Lymphatic migration of unconventional T cells promotes site-specific immunity in distinct lymph nodes.

Lymphatic transport of molecules and migration of myeloid cells to lymph nodes (LNs) continuously inform lymphocytes on changes in drained tissues. Here, using LN transplantation, single-cell RNA-seq, spectral flow cytometry, and a transgenic mouse model for photolabeling, we showed that tissue-derived unconventional T cells (UTCs) migrate via the lymphatic route to locally draining LNs. As each tissue harbored a distinct spectrum of UTCs with locally adapted differentiation states and distinct T cell receptor repertoires, every draining LN was thus populated by a distinctive tissue-determined mix of these lymphocytes. By making use of single UTC lineage-deficient mouse models, we found that UTCs functionally cooperated in interconnected units and generated and shaped characteristic innate and adaptive immune responses that differed between LNs that drained distinct tissues. Lymphatic migration of UTCs is, therefore, a key determinant of site-specific immunity initiated in distinct LNs with potential implications for vaccination strategies and immunotherapeutic approaches.

Melanocyte lineage dynamics in development, growth and disease.

Melanocytes evolved to produce the melanin that gives colour to our hair, eyes and skin. The melanocyte lineage also gives rise to melanoma, the most lethal form of skin cancer. The melanocyte lineage differentiates from neural crest cells during development, and most melanocytes reside in the skin and hair, where they are replenished by melanocyte stem cells. Because the molecular mechanisms necessary for melanocyte specification, migration, proliferation and differentiation are co-opted during melanoma initiation and progression, studying melanocyte development is directly relevant to human disease. Here, through the lens of advances in cellular omic and genomic technologies, we review the latest findings in melanocyte development and differentiation, and how these developmental pathways become dysregulated in disease.

The FOXP3+ Pro-Inflammatory T Cell: A Potential Therapeutic Target in Crohn's Disease.

BACKGROUND & AIMS: The incidence of Crohn's disease (CD) continues to increase worldwide. The contribution of CD4+ cell populations remains to be elucidated. We aimed to provide an in-depth transcriptional assessment of CD4+ T cells driving chronic inflammation in CD. METHODS: We performed single-cell RNA-sequencing in CD4+ T cells isolated from ileal biopsies of patients with CD compared with healthy individuals. Cells underwent clustering analysis, followed by analysis of gene signaling networks. We overlapped our differentially expressed genes with publicly available microarray data sets and performed functional in vitro studies, including an in vitro suppression assay and organoid systems, to model gene expression changes observed in CD regulatory T (Treg) cells and to test predicted therapeutics. RESULTS: We identified 5 distinct FOXP3+ regulatory Treg subpopulations. Tregs isolated from healthy controls represent the origin of pseudotemporal development into inflammation-associated subtypes. These proinflammatory Tregs displayed a unique responsiveness to tumor necrosis factor-α signaling with impaired suppressive activity in vitro and an elevated cytokine response in an organoid coculture system. As predicted in silico, the histone deacetylase inhibitor vorinostat normalized gene expression patterns, rescuing the suppressive function of FOXP3+ cells in vitro. CONCLUSIONS: We identified a novel, proinflammatory FOXP3+ T cell subpopulation in patients with CD and developed a pipeline to specifically target these cells using the US Food and Drug Administration-approved drug vorinostat.

Identification of bZIP Transcription Factors That Regulate the Development of Leaf Epidermal Cells in Arabidopsis thaliana by Single-Cell RNA Sequencing.

Epidermal cells are the main avenue for signal and material exchange between plants and the environment. Leaf epidermal cells primarily include pavement cells, guard cells, and trichome cells. The development and distribution of different epidermal cells are tightly regulated by a complex transcriptional regulatory network mediated by phytohormones, including jasmonic acid, and transcription factors. How the fate of leaf epidermal cells is determined, however, is still largely unknown due to the diversity of cell types and the complexity of their regulation. Here, we characterized the transcriptional profiles of epidermal cells in 3-day-old true leaves of Arabidopsis thaliana using single-cell RNA sequencing. We identified two genes encoding BASIC LEUCINE-ZIPPER (bZIP) transcription factors, namely bZIP25 and bZIP53, which are highly expressed in pavement cells and early-stage meristemoid cells. Densities of pavement cells and trichome cells were found to increase and decrease, respectively, in bzip25 and bzip53 mutants, compared with wild-type plants. This trend was more pronounced in the presence of jasmonic acid, suggesting that these transcription factors regulate the development of trichome cells and pavement cells in response to jasmonic acid.

