Shared Gene Expression Research Articles

Developmental bisphenol S toxicity in two freshwater animal models

Freshwater animals are exposed to anthropogenic contaminants and are biomonitors of water quality and models of the deleterious impacts of exposure. Sponges, such as Ephydatia muelleri, constantly pump water and are effective indicators of water-soluble contaminants. Zebrafish (Danio rerio), native to Southeast Asia, live in the water column and feed at the water-sediment interface and are exposed to both water-soluble and insoluble contaminants. While sponges and zebrafish diverged ∼700 million years ago, they share common genetic elements, and their response to contaminants can be predictive to a wide-range of animals. An emerging contaminant, bisphenol S, was tested to evaluate its toxicity during development. The toxicity and mechanism(s) of action of BPS is not well known. Water-borne exposures to BPS caused differing hatching rates, morphological changes, and shared gene expression changes of toxicologically-relevant genes. This study shows that BPS causes similarly adverse developmental impacts pointing to some overlapping mechanisms of action.

Inhibition of Caspase-1-mediated pyroptosis promotes osteogenic differentiation, offering a therapeutic target for osteoporosis

BackgroundPyroptosis, an emerging inflammatory form of cell death, has been previously demonstrated to stimulate a massive inflammatory response, thus hindering the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs). Nevertheless, the impact of pyroptosis in thwarting osteogenic differentiation and exacerbating the advancement of osteoporosis (OP) remains enigmatic. MethodsWe evaluated the expression levels of pyroptosis-associated indicators, including NOD-like receptor family pyrin domain-containing protein 3 (NLRP3), CASPASE-1, IL-1β, and IL-18, in specimens obtained from femoral heads of OP patients, as well as in an ovariectomy-induced mouse model of OP. Subsequently, the precise roles of pyroptosis in osteogenic differentiation were investigated using bioinformatics analysis, alongside morphological and biochemical assessments. ResultsThe pivotal pyroptotic proteins, including NLRP3, Caspase-1, IL-1β, and IL-18, exhibited significant upregulation within the bone tissue samples of clinical OP cases, as well as in the femoral tissues of ovariectomy (OVX)-induced mouse OP model, displaying a negatively associated with compromised osteogenic capacity, as represented by lessened bone mass, suppressed expression of osteogenic proteins such as Runt-related transcription factor 2 (RUNX2), Alkaline phosphatase (ALP), Osterix (OSX), and Osteopontin (OPN), and increased lipid droplets. Moreover, bioinformatics analysis substantiated shared gene expression patterns between pyroptosis and OP pathology, encompassing NLRP3, Caspase-1, IL-1β, IL-18, etc. Furthermore, our in vitro investigation using ST2 cells revealed that dexamethasone treatment prominently induced pyroptosis while impeding osteogenic differentiation. Notably, gene silencing of Caspase-1 effectively counteracted the inhibitory effects of dexamethasone on osteogenic differentiation, as manifested by increased ALP activity and enhanced expression of RUNX2, ALP, OSX, and OPN. ConclusionOur findings unequivocally underscore that inhibition of Caspase-1-mediated pyroptosis promotes osteogenic differentiation, providing a promising therapeutic target for managing OP.

Shared genetic links between bladder cancer and obesity-related traits: A conjunctional false discovery rate study.

