Preexisting Skin-Resident CD8 and γδ 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 sequencing (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 nonresponders, tumors show evidence of increased tumor proliferation, neuronal stem cell markers, and IL1.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

Riemannian geometry and statistical modeling correct for batch effects and control false discoveries in single-cell surface protein count data.

Recent advances in next generation sequencing-based single-cell technologies have allowed high-throughput quantitative detection of cell-surface proteins along with the transcriptome in individual cells, extending our understanding of the heterogeneity of cell populations in diverse tissues that are in different diseased states or under different experimental conditions. Count data of surface proteins from the cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) technology pose new computational challenges, and there is currently a dearth of rigorous mathematical tools for analyzing the data. This work utilizes concepts and ideas from Riemannian geometry to remove batch effects between samples and develops a statistical framework for distinguishing positive signals from background noise.

Multiregion exome sequencing of ovarian immature teratomas reveals 2N near-diploid genomes, paucity of somatic mutations, and extensive allelic imbalances shared across mature, immature, and disseminated components.

Immature teratoma is a subtype of malignant germ cell tumor of the ovary that occurs most commonly in the first three decades of life, frequently with bilateral ovarian disease. Despite being the second most common malignant germ cell tumor of the ovary, little is known about its genetic underpinnings. Here we performed multiregion whole-exome sequencing to interrogate the genetic zygosity, clonal relationship, DNA copy number, and mutational status of 52 pathologically distinct tumor components from ten females with ovarian immature teratomas, with bilateral tumors present in five cases and peritoneal dissemination in seven cases.

Single-Cell Transcriptomics Reveals Spatial and Temporal Turnover of Keratinocyte Differentiation Regulators.

Keratinocyte differentiation requires intricately coordinated spatiotemporal expression changes that specify epidermis structure and function. This article utilizes single-cell RNA-seq data from 22,338 human foreskin keratinocytes to reconstruct the transcriptional regulation of skin development and homeostasis genes, organizing them by differentiation stage and also into transcription factor (TF)-associated modules. We identify groups of TFs characterized by coordinate expression changes during progression from the undifferentiated basal to the differentiated state and show that these TFs also have concordant differential predicted binding enrichment in the super-enhancers previously reported to turn over between the two states.