22 research outputs found

    A revised multi-tissue, multi-platform epigenetic clock model for methylation array data

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    Epigenetic changes have long been investigated in association with the process of aging in humans. DNA methylation has been extensively used as a surrogate measure of biological age and correlations between "DNA methylation age" and chronological age have been established. A wide variety of epigenetic clocks has been designed to predict age in different tissues and on data obtained from different methylation platforms. We aimed to extend the scope of one of the most used epigenetic age predictors, the Horvath pan-tissue epigenetic clock, to improve its accuracy on data acquired from the latest Illumina methylation platform (BeadChip EPIC). We present three models trained on close to 6,000 samples of various source tissues and platforms and demonstrate their superior performance (Pearson correlation (r) = 0.917-0.921 and median absolute error (MAE) = 3.60-3.85 years) compared to the original model (r= 0.880 and MAE =5.13 years) on a test set of more than 4,000 samples. The gain in accuracy was especially pronounced on EPIC array data (r= 0.89, MAE = 3.54 years vs. r= 0.83, MAE = 6.09 years), which was not available at the time when the original model was created. Our updated epigenetic clocks predict chronological age with great precision in an independent test cohort of samples on multiple tissue types and data platforms. Two of the three presented models exclusively use the covariates of the original epigenetic clock, albeit with different coefficients, allowing for straightforward adaptation for prefiltered datasets previously processed with the original predictor

    Genomic Landscape of Normal and Breast Cancer Tissues in a Hungarian Pilot Cohort

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    A limited number of studies have focused on the mutational landscape of breast cancer in different ethnic populations within Europe and compared the data with other ethnic groups and databases. We performed whole-genome sequencing of 63 samples from 29 Hungarian breast cancer patients. We validated a subset of the identified variants at the DNA level using the Illumina TruSight Oncology (TSO) 500 assay. Canonical breast-cancer-associated genes with pathogenic germline mutations were CHEK2 and ATM. Nearly all the observed germline mutations were as frequent in the Hungarian breast cancer cohort as in independent European populations. The majority of the detected somatic short variants were single-nucleotide polymorphisms (SNPs), and only 8% and 6% of them were deletions or insertions, respectively. The genes most frequently affected by somatic mutations were KMT2C (31%), MUC4 (34%), PIK3CA (18%), and TP53 (34%). Copy number alterations were most common in the NBN, RAD51C, BRIP1, and CDH1 genes. For many samples, the somatic mutational landscape was dominated by mutational processes associated with homologous recombination deficiency (HRD). Our study, as the first breast tumor/normal sequencing study in Hungary, revealed several aspects of the significantly mutated genes and mutational signatures, and some of the copy number variations and somatic fusion events. Multiple signs of HRD were detected, highlighting the value of the comprehensive genomic characterization of breast cancer patient populations

    Loss of BRCA1 or BRCA2 markedly increases the rate of base substitution mutagenesis and has distinct effects on genomic deletions

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    Loss-of-function mutations in the BRCA1 and BRCA2 genes increase the risk of cancer. Owing to their function in homologous recombination repair, much research has focused on the unstable genomic phenotype of BRCA1/2 mutant cells manifest mainly as large-scale rearrangements. We used whole-genome sequencing of multiple isogenic chicken DT40 cell clones to precisely determine the consequences of BRCA1/2 loss on all types of genomic mutagenesis. Spontaneous base substitution mutation rates increased sevenfold upon the disruption of either BRCA1 or BRCA2, and the arising mutation spectra showed strong and specific correlation with a mutation signature associated with BRCA1/2 mutant tumours. To model endogenous alkylating damage, we determined the mutation spectrum caused by methyl methanesulfonate (MMS), and showed that MMS also induces more base substitution mutations in BRCA1/2-deficient cells. Spontaneously arising and MMS-induced insertion/deletion mutations and large rearrangements were also more common in BRCA1/2 mutant cells compared with the wild-type control. A difference in the short deletion phenotypes of BRCA1 and BRCA2 suggested distinct roles for the two proteins in the processing of DNA lesions, as BRCA2 mutants contained more short deletions, with a wider size distribution, which frequently showed microhomology near the breakpoints resembling repair by non-homologous end joining. An increased and prolonged gamma-H2AX signal in MMS-treated BRCA1/2 cells suggested an aberrant processing of stalled replication forks as the cause of increased mutagenesis. The high rate of base substitution mutagenesis demonstrated by our experiments is likely to significantly contribute to the oncogenic effect of the inactivation of BRCA1 or BRCA2.Oncogene advance online publication, 25 July 2016; doi:10.1038/onc.2016.243. © 2016 The Author(s

    Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples

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    Systematic monitoring of SARS-CoV-2 co-infections between different lineages and assessing the risk of intra-host recombinant emergence are crucial for forecasting viral evolution. Here we present a comprehensive analysis of more than 2 million SARS-CoV-2 raw read datasets submitted to the European COVID-19 Data Portal to identify co-infections and intra-host recombination. Co-infection was observed in 0.35% of the investigated cases. Two independent procedures were implemented to detect intra-host recombination. We show that sensitivity is predominantly determined by the density of lineage-defining mutations along the genome, thus we used an expanded list of mutually exclusive defining mutations of specific variant combinations to increase statistical power. We call attention to multiple challenges rendering recombinant detection difficult and provide guidelines for the reduction of false positives arising from chimeric sequences produced during PCR amplification. Additionally, we identify three recombination hotspots of Delta – Omicron BA.1 intra-host recombinants.</p

    Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples

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    Systematic monitoring of SARS-CoV-2 co-infections between different lineages and assessing the risk of intra-host recombinant emergence are crucial for forecasting viral evolution. Here we present a comprehensive analysis of more than 2 million SARS-CoV-2 raw read datasets submitted to the European COVID-19 Data Portal to identify co-infections and intra-host recombination. Co-infection was observed in 0.35% of the investigated cases. Two independent procedures were implemented to detect intra-host recombination. We show that sensitivity is predominantly determined by the density of lineage-defining mutations along the genome, thus we used an expanded list of mutually exclusive defining mutations of specific variant combinations to increase statistical power. We call attention to multiple challenges rendering recombinant detection difficult and provide guidelines for the reduction of false positives arising from chimeric sequences produced during PCR amplification. Additionally, we identify three recombination hotspots of Delta – Omicron BA.1 intra-host recombinants.</p

    A genetikai adatok szerepe a járványok elleni küzdelemben = Genetic data in the fight against pandemics

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    A COVID–19-járvány alatt bizonyossá vált, hogy az adattudományok, az adatok gyors megosztása és a nemzetközi összefogás a hatékony járványkezelés kulcsfontosságú eszközei. A járvány előtt létrejött Újonnan Felbukkanó fertőző betegségek Obszervatóriuma (Versatile Emerging infectious disease Observatory, VEO) nevű nemzetközi konzorcium célja egy olyan monitorozó rendszer kiépítése, amely a potenciálisan veszélyes kórokozókat még az előtt azonosítja, mielőtt azok tömeges megbetegedéseket okoznának, lehetőséget adva ezzel a gyors reagálásra. A járványok megelőzé-sére és kezelésére létrejött nemzetközi együttműködésekben, így a VEO-ban is a kórokozók, vagy a fertőzésnek kitett személyek genetikai szekvencia adatai kiemelkedő fontosságúak. Az ilyen típusú adatok kezelésével kapcsolatban az Európai Unióban többek között a Nagojai Jegyzőkönyv és a GDPR fogalmaz meg elveket, szabályokat

    The Driverless Triple-Wild-Type (BRAF, RAS, KIT) Cutaneous Melanoma: Whole Genome Sequencing Discoveries

