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• Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing

  Somatic mutations accumulate in healthy tissues as we age, giving rise to cancer and potentially contributing to ageing. To study somatic mutations in non-neoplastic tissues, we developed a series of protocols to sequence the genomes of small populations of cells isolated from histological sections. Here, we describe a complete workflow that combines laser-capture microdissection (LCM) with low-input genome sequencing, whilst circumventing the use of whole-genome amplification (WGA). The protocol is subdivided broadly into 4 steps: tissue processing, LCM, low-input library generation and mutation calling and filtering. The tissue processing and LCM steps are provided as general guidelines which may require tailoring based on the specific requirements of the study at hand. Our protocol for low-input library generation utilises enzymatic rather than acoustic fragmentation to generate WGA-free whole-genome libraries. Finally, the mutation calling and filtering strategy has been adapted from previously published protocols to account for artefacts introduced via library creation. To date, we have used this workflow to perform targeted and whole-genome sequencing of small populations of cells (typically 100-1,000 cells) in thousands of microbiopsies from a wide range of human tissues. The low-input DNA protocol is designed to be compatible with liquid handling platforms and make use of equipment and expertise standard to any core sequencing facility. However, obtaining low-input DNA material via LCM requires specialized equipment and expertise. The entire protocol from tissue reception through whole-genome library generation can be accomplished in as little as a week, though 2-3 weeks would be a more typical turnaround time.

  Dataset EGAD00001006088

• Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

  The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

  Study EGAS00001000096

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• In vitro modeling of renal injury-induced cardiac effects using human iPSC-derived organoids

  The bidirectional communication between the heart and kidney essential for physiological homeostasis, with injury in one organ often impairing in the other. Although cardiorenal crosstalk is clinically relevant in conditions such as cardiorenal syndrome (CRS), the underlying molecular and cellular mechanisms remain poorly understood, and in vitro models are lacking. Here, we developed a co-culture system using human induced pluripotent stem cell (hiPSC)-derived kidney organoids (kOs) and cardiac microtissues (cMTs) to model the cardiorenal axis. kOs exposed to nephrotoxic compounds for 72 hours displayed glomerular and tubular damage, reduced cell viability, and altered gene expression. When subsequently co-cultured with cMTs for 72 hours, injured kOs induced secondary cardiac dysfunction characterized by reduced cell viability, impaired contractility, and endothelial cell loss. These findings demonstrate that kidney injury can elicit detrimental effects on cardiac tissues in vitro. This organoid-based platform offers a valuable tool for studying cardiorenal interactions and underlines the potential of multi-organ models for investigating mechanisms of interdependent organ dysfunction.

  Study EGAS50000001300

• Harnessing the Electronic Health Record to Predict Risk of Cardiovascular Disease: Sangre Por Salud (SPS) Biobank GWAS Data

  These data are from subjects in the Sangre Por Salud (SPS) Biobank, a Latino population from the Southwest United States. Subjects were genotyped in 2 batches on the Illumina Multi-ethnic Global Array. Data from this study were used for testing a new cardiovascular risk score and evaluating polygenic risk scores. SPS biobank GWAS data is available on 3699 subjects.

  Study phs003553

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• Extracorporeal Life Support Survival in a Pediatric Hematopoietic Cellular Transplant Recipient with Presumed Graft Versus Host Disease-Related Fulminant Myocarditis

  We report the case of a 15-year-old female with hypodiploid pre-B acute lymphoblastic leukemia status post allogeneic hematopoietic stem cell transplantation (HCT) from a matched unrelated male donor who presented on transplant day +75 with cardiac arrest due to ventricular fibrillation associated with fulminant myocarditis. Using conventional diagnostics, an exhaustive search for microbial pathogens in the heart biopsy as well as nasopharynx, blood, urine, and endotracheal aspirate was performed but did not uncover a candidate pathogen. The family consented to a research study for the use of unbiased next-generation genomic sequencing for pathogen identification in the myocardial biopsy. DNA sequencing was performed on 1.5 x 108 sequencing pairs and no microbial pathogens were identified. Interestingly, a significant component of Y-chromosomal human DNA was identified, suggesting infiltration of at least 10 donor leukocytes per host cell. This finding is grossly consistent with the lymphocyte:myocyte ratio in the biopsy according to visual inspection at 40x magnification. This case merits discussion due to (1) her survival after 17 days of veno-arterial extracorporeal life support (ECLS) and (2) the possibility of cardiotropic graft versus host disease (GVHD).

  Study phs001336

• Induction of fetal meiotic oocytes from embryonic stem cells in cynomolgus monkeys

  Human in vitro oogenesis provides a framework for clarifying the mechanism of human oogenesis. To create its benchmark, it is vital to promote in vitro oogenesis using a model physiologically close to humans. Here, we establish a foundation for in vitro oogenesis in cynomolgus (cy) monkeys: cy female embryonic stem cells harboring one active and one inactive X chromosome (Xa and Xi, respectively) differentiate robustly into primordial germ cell-like cells, which in xenogeneic reconstituted ovaries develop efficiently into oogonia and, remarkably, further into meiotic oocytes at the zygotene stage. This differentiation entails a comprehensive epigenetic reprogramming, including Xi reprogramming, yet, as partly observed in vivo, Xa and Xi remain epigenetically asymmetric with incomplete Xi reactivation. In humans and monkeys, the Xi epigenome in pluripotent stem cells functions as an Xi-reprogramming determinant. We further show that developmental-pathway over-activations with suboptimal up-regulation of relevant meiotic genes impede in vitro meiotic progression. Cy in vitro oogenesis exhibits critical homology with the human system, including with respect to bottlenecks, providing a salient model for advancing human in vitro oogenesis.

  Study JGAS000573