Bladder cancer (BCa) is a common cancer worldwide and is often linked with obesity-related comorbidities, but little is known about the underlying genetic mechanisms. To investigate these mechanisms, we used various quantitative tools, including conditional quantile-quantile (Q-Q) plots, conditional false discovery rate (cFDR), and conjunctional conditional false discovery rate (ccFDR), to explore the pleiotropic enrichment of risk loci between BCa and obesity-related traits. We also performed an expression quantitative trait locus (eQTL) analysis to assess the relationship between shared risk loci and gene expression. Finally, we conducted functional annotation using Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis. Our findings indicated that there was successive enrichment for a range of obesity-related traits, including body fat percentage, body mass index, fasting insulin, type 2 diabetes mellitus, fasting glucose, high-density lipoprotein cholesterol, total triglycerides, and waist-to-hip ratio. Using the tools mentioned above, we identified 18 significant SNPs and 18 closely related genes (cFDR<0.01) under the condition of 8 obesity-related traits. The SNPs included rs143004880, rs73301337, rs10798572, rs11594929, rs17019138, rs2877, rs149795948, rs142509736, rs12727575, rs1571277, rs12131828, rs635634, rs76895963, rs118081211, rs7044247, rs138895564, rs4135275, and rs148023060. Additionally, we identified 15 novel loci using ccFDR, including rs143004880, rs73301337, rs10798572, rs11594929, rs17019138, rs2877, rs142509736, rs1571277, rs635634, rs76895963, rs12131828, rs118081211, rs7044247, rs138895564, and rs4135275. Of the 2 significant loci that modify gene expression, rs12131828 and rs635634 were identified. The functional annotation indicated that the conditional risk genes mainly participated in the regulation of gene silencing. Our study provided evidence of pleiotropic enrichment between BCa and 8 obesity-related traits, and we identified potential genetic mechanisms underlying this relationship. These findings may help in developing targeted clinical treatments for BCa.

Persistence is key: unresolved immune dysfunction is lethal in both COVID-19 and non-COVID-19 sepsis.

Severe COVID-19 and non-COVID-19 pulmonary sepsis share pathophysiological, immunological, and clinical features, suggesting that severe COVID-19 is a form of viral sepsis. Our objective was to identify shared gene expression trajectories strongly associated with eventual mortality between severe COVID-19 patients and contemporaneous non-COVID-19 sepsis patients in the intensive care unit (ICU) for potential therapeutic implications. Whole blood was drawn from 20 COVID-19 patients and 22 non-COVID-19 adult sepsis patients at two timepoints: ICU admission and approximately a week later. RNA-Seq was performed on whole blood to identify differentially expressed genes and significantly enriched pathways. Using systems biology methods, drug candidates targeting key genes in the pathophysiology of COVID-19 and sepsis were identified. When compared to survivors, non-survivors (irrespective of COVID-19 status) had 3.6-fold more "persistent" genes (genes that stayed up/downregulated at both timepoints) (4,289 vs. 1,186 genes); these included persistently downregulated genes in T-cell signaling and persistently upregulated genes in select innate immune and metabolic pathways, indicating unresolved immune dysfunction in non-survivors, while resolution of these processes occurred in survivors. These findings of persistence were further confirmed using two publicly available datasets of COVID-19 and sepsis patients. Systems biology methods identified multiple immunomodulatory drug candidates that could target this persistent immune dysfunction, which could be repurposed for possible therapeutic use in both COVID-19 and sepsis. Transcriptional evidence of persistent immune dysfunction was associated with 28-day mortality in both COVID-19 and non-COVID-19 septic patients. These findings highlight the opportunity for mitigating common mechanisms of immune dysfunction with immunomodulatory therapies for both diseases.

Virus-specific and shared gene expression signatures in immune cells after vaccination in response to influenza and vaccinia stimulation.

In the vaccine era, individuals receive multiple vaccines in their lifetime. Host gene expression in response to antigenic stimulation is usually virus-specific; however, identifying shared pathways of host response across a wide spectrum of vaccine pathogens can shed light on the molecular mechanisms/components which can be targeted for the development of broad/universal therapeutics and vaccines. We isolated PBMCs, monocytes, B cells, and CD8+ T cells from the peripheral blood of healthy donors, who received both seasonal influenza vaccine (within <1 year) and smallpox vaccine (within 1 - 4 years). Each of the purified cell populations was stimulated with either influenza virus or vaccinia virus. Differentially expressed genes (DEGs) relative to unstimulated controls were identified for each in vitro viral infection, as well as for both viral infections (shared DEGs). Pathway enrichment analysis was performed to associate identified DEGs with KEGG/biological pathways. We identified 2,906, 3,888, 681, and 446 DEGs in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, in response to influenza stimulation. Meanwhile, 97, 120, 20, and 10 DEGs were identified as gene signatures in PBMCs, monocytes, B cells, and CD8+ T cells, respectively, upon vaccinia stimulation. The majority of DEGs identified in PBMCs were also found in monocytes after either viral stimulation. Of the virus-specific DEGs, 55, 63, and 9 DEGs occurred in common in PBMCs, monocytes, and B cells, respectively, while no DEGs were shared in infected CD8+ T cells after influenza and vaccinia. Gene set enrichment analysis demonstrated that these shared DEGs were over-represented in innate signaling pathways, including cytokine-cytokine receptor interaction, viral protein interaction with cytokine and cytokine receptor, Toll-like receptor signaling, RIG-I-like receptor signaling pathways, cytosolic DNA-sensing pathways, and natural killer cell mediated cytotoxicity. Our results provide insights into virus-host interactions in different immune cells, as well as host defense mechanisms against viral stimulation. Our data also highlights the role of monocytes as a major cell population driving gene expression in ex vivo PBMCs in response to viral stimulation. The immune response signaling pathways identified in this study may provide specific targets for the development of novel virus-specific therapeutics and improved vaccines for vaccinia and influenza. Although influenza and vaccinia viruses have been selected in this study as pathogen models, this approach could be applicable to other pathogens.

