Single-cell proteo-genomic reference maps of the hematopoietic system enable the purification and massive profiling of precisely defined cell states.

Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry.

Improve consensus partitioning via a hierarchical procedure.

Consensus partitioning is an unsupervised method widely used in high-throughput data analysis for revealing subgroups and assigning stability for the classification. However, standard consensus partitioning procedures are weak for identifying large numbers of stable subgroups. There are two major issues. First, subgroups with small differences are difficult to be separated if they are simultaneously detected with subgroups with large differences. Second, stability of classification generally decreases as the number of subgroups increases. In this work, we proposed a new strategy to solve these two issues by applying consensus partitioning in a hierarchical procedure. We demonstrated hierarchical consensus partitioning can be efficient to reveal more meaningful subgroups. We also tested the performance of hierarchical consensus partitioning on revealing a great number of subgroups with a large deoxyribonucleic acid methylation dataset. The hierarchical consensus partitioning is implemented in the R package cola with comprehensive functionalities for analysis and visualization. It can also automate the analysis only with a minimum of two lines of code, which generates a detailed HTML report containing the complete analysis. The cola package is available at https://bioconductor.org/packages/cola/.

rGREAT: an R/bioconductor package for functional enrichment on genomic regions.

SUMMARY: GREAT (Genomic Regions Enrichment of Annotations Tool) is a widely used tool for functional enrichment on genomic regions. However, as an online tool, it has limitations of outdated annotation data, small numbers of supported organisms and gene set collections, and not being extensible for users. Here, we developed a new R/Bioconductorpackage named rGREAT which implements the GREAT algorithm locally. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions. AVAILABILITY AND IMPLEMENTATION: The package rGREAT is freely available from the Bioconductor project: https://bioconductor.org/packages/rGREAT/. The development version is available at https://github.com/jokergoo/rGREAT. Gene Ontology gene sets for more than 600 organisms retrieved from Ensembl BioMart are presented in an R package BioMartGOGeneSets which is available at https://github.com/jokergoo/BioMartGOGeneSets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The landscape of genomic alterations across childhood cancers.

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.

Author Correction: The landscape of genomic alterations across childhood cancers.

In this Article, author Benedikt Brors was erroneously associated with affiliation number '8' (Department of Developmental Neurobiology, St Jude Children's Research Hospital, Memphis, Tennessee, USA); the author's two other affiliations (affiliations '3' and '7', both at the German Cancer Research Center (DKFZ)) were correct. This has been corrected online.

Human activation-induced deaminase lacks strong replicative strand bias or preference for cytosines in hairpin loops.

Activation-induced deaminase (AID) is a DNA-cytosine deaminase that mediates maturation of antibodies through somatic hypermutation and class-switch recombination. While it causes mutations in immunoglobulin heavy and light chain genes and strand breaks in the switch regions of the immunoglobulin heavy chain gene, it largely avoids causing such damage in the rest of the genome. To help understand targeting by human AID, we expressed it in repair-deficient Escherichia coli and mapped the created uracils in the genomic DNA using uracil pull-down and sequencing, UPD-seq. We found that both AID and the human APOBEC3A preferentially target tRNA genes and transcription start sites, but do not show preference for highly transcribed genes. Unlike A3A, AID did not show a strong replicative strand bias or a preference for hairpin loops. Overlapping uracilation peaks between these enzymes contained binding sites for a protein, FIS, that helps create topological domains in the E. coli genome. To confirm whether these findings were relevant to B cells, we examined mutations from lymphoma and leukemia genomes within AID-preferred sequences. These mutations also lacked replicative strand bias or a hairpin loop preference. We propose here a model for how AID avoids causing mutations in the single-stranded DNA found within replication forks.

Pkgndep: a tool for analyzing dependency heaviness of R packages.

