Genetic evolution of keratinocytes to cutaneous squamous cell carcinoma.

We performed multi-omic profiling of epidermal keratinocytes, precancerous actinic keratoses, and squamous cell carcinomas to understand the molecular transitions during skin carcinogenesis. Single-cell mutational analyses showed that most keratinocytes in normal skin had lower mutation burdens than melanocytes and fibroblasts, however keratinocytes with TP53 or NOTCH1 mutations had substantially higher mutation burdens, suggesting that these mutations prime keratinocytes for transformation by increasing their mutation rate. Mutational profiling and spatial transcriptomics on squamous cell carcinomas adjacent to actinic keratoses revealed TERT promoter and CDKN2A mutations emerging in actinic keratoses, whereas additional mutations inactivating ARID2 and activating the MAPK-pathway delineated the transition to squamous cell carcinomas. Spatial variation in gene expression patterns was common in both tumor and immune cells, with high expression of checkpoint molecules at the invasive front of tumors. In conclusion, this study documents key events during the evolution of cutaneous squamous cell carcinoma.

Discovery and generalization of tissue structures from spatial omics data.

Tissues are organized into anatomical and functional units at different scales. New technologies for high-dimensional molecular profiling in situ have enabled the characterization of structure-function relationships in increasing molecular detail. However, it remains a challenge to consistently identify key functional units across experiments, tissues, and disease contexts, a task that demands extensive manual annotation. Here, we present spatial cellular graph partitioning (SCGP), a flexible method for the unsupervised annotation of tissue structures. We further present a reference-query extension pipeline, SCGP-Extension, that generalizes reference tissue structure labels to previously unseen samples, performing data integration and tissue structure discovery. Our experiments demonstrate reliable, robust partitioning of spatial data in a wide variety of contexts and best-in-class accuracy in identifying expertly annotated structures. Downstream analysis on SCGP-identified tissue structures reveals disease-relevant insights regarding diabetic kidney disease, skin disorder, and neoplastic diseases, underscoring its potential to drive biological insight and discovery from spatial datasets.

Pre-existing skin-resident CD8 and gd T cell circuits mediate immune response in Merkel cell carcinoma and predict immunotherapy efficacy.

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer with a ~50% response rate to immune checkpoint blockade (ICB) therapy. To identify predictive biomarkers, we integrated bulk and single-cell RNA-seq with spatial transcriptomics from a cohort of 186 samples from 116 patients, including bulk RNA-seq from 14 matched pairs pre- and post-ICB. In non-responders, tumors show evidence of increased tumor proliferation, neuronal stem cell markers, and IL-1. Responders have increased type I/II interferons and pre-existing tissue resident (Trm) CD8 or Vd1 gd T cells that functionally converge with overlapping antigen-specific transcriptional programs and clonal expansion of public TCRs. Spatial transcriptomics demonstrated co-localization of T cells with B and dendritic cells, which supply chemokines and co-stimulation. Lastly, ICB significantly increased clonal expansion or recruitment of Trm and Vd1 cells in tumors specifically in responders, underscoring their therapeutic importance. These data identify potential clinically actionable biomarkers and therapeutic targets for MCC.

Skin in the game: a review of single-cell and spatial transcriptomics in dermatological research.

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) are two emerging research technologies that uniquely characterize gene expression microenvironments on a cellular or subcellular level. The skin, a clinically accessible tissue composed of diverse, essential cell populations, serves as an ideal target for these high-resolution investigative approaches. Using these tools, researchers are assembling a compendium of data and discoveries in healthy skin as well as a range of dermatologic pathophysiologies, including atopic dermatitis, psoriasis, and cutaneous malignancies. The ongoing advancement of single-cell approaches, coupled with anticipated decreases in cost with increased adoption, will reshape dermatologic research, profoundly influencing disease characterization, prognosis, and ultimately clinical practice.

Short cell cycle duration is a phenotype of human epidermal stem cells.

BACKGROUND: A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs). METHODS: We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing. RESULTS: We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC. CONCLUSIONS: Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

A single-cell atlas of IL-23 inhibition in cutaneous psoriasis distinguishes clinical response.

Psoriasis vulgaris and other chronic inflammatory diseases improve markedly with therapeutic blockade of interleukin-23 (IL-23) signaling, but the genetic mechanisms underlying clinical responses remain poorly understood. Using single-cell transcriptomics, we profiled immune cells isolated from lesional psoriatic skin before and during IL-23 blockade. In clinically responsive patients, a psoriatic transcriptional signature in skin-resident memory T cells was strongly attenuated. In contrast, poorly responsive patients were distinguished by persistent activation of IL-17-producing T (T17) cells, a mechanism distinct from alternative cytokine signaling or resistance isolated to epidermal keratinocytes. Even in IL-23 blockade-responsive patients, we detected a recurring set of recalcitrant, disease-specific transcriptional abnormalities. This irreversible immunological state may necessitate ongoing IL-23 inhibition. Spatial transcriptomic analyses also suggested that successful IL-23 blockade requires dampening of >90% of IL-17-induced response in lymphocyte-adjacent keratinocytes, an unexpectedly high threshold. Collectively, our data establish a patient-level paradigm for dissecting responses to immunomodulatory treatments.

STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer.

Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.

GLUT3 promotes macrophage signaling and function via RAS-mediated endocytosis in atopic dermatitis and wound healing.

The facilitative GLUT1 and GLUT3 hexose transporters are expressed abundantly in macrophages, but whether they have distinct functions remains unclear. We confirmed that GLUT1 expression increased after M1 polarization stimuli and found that GLUT3 expression increased after M2 stimulation in macrophages. Conditional deletion of Glut3 (LysM-Cre Glut3fl/fl) impaired M2 polarization of bone marrow-derived macrophages. Alternatively activated macrophages from the skin of patients with atopic dermatitis showed increased GLUT3 expression, and a calcipotriol-induced model of atopic dermatitis was rescued in LysM-Cre Glut3fl/fl mice. M2-like macrophages expressed GLUT3 in human wound tissues as assessed by transcriptomics and costaining, and GLUT3 expression was significantly decreased in nonhealing, compared with healing, diabetic foot ulcers. In an excisional wound healing model, LysM-Cre Glut3fl/fl mice showed significantly impaired M2 macrophage polarization and delayed wound healing. GLUT3 promoted IL-4/STAT6 signaling, independently of its glucose transport activity. Unlike plasma membrane-localized GLUT1, GLUT3 was localized primarily to endosomes and was required for the efficient endocytosis of IL-4Rα subunits. GLUT3 interacted directly with GTP-bound RAS in vitro and in vivo through its intracytoplasmic loop domain, and this interaction was required for efficient STAT6 activation and M2 polarization. PAK activation and macropinocytosis were also impaired without GLUT3, suggesting broader roles for GLUT3 in the regulation of endocytosis. Thus, GLUT3 is required for efficient alternative macrophage polarization and function, through a glucose transport-independent, RAS-mediated role in the regulation of endocytosis and IL-4/STAT6 activation.

Isolation of human cutaneous immune cells for single-cell RNA sequencing.

Single-cell RNA sequencing (scRNA-seq) allows for high-resolution analysis of transcriptionally dysregulated cell subpopulations in inflammatory diseases. However, it can be challenging to properly isolate viable immune cells from human skin for scRNA-seq due to its barrier properties. Here, we present a protocol to isolate high-viability human cutaneous immune cells. We describe steps for obtaining and enzymatically dissociating a skin biopsy specimen and isolating immune cells using flow cytometry. We then provide an overview of downstream computational techniques to analyze sequencing data. For complete details on the use and execution of this protocol, please refer to Cook et al. (2022)1 and Liu et al. (2022).2.

A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity.

The homeostatic mechanisms that fail to restrain chronic tissue inflammation in diseases, such as psoriasis vulgaris, remain incompletely understood. We profiled transcriptomes and epitopes of single psoriatic and normal skin-resident T cells, revealing a gradated transcriptional program of coordinately regulated inflammation-suppressive genes. This program, which is sharply suppressed in lesional skin, strikingly restricts Th17/Tc17 cytokine and other inflammatory mediators on the single-cell level. CRISPR-based deactivation of two core components of this inflammation-suppressive program, ZFP36L2 and ZFP36, replicates the interleukin-17A (IL-17A), granulocyte macrophage-colony-stimulating factor (GM-CSF), and interferon gamma (IFNγ) elevation in psoriatic memory T cells deficient in these transcripts, functionally validating their influence. Combinatoric expression analysis indicates the suppression of specific inflammatory mediators by individual program members. Finally, we find that therapeutic IL-23 blockade reduces Th17/Tc17 cell frequency in lesional skin but fails to normalize this inflammatory-suppressive program, suggesting how treated lesions may be primed for recurrence after withdrawal of treatment.

Defining Patient-Level Molecular Heterogeneity in Psoriasis Vulgaris Based on Single-Cell Transcriptomics.

