric CH4 mitigation strategies, which do not compromise animal performance. After outlier?s removal, 2745 animal records (65% of the original data) from 103 studies were retained (from 2011 to 2021) in the LAC database. Potential mitigation strategies were classified into three main categories (i.e., animal breeding, dietary, and rumen manipulation) and up to three subcategories, totaling 34 evaluated strategies. A random effects model weighted by inverse variance was used (Comprehensive Meta-Analysis V3.3.070). Six strategies decreased at least one enteric CH4 metric and simultaneously increased milk yield (MY; dairy cattle) or average daily gain (ADG; beef cattle and sheep). The breed composition F1 Holstein ×Gyr decreased CH4 emission per MY (CH4IMilk) while increasing MY by 99%. Adequate strategies of grazing management under continuous and rotational stocking decreased CH4 emission per ADG (CH4IGain) by 22 and 35%, while increasing ADG by 22 and 71%, respectively. Increased dietary protein concentration, and increased concentrate level through cottonseed meal inclusion, decreased CH4IMilk and CH4IGain by 10 and 20% and increased MY and ADG by 12 and 31%, respectively. Lastly, increased feeding level decreased CH4IGain by 37%, while increasing ADG by 171%. The identified effective mitigation strategies can be adopted by livestock producers according to their specific needs and aid LAC countries in achieving SDG as defined in the Paris Agreement
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