Sample processing obscures cancer-specific alterations in leukemic transcriptomes

The Impact of Blood Sample Processing on Ribonucleic Acid (RNA) Sequencing

In gene quantification and expression analysis, issues with sample selection and processing can be serious, as they can easily introduce irrelevant variables and lead to ambiguous results. This study aims to investigate the extent and mechanism of the impact of sample selection and processing on ribonucleic acid (RNA) sequencing. RNA from PBMCs and blood samples was investigated in this study. The integrity of this RNA was measured under different storage times. All the samples underwent high-throughput sequencing for comprehensive evaluation. The differentially expressed genes and their potential functions were analyzed after the samples were placed at room temperature for 0h, 4h and 8h, and different feature changes in these samples were also revealed. The sequencing results showed that the differences in gene expression were higher with an increased storage time, while the total number of genes detected did not change significantly. There were five genes showing gradient patterns over different storage times, all of which were protein-coding genes that had not been mentioned in previous studies. The effect of different storage times on seemingly the same samples was analyzed in this present study. This research, therefore, provides a theoretical basis for the long-term consideration of whether sample processing should be adequately addressed.

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

Evaluation of Collection and Processing Conditions for Gene Expression Analysis Using Human Myeloid Cells

Background: The population of blast cells among peripheral blood mononuclear cells (PBMCs) obtained from patients is a desirable specimen for analyzing gene expression in diseases including acute myeloid leukemia. Although the enrichment of blast cells often needs to be performed at a central laboratory, acceptable conditions for sample transport from clinical sites remain to be established. Methods: We evaluated storage temperature, duration, and tube type before initiating sample processing for the analysis of cluster of differentiation (CD)33+ myeloid cells among PBMCs as an alternative to CD34+/CD33+ blast cells. Results: CD33+ myeloid cells were successfully purified by MACS. The cell viability and the RNA integrity were sustained during storage up to 48 hours before sample processing. Storage at 4°C had minimal effects on gene expression, whereas storage at room temperature induced the senescence pathway, characterized by the expression of stress-inducible genes. A CPT tube was also better than an ethylenediaminetetraacetic acid tube for minimizing gene expression change. Conclusions: Our study provided important clues for establishing a sample handling approach for gene expression analysis with purified cell fractions from human PBMCs. To keep the variation of gene expression to a minimum, samples should be delivered at 4°C within 48 hours before processing.

Multiplexed screening reveals how cancer-specific alternative polyadenylation shapes tumor growth in vivo

Alternative polyadenylation (APA) is strikingly dysregulated in many cancers. Although global APA dysregulation is frequently associated with poor prognosis, the importance of most individual APA events is controversial simply because few have been functionally studied. Here, we address this gap by developing a CRISPR-Cas9-based screen to manipulate endogenous polyadenylation and systematically quantify how APA events contribute to tumor growth in vivo. Our screen reveals individual APA events that control mouse melanoma growth in an immunocompetent host, with concordant associations in clinical human cancer. For example, forced Atg7 3' UTR lengthening in mouse melanoma suppresses ATG7 protein levels, slows tumor growth, and improves host survival; similarly, in clinical human melanoma, a long ATG7 3' UTR is associated with significantly prolonged patient survival. Overall, our study provides an easily adaptable means to functionally dissect APA in physiological systems and directly quantifies the contributions of recurrent APA events to tumorigenic phenotypes.

Multi-Algorithm Analysis Reveals Pyroptosis-Linked Genes as Pancreatic Cancer Biomarkers

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at late stages, limiting treatment options and survival rates. Pyroptosis-related gene signatures hold promise as PDAC prognostic markers, but limited gene pools and small sample sizes hinder their utility. We aimed to enhance PDAC prognosis with a comprehensive multi-algorithm analysis. Using R, we employed natural language processing and latent Dirichlet allocation on PubMed publications to identify pyroptosis-related genes. We collected PDAC transcriptome data (n = 1273) from various databases, conducted a meta-analysis, and performed differential gene expression analysis on tumour and non-cancerous tissues. Cox and LASSO algorithms were used for survival modelling, resulting in a pyroptosis-related gene expression-based prognostic index. Laboratory and external validations were conducted. Bibliometric analysis revealed that pyroptosis publications focus on signalling pathways, disease correlation, and prognosis. We identified 357 pyroptosis-related genes, validating the significance of BHLHE40, IL18, BIRC3, and APOL1. Elevated expression of these genes strongly correlated with poor PDAC prognosis and guided treatment strategies. Our accessible nomogram model aids in PDAC prognosis and treatment decisions. We established an improved gene signature for pyroptosis-related genes, offering a novel model and nomogram for enhanced PDAC prognosis.

SF3B1 mutation-mediated sensitization to H3B-8800 splicing inhibitor in chronic lymphocytic leukemia

Splicing factor 3B subunit 1 (SF3B1) is involved in pre-mRNA branch site recognition and is the target of antitumor-splicing inhibitors. Mutations in SF3B1 are observed in 15% of patients with chronic lymphocytic leukemia (CLL) and are associated with poor prognosis, but their pathogenic mechanisms remain poorly understood. Using deep RNA-sequencing data from 298 CLL tumor samples and isogenic SF3B1 WT and K700E-mutated CLL cell lines, we characterize targets and pre-mRNA sequence features associated with the selection of cryptic 3' splice sites upon SF3B1 mutation, including an event in the MAP3K7 gene relevant for activation of NF-κB signaling. Using the H3B-8800 splicing modulator, we show, for the first time in CLL, cytotoxic effects in vitro in primary CLL samples and in SF3B1-mutated isogenic CLL cell lines, accompanied by major splicing changes and delayed leukemic infiltration in a CLL xenotransplant mouse model. H3B-8800 displayed preferential lethality towards SF3B1-mutated cells and synergism with the BCL2 inhibitor venetoclax, supporting the potential use of SF3B1 inhibitors as a novel therapeutic strategy in CLL.