Identifying genetic variation underlying human diseases establishes targets for therapeutic development and helps tailor treatments to individual patients. Large-scale transcriptomic profiling has extended the study of such molecular heterogeneity between patients to somatic tissues. However, the lower resolution of bulk RNA profiling, especially in a complex, composite tissue such as the skin, has limited its success. Here we demonstrate approaches to interrogate patient-level molecular variance in a chronic skin inflammatory disease, psoriasis vulgaris, leveraging single-cell RNA-sequencing of CD45+ cells isolated from active lesions. Highly psoriasis-specific transcriptional abnormalities display greater than average inter-individual variance, nominating them as potential sources of clinical heterogeneity. We find that one of these chemokines, CXCL13, demonstrates significant correlation with severity of lesions within our patient series. Our analyses also establish that genes elevated in psoriatic skin-resident memory T cells are enriched for programs orchestrating chromatin and CDC42-dependent cytoskeleton remodeling, specific components of which are distinctly correlated with and against Th17 identity on a single-cell level. Collectively, these analyses describe systematic means to dissect cell type- and patient-level differences in cutaneous psoriasis using high-resolution transcriptional profiles of human inflammatory disease.

Spectral clustering of single-cell multi-omics data on multilayer graphs.

MOTIVATION: Single-cell sequencing technologies that simultaneously generate multimodal cellular profiles present opportunities for improved understanding of cell heterogeneity in tissues. How the multimodal information can be integrated to obtain a common cell type identification, however, poses a computational challenge. Multilayer graphs provide a natural representation of multi-omic single-cell sequencing datasets, and finding cell clusters may be understood as a multilayer graph partition problem. RESULTS: We introduce two spectral algorithms on multilayer graphs, spectral clustering on multilayer graphs and the weighted locally linear (WLL) method, to cluster cells in multi-omic single-cell sequencing datasets. We connect these algorithms through a unifying mathematical framework that represents each layer using a Hamiltonian operator and a mixture of its eigenstates to integrate the multiple graph layers, demonstrating in the process that the WLL method is a rigorous multilayer spectral graph theoretic reformulation of the popular Seurat weighted nearest neighbor (WNN) algorithm. Implementing our algorithms and applying them to a CITE-seq dataset of cord blood mononuclear cells yields results similar to the Seurat WNN analysis. Our work thus extends spectral methods to multimodal single-cell data analysis. AVAILABILITY AND IMPLEMENTATION: The code used in this study can be found at https://github.com/jssong-lab/sc-spectrum. All public data used in the article are accurately cited and described in Materials and Methods and in Supplementary Information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Classification of human chronic inflammatory skin disease based on single-cell immune profiling.

Inflammatory conditions represent the largest class of chronic skin disease, but the molecular dysregulation underlying many individual cases remains unclear. Single-cell RNA sequencing (scRNA-seq) has increased precision in dissecting the complex mixture of immune and stromal cell perturbations in inflammatory skin disease states. We single-cell-profiled CD45+ immune cell transcriptomes from skin samples of 31 patients (7 atopic dermatitis, 8 psoriasis vulgaris, 2 lichen planus (LP), 1 bullous pemphigoid (BP), 6 clinical/histopathologically indeterminate rashes, and 7 healthy controls). Our data revealed active proliferative expansion of the Treg and Trm components and universal T cell exhaustion in human rashes, with a relative attenuation of antigen-presenting cells. Skin-resident memory T cells showed the greatest transcriptional dysregulation in both atopic dermatitis and psoriasis, whereas atopic dermatitis also demonstrated recurrent abnormalities in ILC and CD8+ cytotoxic lymphocytes. Transcript signatures differentiating these rash types included genes previously implicated in T helper cell (TH2)/TH17 diatheses, segregated in unbiased functional networks, and accurately identified disease class in untrained validation data sets. These gene signatures were able to classify clinicopathologically ambiguous rashes with diagnoses consistent with therapeutic response. Thus, we have defined major classes of human inflammatory skin disease at the molecular level and described a quantitative method to classify indeterminate instances of pathologic inflammation. To make this approach accessible to the scientific community, we created a proof-of-principle web interface (RashX), where scientists and clinicians can visualize their patient-level rash scRNA-seq-derived data in the context of our TH2/TH17 transcriptional framework.

Elevated APOBEC mutational signatures implicate chronic injury in etiology of an aggressive head-and-neck squamous cell carcinoma: a case report.