Single-cell analysis of localized prostate cancer patients links high Gleason score with an immunosuppressive profile.

BACKGROUND: Evading immune surveillance is a hallmark for the development of multiple cancer types. Whether immune evasion contributes to the pathogenesis of high-grade prostate cancer (HGPCa) remains an area of active inquiry. METHODS: Through single-cell RNA sequencing and multicolor flow cytometry of freshly isolated prostatectomy specimens and matched peripheral blood, we aimed to characterize the tumor immune microenvironment (TME) of localized prostate cancer (PCa), including HGPCa and low-grade prostate cancer (LGPCa). RESULTS: HGPCa are highly infiltrated by exhausted CD8+ T cells, myeloid cells, and regulatory T cells (TRegs). These HGPCa-infiltrating CD8+ T cells expressed high levels of exhaustion markers including TIM3, TOX, TCF7, PD-1, CTLA4, TIGIT, and CXCL13. By contrast, a high ratio of activated CD8+  effector T cells relative to TRegs and myeloid cells infiltrate the TME of LGPCa. HGPCa CD8+  tumor-infiltrating lymphocytes (TILs) expressed more androgen receptor and prostate-specific membran antigen yet less prostate-specific antigen than the LGPCa CD8+  TILs. The PCa TME was infiltrated by macrophages but these did not clearly cluster by M1 and M2 markers. CONCLUSIONS: Our study reveals a suppressive TME with high levels of CD8+ T cell exhaustion in localized PCa, a finding enriched in HGPCa relative to LGPCa. These studies suggest a possible link between the clinical-pathologic risk of PCa and the associated TME. Our results have implications for our understanding of the immunologic mechanisms of PCa pathogenesis and the implementation of immunotherapy for localized PCa.

Single-cell transcriptomic analysis of oral masticatory and lining mucosa-derived mesenchymal stromal cells.

AIM: To reveal the heterogeneity of ex vivo-cultured human mesenchymal stromal cells derived from either masticatory or lining oral mucosa. MATERIALS AND METHODS: Cells were retrieved from the lamina propria of the hard palate and alveolar mucosa of three individuals. The analysis of transcriptomic-level differences was accomplished using single-cell RNA sequencing. RESULTS: Cluster analysis clearly distinguished between cells from the masticatory and lining oral mucosa, and revealed 11 distinct cell sub-populations, annotated as fibroblasts, smooth muscle cells or mesenchymal stem cells. Interestingly, cells presenting a mesenchymal stem cell-like gene expression pattern were predominantly found in masticatory mucosa. Although cells of masticatory mucosa origin were highly enriched for biological processes associated with wound healing, those from the lining oral mucosa were highly enriched for biological processes associated with the regulation of epithelial cells. CONCLUSIONS: Our previous work had shown that cells from the lining and masticatory oral mucosae are phenotypically heterogeneous. Here, we extend these findings to show that these changes are not the result of differences in averages but rather represent two distinct cell populations, with mesenchymal stem cells more common in masticatory mucosa. These features may contribute to specific physiological functions and have relevance for potential therapeutic interventions.

In Silico Drug Repurposing in Multiple Sclerosis Using scRNA-Seq Data.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system still lacking a cure. Treatment typically focuses on slowing the progression and managing MS symptoms. Single-cell transcriptomics allows the investigation of the immune system-the key player in MS onset and development-in great detail increasing our understanding of MS mechanisms and stimulating the discovery of the targets for potential therapies. Still, de novo drug development takes decades; however, this can be reduced by drug repositioning. A promising approach is to select potential drugs based on activated or inhibited genes and pathways. In this study, we explored the public single-cell RNA data from an experiment with six patients on single-cell RNA peripheral blood mononuclear cells (PBMC) and cerebrospinal fluid cells (CSF) of patients with MS and idiopathic intracranial hypertension. We demonstrate that AIM2 inflammasome, SMAD2/3 signaling, and complement activation pathways are activated in MS in different CSF and PBMC immune cells. Using genes from top-activated pathways, we detected several promising small molecules to reverse MS immune cells' transcriptomic signatures, including AG14361, FGIN-1-27, CA-074, ARP 101, Flunisolide, and JAK3 Inhibitor VI. Among these molecules, we also detected an FDA-approved MS drug Mitoxantrone, supporting the reliability of our approach.