Subgroup-specific gene expression profiles and mixed epistasis in chronic lymphocytic leukemia

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease's diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

Multiparametric senescent cell phenotyping reveals targets of senolytic therapy in the aged murine skeleton

Senescence drives organismal aging, yet the deep characterization of senescent cells in vivo remains incomplete. Here, we apply mass cytometry by time-of-flight using carefully validated antibodies to analyze senescent cells at single-cell resolution. We use multiple criteria to identify senescent mesenchymal cells that are growth-arrested and resistant to apoptosis. These p16 + Ki67-BCL-2+ cells are highly enriched for senescence-associated secretory phenotype and DNA damage markers, are strongly associated with age, and their percentages are increased in late osteoblasts/osteocytes and CD24high osteolineage cells. Moreover, both late osteoblasts/osteocytes and CD24high osteolineage cells are robustly cleared by genetic and pharmacologic senolytic therapies in aged mice. Following isolation, CD24+ skeletal cells exhibit growth arrest, senescence-associated β-galactosidase positivity, and impaired osteogenesis in vitro. These studies thus provide an approach using multiplexed protein profiling to define senescent mesenchymal cells in vivo and identify specific skeletal cell populations cleared by senolytics.

Recursive splicing discovery using lariats in total RNA sequencing

Recursive splicing is a non-canonical splicing mechanism in which an intron is removed in segments via multiple splicing reactions. Relatively few recursive splice sites have been identified with high confidence in human introns, and more comprehensive analyses are needed to better characterize where recursive splicing happens and whether or not it has a regulatory function. In this study, we use an unbiased approach using intron lariats to search for recursive splice sites in constitutive introns and alternative exons in the human transcriptome. We find evidence for recursive splicing in a broader range of intron sizes than previously reported and detail a new location for recursive splicing at the distal ends of cassette exons. In addition, we identify evidence for the conservation of these recursive splice sites among higher vertebrates and the use of these sites to influence alternative exon exclusion. Together, our data demonstrate the prevalence of recursive splicing and its potential influence on gene expression through alternatively spliced isoforms.

Multiparametric senescent cell phenotyping reveals CD24 osteolineage cells as targets of senolytic therapy in the aged murine skeleton

Senescence drives organismal aging, yet the deep characterization of senescent cells in vivo remains incomplete. Here, we applied mass cytometry by time-of-flight (CyTOF) using carefully validated antibodies to analyze senescent cells at single-cell resolution. We used multiple criteria to identify senescent mesenchymal cells that were growth arrested and resistant to apoptosis (p16+/Ki67-/BCL-2+; "p16KB" cells). These cells were highly enriched for senescence-associated secretory phenotype (SASP) and DNA damage markers and were strongly associated with age. p16KB cell percentages were also increased in CD24+ osteolineage cells, which exhibited an inflammatory SASP in aged mice and were robustly cleared by both genetic and pharmacologic senolytic therapies. Following isolation, CD24+ skeletal cells exhibited growth arrest, SA-βgal positivity, and impaired osteogenesis in vitro . These studies thus provide a new approach using multiplexed protein profiling by CyTOF to define senescent mesenchymal cells in vivo and identify a highly inflammatory, senescent CD24+ osteolineage population cleared by senolytics.

Molecular map of chronic lymphocytic leukemia and its impact on outcome

Recent advances in cancer characterization have consistently revealed marked heterogeneity, impeding the completion of integrated molecular and clinical maps for each malignancy. Here, we focus on chronic lymphocytic leukemia (CLL), a B cell neoplasm with variable natural history that is conventionally categorized into two subtypes distinguished by extent of somatic mutations in the heavy-chain variable region of immunoglobulin genes (IGHV). To build the 'CLL map,' we integrated genomic, transcriptomic and epigenomic data from 1,148 patients. We identified 202 candidate genetic drivers of CLL (109 new) and refined the characterization of IGHV subtypes, which revealed distinct genomic landscapes and leukemogenic trajectories. Discovery of new gene expression subtypes further subcategorized this neoplasm and proved to be independent prognostic factors. Clinical outcomes were associated with a combination of genetic, epigenetic and gene expression features, further advancing our prognostic paradigm. Overall, this work reveals fresh insights into CLL oncogenesis and prognostication.

Timing of Blood Sample Processing Affects the Transcriptomic and Epigenomic Profiles in CD4+ T-cells of Atopic Subjects

Optimal pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4⁺ T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, CD4⁺ T-cells were isolated from the first blood sample within 2 h (immediate) or from the second blood sample after 24 h storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed CD4⁺ T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed CD4⁺ T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood CD4⁺ T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operation procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.

Circular RNAs in peripheral blood mononuclear cells are more stable than linear RNAs upon sample processing delay

Circular RNAs (circRNAs) are a novel class of RNAs with closed loop structure. Blood circRNAs are widely acknowledged to be more stable than linear mRNAs, which show promising prospect to be liquid biopsy biomarkers for clinical applications. However, accumulating studies have demonstrated that sample processing delays have profound effects on blood transcriptome expression profiles, wherein knowledge remains elusive about the impacts of prolonged sample processing on blood expression profiles of circRNAs. We collected whole blood samples from three donors and isolated peripheral blood mononuclear cells (PBMCs) at six different incubation time points. We measured total RNA expression profiles using RNA sequencing (RNA‐seq) and investigated the differentially expressed circRNAs, mRNAs and lncRNAs upon blood processing delay. Meanwhile, we explored the underlying inducement of aberrant expression of circRNAs against their corresponding mRNA transcripts. Finally, we utilized rMATS‐turbo and CIRI‐AS, respectively, to screen out differential alternative splicing (AS) events in linear mRNAs and circRNAs. Sample incubation at 4°C lasting to 48 hours (h) led to minimal effects to circRNAs' expression. However, it induced extensive alterations for mRNAs and lncRNAs when the incubation time was beyond 12 h. Additionally, only 2 h processing delays may result in profound impacts on AS events of linear mRNAs, while less impact on the equivalence of circRNAs. Our results suggested that PBMC circRNAs are stable upon sample processing delay, which are more suitable to be liquid biopsy biomarkers.

