Deep learning-based multimodal spatial transcriptomics analysis for cancer.

The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized cancer research, offering unprecedented insights into tumor biology. This book chapter explores the integration of DL with ST to advance cancer diagnostics, treatment planning, and precision medicine. DL, a subset of artificial intelligence, employs neural networks to model complex patterns in vast datasets, significantly enhancing diagnostic and treatment applications. In oncology, convolutional neural networks excel in image classification, segmentation, and tumor volume analysis, essential for identifying tumors and optimizing radiotherapy. The chapter also delves into multimodal data analysis, which integrates genomic, proteomic, imaging, and clinical data to offer a holistic understanding of cancer biology. Leveraging diverse data sources, researchers can uncover intricate details of tumor heterogeneity, microenvironment interactions, and treatment responses. Examples include integrating MRI data with genomic profiles for accurate glioma grading and combining proteomic and clinical data to uncover drug resistance mechanisms. DL's integration with multimodal data enables comprehensive and actionable insights for cancer diagnosis and treatment. The synergy between DL models and multimodal data analysis enhances diagnostic accuracy, personalized treatment planning, and prognostic modeling. Notable applications include ST, which maps gene expression patterns within tissue contexts, providing critical insights into tumor heterogeneity and potential therapeutic targets. In summary, the integration of DL and multimodal ST represents a paradigm shift towards more precise and personalized oncology. This chapter elucidates the methodologies and applications of these advanced technologies, highlighting their transformative potential in cancer research and clinical practice.

Deep learning-based IDH1 gene mutation prediction using histopathological imaging and clinical data.

In the field of histopathology, many studies on the classification of whole slide images (WSIs) using artificial intelligence (AI) technology have been reported. We have studied the disease progression assessment of glioma. Adult-type diffuse gliomas, a type of brain tumor, are classified into astrocytoma, oligodendroglioma, and glioblastoma. Astrocytoma and oligodendroglioma are also called low grade glioma (LGG), and glioblastoma is also called glioblastoma multiforme (GBM). LGG patients frequently have isocitrate dehydrogenase (IDH) mutations. Patients with IDH mutations have been reported to have a better prognosis than patients without IDH mutations. Therefore, IDH mutations are an essential indicator for the classification of glioma. That is why we focused on the IDH1 mutation. In this paper, we aimed to classify the presence or absence of the IDH1 mutation using WSIs and clinical data of glioma patients. Ensemble learning between the WSIs model and the clinical data model is used to classify the presence or absence of IDH1 mutation. By using slide level labels, we combined patch-based imaging information from hematoxylin and eosin (H & E) stained WSIs, along with clinical data using deep image feature extraction and machine learning classifier for predicting IDH1 gene mutation prediction versus wild-type across cohort of 546 patients. We experimented with different deep learning (DL) models including attention-based multiple instance learning (ABMIL) models on imaging data along with gradient boosting machine (LightGBM) for the clinical variables. Further, we used hyperparameter optimization to find the best overall model in terms of classification accuracy. We obtained the highest area under the curve (AUC) of 0.823 for WSIs, 0.782 for clinical data, and 0.852 for ensemble results using MaxViT and LightGBM combination, respectively. Our experimental results indicate that the overall accuracy of the AI models can be improved by using both clinical data and images.

White matter characteristics in children with cerebral palsy prior to selective dorsal rhizotomy: a multicenter diffusion tensor imaging study.