The molecular evolution of mammalian spermatogenesis

The testis is a key male reproductive organ that produces gametes through the process of spermatogenesis. Testis morphologies, sperm phenotypes, and the process of spermatogenesis evolve rapidly in mammals, presumably due to the evolutionary pressure on males to give rise to their own offspring. Here, we review studies illuminating the molecular evolution of the testis, in particular large-scale transcriptomic studies, which were based on bulk tissue samples and, more recently, individual cells. Together with various genomic and epigenomic data, these studies have unveiled the cellular source, molecular mechanisms, and evolutionary forces that underlie the rapid phenotypic evolution of the testis. They also revealed shared (ancestral) and species-specific spermatogenic gene expression programs. The insights and available data that have accumulated also provide a valuable resource for the investigation and treatment of male fertility disorders – a dramatically increasing problem in modern industrial societies.

Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in children with obesity

Obesity in children is related to the development of cardiometabolic complications later in life, where molecular changes of visceral adipose tissue (VAT) and skeletal muscle tissue (SMT) have been proven to be fundamental. The aim of this study is to unveil the gene expression architecture of both tissues in a cohort of Spanish boys with obesity, using a clustering method known as weighted gene co-expression network analysis. For this purpose, we have followed a multi-objective analytic pipeline consisting of three main approaches; identification of gene co-expression clusters associated with childhood obesity, individually in VAT and SMT (intra-tissue, approach I); identification of gene co-expression clusters associated with obesity-metabolic alterations, individually in VAT and SMT (intra-tissue, approach II); and identification of gene co-expression clusters associated with obesity-metabolic alterations simultaneously in VAT and SMT (inter-tissue, approach III). In both tissues, we identified independent and inter-tissue gene co-expression signatures associated with obesity and cardiovascular risk, some of which exceeded multiple-test correction filters. In these signatures, we could identify some central hub genes (e.g., NDUFB8, GUCY1B1, KCNMA1, NPR2, PPP3CC) participating in relevant metabolic pathways exceeding multiple-testing correction filters. We identified the central hub genes PIK3R2, PPP3C and PTPN5 associated with MAPK signaling and insulin resistance terms. This is the first time that these genes have been associated with childhood obesity in both tissues. Therefore, they could be potential novel molecular targets for drugs and health interventions, opening new lines of research on the personalized care in this pathology. This work generates interesting hypotheses about the transcriptomics alterations underlying metabolic health alterations in obesity in the pediatric population.

Transcriptional programming of CD4+ TRM differentiation in viral infection balances effector- and memory-associated gene expression.

After resolution of infection, T cells differentiate into long-lived memory cells that recirculate through secondary lymphoid organs or establish residence in tissues. In contrast to CD8+ tissue-resident memory T cells (TRM), the developmental origins and transcriptional regulation of CD4+ TRM remain largely undefined. Here, we investigated the phenotypic, functional, and transcriptional profiles of CD4+ TRM in the small intestine (SI) responding to acute viral infection, revealing a shared gene expression program and chromatin accessibility profile with circulating TH1 and the progressive acquisition of a mature TRM program. Single-cell RNA sequencing identified heterogeneity among established CD4+ TRM, which were predominantly located in the lamina propria, and revealed a population of cells that coexpressed both effector- and memory-associated genes, including the transcriptional regulators Blimp1, Id2, and Bcl6. TH1-associated Blimp1 and Id2 and TFH-associated Bcl6 were required for early TRM formation and development of a mature TRM population in the SI. These results demonstrate a developmental relationship between TH1 effector cells and the establishment of early TRM, as well as highlighted differences in CD4+ versus CD8+ TRM populations, providing insights into the mechanisms underlying the origins, differentiation, and persistence of CD4+ TRM in response to viral infection.

