Screening cell-cell communication in spatial transcriptomics via collective optimal transport.

Spatial transcriptomic technologies and spatially annotated single-cell RNA sequencing datasets provide unprecedented opportunities to dissect cell-cell communication (CCC). However, incorporation of the spatial information and complex biochemical processes required in the reconstruction of CCC remains a major challenge. Here, we present COMMOT (COMMunication analysis by Optimal Transport) to infer CCC in spatial transcriptomics, which accounts for the competition between different ligand and receptor species as well as spatial distances between cells. A collective optimal transport method is developed to handle complex molecular interactions and spatial constraints. Furthermore, we introduce downstream analysis tools to infer spatial signaling directionality and genes regulated by signaling using machine learning models. We apply COMMOT to simulation data and eight spatial datasets acquired with five different technologies to show its effectiveness and robustness in identifying spatial CCC in data with varying spatial resolutions and gene coverages. Finally, COMMOT identifies new CCCs during skin morphogenesis in a case study of human epidermal development.

An Optimized Enzyme-Nucleobase Pair Enables In Vivo RNA Metabolic Labeling with Improved Cell-Specificity.

Current transcriptome-wide analyses have identified a growing number of regulatory RNA with expression that is characterized in a cell-type-specific manner. Herein, we describe RNA metabolic labeling with improved cell-specificity utilizing the in vivo expression of an optimized uracil phosphoribosyltransferase (UPRT) enzyme. We demonstrate improved selectivity for metabolic incorporation of a modified nucleobase (5-vinyuracil) into nascent RNA, using a battery of tests. The selective incorporation of vinyl-U residues was demonstrated in 3xUPRT LM2 cells through validation with dot blot, qPCR, LC-MS/MS and microscopy analysis. We also report using this approach in a metastatic human breast cancer mouse model for profiling cell-specific nascent RNA.

Exploiting Endogenous Enzymes for Cancer-Cell Selective Metabolic Labeling of RNA in Vivo.

Tissues and organs are composed of many diverse cell types, making cell-specific gene expression profiling a major challenge. Herein we report that endogenous enzymes, unique to a cell of interest, can be utilized to enable cell-specific metabolic labeling of RNA. We demonstrate that appropriately designed "caged" nucleosides can be rendered active by serving as a substrate for cancer-cell specific enzymes to enable RNA metabolic labeling, only in cancer cells. We envision that the ease and high stringency of our approach will enable expression analysis of tumor cells in complex environments.

MTOR promotes basal cell carcinoma growth through atypical PKC.

Advanced basal cell carcinomas (BCCs) are driven by the Hedgehog (HH) pathway and often possess inherent resistance to SMO inhibitors. Identifying and targeting pathways that bypass SMO could provide alternative treatments for patients with advanced or metastatic BCC. Here, we use a combination of RNA-sequencing analysis of advanced human BCC tumor-normal pairs and immunostaining of human and mouse BCC samples to identify an MTOR expression signature in BCC. Pharmacological inhibition of MTOR activity in BCC cells significantly reduces cell proliferation without affecting HH signalling. Similarly, treatment of the Ptch1 fl/fl ; Gli1-CreERT2 mouse BCC tumor model with everolimus reduces tumor growth. aPKC, a downstream target of MTOR, shows reduced activity, suggesting that MTOR promotes tumor growth by activating aPKC and demonstrating that suppressing MTOR could be a promising target for BCC patients.

MTSS1/Src family kinase dysregulation underlies multiple inherited ataxias.

The genetically heterogeneous spinocerebellar ataxias (SCAs) are caused by Purkinje neuron dysfunction and degeneration, but their underlying pathological mechanisms remain elusive. The Src family of nonreceptor tyrosine kinases (SFK) are essential for nervous system homeostasis and are increasingly implicated in degenerative disease. Here we reveal that the SFK suppressor Missing-in-metastasis (MTSS1) is an ataxia locus that links multiple SCAs. MTSS1 loss results in increased SFK activity, reduced Purkinje neuron arborization, and low basal firing rates, followed by cell death. Surprisingly, mouse models for SCA1, SCA2, and SCA5 show elevated SFK activity, with SCA1 and SCA2 displaying dramatically reduced MTSS1 protein levels through reduced gene expression and protein translation, respectively. Treatment of each SCA model with a clinically approved Src inhibitor corrects Purkinje neuron basal firing and delays ataxia progression in MTSS1 mutants. Our results identify a common SCA therapeutic target and demonstrate a key role for MTSS1/SFK in Purkinje neuron survival and ataxia progression.

GLI activation by atypical protein kinase C ι/λ regulates the growth of basal cell carcinomas.

