Challenges of Congenital Heart Surgery in Brazil: It is Time to Designate Pediatric Congenital Heart Surgery Subspecialty.

Congenital heart disease (CHD) affects eight to ten out of every 1,000 births, resulting in approximately 23,057 new cases in Brazil in 2022. About one in four children with CHD requires surgery or other procedures in the first year of life, and it is expected that approximately 81% of these children with CHD will survive until at least 35 years of age. Professionals choosing to specialize in CHD surgery face numerous challenges, not only related to mastering surgical techniques and the complexity of the diseases but also to the lack of recognition by medical societies as a separate subspecialty. Furthermore, families face difficulties when access to services capable of providing treatment for these children. To address these challenges, it is essential to have specialized hospitals, qualified professionals, updated technologies, sustainable industry, appropriate financing, quality assessment systems, and knowledge generation. The path to excellence involves specialization across all involved parties. As we reflect on the importance of Pediatric Cardiovascular Surgery and Congenital Heart Diseases establishing themselves as a subspecialty of Cardiovascular Surgery, it is essential to look beyond our borders to countries like the United States of America and United Kingdom, where this evolution is already a reality. This autonomy has led to significant advancements in research, education, and patient care outcomes, establishing a care model. By following this path in Brazil, we not only align our practice with the highest international standards but also demonstrate our maturity and the ability to meet the specific needs of patients with CHD and those with acquired childhood heart disease.

Analytical validation of NeXT Personal®, an ultra-sensitive personalized circulating tumor DNA assay.

We describe the analytical validation of NeXT Personal®, an ultra-sensitive, tumor-informed circulating tumor DNA (ctDNA) assay for detecting residual disease, monitoring therapy response, and detecting recurrence in patients diagnosed with solid tumor cancers. NeXT Personal uses whole genome sequencing of tumor and matched normal samples combined with advanced analytics to accurately identify up to ~1,800 somatic variants specific to the patient's tumor. A personalized panel is created, targeting these variants and then used to sequence cell-free DNA extracted from patient plasma samples for ultra-sensitive detection of ctDNA. The NeXT Personal analytical validation is based on panels designed from tumor and matched normal samples from two cell lines, and from 123 patients across nine cancer types. Analytical measurements demonstrated a detection threshold of 1.67 parts per million (PPM) with a limit of detection at 95% (LOD95) of 3.45 PPM. NeXT Personal showed linearity over a range of 0.8 to 300,000 PPM (Pearson correlation coefficient = 0.9998). Precision varied from a coefficient of variation of 12.8% to 3.6% over a range of 25 to 25,000 PPM. The assay targets 99.9% specificity, with this validation study measuring 100% specificity and in silico methods giving us a confidence interval of 99.92 to 100%. In summary, this study demonstrates NeXT Personal as an ultra-sensitive, highly quantitative and robust ctDNA assay that can be used to detect residual disease, monitor treatment response, and detect recurrence in patients.

Challenges of Congenital Heart Surgery in Brazil: It is Time to Designate Pediatric Congenital Heart Surgery Subspecialty

ABSTRACT Congenital heart disease (CHD) affects eight to ten out of every 1,000 births, resulting in approximately 23,057 new cases in Brazil in 2022. About one in four children with CHD requires surgery or other procedures in the first year of life, and it is expected that approximately 81% of these children with CHD will survive until at least 35 years of age. Professionals choosing to specialize in CHD surgery face numerous challenges, not only related to mastering surgical techniques and the complexity of the diseases but also to the lack of recognition by medical societies as a separate subspecialty. Furthermore, families face difficulties when access to services capable of providing treatment for these children. To address these challenges, it is essential to have specialized hospitals, qualified professionals, updated technologies, sustainable industry, appropriate financing, quality assessment systems, and knowledge generation. The path to excellence involves specialization across all involved parties. As we reflect on the importance of Pediatric Cardiovascular Surgery and Congenital Heart Diseases establishing themselves as a subspecialty of Cardiovascular Surgery, it is essential to look beyond our borders to countries like the United States of America and United Kingdom, where this evolution is already a reality. This autonomy has led to significant advancements in research, education, and patient care outcomes, establishing a care model. By following this path in Brazil, we not only align our practice with the highest international standards but also demonstrate our maturity and the ability to meet the specific needs of patients with CHD and those with acquired childhood heart disease.

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Kawasaki disease: Surgical treatment.

Kawasaki disease (KD) is a systemic vasculitis of small and medium arteries, preferably affecting coronary arteries. It is one of the most frequent causes of acquired heart disease in children. Despite being comprehensively studied, its etiopathogenesis is not totally explained. The surgical procedures usually become necessary during the late follow-up and may be coronary artery bypass grafting, cardiac defibrillator implantation with or without cardiac resynchronization therapy, or cardiac transplantation.