Regulation of anterior neurectoderm specification and differentiation by BMP signaling in ascidians.

The most anterior structure of the ascidian larva is made of three palps with sensory and adhesive functions essential for metamorphosis. They derive from the anterior neural border and their formation is regulated by FGF and Wnt. Given that they also share gene expression profiles with vertebrate anterior neural tissue and cranial placodes, their study should shed light on the emergence of the unique vertebrate telencephalon. We show that BMP signaling regulates two phases of palp formation in Ciona intestinalis. During gastrulation, the anterior neural border is specified in a domain of inactive BMP signaling, and activating BMP prevented its formation. During neurulation, BMP defines ventral palp identity and indirectly specifies the inter-papilla territory separating the ventral and dorsal palps. Finally, we show that BMP has similar functions in the ascidian Phallusia mammillata, for which we identified novel palp markers. Collectively, we provide a better molecular description of palp formation in ascidians that will be instrumental for comparative studies.

Pushing the boundaries of organ identity: Homology of the grass lemma

Pushing the boundaries of organ identity: Homology of the grass lemma

Shared and disease-specific glial gene expression changes in neurodegenerative diseases.

We found evolutionarily conserved astrocyte and microglia subpopulations shared across multiple brain regions. We reveal similarities and differences between Alzheimer's disease glia and Parkinson's disease glia, as well as regional variance linked to disease pathology and neurodegeneration.

Transcriptomic Deconvolution of Neuroendocrine Neoplasms Predicts Clinically Relevant Characteristics.

Pancreatic neuroendocrine neoplasms (panNENs) are a rare yet diverse type of neoplasia whose precise clinical-pathological classification is frequently challenging. Since incorrect classifications can affect treatment decisions, additional tools which support the diagnosis, such as machine learning (ML) techniques, are critically needed but generally unavailable due to the scarcity of suitable ML training data for rare panNENs. Here, we demonstrate that a multi-step ML framework predicts clinically relevant panNEN characteristics while being exclusively trained on widely available data of a healthy origin. The approach classifies panNENs by deconvolving their transcriptomes into cell type proportions based on shared gene expression profiles with healthy pancreatic cell types. The deconvolution results were found to provide a prognostic value with respect to the prediction of the overall patient survival time, neoplastic grading, and carcinoma versus tumor subclassification. The performance with which a proliferation rate agnostic deconvolution ML model could predict the clinical characteristics was found to be comparable to that of a comparative baseline model trained on the proliferation rate-informed MKI67 levels. The approach is novel in that it complements established proliferation rate-oriented classification schemes whose results can be reproduced and further refined by differentiating between identically graded subgroups. By including non-endocrine cell types, the deconvolution approach furthermore provides an in silico quantification of panNEN dedifferentiation, optimizing it for challenging clinical classification tasks in more aggressive panNEN subtypes.

Single-cell transcriptomic profiling of the zebrafish inner ear reveals molecularly distinct hair cell and supporting cell subtypes.

A major cause of human deafness and vestibular dysfunction is permanent loss of the mechanosensory hair cells of the inner ear. In non-mammalian vertebrates such as zebrafish, regeneration of missing hair cells can occur throughout life. While a comparative approach has the potential to reveal the basis of such differential regenerative ability, the degree to which the inner ears of fish and mammals share common hair cells and supporting cell types remains unresolved. Here, we perform single-cell RNA sequencing of the zebrafish inner ear at embryonic through adult stages to catalog the diversity of hair cells and non-sensory supporting cells. We identify a putative progenitor population for hair cells and supporting cells, as well as distinct hair and supporting cell types in the maculae versus cristae. The hair cell and supporting cell types differ from those described for the lateral line system, a distributed mechanosensory organ in zebrafish in which most studies of hair cell regeneration have been conducted. In the maculae, we identify two subtypes of hair cells that share gene expression with mammalian striolar or extrastriolar hair cells. In situ hybridization reveals that these hair cell subtypes occupy distinct spatial domains within the three macular organs, the utricle, saccule, and lagena, consistent with the reported distinct electrophysiological properties of hair cells within these domains. These findings suggest that primitive specialization of spatially distinct striolar and extrastriolar hair cells likely arose in the last common ancestor of fish and mammals. The similarities of inner ear cell type composition between fish and mammals validate zebrafish as a relevant model for understanding inner ear-specific hair cell function and regeneration.