OBJECTIVE: The aims of this study were to 1) assess and quantify white matter (WM) microstructural characteristics derived from diffusion tensor imaging (DTI) in children with cerebral palsy (CP) prior to selective dorsal rhizotomy (SDR), and 2) investigate potential associations between WM diffusion properties and gross motor function and spasticity in children with spastic CP who underwent SDR. METHODS: This study is a multisite study based on DT images acquired prior to SDR as well as postoperative outcome data. DTI data collected from two sites were harmonized using the ComBat approach to minimize intersite scanner difference. The DTI abnormalities between children with spastic CP and controls were analyzed and correlated with the severity of impaired mobility based on the Gross Motor Function Classification System (GMFCS). The improvement in gross motor function and spasticity after SDR surgery was assessed utilizing the Gross Motor Function Measure-66 (GMFM-66), the Modified Tardieu Scale (MTS), and the modified Ashworth scale (MAS). Alterations in these outcome measures were quantified in association with DTI abnormalities. RESULTS: Significant DTI alterations, including lower fractional anisotropy (FA) in the genu of the corpus callosum (gCC) and higher mean diffusivity (MD) in the gCC and posterior limb of the internal capsule (PLIC), were found in children in the SDR group when compared with the age-matched control group (all p < 0.05). Greater DTI alterations (FA in gCC and MD in gCC and PLIC) were associated with lower mobility levels as determined based on GMFCS level (p < 0.05). The pre- to post-SDR improvement in motor function based on GMFM-66 was statistically significant (p = 0.006 and 0.002 at 6-month and 12-month follow-ups, respectively). The SDR efficacy was also identified as improving spasticity in lower-extremity muscle groups assessed with the MTS and MAS. Partial correlation analysis presented a significant association between pre- to post-SDR MTS alteration and DTI abnormalities. CONCLUSIONS: The findings in the present study provided initial quantitative evidence to establish the WM microstructural characteristics in children with spastic CP prior to SDR surgery. The study generated data for the association between baseline DTI characteristics and mobility in children with CP prior to SDR surgery. The study also demonstrated SDR efficacy in improving motor function and spasticity based on the GMFM-66, MTS, and MAS, respectively, in association with DTI data.

Single cell transcriptomic analysis of HPV16-infected epithelium identifies a keratinocyte subpopulation implicated in cancer.

Persistent HPV16 infection is a major cause of the global cancer burden. The viral life cycle is dependent on the differentiation program of stratified squamous epithelium, but the landscape of keratinocyte subpopulations which support distinct phases of the viral life cycle has yet to be elucidated. Here, single cell RNA sequencing of HPV16 infected compared to uninfected organoids identifies twelve distinct keratinocyte populations, with a subset mapped to reconstruct their respective 3D geography in stratified squamous epithelium. Instead of conventional terminally differentiated cells, an HPV-reprogrammed keratinocyte subpopulation (HIDDEN cells) forms the surface compartment and requires overexpression of the ELF3/ESE-1 transcription factor. HIDDEN cells are detected throughout stages of human carcinogenesis including primary human cervical intraepithelial neoplasias and HPV positive head and neck cancers, and a possible role in promoting viral carcinogenesis is supported by TCGA analyses. Single cell transcriptome information on HPV-infected versus uninfected epithelium will enable broader studies of the role of individual keratinocyte subpopulations in tumor virus infection and cancer evolution.

Outpatient hospital utilization after single event multi-level surgery in children with cerebral palsy.

PURPOSE: This study aimed to examine outpatient hospital utilization (number of specialties seen and number of visits to each specialty) in the year after single event multi-level surgery (SEMLS) in children with cerebral palsy (CP), and to determine if utilization differs across the medical center in the year after compared to the year before SEMLS. METHODS: This retrospective cross-sectional study used electronic medical record data of outpatient hospital utilization in children with CP who underwent SEMLS. RESULTS: Thirty children with CP (Gross Motor Function Classification System Levels I-V, mean age of 9.9 years) were included. In the year after surgery, a significant difference (p = 0.001) was found for the number of specialties seen, with non-ambulatory children seeing more specialties than ambulatory children. No statistically significant difference was found between the number of outpatient visits to each specialty in the year after SEMLS. Compared to the year before SEMLS, fewer therapy visits occurred in the year after SEMLS (p < 0.001) but significantly more visits to orthopaedics (p = 0.001) and radiology (p = 0.001). CONCLUSION: Children with CP had fewer therapy visits but more orthopaedic and radiology visits the year after SEMLS. Nearly half of the children were non-ambulatory. Examination of care needs in children with CP undergoing SEMLS is justified with consideration of ambulatory status, surgical burden, and post-operative immobilization.

Endosomal Sequestration of TLR4 Antibody Induces Myeloid-Derived Suppressor Cells and Reverses Acute Type 1 Diabetes.