Identification of Novel Therapeutic Candidates Against SARS-CoV-2 Infections: An Application of RNA Sequencing Toward mRNA Based Nanotherapeutics

Due to fast transmission and various circulating SARS-CoV-2 variants, a significant increase of coronavirus 2019 infection cases with acute respiratory symptoms has prompted worries about the efficiency of current vaccines. The possible evasion from vaccine immunity urged scientists to identify novel therapeutic targets for developing improved vaccines to manage worldwide COVID-19 infections. Our study sequenced pooled peripheral blood mononuclear cells transcriptomes of SARS-CoV-2 patients with moderate and critical clinical outcomes to identify novel potential host receptors and biomarkers that can assist in developing new translational nanomedicines and vaccine therapies. The dysregulated signatures were associated with humoral immune responses in moderate and critical patients, including B-cell activation, cell cycle perturbations, plasmablast antibody processing, adaptive immune responses, cytokinesis, and interleukin signaling pathway. The comparative and longitudinal analysis of moderate and critically infected groups elucidated diversity in regulatory pathways and biological processes. Several immunoglobin genes (IGLV9-49, IGHV7-4, IGHV3-64, IGHV1-24, IGKV1D-12, and IGKV2-29), ribosomal proteins (RPL29, RPL4P2, RPL5, and RPL14), inflammatory response related cytokines including Tumor Necrosis Factor (TNF, TNFRSF17, and TNFRSF13B), C-C motif chemokine ligands (CCL3, CCL25, CCL4L2, CCL22, and CCL4), C-X-C motif chemokine ligands (CXCL2, CXCL10, and CXCL11) and genes related to cell cycle process and DNA proliferation (MYBL2, CDC20, KIFC1, and UHCL1) were significantly upregulated among SARS-CoV-2 infected patients. 60S Ribosomal protein L29 (RPL29) was a highly expressed gene among all COVID-19 infected groups. Our study suggested that identifying differentially expressed genes (DEGs) based on disease severity and onset can be a powerful approach for identifying potential therapeutic targets to develop effective drug delivery systems against SARS-CoV-2 infections. As a result, potential therapeutic targets, such as the RPL29 protein, can be tested in vivo and in vitro to develop future mRNA-based translational nanomedicines and therapies to combat SARS-CoV-2 infections.

Multiple Mechanisms of NOTCH1 Activation in Chronic Lymphocytic Leukemia: NOTCH1 Mutations and Beyond

Simple Summary

Mutations of the NOTCH1 gene are a validated prognostic marker in chronic lymphocytic leukemia and a potential predictive marker for anti-CD20-based therapies. At present, the most frequent pathological alteration of the NOTCH1 gene is due to somatic genetic mutations, which have a multifaceted functional impact. However, beside NOTCH1 mutations, other factors may lead to activation of the NOTCH1 pathway, and these include mutations of FBXW7, MED12, SPEN, SF3B1 as well as other B-cell pathways. Understanding the preferential strategies though which CLL cells hijack NOTCH1 signaling may present important clues for designing targeted treatment strategies for the management of CLL.

Abstract

The Notch signaling pathway plays a fundamental role for the terminal differentiation of multiple cell types, including B and T lymphocytes. The Notch receptors are transmembrane proteins that, upon ligand engagement, undergo multiple processing steps that ultimately release their intracytoplasmic portion. The activated protein ultimately operates as a nuclear transcriptional co-factor, whose stability is finely regulated. The Notch pathway has gained growing attention in chronic lymphocytic leukemia (CLL) because of the high rate of somatic mutations of the NOTCH1 gene. In CLL, NOTCH1 mutations represent a validated prognostic marker and a potential predictive marker for anti-CD20-based therapies, as pathological alterations of the Notch pathway can provide significant growth and survival advantage to neoplastic clone. However, beside NOTCH1 mutation, other events have been demonstrated to perturb the Notch pathway, namely somatic mutations of upstream, or even apparently unrelated, proteins such as FBXW7, MED12, SPEN, SF3B1, as well as physiological signals from other pathways such as the B-cell receptor. Here we review these mechanisms of activation of the NOTCH1 pathway in the context of CLL; the resulting picture highlights how multiple different mechanisms, that might occur under specific genomic, phenotypic and microenvironmental contexts, ultimately result in the same search for proliferative and survival advantages (through activation of MYC), as well as immune escape and therapy evasion (from anti-CD20 biological therapies). Understanding the preferential strategies through which CLL cells hijack NOTCH1 signaling may present important clues for designing targeted treatment strategies for the management of CLL.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

Pharmacologic modulation of RNA splicing enhances anti-tumor immunity

Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic.

Minor intron retention drives clonal hematopoietic disorders and diverse cancer predisposition

Most eukaryotes harbor two distinct pre-mRNA splicing machineries: the major spliceosome, which removes >99% of introns, and the minor spliceosome, which removes rare, evolutionarily conserved introns. Although hypothesized to serve important regulatory functions, physiologic roles of the minor spliceosome are not well understood. For example, the minor spliceosome component ZRSR2 is subject to recurrent, leukemia-associated mutations, yet functional connections among minor introns, hematopoiesis and cancers are unclear. Here, we identify that impaired minor intron excision via ZRSR2 loss enhances hematopoietic stem cell self-renewal. CRISPR screens mimicking nonsense-mediated decay of minor intron-containing mRNA species converged on LZTR1, a regulator of RAS-related GTPases. LZTR1 minor intron retention was also discovered in the RASopathy Noonan syndrome, due to intronic mutations disrupting splicing and diverse solid tumors. These data uncover minor intron recognition as a regulator of hematopoiesis, noncoding mutations within minor introns as potential cancer drivers and links among ZRSR2 mutations, LZTR1 regulation and leukemias.