Single-Cell Transcriptome Analysis of the Circle of Willis in a Mouse Cerebral Aneurysm Model.

BACKGROUND: The circle of Willis (CoW) is the most common location for aneurysms to form in humans. Although the major cell types of the intracranial vasculature are well known, the heterogeneity and relative contributions of the different cells in healthy and aneurysmal vessels have not been well characterized. Here, we present the first comprehensive analysis of the lineage heterogeneity and altered transcriptomic profiles of vascular cells from healthy and aneurysmal mouse CoW using single-cell RNA sequencing. METHODS: Cerebral aneurysms (CAs) were induced in adult male mice using an elastase model. Single-cell RNA sequencing was then performed on CoW samples obtained from animals that either had aneurysms form or rupture 14 days post-induction. Sham-operated animals served as controls. RESULTS: Unbiased clustering analysis of the transcriptional profiles from >3900 CoW cells identified 19 clusters representing ten cell lineages: vascular smooth muscle cells, endothelial cells fibroblasts, pericytes and immune cells (macrophages, T and B lymphocytes, dendritic cells, mast cells, and neutrophils). The 5 vascular smooth muscle cell subpopulations had distinct transcriptional profiles and were classified as proliferative, stress-induced senescent, quiescent, inflammatory-like, or hyperproliferative. The transcriptional signature of the metabolic pathways of ATP generation was found to be downregulated in 2 major vascular smooth muscle cell clusters when CA was induced. Aneurysm induction led to significant expansion of the total macrophage population, and this expansion was further increased with rupture. Both inflammatory and resolution-phase macrophages were identified, and a massive spike of neutrophils was seen with CA rupture. Additionally, the neutrophil-to-lymphocyte ratio (NLR), which originated from CA induction mirrored what happens in humans. CONCLUSIONS: Our data identify CA disease-relevant transcriptional signatures of vascular cells in the CoW and is searchable via a web-based R/shiny interface.

Machine learning and statistical methods for clustering single-cell RNA-sequencing data.

Single-cell RNAsequencing (scRNA-seq) technologies have enabled the large-scale whole-transcriptome profiling of each individual single cell in a cell population. A core analysis of the scRNA-seq transcriptome profiles is to cluster the single cells to reveal cell subtypes and infer cell lineages based on the relations among the cells. This article reviews the machine learning and statistical methods for clustering scRNA-seq transcriptomes developed in the past few years. The review focuses on how conventional clustering techniques such as hierarchical clustering, graph-based clustering, mixture models, $k$-means, ensemble learning, neural networks and density-based clustering are modified or customized to tackle the unique challenges in scRNA-seq data analysis, such as the dropout of low-expression genes, low and uneven read coverage of transcripts, highly variable total mRNAs from single cells and ambiguous cell markers in the presence of technical biases and irrelevant confounding biological variations. We review how cell-specific normalization, the imputation of dropouts and dimension reduction methods can be applied with new statistical or optimization strategies to improve the clustering of single cells. We will also introduce those more advanced approaches to cluster scRNA-seq transcriptomes in time series data and multiple cell populations and to detect rare cell types. Several software packages developed to support the cluster analysis of scRNA-seq data are also reviewed and experimentally compared to evaluate their performance and efficiency. Finally, we conclude with useful observations and possible future directions in scRNA-seq data analytics. AVAILABILITY: All the source code and data are available at https://github.com/kuanglab/single-cell-review.

Single-cell RNA sequencing analysis of SARS-CoV-2 entry receptors in human organoids.

Coronavirus disease-2019 (COVID-19) is a global pandemic and caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has resulted in millions of deaths worldwide. Reports denote SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2), transmembrane serine protease 2 (TMPRSS2) as its primary entry point into the host cell. However, understanding the biology behind this viral replication, disease mechanism and drug discovery efforts are limited due to the lack of a suitable experimental model. Here, we used single-cell RNA sequencing data of human organoids to analyze expressions of ACE2 and TMPRSS2, in addition to an array of RNA receptors to examine their role in SARS-CoV-2 pathogenesis. ACE2 is abundant in all organoids, except the prostate and brain, and TMPRSS2 is omnipresent. Innate immune pathways are upregulated in ACE2(+) cells of all organoids, except the lungs. Besides this, the expression of low-density lipoprotein receptor is highly enriched in ACE2(+) cells in intestinal, lung, and retinal organoids, with the highest expression in lung organoids. Collectively, this study demonstrates that the organoids can be used as an experimental platform to explore this novel virus disease mechanism and for drug development.

