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The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21)ETV6-RUNX1translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-year-old at relapse, the cell line offers a practical model for the study of high-risk pediatric B-ALL patients. In recent years, short-read DNA and RNA sequencing have emerged as a complement to analog karyotyping techniques in the resolution of structural variants in an oncological context. However, it is challenging to create a comprehensive digital karyotype of a genome with these techniques alone. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole genome sequencing (WGS), IsoSeq RNA-sequencing, and short-read sequencing to create a detailed digital karyotype of the REH cell line. WGS refined the breakpoints of known aberrations and clarified the molecular traits of disrupted ALL-associated genesBTG1andTBL1XR1, as well as the glucocorticoid receptorNR3C1. Several previously underreported structural variants were also uncovered, including deletions affecting the ALL-associated genesVPREB1andNFATC1. Meanwhile, transcriptome sequencing identified seven fusion genes within the genomic breakpoints. Together, our extensive whole-genome investigation makes high-quality open-source data available to the leukemia genomics community.KEY POINTSA complete digital karyotype of the REH cell line was produced with short- and long-read DNA and RNA sequencing technologies.The study enabled precise identification of structural variants, and the fusion genes expressed as the result of these variants.

B-cell lineage acute lymphoblastic leukaemia (B-ALL) is the most common paediatric malignancy. Transcription factor B-cell lymphoma 6 (BCL6) is essential to germinal centre formation and antibody affinity maturation and plays a major role in mature B-cell malignancies. More recently, it was shown to act as a critical downstream regulator in pre-BCR+ B-ALL. We investigated the expression of the BCL6 protein in a population-based cohort of paediatric B-ALL cases and detected moderate to strong positivity through immunohistochemistry in 7% of cases (8/117); however, only two of eight BCL6 cases (25%) co-expressed the ZAP70 protein. In light of these data, the subtype with active pre-BCR signalling constitutes a rare entity in paediatric B-ALL. In three independent larger cohorts with gene expression data, high BCL6 mRNA levels were associated with the TCF3-PBX1, Ph-like, NUTM1, MEF2D and PAX5-alt subgroups and the ‘metagene’ signature for pre-BCR-associated genes. However, higher-than-median BCL6 mRNA level alone was associated with favourable event free survival in the Nordic paediatric cohort, indicating that using BCL6 as a diagnostic marker requires careful design, and evaluation of protein level is needed alongside the genetic or transcriptomic data. publishedVersion

Formalin-fixed, paraffin-embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture-based RNA-sequencing protocol to explore global gene expression in paired fresh-frozen (FF) and FFPE samples from 16 diffuse large B-cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome (r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell-of-origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell-of-origin classification of DLBCL samples.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor–normal genomic DNA (gDNA) samples derived from a breast cancer cell line—which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations—and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

Cancer is a highly heterogeneous disease in need of accurate and non-invasive diagnostic tools. Here, we describe a novel strategy to explore the proteome signature by comprehensive analysis of protein levels using a pan-cancer approach of patients representing the major cancer types. Plasma profiles of 1,463 proteins from more than 1,400 cancer patients representing altogether 12 common cancer types were measured in minute amounts of blood plasma collected at the time of diagnosis and before treatment. AI-based disease prediction models allowed for the identification of a set of proteins associated with each of the analyzed cancers. By combining the results from all cancer types, a panel of proteins suitable for the identification of all individual cancer types was defined. The results are presented in a new open access Human Disease Blood Atlas. The implication for cancer precision medicine of next generation plasma profiling is discussed.

BackgroundEquine asthma (EA) is a heterogenous, complex disease with a significant negative impact on horse welfare and performance. EA and human asthma have fundamental similarities, making EA a useful large animal disease model. Bronchoalveolar lavage (BAL) fluid provides a snapshot sample of the immune cells occupying the alveolar space and is one of the most relevant sample types for studies of chronic inflammation in the lung. In this study, we sequenced single equine BAL-cells in order to study the immune cell landscape of the respiratory tract of horses diagnosed with mild-to-moderate EA and healthy controls.ResultsScRNA-seq analysis of ~63,000 cells from eleven horses diagnosed with mild-moderate asthma (mEA) and eight healthy controls were performed using the Drop-Seq technology. We identified five major immune cell populations in equine BAL; alveolar macrophages (AM), T cells, neutrophils, mast cells and dendritic cells, as well as subtypes thereof. The cellular subtypes demonstrated herein have previously not been characterized in horses. Differential gene expression analysis revealed upregulation of genes in mEA horses, including FKBP5 and CCL24, which have previously been associated with asthma in other species. The most significantly upregulated gene across the cell types in EA was FKBP5, a chaperone protein involved in regulating the assembly, activity, and sensitivity of the glucocorticoid receptorConclusionHerein we demonstrate the first comprehensive scRNA-seq map of the immune-cell populations in BAL from horses with asthma and healthy individuals. The glucocorticoid receptor associated protein FKBP5 was identified as a potential biomarker for EA.