Perfil epidemiológico dos casos de COVID-19 em uma cidade do noroeste paulista / Epidemiological profile of COVID-19 cases in a northwestern city paulista

Introdução: Em 11 de março de 2020 foi declarada pela Organização Mundial da Saúde (OMS) a pandemia da doença pelo coronavírus 2019 (covid-19), responsável por causar infecção respiratória aguda, potencialmente grave e de alta transmissibilidade, o que elevou mundialmente o número de óbitos. Métodos: Trata-se de uma pesquisa documental, aplicada, de abordagem quantitativa e transversal, de coleta e análise de dados de casos notificados, no período de março de 2020 a julho de 2021, nos sistemas e-SUS Notifica (casos de síndrome gripal) e Sivep-Gripe (casos de síndrome respiratória aguda grave e óbitos) do município de Araçatuba (SP), no Noroeste Paulista. As variáveis analisadas foram sexo, faixa etária, presença de comorbidades, desfecho (cura ou óbito) e vacinação. As taxas de letalidade geral e específica foram calculadas, bem como a média móvel de casos e óbitos por semana epidemiológica de ocorrência. Resultados: Foram obtidos 28.890 casos confirmados, dos quais 13.210 do sexo masculino e 15.680 do sexo feminino. Dos 894 óbitos, 482 ocorreram em homens. A letalidade entre pessoas com doença neurológica prévia foi de 50%. Todos os vacinados que vieram a óbito tinham mais de 60 anos e 82,87% possuíam pelo menos um fator de risco. Conclusões: A análise do perfil epidemiológico dos acometidos, da evolução e da gravidade foi de fundamental importância para se determinar e adequar estratégias de mitigação e planejamento de ações e cuidados de saúde no combate ao SARS-CoV-2 no município.

Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms.

PURPOSE: While immune checkpoint blockade (ICB) has become a pillar of cancer treatment, biomarkers that consistently predict patient response remain elusive due to the complex mechanisms driving immune response to tumors. We hypothesized that a multi-dimensional approach modeling both tumor and immune-related molecular mechanisms would better predict ICB response than simpler mutation-focused biomarkers, such as tumor mutational burden (TMB). EXPERIMENTAL DESIGN: Tumors from a cohort of patients with late-stage melanoma (n = 51) were profiled using an immune-enhanced exome and transcriptome platform. We demonstrate increasing predictive power with deeper modeling of neoantigens and immune-related resistance mechanisms to ICB. RESULTS: Our neoantigen burden score, which integrates both exome and transcriptome features, more significantly stratified responders and nonresponders (P = 0.016) than TMB alone (P = 0.049). Extension of this model to include immune-related resistance mechanisms affecting the antigen presentation machinery, such as HLA allele-specific LOH, resulted in a composite neoantigen presentation score (NEOPS) that demonstrated further increased association with therapy response (P = 0.002). CONCLUSIONS: NEOPS proved the statistically strongest biomarker compared with all single-gene biomarkers, expression signatures, and TMB biomarkers evaluated in this cohort. Subsequent confirmation of these findings in an independent cohort of patients (n = 110) suggests that NEOPS is a robust, novel biomarker of ICB response in melanoma.

STK11/LKB1 Loss of Function Is Associated with Global DNA Hypomethylation and S-Adenosyl-Methionine Depletion in Human Lung Adenocarcinoma.

STK11 (liver kinase B1, LKB1) is the fourth most frequently mutated gene in lung adenocarcinoma, with loss of function observed in up to 30% of all cases. Our previous work identified a 16-gene signature for LKB1 loss of function through mutational and nonmutational mechanisms. In this study, we applied this genetic signature to The Cancer Genome Atlas (TCGA) lung adenocarcinoma samples and discovered a novel association between LKB1 loss and widespread DNA demethylation. LKB1-deficient tumors showed depletion of S-adenosyl-methionine (SAM-e), which is the primary substrate for DNMT1 activity. Lower methylation following LKB1 loss involved repetitive elements (RE) and altered RE transcription, as well as decreased sensitivity to azacytidine. Demethylated CpGs were enriched for FOXA family consensus binding sites, and nuclear expression, localization, and turnover of FOXA was dependent upon LKB1. Overall, these findings demonstrate that a large number of lung adenocarcinomas exhibit global hypomethylation driven by LKB1 loss, which has implications for both epigenetic therapy and immunotherapy in these cancers. SIGNIFICANCE: Lung adenocarcinomas with LKB1 loss demonstrate global genomic hypomethylation associated with depletion of SAM-e, reduced expression of DNMT1, and increased transcription of repetitive elements.