SUMMARY: Numerous R packages have been developed for bioinformatics analysis in the last decade and dependencies among packages have become critical issues to consider. In this work, we proposed a new metric named dependency heaviness that measures the number of dependencies that a parent uniquely brings to a package and we proposed possible solutions for reducing the complexity of dependencies by optimizing the use of heavy parents. We implemented the metric in a new R package pkgndep which provides an intuitive way for dependency heaviness analysis. Based on pkgndep, we additionally performed a global analysis of dependency heaviness on CRAN and Bioconductor ecosystems and we revealed top packages that have significant contributions of high dependency heaviness to their child packages. AVAILABILITY AND IMPLEMENTATION: The package pkgndep and documentations are freely available from the Comprehensive R Archive Network https://cran.r-project.org/package=pkgndep. The dependency heaviness analysis for all 22 076 CRAN and Bioconductor packages retrieved on June 8, 2022 are available at https://pkgndep.github.io/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Make Interactive Complex Heatmaps in R.

SUMMARY: Heatmap is a powerful visualization method on two-dimensional data to reveal patterns shared by subsets of rows and columns. In this work, we introduce a new R package InteractiveComplexHeatmap that brings interactivity to the widely used ComplexHeatmap package. InteractiveComplexHeatmap is designed with an easy-to-use interface where static complex heatmaps can be directly exported to an interactive Shiny web application only with one additional line of code. InteractiveComplexHeatmap also provides flexible functionalities for integrating interactive heatmap widgets to build more complex and customized Shiny web applications. AVAILABILITY AND IMPLEMENTATION: The InteractiveComplexHeatmap package and documentations are freely available from the Bioconductor project: https://bioconductor.org/packages/InteractiveComplexHeatmap/. A complete and printer-friendly version of the documentation can also be found in Supplementary File S1. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

spiralize: an R package for visualizing data on spirals.

SUMMARY: Spiral layout has two major advantages for data visualization. First, it is able to visualize data with long axes, which greatly improves the resolution of visualization. Second, it is efficient for time series data to reveal periodic patterns. Here, we present the R package spiralize that provides a general solution for visualizing data on spirals. spiralize implements numerous graphics functions so that self-defined high-level graphics can be easily implemented by users. The flexibility and power of spiralize are demonstrated by five examples from real-world datasets. AVAILABILITY AND IMPLEMENTATION: The spiralize package and documentations are freely available at the Comprehensive R Archive Network (CRAN) https://CRAN.R-project.org/package=spiralize. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Focal structural variants revealed by whole genome sequencing disrupt the histone demethylase KDM4C in B-cell lymphomas.

Histone methylation-modifiers, such as EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%), also identified by prior exome or RNA-sequencing studies, we here found recurrent alterations to KDM4C in chromosome 9p24, encoding a histone demethylase. Focal structural variation was the main mechanism of KDM4C alterations, and was independent from 9p24 amplification. We also identified KDM4C alterations in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNA-sequencing and genome sequencing data we predict that KDM4C structural variants result in loss-offunction. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as a tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as a putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas.

Levodopa-refractory hyperprolactinemia and pituitary findings in inherited disorders of biogenic amine metabolism.

Elevated serum prolactin concentrations occur in inherited disorders of biogenic amine metabolism because dopamine deficiency leads to insufficient inhibition of prolactin secretion. This work from the International Working Group on Neurotransmitter Related Disorders (iNTD) presents the results of the first standardized study on levodopa-refractory hyperprolactinemia (LRHP; >1000 mU/L) and pituitary magnetic resonance imaging (MRI) abnormalities in patients with inherited disorders of biogenic amine metabolism. Twenty-six individuals had LRHP or abnormal pituitary findings on MRI. Tetrahydrobiopterin deficiencies were the most common diagnoses (n = 22). The median age at diagnosis of LRHP was 16 years (range: 2.5-30, 1st-3rd quartiles: 12.25-17 years). Twelve individuals (nine females) had symptoms attributed to hyperprolactinemia: menstruation-related abnormalities (n = 7), pubertal delay or arrest (n = 5), galactorrhea (n = 3), and decreased sexual functions (n = 2). MRI of the pituitary gland was obtained in 21 individuals; six had heterogeneity/hyperplasia of the gland, five had adenoma, and 10 had normal findings. Eleven individuals were treated with the dopamine agonist cabergoline, ameliorating the hyperprolactinemia-related symptoms in all those assessed. Routine monitoring of these symptoms together with prolactin concentrations, especially after the first decade of life, should be taken into consideration during follow-up evaluations. The potential of slow-release levodopa formulations and low-dose dopamine agonists as part of first-line therapy in the prevention and treatment of hyperprolactinemia should be investigated further in animal studies and human trials. This work adds hyperprolactinemia-related findings to the current knowledge of the phenotypic spectrum of inherited disorders of biogenic amine metabolism.