Association between particulate matter containing EPFRs and neutrophilic asthma through AhR and Th17.

BACKGROUND: Epidemiological data associate high levels of combustion-derived particulate matter (PM) with deleterious respiratory outcomes, but the mechanism underlying those outcomes remains elusive. It has been acknowledged by the World Health Organization that PM exposure contributes to more than 4.2 million all-cause mortalities worldwide each year. Current literature demonstrates that PM exacerbates respiratory diseases, impairs lung function, results in chronic respiratory illnesses, and is associated with increased mortality. The proposed mechanisms revolve around oxidative stress and inflammation promoting pulmonary physiological remodeling. However, our previous data found that PM is capable of inducing T helper cell 17 (Th17) immune responses via aryl hydrocarbon receptor (Ahr) activation, which was associated with neutrophilic invasion characteristic of steroid insensitive asthma. METHODS: In the present study, we utilized a combination of microarray and single cell RNA sequencing data to analyze the immunological landscape in mouse lungs following acute exposure to combustion derived particulate matter. RESULTS: We present data that suggest epithelial cells produce specific cytokines in the aryl hydrocarbon receptor (Ahr) pathway that inform dendritic cells to initiate the production of pathogenic T helper (eTh17) cells. Using single-cell RNA sequencing analysis, we observed that upon exposure epithelial cells acquire a transcriptomic profile indicative of increased Il-17 signaling, Ahr activation, Egfr signaling, and T cell receptor and co-stimulatory signaling pathways. Epithelial cells further showed, Ahr activation is brought on by Ahr/ARNT nuclear translocation and activation of tyrosine kinase c-src, Egfr, and subsequently Erk1/2 pathways. CONCLUSIONS: Collectively, our data corroborates that PM initiates an eTh17 specific inflammatory response causing neutrophilic asthma through pathways in epithelial, dendritic, and T cells that promote eTh17 differentiation during initial PM exposure.

Kidney Single-Cell Atlas Reveals Myeloid Heterogeneity in Progression and Regression of Kidney Disease.

BACKGROUND: Little is known about the roles of myeloid cell subsets in kidney injury and in the limited ability of the organ to repair itself. Characterizing these cells based only on surface markers using flow cytometry might not provide a full phenotypic picture. Defining these cells at the single-cell, transcriptomic level could reveal myeloid heterogeneity in the progression and regression of kidney disease. METHODS: Integrated droplet- and plate-based single-cell RNA sequencing were used in the murine, reversible, unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single-cell level during renal injury and the resolution of fibrosis. Paired blood exchange tracked the fate of monocytes recruited to the injured kidney. RESULTS: A single-cell atlas of the kidney generated using transcriptomics revealed marked changes in the proportion and gene expression of renal cell types during injury and repair. Conventional flow cytometry markers would not have identified the 12 myeloid cell subsets. Monocytes recruited to the kidney early after injury rapidly adopt a proinflammatory, profibrotic phenotype that expresses Arg1, before transitioning to become Ccr2+ macrophages that accumulate in late injury. Conversely, a novel Mmp12+ macrophage subset acts during repair. CONCLUSIONS: Complementary technologies identified novel myeloid subtypes, based on transcriptomics in single cells, that represent therapeutic targets to inhibit progression or promote regression of kidney disease.

Single-Cell RNA Sequencing Reveals Renal Endothelium Heterogeneity and Metabolic Adaptation to Water Deprivation.