Growth of basal cell carcinomas (BCCs) requires high levels of hedgehog (HH) signalling through the transcription factor GLI. Although inhibitors of membrane protein smoothened (SMO) effectively suppress HH signalling, early tumour resistance illustrates the need for additional downstream targets for therapy. Here we identify atypical protein kinase C ι/λ (aPKC-ι/λ) as a novel GLI regulator in mammals. aPKC-ι/λ and its polarity signalling partners co-localize at the centrosome and form a complex with missing-in-metastasis (MIM), a scaffolding protein that potentiates HH signalling. Genetic or pharmacological loss of aPKC-ι/λ function blocks HH signalling and proliferation of BCC cells. Prkci is a HH target gene that forms a positive feedback loop with GLI and exists at increased levels in BCCs. Genome-wide transcriptional profiling shows that aPKC-ι/λ and SMO control the expression of similar genes in tumour cells. aPKC-ι/λ functions downstream of SMO to phosphorylate and activate GLI1, resulting in maximal DNA binding and transcriptional activation. Activated aPKC-ι/λ is upregulated in SMO-inhibitor-resistant tumours and targeting aPKC-ι/λ suppresses signalling and growth of resistant BCC cell lines. These results demonstrate that aPKC-ι/λ is critical for HH-dependent processes and implicates aPKC-ι/λ as a new, tumour-selective therapeutic target for the treatment of SMO-inhibitor-resistant cancers.

Cell-Selective Bioorthogonal Metabolic Labeling of RNA.

Stringent chemical methods to profile RNA expression within discrete cellular populations remains a key challenge in biology. To address this issue, we developed a chemical-genetic strategy for metabolic labeling of RNA. Cell-specific labeling of RNA can be profiled and imaged using bioorthogonal chemistry. We anticipate that this platform will provide the community with a much-needed chemical toolset for cell-type specific profiling of cell-specific transcriptomes derived from complex biological systems.

Partitioning-defective protein 6 (Par-6) activates atypical protein kinase C (aPKC) by pseudosubstrate displacement.

Atypical protein kinase C (aPKC) controls cell polarity by modulating substrate cortical localization. Aberrant aPKC activity disrupts polarity, yet the mechanisms that control aPKC remain poorly understood. We used a reconstituted system with purified components and a cultured cell cortical displacement assay to investigate aPKC regulation. We find that aPKC is autoinhibited by two domains within its NH(2)-terminal regulatory half, a pseudosubstrate motif that occupies the kinase active site, and a C1 domain that assists in this process. The Par complex member Par-6, previously thought to inhibit aPKC, is a potent activator of aPKC in our assays. Par-6 and aPKC interact via PB1 domain heterodimerization, and this interaction activates aPKC by displacing the pseudosubstrate, although full activity requires the Par-6 CRIB-PDZ domains. We propose that, along with its previously described roles in controlling aPKC localization, Par-6 allosterically activates aPKC to allow for high spatial and temporal control of substrate phosphorylation and polarization.

Leveraging gene correlations in single cell transcriptomic data.

BACKGROUND: Many approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data-looking for rare cell types, subtleties of cell states, and details of gene regulatory networks-there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data when ground truth about biological variation is unknown (i.e., usually). RESULTS: We approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization-a step that skews distributions, particularly for sparse data-and calculate p-values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene-gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships. CONCLUSIONS: New insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene-gene correlations.

Distinct mechanisms for sebaceous gland self-renewal and regeneration provide durability in response to injury.

Sebaceous glands (SGs) release oils that protect our skin, but how these glands respond to injury has not been previously examined. Here, we report that SGs are largely self-renewed by dedicated stem cell pools during homeostasis. Using targeted single cell RNA-sequencing, we uncovered both direct and indirect paths by which these resident SG progenitors ordinarily differentiate into sebocytes, including transit through a PPARγ+Krt5+ transitional cell state. Upon skin injury, however, SG progenitors depart their niche, reepithelialize the wound, and are replaced by hair follicle-derived stem cells. Furthermore, following targeted genetic ablation of >99% of SGs from dorsal skin, these glands unexpectedly regenerate within weeks. This regenerative process is mediated by alternative stem cells originating from the hair follicle bulge, is dependent upon FGFR signaling, and can be accelerated by inducing hair growth. Altogether, our studies demonstrate that stem cell plasticity promotes SG durability following injury.

Distinct mechanisms for sebaceous gland self-renewal and regeneration provide durability in response to injury.