B‐cell precursor acute lymphoblastic leukemia (BCP‐ALL) can be classified into subtypes according to the genetic aberrations they display. For instance, the translocation t(12;21)(p13;q22), representing the ETV6‐RUNX1 fusion gene (ER), is present in a quarter of BCP‐ALL cases. However, around 10% of the cases lack classifying chromosomal abnormalities (B‐other). In pediatric ER BCP‐ALL, rearrangement mediated by RAG (recombination‐activating genes) has been proposed as the predominant driver of oncogenic rearrangement. Herein we analyzed almost 1600 pediatric BCP‐ALL samples to determine which subtypes express RAG. We demonstrate that RAG1 mRNA levels are especially high in the ETV6‐RUNX1 (ER) subtype and in a subset of B‐other samples. We also define 31 genes that are co‐expressed with RAG1 (RAG1‐signature) in the ER subtype, a signature that also identifies this subset of B‐other samples. Moreover, this subset also shares leukemia and pro‐B gene expression signatures as well as high levels of the ETV6 target genes (BIRC7, WBP1L, CLIC5, ANGPTL2) with the ER subtype, indicating that these B‐other cases are the recently identified ER‐like subtype. We validated our results in a cohort where ER‐like has been defined, which confirmed expression of the RAG1‐signature in this recently described subtype. Taken together, our results demonstrate that the RAG1‐signature identifies the ER‐like subtype. As there are no definitive genetic markers to identify this novel subtype, the RAG1‐signature represents a means to screen for this leukemia in children., The recombination‐activating genes (RAG) may play a role in leukemogenesis. We determined, therefore, in around 1600 BCP‐ALL samples which subtypes express RAG and defined a set of co‐expressed genes, the RAG1‐signature, which was thereafter used to identify potential new subtypes. We demonstrate that the RAG1‐signature identifies the recently described ETV6‐RUNX1‐like BCP‐ALL.

Purpose of the study: This study was aimed at identifying epigenome signature associated with risk of pediatric leukemia and uncovering molecular precursors of leukemia at birth in the blood of children before they develop the disease. Pediatric cancer is the leading cause of disease-related mortality in children and adolescents, with increasing incidence worldwide and lifelong sequelae in survivors. The most common form is leukemia, the causes of which are largely unknown. Growing evidence points to an origin in utero, when global redistribution of the epigenome modifications occurs driving tissue differentiation. Here, we sought to identify genome-wide differentially methylated genes at birth in newborns who later developed pediatric precursor B-cell ALL (pre-B ALL), compared with those who did not. Experimental procedures: Epigenome-wide DNA methylation was profiled in neonatal blood, with follow-up to pediatric pre-B ALL, using double-blinded analyses between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was done using an independent technology and population (totaling 317 cases and 483 control) and complemented with pan-tissue methylation-stability (n=5,023 tissues; 30 types) and methylation-expression (n=2,294 tissues; 26 types) analyses. At diagnosis, methylation analysis was performed in leukemia tissues from pre-B ALL patients (n=644) with at least ten-year follow-up. Results: We found a limited number of loci (among which an imprinted tumor suppressor gene) as being significantly hypermethylated at birth in nested cases relative to controls in all tested populations, including European and Hispanic ancestries. Some DMRs were found to be stable over follow-up years after birth and across surrogate blood and target bone marrow tissues. Differential methylation was found to be associated with a change in gene expression and with worse pre-B ALL patient survival, supporting a functional and translational role for differential methylation. Conclusions: Our results provide proof-of-concept to detect at birth epigenetic alterations predisposing to childhood leukemia, reproducible in three continents and two ethnicities. DNA methylation alterations evident before diagnosis could be precursors of pediatric pre-B ALL development and actionable targets for risk assessment and prognosis. Citation Format: Akram Ghantous, Semira Gonseth Nusslé, Farah Nassar, Natalia Spitz, Alexei Novoloaca, Olga Krali, Ritu Roy, Shaobo Li, Maxime Caron, Lilys Lam, Peter Daniel Fransquet, John Casement, John Strathdee, Mark S. Pearce, Helen M. Hansen, Adam J. De Smith, Daniel Sinnett, Siri Eldevik Håberg, Jill McKay, Jessica Nordlund, Per Magnus, Terence Dwyer, Richard Saffery, Joseph Leo Wiemels, Monica Cheng Munthe-Kaas, Zdenko Herceg. Epigenome-wide DNA methylation alterations precede diagnosis since birth and affect prognosis of pediatric B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB362.