BACKGROUND: Renal endothelial cells from glomerular, cortical, and medullary kidney compartments are exposed to different microenvironmental conditions and support specific kidney processes. However, the heterogeneous phenotypes of these cells remain incompletely inventoried. Osmotic homeostasis is vitally important for regulating cell volume and function, and in mammals, osmotic equilibrium is regulated through the countercurrent system in the renal medulla, where water exchange through endothelium occurs against an osmotic pressure gradient. Dehydration exposes medullary renal endothelial cells to extreme hyperosmolarity, and how these cells adapt to and survive in this hypertonic milieu is unknown. METHODS: We inventoried renal endothelial cell heterogeneity by single-cell RNA sequencing >40,000 mouse renal endothelial cells, and studied transcriptome changes during osmotic adaptation upon water deprivation. We validated our findings by immunostaining and functionally by targeting oxidative phosphorylation in a hyperosmolarity model in vitro and in dehydrated mice in vivo. RESULTS: We identified 24 renal endothelial cell phenotypes (of which eight were novel), highlighting extensive heterogeneity of these cells between and within the cortex, glomeruli, and medulla. In response to dehydration and hypertonicity, medullary renal endothelial cells upregulated the expression of genes involved in the hypoxia response, glycolysis, and-surprisingly-oxidative phosphorylation. Endothelial cells increased oxygen consumption when exposed to hyperosmolarity, whereas blocking oxidative phosphorylation compromised endothelial cell viability during hyperosmotic stress and impaired urine concentration during dehydration. CONCLUSIONS: This study provides a high-resolution atlas of the renal endothelium and highlights extensive renal endothelial cell phenotypic heterogeneity, as well as a previously unrecognized role of oxidative phosphorylation in the metabolic adaptation of medullary renal endothelial cells to water deprivation.

Transcriptional Differences in Lipid-Metabolizing Enzymes in Murine Sebocytes Derived from Sebaceous Glands of the Skin and Preputial Glands.

Sebaceous glands are adnexal structures, which critically contribute to skin homeostasis and the establishment of a functional epidermal barrier. Sebocytes, the main cell population found within the sebaceous glands, are highly specialized lipid-producing cells. Sebaceous gland-resembling tissue structures are also found in male rodents in the form of preputial glands. Similar to sebaceous glands, they are composed of lipid-specialized sebocytes. Due to a lack of adequate organ culture models for skin sebaceous glands and the fact that preputial glands are much larger and easier to handle, previous studies used preputial glands as a model for skin sebaceous glands. Here, we compared both types of sebocytes, using a single-cell RNA sequencing approach, to unravel potential similarities and differences between the two sebocyte populations. In spite of common gene expression patterns due to general lipid-producing properties, we found significant differences in the expression levels of genes encoding enzymes involved in the biogenesis of specialized lipid classes. Specifically, genes critically involved in the mevalonate pathway, including squalene synthase, as well as the sphingolipid salvage pathway, such as ceramide synthase, (acid) sphingomyelinase or acid and alkaline ceramidases, were significantly less expressed by preputial gland sebocytes. Together, our data revealed tissue-specific sebocyte populations, indicating major developmental, functional as well as biosynthetic differences between both glands. The use of preputial glands as a surrogate model to study skin sebaceous glands is therefore limited, and major differences between both glands need to be carefully considered before planning an experiment.

Single-cell RNA sequencing identifies interferon-inducible monocytes/macrophages as a cellular target for mitigating the progression of abdominal aortic aneurysm and rupture risk.

AIMS: Abdominal aortic aneurysm (AAA) represents a life-threatening condition characterized by medial layer degeneration of the abdominal aorta. Nevertheless, knowledge regarding changes in regulators associated with aortic status remains incomplete. A thorough understanding of cell types and signalling pathways involved in the development and progression of AAAs is essential for the development of medical therapy. METHODS AND RESULTS: We harvested specimens of the abdominal aorta with different pathological features in Angiotensin II (AngII)-infused ApoE-/- mice, conducted scRNA-seq, and identified a unique population of interferon-inducible monocytes/macrophages (IFNICs), which were amply found in the AAAs. Gene set variation analysis revealed that activation of the cytosolic DNA sensing cGAS-STING and JAK-STAT pathways promoted the secretion of type I interferons in monocytes/macrophages and differentiated them into IFNICs. We generated myeloid cell-specific deletion of Sting1 (Lyz2-Cre+/-; Sting1flox/flox) mice and performed bone marrow transplantation and found that myeloid cell-specific deletion of Sting1 or Ifnar1 significantly reduced the incidence of AAA, aortic rupture rate, and diameter of the abdominal aorta. Mechanistically, the activated pyroptosis- and inflammation-related signalling pathways, regulated by IRF7 in IFNICs, play critical roles in the developing AAAs. CONCLUSION: IFNICs are a unique monocyte/macrophage subset implicated in the development of AAAs and aortic rupture.