We previously showed that treating NOD mice with an agonistic monoclonal anti-TLR4/MD2 antibody (TLR4-Ab) reversed acute type 1 diabetes (T1D). Here, we show that TLR4-Ab reverses T1D by induction of myeloid-derived suppressor cells (MDSCs). Unbiased gene expression analysis after TLR4-Ab treatment demonstrated upregulation of genes associated with CD11b+Ly6G+ myeloid cells and downregulation of T-cell genes. Further RNA sequencing of purified, TLR4-Ab-treated CD11b+ cells showed significant upregulation of genes associated with bone marrow-derived CD11b+ cells and innate immune system genes. TLR4-Ab significantly increased percentages and numbers of CD11b+ cells. TLR4-Ab-induced CD11b+ cells, derived ex vivo from TLR4-Ab-treated mice, suppress T cells, and TLR4-Ab-conditioned bone marrow cells suppress acute T1D when transferred into acutely diabetic mice. Thus, the TLR4-Ab-induced CD11b+ cells, by the currently accepted definition, are MDSCs able to reverse T1D. To understand the TLR4-Ab mechanism, we compared TLR4-Ab with TLR4 agonist lipopolysaccharide (LPS), which cannot reverse T1D. TLR4-Ab remains sequestered at least 48 times longer than LPS within early endosomes, alters TLR4 signaling, and downregulates inflammatory genes and proteins, including nuclear factor-κB. TLR4-Ab in the endosome, therefore, induces a sustained, attenuated inflammatory response, providing an ideal "second signal" for the activation/maturation of MDSCs that can reverse acute T1D.

Identification of distinct tumor cell populations and key genetic mechanisms through single cell sequencing in hepatoblastoma.

Hepatoblastoma (HB) is the most common primary liver malignancy of childhood, and molecular investigations are limited and effective treatment options for chemoresistant disease are lacking. There is a knowledge gap in the investigation of key driver cells of HB in tumor. Here we show single cell ribonucleic acid sequencing (scRNAseq) analysis of human tumor, background liver, and patient derived xenograft (PDX) to demonstrate gene expression patterns within tumor and to identify intratumor cell subtype heterogeneity to define differing roles in pathogenesis based on intracellular signaling in pediatric HB. We have identified a driver tumor cell cluster in HB by genetic expression which can be examined to define disease mechanism and treatments. Identification of both critical mechanistic pathways combined with unique cell populations provide the basis for discovery and investigation of novel treatment strategies in vitro and in vivo.

A roadmap for the Human Developmental Cell Atlas.

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.

A First-In-Class, Humanized Antibody Targeting Alternatively Spliced Tissue Factor: Preclinical Evaluation in an Orthotopic Model of Pancreatic Ductal Adenocarcinoma.

In 2021, pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer deaths in the United States. This is largely due to a lack of symptoms and limited treatment options, which extend survival by only a few weeks. There is thus an urgent need to develop new therapies effective against PDAC. Previously, we have shown that the growth of PDAC cells is suppressed when they are co-implanted with RabMab1, a rabbit monoclonal antibody specific for human alternatively spliced tissue factor (asTF). Here, we report on humanization of RabMab1, evaluation of its binding characteristics, and assessment of its in vivo properties. hRabMab1 binds asTF with a KD in the picomolar range; suppresses the migration of high-grade Pt45.P1 cells in Boyden chamber assays; has a long half-life in circulation (~ 5 weeks); and significantly slows the growth of pre-formed orthotopic Pt45.P1 tumors in athymic nude mice when administered intravenously. Immunohistochemical analysis of tumor tissue demonstrates the suppression of i) PDAC cell proliferation, ii) macrophage infiltration, and iii) neovascularization, whereas RNAseq analysis of tumor tissue reveals the suppression of pathways that promote cell division and focal adhesion. This is the first proof-of-concept study whereby a novel biologic targeting asTF has been investigated as a systemically administered single agent, with encouraging results. Given that hRabMab1 has a favorable PK profile and is able to suppress the growth of human PDAC cells in vivo, it comprises a promising candidate for further clinical development.

Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. This consortium has regularly held topic-focused biannual face-to-face symposiums. These meetings are a place to review cancer informatics and data science priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues that we faced at our respective institutions and cancer centers. Here, we provide meeting highlights from the latest CI4CC Symposium, which was delayed from its original April 2020 schedule because of the COVID-19 pandemic and held virtually over three days (September 24, October 1, and October 8) in the fall of 2020. In addition to the content presented, we found that holding this event virtually once a week for 6 hours was a great way to keep the kind of deep engagement that a face-to-face meeting engenders. This is the second such publication of CI4CC Symposium highlights, the first covering the meeting that took place in Napa, California, from October 14-16, 2019. We conclude with some thoughts about using data science to learn from every child with cancer, focusing on emerging activities of the National Cancer Institute's Childhood Cancer Data Initiative.

Stratification of risk of progression to colectomy in ulcerative colitis via measured and predicted gene expression.