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing

Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMC up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

•

Studies of human blood cells and plasma are highly sensitive to process variability

•

Time variability distorts biology in cutting-edge single-cell and multiplex assays

•

Longitudinal, multi-modal, and aligned data enable data qualification and exploration

•

Dataset holds potential novel, multi-modal biological correlations and hypotheses

Convergent organization of aberrant MYB complex controls oncogenic gene expression in acute myeloid leukemia

Dysregulated gene expression contributes to most prevalent features in human cancers. Here, we show that most subtypes of acute myeloid leukemia (AML) depend on the aberrant assembly of MYB transcriptional co-activator complex. By rapid and selective peptidomimetic interference with the binding of CBP/P300 to MYB, but not CREB or MLL1, we find that the leukemic functions of MYB are mediated by CBP/P300 co-activation of a distinct set of transcription factor complexes. These MYB complexes assemble aberrantly with LYL1, E2A, C/EBP family members, LMO2, and SATB1. They are organized convergently in genetically diverse subtypes of AML and are at least in part associated with inappropriate transcription factor co-expression. Peptidomimetic remodeling of oncogenic MYB complexes is accompanied by specific proteolysis and dynamic redistribution of CBP/P300 with alternative transcription factors such as RUNX1 to induce myeloid differentiation and apoptosis. Thus, aberrant assembly and sequestration of MYB:CBP/P300 complexes provide a unifying mechanism of oncogenic gene expression in AML. This work establishes a compelling strategy for their pharmacologic reprogramming and therapeutic targeting for diverse leukemias and possibly other human cancers caused by dysregulated gene control.

The origins and consequences of UPF1 variants in pancreatic adenosquamous carcinoma

Pancreatic adenosquamous carcinoma (PASC) is an aggressive cancer whose mutational origins are poorly understood. An early study reported high-frequency somatic mutations affecting UPF1, a nonsense-mediated mRNA decay (NMD) factor, in PASC, but subsequent studies did not observe these lesions. The corresponding controversy about whether UPF1 mutations are important contributors to PASC has been exacerbated by a paucity of functional studies. Here, we modeled two UPF1 mutations in human and mouse cells to find no significant effects on pancreatic cancer growth, acquisition of adenosquamous features, UPF1 splicing, UPF1 protein, or NMD efficiency. We subsequently discovered that 45% of UPF1 mutations reportedly present in PASCs are identical to standing genetic variants in the human population, suggesting that they may be non-pathogenic inherited variants rather than pathogenic mutations. Our data suggest that UPF1 is not a common functional driver of PASC and motivate further attempts to understand the genetic origins of these malignancies.

The effects of sample handling on proteomics assessed by reverse phase protein arrays (RPPA): Functional proteomic profiling in leukemia

Reverse phase protein arrays (RPPA) can assess protein expression and activation states in large numbers of samples (n > 1000) and evidence suggests feasibility in the setting of multi-institution clinical trials. Despite evidence in solid tumors, little is known about protein stability in leukemia. Proteins collected from leukemia cells in blood and bone marrow biopsies must be sufficiently stable for analysis. Using 58 leukemia samples, we initially assessed protein/phospho-protein integrity for the following preanalytical variables: 1) shipping vs local processing, 2) temperature (4 °C vs ambient temperature), 3) collection tube type (heparin vs Cell Save (CS) preservation tubes), 4) treatment effect (pre- vs post-chemotherapy) and 5) transit time. Next, we assessed 1515 samples from the Children's Oncology Group Phase 3 AML clinical trial (AAML1031, NCT01371981) for the effects of transit time and tube type. Protein expression from shipped blood samples was stable if processed in ≤72 h. While protein expression in pre-chemotherapy samples was stable in both heparin and CS tubes, post-chemotherapy samples were stable in only CS tubes. RPPA protein extremes is a successful quality control measure to identify and exclude poor quality samples. These data demonstrate that a majority of shipped proteins can be accurately assessed using RPPA. SIGNIFICANCE: RPPA can assess protein abundance and activation states in large numbers of samples using small amounts of material, making this method ideal for use in multi-institution clinical trials. However, there is little known about the effect of preanalytical handling variables on protein stability and the integrity of protein concentrations after sample collection and shipping. In this study, we used RPPA to assess preanalytical variables that could potentially affect protein concentrations. We found that the preanalytical variables of shipping, transit time, and temperature had minimal effects on RPPA protein concentration distributions in peripheral blood and bone marrow, demonstrating that these preanalytical variables could be successfully managed in a multi-site clinical trial setting.

RainDrop: Rapid activation matrix computation for droplet-based single-cell RNA-seq reads

Background

Obtaining data from single-cell transcriptomic sequencing allows for the investigation of cell-specific gene expression patterns, which could not be addressed a few years ago. With the advancement of droplet-based protocols the number of studied cells continues to increase rapidly. This establishes the need for software tools for efficient processing of the produced large-scale datasets. We address this need by presenting RainDrop for fast gene-cell count matrix computation from single-cell RNA-seq data produced by 10x Genomics Chromium technology.

Results

RainDrop can process single-cell transcriptomic datasets consisting of 784 million reads sequenced from around 8.000 cells in less than 40 minutes on a standard workstation. It significantly outperforms the established Cell Ranger pipeline and the recently introduced Alevin tool in terms of runtime by a maximal (average) speedup of 30.4 (22.6) and 3.5 (2.4), respectively, while keeping high agreements of the generated results.

Conclusions

RainDrop is a software tool for highly efficient processing of large-scale droplet-based single-cell RNA-seq datasets on standard workstations written in C++. It is available at https://gitlab.rlp.net/stnieble/raindrop.

Sampling time-dependent artifacts in single-cell genomics studies

Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis

Single-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

Maeve O’Huallachain et al. report a method that enables simultaneous, ultra-high throughput single-cell barcoding for targeted single-cell protein and RNA analysis. They show the utility of their method in analyses of mRNA and protein expression in human and mouse cells.