Sebaceous glands (SGs) release oils that protect our skin, but how these glands respond to injury has not been previously examined. Here, we report that SGs are largely self-renewed by dedicated stem cell pools during homeostasis. Using targeted single-cell RNA sequencing, we uncovered both direct and indirect paths by which resident SG progenitors ordinarily differentiate into sebocytes, including transit through a Krt5+PPARγ+ transitional basal cell state. Upon skin injury, however, SG progenitors depart their niche, reepithelialize the wound, and are replaced by hair-follicle-derived stem cells. Furthermore, following targeted genetic ablation of >99% of SGs from dorsal skin, these glands unexpectedly regenerate within weeks. This regenerative process is mediated by alternative stem cells originating from the hair follicle bulge, is dependent upon FGFR2 signaling, and can be accelerated by inducing hair growth. Altogether, our studies demonstrate that stem cell plasticity promotes SG durability following injury.

Single-cell transcriptomics of human-skin-equivalent organoids.

Several methods for generating human-skin-equivalent (HSE) organoid cultures are in use to study skin biology; however, few studies thoroughly characterize these systems. To fill this gap, we use single-cell transcriptomics to compare in vitro HSEs, xenograft HSEs, and in vivo epidermis. By combining differential gene expression, pseudotime analyses, and spatial localization, we reconstruct HSE keratinocyte differentiation trajectories that recapitulate known in vivo epidermal differentiation pathways and show that HSEs contain major in vivo cellular states. However, HSEs also develop unique keratinocyte states, an expanded basal stem cell program, and disrupted terminal differentiation. Cell-cell communication modeling shows aberrant epithelial-to-mesenchymal transition (EMT)-associated signaling pathways that alter upon epidermal growth factor (EGF) supplementation. Last, xenograft HSEs at early time points post transplantation significantly rescue many in vitro deficits while undergoing a hypoxic response that drives an alternative differentiation lineage. This study highlights the strengths and limitations of organoid cultures and identifies areas for potential innovation.

ERK2 MAP kinase regulates SUFU binding by multisite phosphorylation of GLI1.

Crosstalk between the Hedgehog and MAPK signaling pathways occurs in several types of cancer and contributes to clinical resistance to Hedgehog pathway inhibitors. Here we show that MAP kinase-mediated phosphorylation weakens the binding of the GLI1 transcription factor to its negative regulator SUFU. ERK2 phosphorylates GLI1 on three evolutionarily conserved target sites (S102, S116, and S130) located near the high-affinity binding site for SUFU; these phosphorylations cooperate to weaken the affinity of GLI1-SUFU binding by over 25-fold. Phosphorylation of any one, or even any two, of the three sites does not result in the level of SUFU release seen when all three sites are phosphorylated. Tumor-derived mutations in R100 and S105, residues bordering S102, also diminish SUFU binding, collectively defining a novel evolutionarily conserved SUFU affinity-modulating region. In cultured mammalian cells, GLI1 variants containing phosphomimetic substitutions of S102, S116, and S130 displayed an increased ability to drive transcription. We conclude that multisite phosphorylation of GLI1 by ERK2 or other MAP kinases weakens GLI1-SUFU binding, thereby facilitating GLI1 activation and contributing to both physiological and pathological crosstalk.

Single-cell analysis of human basal cell carcinoma reveals novel regulators of tumor growth and the tumor microenvironment.

How basal cell carcinoma (BCC) interacts with its tumor microenvironment to promote growth is unclear. We use singe-cell RNA sequencing to define the human BCC ecosystem and discriminate between normal and malignant epithelial cells. We identify spatial biomarkers of tumors and their surrounding stroma that reinforce the heterogeneity of each tissue type. Combining pseudotime, RNA velocity-PAGA, cellular entropy, and regulon analysis in stromal cells reveals a cancer-specific rewiring of fibroblasts, where STAT1, TGF-ß, and inflammatory signals induce a noncanonical WNT5A program that maintains the stromal inflammatory state. Cell-cell communication modeling suggests that tumors respond to the sudden burst of fibroblast-specific inflammatory signaling pathways by producing heat shock proteins, whose expression we validated in situ. Last, dose-dependent treatment with an HSP70 inhibitor suppresses in vitro vismodegib-resistant BCC cell growth, Hedgehog signaling, and in vivo tumor growth in a BCC mouse model, validating HSP70's essential role in tumor growth and reinforcing the critical nature of tumor microenvironment cross-talk in BCC progression.

PI3K Promotes Basal Cell Carcinoma Growth Through Kinase-Induced p21 Degradation.