BACKGROUND: Aggressive squamous cell carcinomas (SCCs) present frequently in the context of chronic skin injury occurring in patients with the congenital blistering disease recessive dystrophic epidermolysis bullosa. Recently, these cancers were shown to harbor mutation signatures associated with endogenous deaminases of the active polynucleotide cytosine deaminase family, collectively termed APOBEC, and clock-like COSMIC [Catalogue of Somatic Mutations in Cancer] signatures, which are associated with normal aging and might result from cumulative DNA replication errors. We present a case of a nasal septal SCC arising in the context of recurrent injury, but also modest past tobacco use. Our genetic analysis of this tumor reveals unusually high APOBEC and clock-like but low tobacco-related COSMIC signatures, suggesting that chronic injury may have played a primary role in somatic mutation. This case report demonstrates how signature-based analyses may implicate key roles for certain mutagenic forces in individual malignancies such as head-and-neck SCC, with multiple etiological origins. CASE PRESENTATION: We report the case of a 43-year-old male former smoker who presented with congestion and swelling following a traumatic nasal fracture. During surgery, the mucosa surrounding the right nasal valve appeared abnormal, and biopsies revealed invasive keratinizing SCC. Frozen section biopsies revealed multiple areas to be positive for SCC. Gene sequencing showed loss of PTEN (exons 2-8), CDKN2A/B and TP53 (exons 8-9), MYC amplification, and BLM S338*. Exome sequencing data also revealed that 36% of mutations matched an APOBEC mutational signature (COSMIC signatures 2 and 13) and 53% of mutations matched the clock-like mutation signature (COSMIC signature 5). These proportions place this tumor in the 90th percentile bearing each signature, independently, in a reference data set combining cutaneous and The Cancer Genome Atlas (TCGA) head and neck SCC data. In contrast, few mutations harbored a tobacco-related COSMIC signature 4, representing about the 10th percentile in our reference SCC data set. The patient was treated with partial rhinectomy with local flap reconstruction, bilateral neck dissection, and adjuvant radiation therapy; the patient remains disease-free to date. CONCLUSION: Based on comparative mutational signature analysis, we propose that the history of tobacco use and traumatic injury may have collaborated in activating APOBEC enzymes and the clock-like mutational process, ultimately leading to cancer formation. Clinical awareness of the relationship between epithelial injury and tumorigenesis should enhance earlier detection of this particularly aggressive type of cancer.

Evolution of late-stage metastatic melanoma is dominated by aneuploidy and whole genome doubling.

Although melanoma is initiated by acquisition of point mutations and limited focal copy number alterations in melanocytes-of-origin, the nature of genetic changes that characterise lethal metastatic disease is poorly understood. Here, we analyze the evolution of human melanoma progressing from early to late disease in 13 patients by sampling their tumours at multiple sites and times. Whole exome and genome sequencing data from 88 tumour samples reveals only limited gain of point mutations generally, with net mutational loss in some metastases. In contrast, melanoma evolution is dominated by whole genome doubling and large-scale aneuploidy, in which widespread loss of heterozygosity sculpts the burden of point mutations, neoantigens and structural variants even in treatment-naïve and primary cutaneous melanomas in some patients. These results imply that dysregulation of genomic integrity is a key driver of selective clonal advantage during melanoma progression.

Single-Cell Profiling Reveals Divergent, Globally Patterned Immune Responses in Murine Skin Inflammation.

Inflammatory response heterogeneity has impeded high-resolution dissection of diverse immune cell populations during activation. We characterize mouse cutaneous immune cells by single-cell RNA sequencing, after inducing inflammation using imiquimod and oxazolone dermatitis models. We identify 13 CD45+ subpopulations, which broadly represent most functionally characterized immune cell types. Oxazolone pervasively upregulates Jak2/Stat3 expression across T cells and antigen-presenting cells (APCs). Oxazolone also induces Il4/Il13 expression in newly infiltrating basophils, and Il4ra and Ccl24, most prominently in APCs. In contrast, imiquimod broadly upregulates Il17/Il22 and Ccl4/Ccl5. A comparative analysis of single-cell inflammatory transcriptional responses reveals that APC response to oxazolone is tightly restricted by cell identity, whereas imiquimod enforces shared programs on multiple APC populations in parallel. These global molecular patterns not only contrast immune responses on a systems level but also suggest that the mechanisms of new sources of inflammation can eventually be deduced by comparison to known signatures.

Cells from discarded dressings differentiate chronic from acute wounds in patients with Epidermolysis Bullosa.

Impaired wound healing complicates a wide range of diseases and represents a major cost to healthcare systems. Here we describe the use of discarded wound dressings as a novel, cost effective, accessible, and non-invasive method of isolating viable human cells present at the site of skin wounds. By analyzing 133 discarded wound dressings from 51 patients with the inherited skin-blistering disease epidermolysis bullosa (EB), we show that large numbers of cells, often in excess of 100 million per day, continually infiltrate wound dressings. We show, that the method is able to differentiate chronic from acute wounds, identifying significant increases in granulocytes in chronic wounds, and we show that patients with the junctional form of EB have significantly more cells infiltrating their wounds compared with patients with recessive dystrophic EB. Finally, we identify subsets of granulocytes and T lymphocytes present in all wounds paving the way for single cell profiling of innate and adaptive immune cells with relevance to wound pathologies. In summary, our study delineates findings in EB that have potential relevance for all chronic wounds, and presents a method of cellular isolation that has wide reaching clinical application.

Pervasive chromosomal instability and karyotype order in tumour evolution.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.