Loss of MBNL1 induces RNA misprocessing in the thymus and peripheral blood

The thymus is a primary lymphoid organ that plays an essential role in T lymphocyte maturation and selection during development of one arm of the mammalian adaptive immune response. Although transcriptional mechanisms have been well documented in thymocyte development, co-/post-transcriptional modifications are also important but have received less attention. Here we demonstrate that the RNA alternative splicing factor MBNL1, which is sequestered in nuclear RNA foci by C(C)UG microsatellite expansions in myotonic dystrophy (DM), is essential for normal thymus development and function. Mbnl1 129S1 knockout mice develop postnatal thymic hyperplasia with thymocyte accumulation. Transcriptome analysis indicates numerous gene expression and RNA mis-splicing events, including transcription factors from the TCF/LEF family. CNBP, the gene containing an intronic CCTG microsatellite expansion in DM type 2 (DM2), is coordinately expressed with MBNL1 in the developing thymus and DM2 CCTG expansions induce similar transcriptome alterations in DM2 blood, which thus serve as disease-specific biomarkers.

RNA-Seq of human whole blood: Evaluation of globin RNA depletion on Ribo-Zero library method

Peripheral blood is a highly accessible biofluid providing a rich source of information about human physiology and health status. However, for studies of the blood transcriptome with RNA sequencing (RNA-Seq) techniques, high levels of hemoglobin mRNAs (hgbRNA) present in blood can occupy valuable sequencing space, impacting detection and quantification of non-hgbRNAs. In this study, we evaluated two methods for preparing ribosomal RNA (rRNA)-depleted sequencing libraries for RNA-Seq of whole blood, one of which is also designed to deplete hgbRNAs. Two experiments were performed: one evaluating library performance across 6 human blood samples and the other examining library reproducibility and performance in a two-subject subset. We find that addition of hgbRNA depletion to the rRNA-depletion protocol for library preparation from blood RNA effectively reduces highly abundant hgbRNA reads; however, it does not result in a statistically significant increase in differentially expressed genes in our patient-control study. Bioinformatic removal of globin gene counts in non-hgbRNA depleted libraries provides improvement in overall performance of these libraries. We conclude that use of a standard ribosomal RNA depletion method for library preparation coupled with bioinformatic removal of globin gene counts is sufficient for reproducible and sensitive measurement of both coding and noncoding RNAs in the blood transcriptome.

Transgenic mice expressing tunable levels of DUX4 develop characteristic facioscapulohumeral muscular dystrophy-like pathophysiology ranging in severity

Background

All types of facioscapulohumeral muscular dystrophy (FSHD) are caused by the aberrant activation of the somatically silent DUX4 gene, the expression of which initiates a cascade of cellular events ultimately leading to FSHD pathophysiology. Typically, progressive skeletal muscle weakness becomes noticeable in the second or third decade of life, yet there are many individuals who are genetically FSHD but develop symptoms much later in life or remain relatively asymptomatic throughout their lives. Conversely, FSHD may clinically present prior to 5–10 years of age, ultimately manifesting as a severe early-onset form of the disease. These phenotypic differences are thought to be due to the timing and levels of DUX4 misexpression.

Methods

FSHD is a dominant gain-of-function disease that is amenable to modeling by DUX4 overexpression. We have recently created a line of conditional DUX4 transgenic mice, FLExDUX4, that develop a myopathy upon induction of human DUX4-fl expression in skeletal muscle. Here, we use the FLExDUX4 mouse crossed with the skeletal muscle-specific and tamoxifen-inducible line ACTA1-MerCreMer to generate a highly versatile bi-transgenic mouse model with chronic, low-level DUX4-fl expression and cumulative mild FSHD-like pathology that can be reproducibly induced to develop more severe pathology via tamoxifen induction of DUX4-fl in skeletal muscles.

Results

We identified conditions to generate FSHD-like models exhibiting reproducibly mild, moderate, or severe DUX4-dependent pathophysiology and characterized progression of pathology. We assayed DUX4-fl mRNA and protein levels, fitness, strength, global gene expression, and histopathology, all of which are consistent with an FSHD-like myopathic phenotype. Importantly, we identified sex-specific and muscle-specific differences that should be considered when using these models for preclinical studies.

Conclusions

The ACTA1-MCM;FLExDUX4 bi-transgenic mouse model has mild FSHD-like pathology and detectable muscle weakness. The onset and progression of more severe DUX4-dependent pathologies can be controlled via tamoxifen injection to increase the levels of mosaic DUX4-fl expression, providing consistent and readily screenable phenotypes for assessing therapies targeting DUX4-fl mRNA and/or protein and are useful to investigate certain conserved downstream FSHD-like pathophysiology. Overall, this model supports that DUX4 expression levels in skeletal muscle directly correlate with FSHD-like pathology by numerous metrics.

RNA isoform screens uncover the essentiality and tumor-suppressor activity of ultraconserved poison exons

While RNA-seq has enabled comprehensive quantification of alternative splicing, no correspondingly high-throughput assay exists for functionally interrogating individual isoforms. We describe pgFARM (paired guide RNAs for alternative exon removal), a CRISPR-Cas9-based method to manipulate isoforms independent of gene inactivation. This approach enabled rapid suppression of exon recognition in polyclonal settings to identify functional roles for individual exons, such as an SMNDC1 cassette exon that regulates pan-cancer intron retention. We generalized this method to a pooled screen to measure the functional relevance of 'poison' cassette exons, which disrupt their host genes' reading frames yet are frequently ultraconserved. Many poison exons were essential for the growth of both cultured cells and lung adenocarcinoma xenografts, while a subset had clinically relevant tumor-suppressor activity. The essentiality and cancer relevance of poison exons are likely to contribute to their unusually high conservation and contrast with the dispensability of other ultraconserved elements for viability.