A single-cell atlas of murine reproductive tissues during preterm labor

Preterm birth, the leading cause of perinatal morbidity and mortality worldwide, frequently results from the syndrome of preterm labor. The best-established causal link to preterm labor is intra-amniotic infection, which involves premature activation of the parturition cascade in the reproductive tissues. Herein, we utilize single-cell RNA sequencing (scRNA-seq) to generate a single-cell atlas of the murine uterus, decidua, and cervix in a model of infection-induced preterm labor. We show that preterm labor affects the transcriptomic profiles of specific immune and non-immune cell subsets. Shared and tissue-specific gene expression signatures are identified among affected cells. Determination of intercellular communications implicates specific cell types in preterm labor-associated signaling pathways across tissues. In silico comparison of murine and human uterine cell-cell interactions reveals conserved signaling pathways implicated in labor. Thus, our scRNA-seq data provide insights into the preterm labor-driven cellular landscape and communications in reproductive tissues.

Gene expression profiling in NOD mice reveals that B cells are highly educated by the pancreatic environment during autoimmune diabetes

Aims/hypothesisB cells play an important role in driving the development of type 1 diabetes; however, it remains unclear how they contribute to local beta cell destruction during disease progression. Here, we use gene expression profiling of B cell subsets identified in inflamed pancreatic tissue to explore their primary functional role during the progression of autoimmune diabetes.MethodsTranscriptional profiling was performed on FACS-sorted B cell subsets isolated from pancreatic islets and the pancreatic lymph nodes of NOD mice.ResultsB cells are highly modified by the inflamed pancreatic tissue and can be distinguished by their transcriptional profile from those in the lymph nodes. We identified both a discrete and a core shared gene expression profile in islet CD19+CD138– and CD19+CD138+ B cell subsets, the latter of which is known to have enriched autoreactivity during diabetes development. On localisation to pancreatic islets, compared with CD138– B cells, CD138+ B cells overexpress genes associated with adhesion molecules and growth factors. Their shared signature consists of gene expression changes related to the differentiation of antibody-secreting cells and gene regulatory networks associated with IFN signalling pathways, proinflammatory cytokines and Toll-like receptor (TLR) activation. Finally, abundant TLR7 expression was detected in islet B cells and was enhanced specifically in CD138+ B cells.Conclusions/interpretationOur study provides a detailed transcriptional analysis of islet B cells. Specific gene signatures and interaction networks have been identified that point towards a functional role for B cells in driving autoimmune diabetes.Graphical abstract

Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria.

Protein concentrations are set by a complex interplay between gene-specific regulatory processes and systemic factors, including cell volume and shared gene expression machineries. Elucidating this interplay is crucial for discerning and designing gene regulatory systems. We quantitatively characterized gene-specific and systemic factors that affect transcription and translation genome-wide for Escherichia coli across many conditions. The results revealed two design principles that make regulation of gene expression insulated from concentrations of shared machineries: RNA polymerase activity is fine-tuned to match translational output, and translational characteristics are similar across most messenger RNAs (mRNAs). Consequently, in bacteria, protein concentration is set primarily at the promoter level. A simple mathematical formula relates promoter activities and protein concentrations across growth conditions, enabling quantitative inference of gene regulation from omics data.