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of individuals with ulcerative colitis (UC) require colectomy within 5 years of diagnosis, but polygenic risk scores (PRSs) utilizing findings from genome-wide association studies (GWASs) are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a transcriptional risk score (TRS). Here, we demonstrate that a measured TRS based on bulk rectal gene expression in the PROTECT inception cohort study has a positive predictive value approaching 50% for colectomy. Single-cell profiling demonstrates that the genes are active in multiple diverse cell types from both the epithelial and immune compartments. Expression quantitative trait locus (QTL) analysis identifies genes with differential effects at baseline and week 52 follow-up, but for the most part, differential expression associated with colectomy risk is independent of local genetic regulation. Nevertheless, a predicted polygenic transcriptional risk score (PPTRS) derived by summation of transcriptome-wide association study (TWAS) effects identifies UC-affected individuals at 5-fold elevated risk of colectomy with data from the UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with TWASs for stratification of risk of disease complications.

African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors associated with immunologic functions and environmental exposures.

The COVID-19 pandemic has affected African American populations disproportionately with respect to prevalence, and mortality. Expression profiles represent snapshots of combined genetic, socio-environmental (including socioeconomic and environmental factors), and physiological effects on the molecular phenotype. As such, they have potential to improve biological understanding of differences among populations, and provide therapeutic biomarkers and environmental mitigation strategies. Here, we undertook a large-scale assessment of patterns of gene expression between African Americans and European Americans, mining RNA-Seq data from 25 non-diseased and diseased (tumor) tissue-types. We observed the widespread enrichment of pathways implicated in COVID-19 and integral to inflammation and reactive oxygen stress. Chemokine CCL3L3 expression is up-regulated in African Americans. GSTM1, encoding a glutathione S-transferase that metabolizes reactive oxygen species and xenobiotics, is upregulated. The little-studied F8A2 gene is up to 40-fold more highly expressed in African Americans; F8A2 encodes HAP40 protein, which mediates endosome movement, potentially altering the cellular response to SARS-CoV-2. African American expression signatures, superimposed on single cell-RNA reference data, reveal increased number or activity of esophageal glandular cells and lung ACE2-positive basal keratinocytes. Our findings establish basal prognostic signatures that can be used to refine approaches to minimize risk of severe infection and improve precision treatment of COVID-19 for African Americans. To enable dissection of causes of divergent molecular phenotypes, we advocate routine inclusion of metadata on genomic and socio-environmental factors for human RNA-sequencing studies.

Therapeutic Opportunities for Intestinal Angioectasia- Targeting PPARγ and Oxidative Stress.

Recurrent and acute bleeding from intestinal tract angioectasia (AEC) presents a major challenge for clinical intervention. Current treatments are empiric, with frequent poor clinical outcomes. Improvements in understanding the pathophysiology of these lesions will help guide treatment. Using data from the US Food and Drug Administration (FDA)'s Adverse Event Reporting System (FAERS), we analyzed 12 million patient reports to identify drugs inversely correlated with gastrointestinal bleeding and potentially limiting AEC severity. FAERS analysis revealed that drugs used in patients with diabetes and those targeting PPARγ-related mechanisms were associated with decreased AEC phenotypes (P < 0.0001). Electronic health records (EHRs) at University of Cincinnati Hospital were analyzed to validate FAERS analysis. EHR data showed a 5.6% decrease in risk of AEC and associated phenotypes in patients on PPARγ agonists. Murine knockout models of AEC phenotypes were used to construct a gene-regulatory network of candidate drug targets and pathways, which revealed that wound healing, vasculature development and regulation of oxidative stress were impacted in AEC pathophysiology. Human colonic tissue was examined for expression differences across key pathway proteins, PPARγ, HIF1α, VEGF, and TGFß1. In vitro analysis of human AEC tissues showed lower expression of PPARγ and TGFß1 compared with controls (0.55 ± 0.07 and 0.49 ± 0.05). National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) RNA-Seq data was analyzed to substantiate human tissue findings. This integrative discovery approach showing altered expression of key genes involved in oxidative stress and injury repair mechanisms presents novel insight into AEC etiology, which will improve targeted mechanistic studies and more optimal medical therapy for AEC.

Mucosal Inflammatory and Wound Healing Gene Programs Reveal Targets for Stricturing Behavior in Pediatric Crohn's Disease.