Identification of immune characteristic biomarkers and therapeutic targets in cuproptosis for sepsis by integrated bioinformatics analysis and single-cell RNA sequencing analysis.

Background: Cuproptosis is a copper-dependent cell death that is connected to the development and immune response of multiple diseases. However, the function of cuproptosis in the immune characteristics of sepsis remains unclear. Method: We obtained two sepsis datasets (GSE9960 and GSE134347) from the GEO database and classified the raw data with R packages. Cuproptosis-related genes were manually curated, and differentially expressed cuproptosis-related genes (DECuGs) were identified. Afterwards, we applied enrichment analysis and identified key DECuGs by performing machine learning techniques. Then, the immune cell infiltrations and correlation between DECuGs and immunocyte features were created by the CIBERSORT algorithm. Subsequently, unsupervised hierarchical clustering analysis was performed based on key DECuGs. We then constructed a ceRNA network based on key DECuGs by using multi-step computational strategies and predicted potential drugs in the DrugBank database. Finally, the role of these key genes in immune cells was validated at the single-cell RNA level between septic patients and healthy controls. Results: Overall, 16 DECuGs were obtained, and most of them had lower expression levels in sepsis samples. Afterwards, we obtained six key DECuGs by performing machine learning. Then, the LIPT1-T-cell CD4 memory resting was the most positively correlated DECuG-immunocyte pair. Subsequently, two different subclusters were identified by six DECuGs. Bioinformatics analysis revealed that there were different immune characteristics between the two subclusters. Moreover, we identified the key lncRNA OIP5-AS1 within the ceRNA network and obtained 4 drugs that may represent novel drugs for sepsis. Finally, these key DECuGs were statistically significantly dysregulated in another validation set and showed a major distribution in monocytes, T cells, B cells, NK cells and platelets at the single-cell RNA level. Conclusion: These findings suggest that cuproptosis might promote the progression of sepsis by affecting the immune system and metabolic dysfunction, which provides a new direction for understanding potential pathogenic processes and therapeutic targets in sepsis.

Single-cell transcriptomics reveals the ameliorative effect of rosmarinic acid on diabetic nephropathy-induced kidney injury by modulating oxidative stress and inflammation.

Diabetic nephropathy (DN) is a severe complication of diabetes, characterized by changes in kidney structure and function. The natural product rosmarinic acid (RA) has demonstrated therapeutic effects, including anti-inflammation and anti-oxidative-stress, in renal damage or dysfunction. In this study, we characterized the heterogeneity of the cellular response in kidneys to DN-induced injury and RA treatment at single cell levels. Our results demonstrated that RA significantly alleviated renal tubular epithelial injury, particularly in the proximal tubular S1 segment and on glomerular epithelial cells known as podocytes, while attenuating the inflammatory response of macrophages, oxidative stress, and cytotoxicity of natural killer cells. These findings provide a comprehensive understanding of the mechanisms by which RA alleviates kidney damage, oxidative stress, and inflammation, offering valuable guidance for the clinical application of RA in the treatment of DN.

Patient-Derived Organoids Recapitulate Pathological Intrinsic and Phenotypic Features of Fibrous Dysplasia.

Fibrous dysplasia (FD) is a rare bone disorder characterized by the replacement of normal bone with benign fibro-osseous tissue. Developments in our understanding of the pathophysiology and treatment options are impeded by the lack of suitable research models. In this study, we developed an in vitro organotypic model capable of recapitulating key intrinsic and phenotypic properties of FD. Initially, transcriptomic profiling of individual cells isolated from patient lesional tissues unveiled intralesional molecular and cellular heterogeneity. Leveraging these insights, we established patient-derived organoids (PDOs) using primary cells obtained from patient FD lesions. Evaluation of PDOs demonstrated preservation of fibrosis-associated constituent cell types and transcriptional signatures observed in FD lesions. Additionally, PDOs retained distinct constellations of genomic and metabolic alterations characteristic of FD. Histological evaluation further corroborated the fidelity of PDOs in recapitulating important phenotypic features of FD that underscore their pathophysiological relevance. Our findings represent meaningful progress in the field, as they open up the possibility for in vitro modeling of rare bone lesions in a three-dimensional context and may signify the first step towards creating a personalized platform for research and therapeutic studies.