The whole-genome landscape of medulloblastoma subtypes.

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

cola: an R/Bioconductor package for consensus partitioning through a general framework.

Classification of high-throughput genomic data is a powerful method to assign samples to subgroups with specific molecular profiles. Consensus partitioning is the most widely applied approach to reveal subgroups by summarizing a consensus classification from a list of individual classifications generated by repeatedly executing clustering on random subsets of the data. It is able to evaluate the stability of the classification. We implemented a new R/Bioconductor package, cola, that provides a general framework for consensus partitioning. With cola, various parameters and methods can be user-defined and easily integrated into different steps of an analysis, e.g., feature selection, sample classification or defining signatures. cola provides a new method named ATC (ability to correlate to other rows) to extract features and recommends spherical k-means clustering (skmeans) for subgroup classification. We show that ATC and skmeans have better performance than other commonly used methods by a comprehensive benchmark on public datasets. We also benchmark key parameters in the consensus partitioning procedure, which helps users to select optimal parameter values. Moreover, cola provides rich functionalities to apply multiple partitioning methods in parallel and directly compare their results, as well as rich visualizations. cola can automate the complete analysis and generates a comprehensive HTML report.

Bcl-xL as prognostic marker and potential therapeutic target in cholangiocarcinoma.

Intrahepatic, perihilar, and distal cholangiocarcinoma (iCCA, pCCA, dCCA) are highly malignant tumours with increasing mortality rates due to therapy resistances. Among the mechanisms mediating resistance, overexpression of anti-apoptotic Bcl-2 proteins (Bcl-2, Bcl-xL , Mcl-1) is particularly important. In this study, we investigated whether antiapoptotic protein patterns are prognostically relevant and potential therapeutic targets in CCA. Bcl-2 proteins were analysed in a pan-cancer cohort from the NCT/DKFZ/DKTK MASTER registry trial (n = 1140, CCA n = 72) via RNA-sequencing and transcriptome-based protein activity interference revealing high ranks of CCA for Bcl-xL and Mcl-1. Expression of Bcl-xL , Mcl-1, and Bcl-2 was assessed in human CCA tissue and cell lines compared with cholangiocytes by immunohistochemistry, immunoblotting, and quantitative-RT-PCR. Immunohistochemistry confirmed the upregulation of Bcl-xL and Mcl-1 in iCCA tissues. Cell death of CCA cell lines upon treatment with specific small molecule inhibitors of Bcl-xL (Wehi-539), of Mcl-1 (S63845), and Bcl-2 (ABT-199), either alone, in combination with each other or together with chemotherapeutics was assessed by flow cytometry. Targeting Bcl-xL induced cell death and augmented the effect of chemotherapy in CCA cells. Combined inhibition of Bcl-xL and Mcl-1 led to a synergistic increase in cell death in CCA cell lines. Correlation between Bcl-2 protein expression and survival was analysed within three independent patient cohorts from cancer centers in Germany comprising 656 CCA cases indicating a prognostic value of Bcl-xL in CCA depending on the CCA subtype. Collectively, these observations identify Bcl-xL as a key protein in cell death resistance of CCA and may pave the way for clinical application.