BACKGROUND AND AIMS: Ileal strictures are the major indication for resective surgery in Crohn's disease (CD). We aimed to define ileal gene programs present at diagnosis linked with future stricturing behavior during five year follow-up, and to identify potential small molecules to reverse these gene signatures. METHODS: Antimicrobial serologies and pre-treatment ileal gene expression were assessed in a representative subset of 249 CD patients within the RISK multicenter pediatric CD inception cohort study, including 113 that are unique to this report. These data were used to define genes associated with stricturing behavior and for model testing to predict stricturing behavior. A bioinformatics approach to define small molecules which may reverse the stricturing gene signature was applied. RESULTS: 19 of the 249 patients developed isolated B2 stricturing behavior during follow-up, while 218 remained B1 inflammatory. Using deeper RNA sequencing than in our prior report, we have now defined an inflammatory gene signature including an oncostatin M co-expression signature, tightly associated with extra-cellular matrix (ECM) gene expression in those who developed stricturing complications. We further computationally prioritize small molecules targeting macrophage and fibroblast activation and angiogenesis which may reverse the stricturing gene signature. A model containing ASCA and CBir1 serologies and a refined eight ECM gene set was significantly associated with stricturing development by year five after diagnosis (AUC (95th CI) = 0.82 (0.7-0.94)). CONCLUSION: An ileal gene program for macrophage and fibroblast activation is linked to stricturing complications in treatment naïve pediatric CD, and may inform novel small molecule therapeutic approaches.

The elephant in the lung: Integrating lineage-tracing, molecular markers, and single cell sequencing data to identify distinct fibroblast populations during lung development and regeneration.

During lung development, the mesenchyme and epithelium are dependent on each other for instructive morphogenic cues that direct proliferation, cellular differentiation and organogenesis. Specification of epithelial and mesenchymal cell lineages occurs in parallel, forming cellular subtypes that guide the formation of both transitional developmental structures and the permanent architecture of the adult lung. While epithelial cell types and lineages have been relatively well-defined in recent years, the definition of mesenchymal cell types and lineage relationships has been more challenging. Transgenic mouse lines with permanent and inducible lineage tracers have been instrumental in identifying lineage relationships among epithelial progenitor cells and their differentiation into distinct airway and alveolar epithelial cells. Lineage tracing experiments with reporter mice used to identify fibroblast progenitors and their lineage trajectories have been limited by the number of cell specific genes and the developmental timepoint when the lineage trace was activated. In this review, we discuss major developmental mesenchymal lineages, focusing on time of origin, major cell type, and other lineage derivatives, as well as the transgenic tools used to find and define them. We describe lung fibroblasts using function, location, and molecular markers in order to compare and contrast cells with similar functions. The temporal and cell-type specific expression of fourteen "fibroblast lineage" genes were identified in single-cell RNA-sequencing data from LungMAP in the LGEA database. Using these lineage signature genes as guides, we clustered murine lung fibroblast populations from embryonic day 16.5 to postnatal day 28 (E16.5-PN28) and generated heatmaps to illustrate expression of transcription factors, signaling receptors and ligands in a temporal and population specific manner.

Proteasomal adaptations underlying carfilzomib-resistance in human bone marrow plasma cells.

Donor-specific antibodies (DSAs) have a deleterious effect on allografts and remain a major immunologic barrier in transplantation. Current therapies to eliminate DSAs are ineffective in highly HLA-sensitized patients. Proteasome inhibitors have been employed as a strategy to target bone marrow plasma cells (BMPCs), the source of long-term antibody production; however, their efficacy has been limited by poorly defined drug-resistance mechanisms. Here, we performed transcriptomic profiling of CD138+ BMPCs that survived in vivo desensitization therapy with the proteasome inhibitor carfilzomib to identify mechanisms of drug resistance. The results revealed a genomic signature that included increased expression of the immunoproteasome, a highly specialized proteasomal variant. Western blotting and functional studies demonstrated that catalytically active immunoproteasomes and the immunoproteasome activator PA28 were upregulated in carfilzomib-resistant BMPCs. Carfilzomib-resistant BMPCs displayed reduced sensitivity to the proteasome inhibitors carfilzomib, bortezomib, and ixazomib, but enhanced sensitivity to an immunoproteasome-specific inhibitor ONX-0914. Finally, in vitro carfilzomib treatment of BMPCs from HLA-sensitized patients increased levels of the immunoproteasome ß5i (PSMB8) catalytic subunit suggesting that carfilzomib therapy directly induces an adaptive immunoproteasome response. Taken together, our results indicate that carfilzomib induces structural changes in proteasomes and immunoproteasome formation.