Spliceosomal disruption of the non-canonical BAF complex in cancer

SF3B1 is the most commonly mutated RNA splicing factor in cancer^1-4, but the mechanisms by which SF3B1 mutations promote malignancy are poorly understood. Here we integrated pan-cancer splicing analyses with a positive-enrichment CRISPR screen to prioritize splicing alterations that promote tumorigenesis. We report that diverse SF3B1 mutations converge on repression of BRD9, which is a core component of the recently described non-canonical BAF chromatin-remodelling complex that also contains GLTSCR1 and GLTSCR1L^5-7. Mutant SF3B1 recognizes an aberrant, deep intronic branchpoint within BRD9 and thereby induces the inclusion of a poison exon that is derived from an endogenous retroviral element and subsequent degradation of BRD9 mRNA. Depletion of BRD9 causes the loss of non-canonical BAF at CTCF-associated loci and promotes melanomagenesis. BRD9 is a potent tumour suppressor in uveal melanoma, such that correcting mis-splicing of BRD9 in SF3B1-mutant cells using antisense oligonucleotides or CRISPR-directed mutagenesis suppresses tumour growth. Our results implicate the disruption of non-canonical BAF in the diverse cancer types that carry SF3B1 mutations and suggest a mechanism-based therapeutic approach for treating these malignancies.

Coordinated alterations in RNA splicing and epigenetic regulation drive leukaemogenesis

Transcription and pre-mRNA splicing are key steps in the control of gene expression and mutations in genes regulating each of these processes are common in leukaemia1,2. Despite the frequent overlap of mutations affecting epigenetic regulation and splicing in leukaemia, how these processes influence one another to promote leukaemogenesis is not understood and, to our knowledge, there is no functional evidence that mutations in RNA splicing factors initiate leukaemia. Here, through analyses of transcriptomes from 982 patients with acute myeloid leukaemia, we identified frequent overlap of mutations in IDH2 and SRSF2 that together promote leukaemogenesis through coordinated effects on the epigenome and RNA splicing. Whereas mutations in either IDH2 or SRSF2 imparted distinct splicing changes, co-expression of mutant IDH2 altered the splicing effects of mutant SRSF2 and resulted in more profound splicing changes than either mutation alone. Consistent with this, co-expression of mutant IDH2 and SRSF2 resulted in lethal myelodysplasia with proliferative features in vivo and enhanced self-renewal in a manner not observed with either mutation alone. IDH2 and SRSF2 double-mutant cells exhibited aberrant splicing and reduced expression of INTS3, a member of the integrator complex3, concordant with increased stalling of RNA polymerase II (RNAPII). Aberrant INTS3 splicing contributed to leukaemogenesis in concert with mutant IDH2 and was dependent on mutant SRSF2 binding to cis elements in INTS3 mRNA and increased DNA methylation of INTS3. These data identify a pathogenic crosstalk between altered epigenetic state and splicing in a subset of leukaemias, provide functional evidence that mutations in splicing factors drive myeloid malignancy development, and identify spliceosomal changes as a mediator of IDH2-mutant leukaemogenesis.

RNA sequencing for research and diagnostics in clinical oncology

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.

DUX4 Suppresses MHC Class I to Promote Cancer Immune Evasion and Resistance to Checkpoint Blockade

Advances in cancer immunotherapies make it critical to identify genes that modulate antigen presentation and tumor-immune interactions. We report that DUX4, an early embryonic transcription factor that is normally silenced in somatic tissues, is re-expressed in diverse solid cancers. Both cis-acting inherited genetic variation and somatically acquired mutations in trans-acting repressors contribute to DUX4 re-expression in cancer. Although many DUX4 target genes encode self-antigens, DUX4-expressing cancers were paradoxically characterized by reduced markers of anti-tumor cytolytic activity and lower major histocompatibility complex (MHC) class I gene expression. We demonstrate that DUX4 expression blocks interferon-γ-mediated induction of MHC class I, implicating suppressed antigen presentation in DUX4-mediated immune evasion. Clinical data in metastatic melanoma confirmed that DUX4 expression was associated with significantly reduced progression-free and overall survival in response to anti-CTLA-4. Our results demonstrate that cancers can escape immune surveillance by reactivating a normal developmental pathway and identify a therapeutically relevant mechanism of cell-intrinsic immune evasion.

Blood circRNAs as biomarkers for the diagnosis of community-acquired pneumonia

Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy-to-monitor and highly stable materials for diagnosing Community-acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP-related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA-miRNA-mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus-infection-related signaling pathways (such as HTLV-1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP-related regulatory interactions that should inform future hypothesis-driven research into the causes and potential treatment of this widespread and frequently fatal disease.

Aberrant splicing in B-cell acute lymphoblastic leukemia

Aberrant splicing is a hallmark of leukemias with mutations in splicing factor (SF)-encoding genes. Here we investigated its prevalence in pediatric B-cell acute lymphoblastic leukemias (B-ALL), where SFs are not mutated. By comparing these samples to normal pro-B cells, we found thousands of aberrant local splice variations (LSVs) per sample, with 279 LSVs in 241 genes present in every comparison. These genes were enriched in RNA processing pathways and encoded ∼100 SFs, e.g. hnRNPA1. HNRNPA1 3'UTR was most pervasively mis-spliced, yielding the transcript subject to nonsense-mediated decay. To mimic this event, we knocked it down in B-lymphoblastoid cells and identified 213 hnRNPA1-regulated exon usage events comprising the hnRNPA1 splicing signature in pediatric leukemia. Some of its elements were LSVs in DICER1 and NT5C2, known cancer drivers. We searched for LSVs in other leukemia and lymphoma drivers and discovered 81 LSVs in 41 additional genes. Seventy-seven LSVs out of 81 were confirmed using two large independent B-ALL RNA-seq datasets, and the twenty most common B-ALL drivers, including NT5C2, showed higher prevalence of aberrant splicing than of somatic mutations. Thus, post-transcriptional deregulation of SF can drive widespread changes in B-ALL splicing and likely contributes to disease pathogenesis.

Determining cell type abundance and expression from bulk tissues with digital cytometry

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.