Abstract A001: Shared gene expression and immune pathway changes associated with progression from nevi to melanoma

Abstract There is a need to identify biomarkers of melanoma progression to assist the development of chemoprevention strategies to lower melanoma incidence. In this study, we assessed the feasibility of creating a molecular signature for melanomagenesis using three publicly available RNA sequencing and microarray expression datasets. We performed differential expression and regularized regression analyses across nevi and melanoma samples to identify consistent genes associated with melanomagenesis. The regularized regression models demonstrated that a small number of genes could successfully distinguish between nevi and melanoma, providing evidence for the feasibility of creating a molecular signature. Differential expression analysis identified consistent upregulation of C1QB, CXCL9, CXCL10, DFNA5 (GSDME), FCGR1B, and PRAME in melanoma and consistent downregulation of SCGB1D2 in melanoma compared to nevi. Additionally, each of these genes demonstrated a linear association with the progression from benign nevi to dysplastic nevi, to radial growth phase melanoma to vertical growth phase melanoma, providing additional evidence for their role in melanomagenesis. Subsequent pathway analysis demonstrated significant enrichment of immune-related pathways among the differentially expressed genes. Overall, this study 1) demonstrates the feasibility of creating a gene signature for melanomagenesis and 2) highlights genes and pathways of interest for melanoma progression. We are in the process of generating a new dataset with benign nevi, dysplastic nevi, and melanoma with which to build and validate a molecular signature of melanoma. Citation Format: Elizabeth S. Borden, Anngela C. Adams, Kenneth H. Buetow, Melissa A. Wilson, Julie E. Bauman, Clara Curiel-Lewandrowski, H.-H. Sherry Chow, Bonnie J. LaFleur, Karen Taraszka Hastings. Shared gene expression and immune pathway changes associated with progression from nevi to melanoma [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr A001.

Abstract A006: Shared gene expression and immune pathway changes associated with progression from nevi to melanoma

Abstract There is a need to identify biomarkers of melanoma progression to assist the development of chemoprevention strategies to lower melanoma incidence. In this study, we assessed the feasibility of creating a molecular signature for melanomagenesis using three publicly available RNA sequencing and microarray expression datasets. We performed differential expression and regularized regression analyses across nevi and melanoma samples to identify consistent genes associated with melanomagenesis. The regularized regression models demonstrated that a small number of genes could successfully distinguish between nevi and melanoma, providing evidence for the feasibility of creating a molecular signature. Differential expression analysis identified consistent upregulation of C1QB, CXCL9, CXCL10, DFNA5 (GSDME), FCGR1B, and PRAME in melanoma and consistent downregulation of SCGB1D2 in melanoma compared to nevi. Additionally, each of these genes demonstrated a linear association with the progression from benign nevi to dysplastic nevi, to radial growth phase melanoma to vertical growth phase melanoma, providing additional evidence for their role in melanomagenesis. Subsequent pathway analysis demonstrated significant enrichment of immune-related pathways among the differentially expressed genes. Overall, this study 1) demonstrates the feasibility of creating a gene signature for melanomagenesis and 2) highlights genes and pathways of interest for melanoma progression. We are in the process of generating a new dataset with benign nevi, dysplastic nevi, and melanoma with which to build and validate a molecular signature of melanoma. Citation Format: Elizabeth S. Borden, Anngela C. Adams, Kenneth H. Buetow, Melissa A. Wilson, Julie E. Bauman, Clara Curiel-Lewandrowski, H.-H. Sherry Chow, Bonnie J. LaFleur, Karen Taraszka Hastings. Shared gene expression and immune pathway changes associated with progression from nevi to melanoma [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr A006.

A Multi-Cohort Gene Expression Classifier (ALLCatchR) Identifies B-Precursor ALL Subtypes and Their Developmental Trajectories across Age Groups