Poly(ADP-ribose) polymerase inhibition in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with limited treatment options. Recently, the poly(ADP-ribose) polymerase inhibitor (PARPi) olaparib has been approved for maintenance therapy after successful platinum-based chemotherapy in patients with germline mutations in BRCA1 and BRCA2. Approval was based on the POLO study that has shown a significant improvement in progression-free survival for patients with metastatic PDAC after at least 4 months of platinum-based chemotherapy. Hopefully, this first biomarker-directed targeted therapy for a relevant subgroup of pancreatic cancer patients is only the beginning of an era of personalized therapy for pancreatic cancer. The potential role for PARPi in improving survival in patients with pancreatic cancer containing somatic tumor mutations has yet to be established. Multiple studies investigating whether PARPi therapy might benefit a larger group of pancreatic cancer patients with homologous recombination repair deficiency and whether combinations with chemotherapy, immunotherapy, or small molecules can improve efficacy are currently underway. We here review the molecular basis for PARPi therapy in PDAC patients and recent developments in clinical studies.

Analysis of mutational signatures with yet another package for signature analysis.

Different mutational processes leave characteristic patterns of somatic mutations in the genome that can be identified as mutational signatures. Determining the contributions of mutational signatures to cancer genomes allows not only to reconstruct the etiology of somatic mutations, but can also be used for improved tumor classification and support therapeutic decisions. We here present the R package yet another package for signature analysis (YAPSA) to deconvolute the contributions of mutational signatures to tumor genomes. YAPSA provides in-built collections from the COSMIC and PCAWG SNV signature sets as well as the PCAWG Indel signatures and employs signature-specific cutoffs to increase sensitivity and specificity. Furthermore, YAPSA allows to determine 95% confidence intervals for signature exposures, to perform constrained stratified signature analyses to obtain enrichment and depletion patterns of the identified signatures and, when applied to whole exome sequencing data, to correct for the triplet content of individual target capture kits. With this functionality, YAPSA has proved to be a valuable tool for analysis of mutational signatures in molecular tumor boards in a precision oncology context. YAPSA is available at R/Bioconductor (http://bioconductor.org/packages/3.12/bioc/html/YAPSA.html).

The mutational landscape of Burkitt-like lymphoma with 11q aberration is distinct from that of Burkitt lymphoma.

The new recently described provisional lymphoma category Burkitt-like lymphoma with 11q aberration comprises cases similar to Burkitt lymphoma (BL) on morphological, immunophenotypic and gene-expression levels but lacking the IG-MYC translocation. They are characterized by a peculiar imbalance pattern on chromosome 11, but the landscape of mutations is not yet described. Thus, we investigated 15 MYC-negative Burkitt-like lymphoma with 11q aberration (mnBLL,11q,) cases by copy-number analysis and whole-exome sequencing. We refined the regions of 11q imbalance and identified the INO80 complex-associated gene NFRKB as a positional candidate in 11q24.3. Next to recurrent gains in 12q13.11-q24.32 and 7q34-qter as well as losses in 13q32.3-q34, we identified 47 genes recurrently affected by protein-changing mutations (each ≥3 of 15 cases). Strikingly, we did not detect recurrent mutations in genes of the ID3-TCF3 axis or the SWI/SNF complex that are frequently altered in BL, or in genes frequently mutated in germinal center-derived B-cell lymphomas like KMT2D or CREBBP An exception is GNA13, which was mutated in 7 of 15 cases. We conclude that the genomic landscape of mnBLL,11q, differs from that of BL both at the chromosomal and mutational levels. Our findings implicate that mnBLL,11q, is a lymphoma category distinct from BL at the molecular level.

Germline SDHB-inactivating mutation in gastric spindle cell sarcoma.