To mock or not: a comprehensive comparison of mock IP and DNA input for ChIP-seq.

Chromatin immunoprecipitation (IP) followed by sequencing (ChIP-seq) is the gold standard to detect transcription-factor (TF) binding sites in the genome. Its success depends on appropriate controls removing systematic biases. The predominantly used controls, i.e. DNA input, correct for uneven sonication, but not for nonspecific interactions of the IP antibody. Another type of controls, 'mock' IP, corrects for both of the issues, but is not widely used because it is considered susceptible to technical noise. The tradeoff between the two control types has not been investigated systematically. Therefore, we generated comparable DNA input and mock IP experiments. Because mock IPs contain only nonspecific interactions, the sites predicted from them using DNA input indicate the spurious-site abundance. This abundance is highly correlated with the 'genomic activity' (e.g. chromatin openness). In particular, compared to cell lines, complex samples such as whole organisms have more spurious sites-probably because they contain multiple cell types, resulting in more expressed genes and more open chromatin. Consequently, DNA input and mock IP controls performed similarly for cell lines, whereas for complex samples, mock IP substantially reduced the number of spurious sites. However, DNA input is still informative; thus, we developed a simple framework integrating both controls, improving binding site detection.

FANCY: fast estimation of privacy risk in functional genomics data.

MOTIVATION: Functional genomics data are becoming clinically actionable, raising privacy concerns. However, quantifying privacy leakage via genotyping is difficult due to the heterogeneous nature of sequencing techniques. Thus, we present FANCY, a tool that rapidly estimates the number of leaking variants from raw RNA-Seq, ATAC-Seq and ChIP-Seq reads, without explicit genotyping. FANCY employs supervised regression using overall sequencing statistics as features and provides an estimate of the overall privacy risk before data release. RESULTS: FANCY can predict the cumulative number of leaking SNVs with an average 0.95 R2 for all independent test sets. We realize the importance of accurate prediction when the number of leaked variants is low. Thus, we develop a special version of the model, which can make predictions with higher accuracy when the number of leaking variants is low. AVAILABILITY AND IMPLEMENTATION: A python and MATLAB implementation of FANCY, as well as custom scripts to generate the features can be found at https://github.com/gersteinlab/FANCY. We also provide jupyter notebooks so that users can optimize the parameters in the regression model based on their own data. An easy-to-use webserver that takes inputs and displays results can be found at fancy.gersteinlab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GENCODE 2021.

The GENCODE project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics. GENCODE annotation processes make use of primary data and bioinformatic tools and analysis generated both within the consortium and externally to support the creation of transcript structures and the determination of their function. Here, we present improvements to our annotation infrastructure, bioinformatics tools, and analysis, and the advances they support in the annotation of the human and mouse genomes including: the completion of first pass manual annotation for the mouse reference genome; targeted improvements to the annotation of genes associated with SARS-CoV-2 infection; collaborative projects to achieve convergence across reference annotation databases for the annotation of human and mouse protein-coding genes; and the first GENCODE manually supervised automated annotation of lncRNAs. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

Origins and characterization of variants shared between databases of somatic and germline human mutations.

BACKGROUND: Mutations arise in the human genome in two major settings: the germline and the soma. These settings involve different inheritance patterns, time scales, chromatin structures, and environmental exposures, all of which impact the resulting distribution of substitutions. Nonetheless, many of the same single nucleotide variants (SNVs) are shared between germline and somatic mutation databases, such as between the gnomAD database of 120,000 germline exomes and the TCGA database of 10,000 somatic exomes. Here, we sought to explain this overlap. RESULTS: After strict filtering to exclude common germline polymorphisms and sites with poor coverage or mappability, we found 336,987 variants shared between the somatic and germline databases. A uniform statistical model explains 34% of these shared variants; a model that incorporates the varying mutation rates of the basic mutation types explains another 50% of shared variants; and a model that includes extended nucleotide contexts (e.g. surrounding 3 bases on either side) explains an additional 4% of shared variants. Analysis of read depth finds mixed evidence that up to 4% of the shared variants may represent germline variants leaked into somatic call sets. 9% of the shared variants are not explained by any model. Sequencing errors and convergent evolution did not account for these. We surveyed other factors as well: Cancers driven by endogenous mutational processes share a greater fraction of variants with the germline, and recently derived germline variants were more likely to be somatically shared than were ancient germline ones. CONCLUSIONS: Overall, we find that shared variants largely represent bona fide biological occurrences of the same variant in the germline and somatic setting and arise primarily because DNA has some of the same basic chemical vulnerabilities in either setting. Moreover, we find mixed evidence that somatic call-sets leak appreciable numbers of germline variants, which is relevant to genomic privacy regulations. In future studies, the similar chemical vulnerability of DNA between the somatic and germline settings might be used to help identify disease-related genes by guiding the development of background-mutation models that are informed by both somatic and germline patterns of variation.