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    The genetic makeup of the triple-wild-type melanoma (BRAF, NRAS and NF1) has been known for some time, but those studies grouped together rare histopathological versions with common ones, as well as mucosal and even uveal ones. Here we used whole genome sequencing to genetically characterize the triple-wild-type melanoma (TWM), termed here as BRAF, RAS and KIT wild type (the most frequent oncogenic drivers of skin melanoma), using the most common histological forms and excluding rare ones. All these tumors except one were clearly induced by UV based on the mutational signature. The tumor mutational burden was low in TWM, except in the NF1 mutant forms, and a relatively high frequency of elevated LOH scores suggested frequent homologue recombination deficiency, but this was only confirmed by the mutation signature in one case. Furthermore, all these TWMs were microsatellite-stabile. In this driverless setting, we revealed rare oncogenic drivers known from melanoma or other cancer types and identified rare actionable tyrosine kinase mutations in NTRK1, RET and VEGFR1. Mutations of TWM identified genes involved in antitumor immunity (negative and positive predictors of immunotherapy), Ca++ and BMP signaling. The two regressed melanomas of this cohort shared a 17-gene mutation signature, containing genes involved in antitumor immunity and several cell surface receptors. Even with this comprehensive genomic approach, a few cases remained driverless, suggesting that unrecognized drivers are hiding among passenger mutations

    Genomic Landscape of Normal and Breast Cancer Tissues in a Hungarian Pilot Cohort

    Get PDF
    A limited number of studies have focused on the mutational landscape of breast cancer in different ethnic populations within Europe and compared the data with other ethnic groups and databases. We performed whole-genome sequencing of 63 samples from 29 Hungarian breast cancer patients. We validated a subset of the identified variants at the DNA level using the Illumina TruSight Oncology (TSO) 500 assay. Canonical breast-cancer-associated genes with pathogenic germline mutations were CHEK2 and ATM. Nearly all the observed germline mutations were as frequent in the Hungarian breast cancer cohort as in independent European populations. The majority of the detected somatic short variants were single-nucleotide polymorphisms (SNPs), and only 8% and 6% of them were deletions or insertions, respectively. The genes most frequently affected by somatic mutations were KMT2C (31%), MUC4 (34%), PIK3CA (18%), and TP53 (34%). Copy number alterations were most common in the NBN, RAD51C, BRIP1, and CDH1 genes. For many samples, the somatic mutational landscape was dominated by mutational processes associated with homologous recombination deficiency (HRD). Our study, as the first breast tumor/normal sequencing study in Hungary, revealed several aspects of the significantly mutated genes and mutational signatures, and some of the copy number variations and somatic fusion events. Multiple signs of HRD were detected, highlighting the value of the comprehensive genomic characterization of breast cancer patient populations

    Expression patterns and prognostic relevance of subtype-specific transcription factors in surgically resected small cell lung cancer : an international multicenter study

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    The tissue distribution and prognostic relevance of subtype-specific proteins (ASCL1, NEUROD1, POU2F3, YAP1) present an evolving area of research in small cell lung cancer (SCLC). The expression of subtype-specific transcription factors and P53 and RB1 proteins were measured by immunohistochemistry (IHC) in 386 surgically resected SCLC samples. Correlations between subtype-specific proteins and in vitro efficacy of various therapeutic agents were investigated by proteomics and cell viability assays in 26 human SCLC cell lines. Besides SCLC-A (ASCL1-dominant), SCLC-AN (combined ASCL1/NEUROD1), SCLC-N (NEUROD1-dominant) and SCLC-P (POU2F3-dominant), IHC and cluster analyses identified a quadruple-negative SCLC subtype (SCLC-QN). No unique YAP1-subtype was found. The highest overall survival rates were associated with non-neuroendocrine subtypes (SCLC-P and SCLC-QN) and the lowest with neuroendocrine subtypes (SCLC-A, SCLC-N, SCLC-AN). In univariate analyses, high ASCL1 expression was associated with poor prognosis and high POU2F3 expression with good prognosis. Notably, high ASCL1 expression influenced survival outcomes independently of other variables in a multivariate model. High POU2F3 and YAP1 protein abundances correlated with sensitivity and resistance to standard-of-care chemotherapeutics, respectively. Specific correlation patterns were also found between the efficacy of targeted agents and subtype-specific protein abundances. In conclusion, we have investigated the clinicopathological relevance of SCLC molecular subtypes in a large cohort of surgically resected specimens. Differential IHC expression of ASCL1, NEUROD1 and POU2F3 defines SCLC subtypes. No YAP1-subtype can be distinguished by IHC. High POU2F3 expression is associated with improved survival in a univariate analysis, whereas elevated ASCL1 expression is an independent negative prognosticator. Proteomic and cell viability assays of human SCLC cell lines reveal distinct vulnerability profiles defined by transcription regulators
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