Atlas of RNA sequencing profiles for normal human tissues

Comprehensive analysis of molecular pathology requires a collection of reference samples representing normal tissues from healthy donors. For the available limited collections of normal tissues from postmortal donors, there is a problem of data incompatibility, as different datasets generated using different experimental platforms often cannot be merged in a single panel. Here, we constructed and deposited the gene expression database of normal human tissues based on uniformly screened original sequencing data. In total, 142 solid tissue samples representing 20 organs were taken from post-mortal human healthy donors of different age killed in road accidents no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. We then compared them with the 758 transcriptomic profiles taken from the other databases. We found that overall 463 biosamples showed tissue-specific rather than platform- or database-specific clustering and could be aggregated in a single database termed Oncobox Atlas of Normal Tissue Expression (ANTE). Our data will be useful to all those working with the analysis of human gene expression.

A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia

Acute myelogenous leukaemia (AML) is associated with risk factors that are largely unknown and with a heterogeneous response to treatment. Here, we provide a comprehensive quantitative understanding of AML proteomic heterogeneities and hallmarks by using the AML proteome atlas, a proteomics database that we have newly derived from MetaGalaxy analyses, for the proteomic profiling of 205 AML patients and 111 leukaemia cell lines. The analysis of the dataset revealed 154 functional patterns based on common molecular pathways, 11 constellations of correlated functional patterns, and 13 signatures that stratify the patients’ outcomes. We find limited overlap between proteomics data and both cytogenetics and genetic mutations, and also that leukaemia cell lines show limited proteomic similarities with cells from AML patients, suggesting that a deeper focus on patient-derived samples is needed to gain disease-relevant insights. The AML proteome atlas provides a knowledge base for proteomic patterns in AML, a guide to leukaemia cell-line selection, and a broadly applicable computational approach for quantifying the heterogeneities of protein expression and proteomic hallmarks in AML.

Alevin efficiently estimates accurate gene abundances from dscRNA-seq data

We introduce alevin, a fast end-to-end pipeline to process droplet-based single-cell RNA sequencing data, performing cell barcode detection, read mapping, unique molecular identifier (UMI) deduplication, gene count estimation, and cell barcode whitelisting. Alevin's approach to UMI deduplication considers transcript-level constraints on the molecules from which UMIs may have arisen and accounts for both gene-unique reads and reads that multimap between genes. This addresses the inherent bias in existing tools which discard gene-ambiguous reads and improves the accuracy of gene abundance estimates. Alevin is considerably faster, typically eight times, than existing gene quantification approaches, while also using less memory.

Blood handling and leukocyte isolation methods impact the global transcriptome of immune cells

Background

Transcriptional profiling with ultra-low input methods can yield valuable insights into disease, particularly when applied to the study of immune cells using RNA-sequencing. The advent of these methods has allowed for their use in profiling cells collected in clinical trials and other studies that involve the coordination of human-derived material. To date, few studies have sought to quantify what effects that collection and handling of this material can have on resulting data.

Results

We characterized the global effects of blood handling, methods for leukocyte isolation, and preservation media on low numbers of immune cells isolated from blood. We found overall that storage/shipping temperature of blood prior to leukocyte isolation and sorting led to global changes in both CD8⁺ T cells and monocytes, including alterations in immune-related gene sets. We found that the use of a leukocyte filtration system minimized these alterations and we applied this method to generate high-quality transcriptional data from sorted immune cells isolated from the blood of intracerebral hemorrhage patients and matched healthy controls.

Conclusions

Our data underscore the necessity of processing samples with comparably defined protocols prior to transcriptional profiling and demonstrate that a filtration method can be applied to quickly isolate immune cells of interest while minimizing transcriptional bias.

Electronic supplementary material

The online version of this article (10.1186/s12865-018-0268-6) contains supplementary material, which is available to authorized users.

Synthetic Lethal and Convergent Biological Effects of Cancer-Associated Spliceosomal Gene Mutations

Mutations affecting RNA splicing factors are the most common genetic alterations in myelodysplastic syndrome (MDS) patients and occur in a mutually exclusive manner. The basis for the mutual exclusivity of these mutations and how they contribute to MDS is not well understood. Here we report that although different spliceosome gene mutations impart distinct effects on splicing, they are negatively selected for when co-expressed due to aberrant splicing and downregulation of regulators of hematopoietic stem cell survival and quiescence. In addition to this synthetic lethal interaction, mutations in the splicing factors SF3B1 and SRSF2 share convergent effects on aberrant splicing of mRNAs that promote nuclear factor κB signaling. These data identify shared consequences of splicing-factor mutations and the basis for their mutual exclusivity.

Insight into origins, mechanisms, and utility of DNA methylation in B-cell malignancies

Understanding how tumor cells fundamentally alter their identity is critical to identify specific vulnerabilities for use in precision medicine. In B-cell malignancy, knowledge of genetic changes has resulted in great gains in our understanding of the biology of tumor cells, impacting diagnosis, prognosis, and treatment. Despite this knowledge, much remains to be explained as genetic events do not completely explain clinical behavior and outcomes. Many patients lack recurrent driver mutations, and said drivers can persist in nonmalignant cells of healthy individuals remaining cancer-free for decades. Epigenetics has emerged as a valuable avenue to further explain tumor phenotypes. The epigenetic landscape is the software that powers and stabilizes cellular identity by abridging a broad genome into the essential information required per cell. A genome-level view of B-cell malignancies reveals complex but recurrent epigenetic patterns that define tumor types and subtypes, permitting high-resolution classification and novel insight into tumor-specific mechanisms. Epigenetic alterations are guided by distinct cellular processes, such as polycomb-based silencing, transcription, signaling pathways, and transcription factor activity, and involve B-cell-specific aspects, such as activation-induced cytidine deaminase activity and germinal center-specific events. Armed with a detailed knowledge of the epigenetic events that occur across the spectrum of B-cell differentiation, B-cell tumor-specific aberrations can be detected with improved accuracy and serve as a model for identification of tumor-specific events in cancer. Insight gained through recent efforts may prove valuable in guiding the use of both epigenetic- and nonepigenetic-based therapies.

Most human introns are recognized via multiple and tissue-specific branchpoints

Pineda and Bradley demonstrate that almost all human introns contain multiple branchpoints. Approximately three-quarters of constitutive introns exhibit tissue-specific branchpoint usage.