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition.

About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage-fusion-bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements.

The Long interspersed nuclear element 1 (LINE-1) is a primary source of genetic variation in humans and other mammals. Despite its importance, LINE-1 activity remains difficult to study because of its highly repetitive nature. Here, we developed and validated a method called TeXP to gauge LINE-1 activity accurately. TeXP builds mappability signatures from LINE-1 subfamilies to deconvolve the effect of pervasive transcription from autonomous LINE-1 activity. In particular, it apportions the multiple reads aligned to the many LINE-1 instances in the genome into these two categories. Using our method, we evaluated well-established cell lines, cell-line compartments and healthy tissues and found that the vast majority (91.7%) of transcriptome reads overlapping LINE-1 derive from pervasive transcription. We validated TeXP by independently estimating the levels of LINE-1 autonomous transcription using ddPCR, finding high concordance. Next, we applied our method to comprehensively measure LINE-1 activity across healthy somatic cells, while backing out the effect of pervasive transcription. Unexpectedly, we found that LINE-1 activity is present in many normal somatic cells. This finding contrasts with earlier studies showing that LINE-1 has limited activity in healthy somatic tissues, except for neuroprogenitor cells. Interestingly, we found that the amount of LINE-1 activity was associated with the with the amount of cell turnover, with tissues with low cell turnover rates (e.g. the adult central nervous system) showing lower LINE-1 activity. Altogether, our results show how accounting for pervasive transcription is critical to accurately quantify the activity of highly repetitive regions of the human genome.

Retroposed copies of RET gene: a somatically acquired event in medullary thyroid carcinoma.

BACKGROUND: Different pathogenic germline mutations in the RET oncogene are identified in MEN 2, a hereditary syndrome characterized by medullary thyroid carcinoma (MTC) and other endocrine tumors. Although genetic predisposition is recognized, not all RET mutation carriers will develop the disease during their lifetime or, likewise, RET mutation carriers belonging to the same family may present clinical heterogeneity. It has been suggested that a single germline mutation might not be sufficient for development of MEN 2-associated tumors and a somatic bi-allelic alteration might be required. Here we investigated the presence of somatic second hit mutation in the RET gene in MTC. METHODS: We integrated Multiplex Ligation-dependent Probe Amplification (MLPA) and whole exome sequencing (WES) to search for copy number alteration (CNA) in the RET gene in MTC samples and medullary thyroid cell lines (TT and MZ-CR-1). We next found reads spanning exon-exon boundaries on RET, an indicative of retrocopy. We subsequently searched for RET retrocopies in the human reference genome (GRCh37) and in the 1000 Genomes Project data, by looking for reads reporting joined exons in the RET locus or distinct genomic regions. To determine RET retrocopy specificity and recurrence, DNA isolated from sporadic and MEN 2-associated MTC (n = 37), peripheral blood (n = 3) and papillary thyroid carcinomas with RET fusion (n = 10) samples were tested using PCR-sequencing methodology. RESULTS: Through MLPA we have found evidence of CNA in the RET gene in MTC samples and MTC cell lines. WES analysis reinforced the presence of the CNA and hinted for a retroposed copy of RET not found in the human reference genome and 1.000 Genomes Project. Extended analysis confirmed the presence of a somatic MTC-related retrocopy of RET in both sporadic and hereditary tumors. We further unveiled a recurrent (28%) novel point mutation (p.G548 V) found exclusively in the retrocopy of RET. The mutation was also found in cDNA of mutated samples, suggesting it might be functional. CONCLUSION: We here report a somatic specific RET retroposed copy in MTC samples and cell lines. Our results support the idea that generation of retrocopies in somatic cells is likely to contribute to MTC genesis and progression.

Genomics and data science: an application within an umbrella.

Data science allows the extraction of practical insights from large-scale data. Here, we contextualize it as an umbrella term, encompassing several disparate subdomains. We focus on how genomics fits as a specific application subdomain, in terms of well-known 3 V data and 4 M process frameworks (volume-velocity-variety and measurement-mining-modeling-manipulation, respectively). We further analyze the technical and cultural "exports" and "imports" between genomics and other data-science subdomains (e.g., astronomy). Finally, we discuss how data value, privacy, and ownership are pressing issues for data science applications, in general, and are especially relevant to genomics, due to the persistent nature of DNA.

GENCODE reference annotation for the human and mouse genomes.

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.

Comprehensive functional genomic resource and integrative model for the human brain.

Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with >88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.