Image-based profiling and deep learning reveal morphological heterogeneity of colorectal cancer organoids.

Patient-derived organoids have proven to be a highly relevant model for evaluating of disease mechanisms and drug efficacies, as they closely recapitulate in vivo physiology. Colorectal cancer organoids, specifically, exhibit a diverse range of morphologies, which have been analyzed with image-based profiling. However, the relationship between morphological subtypes and functional parameters of the organoids remains underexplored. Here, we identified two distinct morphological subtypes ("cystic" and "solid") across 31360 bright field images using image-based profiling, which correlated differently with viability and apoptosis level of colorectal cancer organoids. Leveraging object detection neural networks, we were able to categorize single organoids achieving higher viability scores as "cystic" than "solid" subtype. Furthermore, a deep generative model was proposed to predict apoptosis intensity based on a apoptosis-featured dataset encompassing over 17000 bright field and matched fluorescent images. Notably, a significant correlation of 0.91 between the predicted value and ground truth was achived, underscoring the feasibility of this generative model as a potential means for assessing organoid functional parameters. The underlying cellular heterogeneity of the organoids, i.e., conserved colonic cell types and rare immune components, was also verified with scRNA sequencing, implying a compromised tumor microenvironment. Additionally, the "cystic" subtype was identified as a relapse phenotype featuring intestinal stem cell signatures, suggesting that this visually discernible relapse phenotype shows potential as a novel biomarker for colorectal cancer diagnosis and prognosis. In summary, our findings demonstrate that the morphological heterogeneity of colorectal cancer organoids explicitly recapitulate the association of phenotypic features and exogenous perturbations through the image-based profiling, providing new insights into disease mechanisms.

High-resolution transcriptomics analysis of CXCL13+ EPSTI1+ CDK1+ cells with a specific focus on lung adenocarcinoma.

Background: Programmed cell death ligand 1 (PD-L1) blocking therapy has transformed the treatment of lung adenocarcinoma (LUAD), which has significantly changed the landscape of immunotherapy. We aimed to explore specific cell subpopulations to understand tumor progression and identify markers of response to PD-L1 blocking therapy. Methods: Bulk, fluorescence-activated cell sorting (FACS), and single-cell RNA (scRNA) sequencing were used to profile CXCL13, EPSTI1, and CDK1. The gene set variation analysis (GSVA) R package was utilized for score calculation, and prognostic analyses included receiver operating characteristic (ROC) curves, Cox proportional hazard models, and meta-analysis. Additionally, we analyzed tumor microenvironment (TME), genomics, compound perturbations, and clinical indicators. The high-dimensional analysis captured the intrinsic characteristics of the subpopulation. Furthermore, subpopulation differential genes were used for enrichment analysis of transcription factors and compounds. Results: Literature and website analyses supported the essential role of CXCL13, CDK1, and EPSTI1 in immunotherapy. This led us to focus specifically on LUAD by representing a pan-cancer profile of immune-sensitive genes. Logically, the high-characteristic population may consist of samples positive for CXCL13, EPSTI1, and CDK1. The three-gene signature was a favorable indicator of immunotherapy response in the Stand Up to Cancer-Mark Foundation (SU2C-MARK) LUAD cohort but showed a poor prognosis before treatment in the Lung Cancer Explorer (LCE) database. Further mechanistic exploration revealed specific mutations associated with the three-gene signature in SU2C-MARK LUAD, such as STK11. In The Cancer Genome Atlas (TCGA)-LUAD cohort, the high-scoring group exhibited a higher tumor mutational burden (TMB) and global methylation but a lower fraction genome altered (FGA) and estimated tumor purity. Moreover, dasatinib demonstrated sensitivity in the high-scoring group. The co-localization of the CXCL13, EPSTI1, and CDK1 subpopulation was validated through spatial transcriptome and immunohistochemical databases. Assessment of the subpopulation depicted high-resolution intercellular communication. Maintenance of specific pathways, such as TNF, CD74, and CD44, contributed to immunotherapy sensitivity. Finally, the subpopulation-enriched targets and drugs were confirmed through ConnectivityMap (CMAP) analysis and multi-omics, respectively. Conclusions: In this study, positive samples for CXCL13, EPSTI1, and CDK1 exhibited poor prognostic significance in treatment-naïve LUAD cases but demonstrated benefits from PD-L1 blockade and dasatinib therapies.