Although branchpoint recognition is an essential component of intron excision during the RNA splicing process, the branchpoint itself is frequently assumed to be a basal, rather than regulatory, sequence feature. However, this assumption has not been systematically tested due to the technical difficulty of identifying branchpoints and quantifying their usage. Here, we analyzed ∼1.31 trillion reads from 17,164 RNA sequencing data sets to demonstrate that almost all human introns contain multiple branchpoints. This complexity holds even for constitutive introns, 95% of which contain multiple branchpoints, with an estimated five to six branchpoints per intron. Introns upstream of the highly regulated ultraconserved poison exons of SR genes contain twice as many branchpoints as the genomic average. Approximately three-quarters of constitutive introns exhibit tissue-specific branchpoint usage. In an extreme example, we observed a complete switch in branchpoint usage in the well-studied first intron of HBB (β-globin) in normal bone marrow versus metastatic prostate cancer samples. Our results indicate that the recognition of most introns is unexpectedly complex and tissue-specific and suggest that alternative splicing catalysis typifies the majority of introns even in the absence of differences in the mature mRNA.

Model systems of DUX4 expression recapitulate the transcriptional profile of FSHD cells

Facioscapulohumeral dystrophy (FSHD) is caused by the mis-expression of the double-homeodomain transcription factor DUX4 in skeletal muscle cells. Many different cell culture models have been developed to study the pathophysiology of FSHD, frequently based on endogenous expression of DUX4 in FSHD cells or by mis-expression of DUX4 in control human muscle cells. Although results generated using each model are generally consistent, differences have also been reported, making it unclear which model(s) faithfully recapitulate DUX4 and FSHD biology. In this study, we systematically compared RNA-seq data generated from three different models of FSHD—lentiviral-based DUX4 expression in myoblasts, doxycycline-inducible DUX4 in myoblasts, and differentiated human FSHD myocytes expressing endogenous DUX4—and show that the DUX4-associated gene expression signatures of each dataset are highly correlated (Pearson’s correlation coefficient, r ∼ 0.75-0.85). The few robust differences were attributable to different states of cell differentiation and other differences in experimental design. Our study describes a model system for inducible DUX4 expression that enables reproducible and synchronized experiments and validates the fidelity and FSHD relevance of multiple distinct models of DUX4 expression.

Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis

BACKGROUND

Circular RNAs (circRNAs) are a class of novel RNAs with important biological functions, and aberrant expression of circRNAs has been implicated in human diseases. However, the feasibility of using blood circRNAs as disease biomarkers is largely unknown.

METHODS

We explored the potential of using human peripheral blood mononuclear cell (PBMC) circRNAs as marker molecules to diagnose active pulmonary tuberculosis (TB).

FINDINGS

First, we demonstrated that circRNAs are widely expressed in human PBMCs and that many are abundant enough to be detected. Second, we found that the magnitude of PBMC circRNAs in TB patients was higher than that in the paired healthy controls. Compared with host linear transcripts, the circRNAs within several pathways are disproportionately upregulated in active TB patients, including "Cytokine-cytokine receptor interaction", "Chemokine signaling pathway", "Neurotrophin signaling pathway", and "Bacterial invasion of epithelial cells". Based on the differentially expressed circRNAs within these pathways, we developed a PBMC circRNA-based molecular signature differentiating active TB patients from healthy controls. We validated the classification power of the PBMC circRNA signature in an independent cohort with the area under the receiver operating characteristic curve (AUC) at 0.946.

INTERPRETATION

Our results suggest that PBMC circRNAs are potentially reliable marker molecules in TB diagnosis.

Impact of Specimen Heterogeneity on Biomarkers in Repository Samples from Patients with Acute Myeloid Leukemia: A SWOG Report

INTRODUCTION

Current prognostic models for acute myeloid leukemia (AML) are inconsistent at predicting clinical outcomes for individual patients. Variability in the quality of specimens utilized for biomarker discovery and validation may contribute to this prognostic inconsistency.

METHODS

We evaluated the impact of sample heterogeneity on prognostic biomarkers and methods to mitigate any adverse effects of this heterogeneity in 240 cryopreserved bone marrow and peripheral blood specimens from AML patients enrolled on SWOG (Southwest Oncology Group) trials.

RESULTS

Cryopreserved samples displayed a broad range in viability (37% with viabilities ≤60%) and nonleukemic cell contamination (13% with lymphocyte percentages >20%). Specimen viability was impacted by transport time, AML immunophenotype, and, potentially, patients' age. The viability and cellular heterogeneity in unsorted samples significantly altered biomarker results. Enriching for viable AML blasts improved the RNA quality from specimens with poor viability and refined results for both DNA and RNA biomarkers. For example, FLT3-ITD allelic ratio, which is currently utilized to risk-stratify AML patients, was on average 1.49-fold higher in the viable AML blasts than in the unsorted specimens.

CONCLUSION

To our knowledge, this is the first study to provide evidence that using cryopreserved specimens can introduce uncontrollable variables that may impact biomarker results and enrichment for viable AML blasts may mitigate this impact.

Consensus-Driven Development of a Terminology for Biobanking, the Duke Experience

Biobanking at Duke University has existed for decades and has grown over time in silos and based on specialized needs, as is true with most biomedical research centers. These silos developed informatics systems to support their own individual requirements, with no regard for semantic or syntactic interoperability. Duke undertook an initiative to implement an enterprise-wide biobanking information system to serve its many diverse biobanking entities. A significant part of this initiative was the development of a common terminology for use in the commercial software platform. Common terminology provides the foundation for interoperability across biobanks for data and information sharing. We engaged experts in research, informatics, and biobanking through a consensus-driven process to agree on 361 terms and their definitions that encompass the lifecycle of a biospecimen. Existing standards, common terms, and data elements from published articles provided a foundation on which to build the biobanking terminology; a broader set of stakeholders then provided additional input and feedback in a secondary vetting process. The resulting standardized biobanking terminology is now available for sharing with the biobanking community to serve as a foundation for other institutions who are considering a similar initiative.