The molecular landscape of B cell precursor acute lymphoblastic leukemia (BCP-ALL) describes >20 disease subtypes defined by initiating genomic alterations and corresponding gene expression signatures. Some subtypes represent phenocopies with shared gene expression signatures but distinct or absent genomic drivers. The majority of BCP-ALL subtypes have been acknowledged as diagnostic entities by the currently revised classifications of hematologic malignancies (WHO-HAEM5 / International Consensus Classification). Thus, unified diagnostic approaches are needed to systematically identify subtypes in individual BCP-ALL cases in clinical routine. Gene expression signatures represent the shared functional equivalent of heterogeneous genomic driver alterations. Therefore, we established a gene expression-based classifier to identify BCP-ALL subtypes and related clinical and biological phenotypes. We analyzed a total of n=3477 BCP-ALL gene expression profiles obtained from transcriptome sequencing of adult (n=1253) and pediatric patients (n=2224) including publicly available (n=2074; Gu Z et al. Nat. Genet. 2019; Schmidt B. et al. Blood Adv. 2022) and own data sets (n=1403) from adult and pediatric European study groups (GMALL, AIEOP-BFM, CELL). Raw read counts from 6 cohorts representing heterogeneous library preps (i.e., stranded/unstranded; mRNA/total RNA), sequencing platforms/depths, and gene count quantifications were included. All samples had been previously allocated to molecular BCP-ALL subtypes based on integration of independent genomic profiling, gene fusion calling and gene expression. For classification, data with defined subgroup allocation were randomly split into training (n=1831; 70%) and testing sets (n=785; 30%) and two hold-out studies (n=305). To define gene expression signatures of 21 BCP-ALL subtypes, we used training set samples and extracted specific gene sets employing different feature selection algorithms as well as ranking of genes in individual subtypes. Based on these definitions we established a BCP-ALL subtype classifier (ALLCatchR), which integrates machine learning models (support vector machines) and nearest-neighbors associations of single sample gene set enrichment analyses (Fig. A). ALLCatchR performed molecular subtype allocation for the testing set at high sensitivity (0.934±0.165) and specificity (0.997±0.005) on average across subtypes. A similar performance was achieved in the two hold-out cohorts despite completely independent data structures which have not been shown to the classifier (sensitivity: 0.946±0.097 / specificity: 0.996±0.007). Overall accuracies of 0.952 and 0.92 for testing and hold-out-data sets indicate that ALLCatchR reliably identifies molecular BCP-ALL subtypes in mixed adult / pediatric cohorts based on gene expression profiles alone (Fig. A, below). Among n=44/1090 (4%) samples of the combined hold-out/testing set with ambiguous subtype allocation (deemed 'unclassified'), ALLCatchR provides candidate subtype allocations (sensitivity: 0.671±0.393 / specificity: 0.978±0.036) for confirmation based on genomic driver alterations. In addition, we modified our classifier to predict baseline variables such as patient's sex (accuracy: 0.991), immunophenotype (accuracy: 0.935) or blast count (R=0.633). To define the corresponding B cell differentiation stage of origin, we compared BCP-ALL subtypes to differentiation stage-specific gene sets extracted from 7 FACS-sorted lymphopoietic subsets from healthy bone marrow donors (n=4). We observed defined BCP-ALL subtype-specific enrichment patterns which can be grouped along 4 major differentiation stages (Pro-B to Pre-B-II-Large, Fig. 1B) with a high degree of similarity in independent adult and pediatric cohorts. Thus, B cell developmental trajectories underlying BCP-ALL subtypes are dissected at high resolution by gene expression profiling and differentiation stages may favor the selection of specific leukemogenic drivers. ALLCatchR is a gene expression classifier for 21 established BCP-ALL molecular subtypes, which performs at independently validated cohorts with an accuracy of >90% and allows imputation of clinical baseline variables as well as underlying B cell developmental trajectories. It provides a reliable basis for systematic diagnostic approaches in pediatric and adult BCP-ALL patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

En1 and Lmx1b do not recapitulate embryonic dorsal-ventral limb patterning functions during mouse digit tip regeneration.

The mouse digit tip regenerates following amputation. How the regenerate is patterned is unknown, but a long-standing hypothesis proposes developmental patterning mechanisms are re-used during regeneration. The digit tip bone exhibits dorsal-ventral (DV) polarity, so we focus on En1 and Lmx1b, two factors necessary for DV patterning during limb development. We investigate whether they are re-expressed during regeneration in a developmental-like pattern and whether they direct DV morphology of the regenerate. We find that both En1 and Lmx1b are expressed in the regenerating digit tip epithelium and mesenchyme, respectively, but without DV polarity. Conditional genetics and quantitative analysis of digit tip bone morphology determine that genetic deletion of En1 or Lmx1b in adult digit tip regeneration modestly reduces bone regeneration but does not affect DV patterning. Collectively, our data suggest that, while En1 and Lmx1b are re-expressed during mouse digit tip regeneration, they do not define the DV axis during regeneration.