Elimination of the fibrinogen integrin αMß2-binding motif improves renal pathology in mice with sickle cell anemia.

Sickle cell anemia (SCA) is caused by a point mutation in the ß-globin gene that leads to devastating downstream consequences including chronic hemolytic anemia, episodic vascular occlusion, and cumulative organ damage resulting in death. SCA patients show coagulation activation and inflammation even in the absence of vascular occlusion. The coagulation factor fibrinogen is not only central to hemostasis but also plays important roles in pathologic inflammatory processes, in part by engaging neutrophils/macrophages through the αMß2 integrin receptor. To determine whether fibrin(ogen)-mediated inflammation is a driver of SCA-associated pathologies, hematopoietic stem cells from Berkeley sickle mice were transplanted into homozygous Fibγ390-396A mice that express normal levels of a mutant form of fibrin(ogen) that does not engage αMß2 Fibγ390-396A mice with SCA displayed an impressive reduction of reactive oxygen species (ROS) in white blood cells (WBCs), decreased circulating inflammatory cytokines/chemokines, and significantly improved SCA-associated glomerular pathology highlighted by reduced glomerulosclerosis, inflammatory cell infiltration, ischemic lesions, mesangial thickening, mesangial hypercellularity, and glomerular enlargement. In addition, Fibγ390-396A mice with SCA had improved glomerular protective responses and podocyte/mesangial transcriptional signatures that resulted in reduced albuminuria. Interestingly, the fibrinogen γ390-396A mutation had a negligible effect on cardiac, lung, and liver functions and pathologies in the context of SCA over a year-long observation period. Taken together, our data support that fibrinogen significantly contributes to WBC-driven inflammation and ROS production, which is a key driver of SCA-associated glomerulopathy, and may represent a novel therapeutic target against irreversible kidney damage in SCA.

Single-Cell Transcriptomics Uncovers Glial Progenitor Diversity and Cell Fate Determinants during Development and Gliomagenesis.

The identity and degree of heterogeneity of glial progenitors and their contributions to brain tumor malignancy remain elusive. By applying lineage-targeted single-cell transcriptomics, we uncover an unanticipated diversity of glial progenitor pools with unique molecular identities in developing brain. Our analysis identifies distinct transitional intermediate states and their divergent developmental trajectories in astroglial and oligodendroglial lineages. Moreover, intersectional analysis uncovers analogous intermediate progenitors during brain tumorigenesis, wherein oligodendrocyte-progenitor intermediates are abundant, hyper-proliferative, and progressively reprogrammed toward a stem-like state susceptible to further malignant transformation. Similar actively cycling intermediate progenitors are prominent components in human gliomas with distinct driver mutations. We further unveil lineage-driving networks underlying glial fate specification and identify Zfp36l1 as necessary for oligodendrocyte-astrocyte lineage transition and glioma growth. Together, our results resolve the dynamic repertoire of common and divergent glial progenitors during development and tumorigenesis and highlight Zfp36l1 as a molecular nexus for balancing glial cell-fate decision and controlling gliomagenesis.

Single-cell RNA sequencing identifies inflammatory tissue T cells in eosinophilic esophagitis.

T cell heterogeneity is highly relevant to allergic disorders. We resolved the heterogeneity of human tissue CD3+ T cells during allergic inflammation, focusing on a tissue-specific allergic disease, eosinophilic esophagitis (EoE). We investigated 1088 single T cells derived from patients with a spectrum of disease activity. Eight disparate tissue T cell subtypes (designated T1-T8) were identified, with T7 and T8 enriched in the diseased tissue. The phenotypes of T7 and T8 resemble putative Treg (FOXP3+) and effector Th2-like (GATA3+) cells, respectively. Prodigious levels of IL-5 and IL-13 were confined to HPGDS+ CRTH2+IL-17RB+FFAR3+CD4+ T8 effector Th2 cells. EoE severity closely paralleled a lipid/fatty acid-induced activation node highlighted by the expression of the short-chain fatty acid receptor FFAR3. Ligands for FFAR3 induced Th2 cytokine production from human and murine T cells, including in an in vivo allergy model. Therefore, we elucidated the defining characteristics of tissue-residing CD3+ T cells in EoE, a specific enrichment of CD4+ Treg and effector Th2 cells, confinement of type 2 cytokine production to the CD4+ effector population, a highly likely role for FFAR3 in amplifying local Th2 responses in EoE, and a resource to further dissect tissue lymphocytes and allergic responses.