Gastrointestinal stromal tumors (GISTs) are the most frequent mesenchymal tumors of the gastrointestinal tract. Inactivating mutations or epigenetic deregulation of succinate dehydrogenase complex (SDH) genes are considered defining features of a subset of GIST occurring in the stomach. Based on comprehensive molecular profiling and biochemical analysis within a precision oncology program, we identified hallmarks of SDH deficiency (germline SDHB-inactivating mutation accompanied by somatic loss of heterozygosity, lack of SDHB expression, global DNA hypermethylation, and elevated succinate/fumarate ratio) in a 40-year-old woman with undifferentiated gastric spindle cell sarcoma that did not meet the diagnostic criteria for other mesenchymal tumors of the stomach, including GIST. These data reveal that the loss of SDH function can be involved in the pathogenesis of non-GIST sarcoma of the gastrointestinal tract.

IG-MYC + neoplasms with precursor B-cell phenotype are molecularly distinct from Burkitt lymphomas.

The WHO Classification of Tumours of Haematopoietic and Lymphoid Tissue notes instances of Burkitt lymphoma/leukemia (BL) with IG-MYC rearrangement displaying a B-cell precursor immunophenotype (termed herein "preBLL"). To characterize the molecular pathogenesis of preBLL, we investigated 13 preBLL cases (including 1 cell line), of which 12 were analyzable using genome, exome, and targeted sequencing, imbalance mapping, and DNA methylation profiling. In 5 patients with reads across the IG-MYC breakpoint junctions, we found evidence that the translocation derived from an aberrant VDJ recombination, as is typical for IG translocations arising in B-cell precursors. Genomic changes like biallelic IGH translocations or VDJ rearrangements combined with translocation into the VDJ region on the second allele, potentially preventing expression of a productive immunoglobulin, were detected in 6 of 13 cases. We did not detect mutations in genes frequently altered in BL, but instead found activating NRAS and/or KRAS mutations in 7 of 12 preBLLs. Gains on 1q, recurrent in BL and preB lymphoblastic leukemia/lymphoma (pB-ALL/LBL), were detected in 7 of 12 preBLLs. DNA methylation profiling showed preBLL to cluster with precursor B cells and pB-ALL/LBL, but apart from BL. We conclude that preBLL genetically and epigenetically resembles pB-ALL/LBL rather than BL. Therefore, we propose that preBLL be considered as a pB-ALL/LBL with recurrent genetic abnormalities.

Mutational patterns and regulatory networks in epigenetic subgroups of meningioma.

DNA methylation patterns delineate clinically relevant subgroups of meningioma. We previously established the six meningioma methylation classes (MC) benign 1-3, intermediate A and B, and malignant. Here, we set out to identify subgroup-specific mutational patterns and gene regulation. Whole genome sequencing was performed on 62 samples across all MCs and WHO grades from 62 patients with matched blood control, including 40 sporadic meningiomas and 22 meningiomas arising after radiation (Mrad). RNA sequencing was added for 18 of these cases and chromatin-immunoprecipitation for histone H3 lysine 27 acetylation (H3K27ac) followed by sequencing (ChIP-seq) for 16 samples. Besides the known mutations in meningioma, structural variants were found as the mechanism of NF2 inactivation in a small subset (5%) of sporadic meningiomas, similar to previous reports for Mrad. Aberrations of DMD were found to be enriched in MCs with NF2 mutations, and DMD was among the most differentially upregulated genes in NF2 mutant compared to NF2 wild-type cases. The mutational signature AC3, which has been associated with defects in homologous recombination repair (HRR), was detected in both sporadic meningioma and Mrad, but widely distributed across the genome in sporadic cases and enriched near genomic breakpoints in Mrad. Compared to the other MCs, the number of single nucleotide variants matching the AC3 pattern was significantly higher in the malignant MC, which also exhibited higher genomic instability, determined by the numbers of both large segments affected by copy number alterations and breakpoints between large segments. ChIP-seq analysis for H3K27ac revealed a specific activation of genes regulated by the transcription factor FOXM1 in the malignant MC. This analysis also revealed a super enhancer near the HOXD gene cluster in this MC, which, together with general upregulation of HOX genes in the malignant MC, indicates a role of HOX genes in meningioma aggressiveness. This data elucidates the biological mechanisms rendering different epigenetic subgroups of meningiomas, and suggests leveraging HRR as a novel therapeutic target.