Background: Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30–50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers. Methods: We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (N = 111 and N = 37). Results: The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers. Conclusions: The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Ovarian cancer is the eighth most common cancer among women and has a 5-year survival of only 30-50%. The survival is close to 90% for patients in stage I but only 20% for patients in stage IV. The presently available biomarkers have insufficient sensitivity and specificity for early detection and there is an urgent need to identify novel biomarkers.We employed the Explore PEA technology for high-precision analysis of 1463 plasma proteins and conducted a discovery and replication study using two clinical cohorts of previously untreated patients with benign or malignant ovarian tumours (The discovery analysis identified 32 proteins that had significantly higher levels in malignant cases as compared to benign diagnoses, and for 28 of these, the association was replicated in the second cohort. Multivariate modelling identified three highly accurate models based on 4 to 7 proteins each for separating benign tumours from early-stage and/or late-stage ovarian cancers, all with AUCs above 0.96 in the replication cohort. We also developed a model for separating the early-stage from the late-stage achieving an AUC of 0.81 in the replication cohort. These models were based on eleven proteins in total (ALPP, CXCL8, DPY30, IL6, IL12, KRT19, PAEP, TSPAN1, SIGLEC5, VTCN1, and WFDC2), notably without MUCIN-16. The majority of the associated proteins have been connected to ovarian cancer but not identified as potential biomarkers.The results show the ability of using high-precision proteomics for the identification of novel plasma protein biomarker candidates for the early detection of ovarian cancer.

Whole-genome sequencing (WGS) and whole-transcriptome sequencing (WTS), with the ability to provide comprehensive genomic information, have become the focal point of research interest as novel techniques that can support precision diagnostics in routine clinical care of patients with various cancer types, including hematological malignancies. This national multi-center study, led by Genomic Medicine Sweden, aims to evaluate whether combined application of WGS and WTS (WGTS) is technically feasible and can be implemented as an efficient diagnostic tool in patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). In addition to clinical impact assessment, a health-economic evaluation of such strategy will be performed.The study comprises four phases (i.e., retrospective, prospective, real-time validation, and follow-up) including approximately 700 adult and pediatric Swedish AML and ALL patients. Results of WGS for tumor (90×) and normal/germline (30×) samples as well as WTS for tumors only will be compared to current standard of care diagnostics. Primary study endpoints are diagnostic efficiency and improved diagnostic yield. Secondary endpoints are technical and clinical feasibility for routine implementation, clinical utility, and health-economic impact.Data from this national multi-center study will be used to evaluate clinical performance of the integrated WGTS diagnostic workflow compared with standard of care. The study will also elucidate clinical and health-economic impacts of a combined WGTS strategy when implemented in routine clinical care.[https://doi.org/10.1186/ISRCTN66987142], identifier [ISRCTN66987142].

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies., Measurement(s)Somatic Mutation AnalysisTechnology Type(s)whole genome sequencing • Whole Exome SequencingFactor Type(s)sequencing platform • sample prepration • library preparation • bioinformatics methodSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16713655

SummaryDNA methylation is a central epigenetic mark that has diverse roles in gene regulation, development, and maintenance of genome integrity. 5 methyl cytosine (5mC) can be interrogated at base resolution in single cells by using bisulfite sequencing (scWGBS). Several different scWGBS strategies have been described in recent years to study DNA methylation in single cells. However, there remain limitations with respect to cost-efficiency and yield. Herein, we present a new development in the field of scWGBS library preparation; single cell Splinted Ligation Adapter Tagging (scSPLAT). scSPLAT employs a pooling strategy to facilitate sample preparation at a higher scale and throughput than previously possible. We demonstrate the accuracy and robustness of the method by generating data from 225 single K562 cells and from 309 single liver nuclei and compare scSPLAT against other scWGBS methods.MotivationscWGBS library preparation in a one-cell-per-library format presents practical and economical constraints to the number of cells that can be analyzed in a research project. In addition, most of the current scWGBS methods suffer from low read alignment rates. We present a scWGBS protocol which mitigates these issues, empowering single-cell DNA methylation analysis at an increased scale.

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. Supplementary Information The online version contains supplementary material available at 10.1007/s00439-021-02397-7.

Mosaic loss of chromosome Y (LOY) in immune cells is a male-specific mutation associated with increased risk for morbidity and mortality. TheCD99gene, positioned in the pseudoautosomal regions of chromosomes X and Y, encodes a cell surface protein essential for several key properties of leukocytes and immune system functions. Here we used CITE-seq for simultaneous quantification ofCD99derived mRNA and cell surface CD99 protein abundance in relation to LOY in single cells. The abundance of CD99 molecules was lower on the surfaces of LOY cells compared with cells without this aneuploidy in all six types of leukocytes studied, while the abundance of CD proteins encoded by genes located on autosomal chromosomes were independent from LOY. These results connect LOY in single cells with immune related cellular properties at the protein level, providing mechanistic insight regarding disease vulnerability in men affected with mosaic chromosome Y loss in blood leukocytes.

Pediatric acute myeloid leukemia (AML) is a heterogeneous disease composed of clinically relevant subtypes defined by recurrent cytogenetic aberrations. The majority of the aberrations used in risk grouping for treatment decisions are extensively studied, but still a large proportion of pediatric AML patients remain cytogenetically undefined and would therefore benefit from additional molecular investigation. As aberrant epigenetic regulation has been widely observed during leukemogenesis, we hypothesized that DNA methylation signatures could be used to predict molecular subtypes and identify signatures with prognostic impact in AML. To study genome-wide DNA methylation, we analyzed 123 diagnostic and 19 relapse AML samples on Illumina 450k DNA methylation arrays. We designed and validated DNA methylation-based classifiers for AML cytogenetic subtype, resulting in an overall test accuracy of 91%. Furthermore, we identified methylation signatures associated with outcome in t(8, 21)/RUNX1-RUNX1T1, normal karyotype, and MLL/KMT2A-rearranged subgroups (p &lt, 0.01). Overall, these results further underscore the clinical value of DNA methylation analysis in AML.

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies. Background & Summary The NGS technology has become a powerful tool for precision medicine. More researchers and clinicians are utilizing NGS to identify clinically actionable mutations in cancer patients and to establish targeted therapies for patients based on the patient’s genetic makeup or genetic variants of their tumor1, there is a critical need to have a full understanding of the many different variables affecting the NGS analysis output. The rapid growing number of sample processing protocols, library preparation methods, sequencing platforms, and bioinformatics pipelines to detect mutations in cancer genome, presents great technical challenges for the accuracy and reproducibility of utilizing NGS for cancer genome mutation detections. To investigate how these experimental and analytical elements may affect mutation detection accuracy, recently we carried out a comprehensive benchmarking study using both whole-genome (WGS) and whole-exome sequencing (WES) data sets generated from two well-characterized reference samples: a human breast cancer cell line (HCC1395) and a B lymphocytes cell line (HCC1395BL) derived from the same donor (NBT-RS47789). We generated WGS and WES data using various NGS library preparation protocols, seven NGS platforms at six centers (NBT-A46164B).

Funder: Kjell och Märta Beijers Stiftelse (SE), Funder: Hjärnfonden; doi: http://dx.doi.org/10.13039/501100003792, Funder: Cancerfonden; doi: http://dx.doi.org/10.13039/501100002794, Funder: Vetenskapsrådet; doi: http://dx.doi.org/10.13039/501100004359, Funder: Alzheimerfonden; doi: http://dx.doi.org/10.13039/501100008599, Funder: Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse (SE), Funder: Science for Life Laboratory (SE), Funder: Fundacja na rzecz Nauki Polskiej (PL), Funder: Uppsala University, Epidemiological investigations show that mosaic loss of chromosome Y (LOY) in leukocytes is associated with earlier mortality and morbidity from many diseases in men. LOY is the most common acquired mutation and is associated with aberrant clonal expansion of cells, yet it remains unclear whether this mosaicism exerts a direct physiological effect. We studied DNA and RNA from leukocytes in sorted- and single-cells in vivo and in vitro. DNA analyses of sorted cells showed that men diagnosed with Alzheimer’s disease was primarily affected with LOY in NK cells whereas prostate cancer patients more frequently displayed LOY in CD4 + T cells and granulocytes. Moreover, bulk and single-cell RNA sequencing in leukocytes allowed scoring of LOY from mRNA data and confirmed considerable variation in the rate of LOY across individuals and cell types. LOY-associated transcriptional effect (LATE) was observed in ~ 500 autosomal genes showing dysregulation in leukocytes with LOY. The fraction of LATE genes within specific cell types was substantially larger than the fraction of LATE genes shared between different subsets of leukocytes, suggesting that LOY might have pleiotropic effects. LATE genes are involved in immune functions but also encode proteins with roles in other diverse biological processes. Our findings highlight a surprisingly broad role for chromosome Y, challenging the view of it as a “genetic wasteland”, and support the hypothesis that altered immune function in leukocytes could be a mechanism linking LOY to increased risk for disease.

The mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) are not fully understood. We performed whole genome sequencing of samples collected at diagnosis, relapse(s) and remission from 29 Nordic patients. Somatic point mutations and large-scale structural variants were called using individually matched remission samples as controls, and allelic expression of the mutations was assessed in ALL cells using RNA-sequencing. We observed an increased burden of somatic mutations at relapse, compared to diagnosis, and at second relapse compared to first relapse. In addition to 29 known ALL driver genes, of which nine genes carried recurrent protein-coding mutations in our sample set, we identified putative non-protein coding mutations in regulatory regions of seven additional genes that have not previously been described in ALL. Cluster analysis of hundreds of somatic mutations per sample revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse. The evolutionary trajectories provide insight into the mutational mechanisms leading relapse in ALL and could offer biomarkers for improved risk prediction in individual patients. Funding Agencies|CancerfondenSwedish Cancer Society [CAN2018/623] Funding Source: Medline; Barncancerfonden [PR2017-0023, PR2019-0046] Funding Source: Medline

Structural chromosomal rearrangements that can lead to in-frame gene-fusions are a leading source of information for diagnosis, risk stratification, and prognosis in pediatric acute lymphoblastic leukemia (ALL). Traditional methods such as karyotyping and FISH struggle to accurately identify and phase such large-scale chromosomal aberrations in ALL genomes. We therefore evaluated linked-read WGS for detecting chromosomal rearrangements in primary samples of from 12 patients diagnosed with ALL. We assessed the effect of input DNA quality on phased haplotype block size and the detectability of copy number aberrations and structural variants in the ALL genomes. We found that biobanked DNA isolated by standard column-based extraction methods was sufficient to detect chromosomal rearrangements even at low 10x sequencing coverage. Linked-read WGS enabled precise, allele-specific, digital karyotyping at a base-pair resolution for a wide range of structural variants including complex rearrangements and aneuploidy assessment. With use of haplotype information from the linked-reads, we also identified previously unknown structural variants, such as a compound heterozygous deletion of ERG in a patient with the DUX4-IGH fusion gene. We conclude that linked-read WGS allows detection of important pathogenic variants in ALL genomes at a resolution beyond that of traditional karyotyping and FISH.

Intrachromosomal amplification of chromosome 21 (iAMP21) is a cytogenetic subtype associated with relapse and poor prognosis in pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL). The biology behind the high relapse risk is unknown and the aim of this study was to further characterize the genomic and transcriptional landscape of iAMP21. Using DNA arrays and sequencing, we could identify rearrangements and aberrations characteristic for iAMP21. RNA sequencing revealed that only half of the genes in the minimal region of amplification (20/45) were differentially expressed in iAMP21. Among them were the top overexpressed genes (p < 0.001) in iAMP21 vs. BCP ALL without iAMP21 and three candidate genes could be identified, the tyrosine kinase gene DYRK1A and chromatin remodeling genes CHAF1B and SON. While overexpression of DYRK1A and CHAF1B is associated with poor prognosis in malignant diseases including myeloid leukemia, this is the first study to show significant correlation with iAMP21-positive ALL.

The remarkable advances in high throughput sequencing have brought unprecedented progression to the field of epigenomic research, particularly in the area of genome-wide DNA methylation analysis. The variety of approaches available have enabled genome-wide profiling of countless cell types and states, resulting in findings that have proved instrumental for advancing our understanding of cellular identity in development, health, and disease. The methylome-wide approaches that are available today vary in many aspects, such as required DNA input, degree of genomic resolution and coverage, and ability of quantification. This chapter discusses the historical development, proven modifications, and the many applications for analysis of DNA methylation and other base modifications on a global scale, as well as their translational potential.