Basal cell carcinoma (BCC) is a locally invasive epithelial cancer that is primarily driven by the Hedgehog (HH) pathway. Advanced BCCs are a critical subset of BCCs that frequently acquire resistance to Smoothened (SMO) inhibitors and identifying pathways that bypass SMO could provide alternative treatments for patients with advanced or metastatic BCC. Here, we use a combination of RNA-sequencing analysis of advanced human BCC tumor-normal pairs and immunostaining of human and mouse BCC samples to identify a PI3K pathway expression signature in BCC. Pharmacological inhibition of PI3K activity in BCC cells significantly reduces cell proliferation and HH signaling. However, treatment of Ptch1fl/fl ; Gli1-CreERT2 mouse BCCs with the PI3K inhibitor BKM120 results in a reduction of tumor cell growth with no significant effect on HH signaling. Downstream PI3K components aPKC and Akt1 showed a reduction in active protein, whereas their substrate, cyclin-dependent kinase inhibitor p21, showed a concomitant increase in protein stability. Our results suggest that PI3K promotes BCC tumor growth by kinase-induced p21 degradation without altering HH signaling.

OVOL1 Regulates Psoriasis-Like Skin Inflammation and Epidermal Hyperplasia.

Psoriasis is a common inflammatory skin disease characterized by aberrant inflammation and epidermal hyperplasia. Molecular mechanisms that regulate psoriasis-like skin inflammation remain to be fully understood. Here, we show that the expression of Ovol1 (encoding ovo-like 1 transcription factor) is upregulated in psoriatic skin, and its deletion results in aggravated psoriasis-like skin symptoms following stimulation with imiquimod. Using bulk and single-cell RNA sequencing, we identify molecular changes in the epidermal, fibroblast, and immune cells of Ovol1-deficient skin that reflect an altered course of epidermal differentiation and enhanced inflammatory responses. Furthermore, we provide evidence for excessive full-length IL-1α signaling in the microenvironment of imiquimod-treated Ovol1-deficient skin that functionally contributes to immune cell infiltration and epidermal hyperplasia. Collectively, our study uncovers a protective role for OVOL1 in curtailing psoriasis-like inflammation and the associated skin pathology.

Divergent Resistance Mechanisms to Immunotherapy Explain Responses in Different Skin Cancers.

The advent of immune checkpoint therapy for metastatic skin cancer has greatly improved patient survival. However, most skin cancer patients are refractory to checkpoint therapy, and furthermore, the intra-immune cell signaling driving response to checkpoint therapy remains uncharacterized. When comparing the immune transcriptome in the tumor microenvironment of melanoma and basal cell carcinoma (BCC), we found that the presence of memory B cells and macrophages negatively correlate in both cancers when stratifying patients by their response, with memory B cells more present in responders. Moreover, inhibitory immune signaling mostly decreases in melanoma responders and increases in BCC responders. We further explored the relationships between macrophages, B cells and response to checkpoint therapy by developing a stochastic differential equation model which qualitatively agrees with the data analysis. Our model predicts BCC to be more refractory to checkpoint therapy than melanoma and predicts the best qualitative ratio of memory B cells and macrophages for successful treatment.

Single cell transcriptomics of human epidermis identifies basal stem cell transition states.

How stem cells give rise to epidermis is unclear despite the crucial role the epidermis plays in barrier and appendage formation. Here we use single cell-RNA sequencing to interrogate basal stem cell heterogeneity of human interfollicular epidermis and find four spatially distinct stem cell populations at the top and bottom of rete ridges and transitional positions between the basal and suprabasal epidermal layers. Cell-cell communication modeling suggests that basal cell populations serve as crucial signaling hubs to maintain epidermal communication. Combining pseudotime, RNA velocity, and cellular entropy analyses point to a hierarchical differentiation lineage supporting multi-stem cell interfollicular epidermal homeostasis models and suggest that transitional basal stem cells are stable states essential for proper stratification. Finally, alterations in differentially expressed transitional basal stem cell genes result in severe thinning of human skin equivalents, validating their essential role in epidermal homeostasis and reinforcing the critical nature of basal stem cell heterogeneity.

AP-1 and TGFß cooperativity drives non-canonical Hedgehog signaling in resistant basal cell carcinoma.

Tumor heterogeneity and lack of knowledge about resistant cell states remain a barrier to targeted cancer therapies. Basal cell carcinomas (BCCs) depend on Hedgehog (Hh)/Gli signaling, but can develop mechanisms of Smoothened (SMO) inhibitor resistance. We previously identified a nuclear myocardin-related transcription factor (nMRTF) resistance pathway that amplifies noncanonical Gli1 activity, but characteristics and drivers of the nMRTF cell state remain unknown. Here, we use single cell RNA-sequencing of patient tumors to identify three prognostic surface markers (LYPD3, TACSTD2, and LY6D) which correlate with nMRTF and resistance to SMO inhibitors. The nMRTF cell state resembles transit-amplifying cells of the hair follicle matrix, with AP-1 and TGFß cooperativity driving nMRTF activation. JNK/AP-1 signaling commissions chromatin accessibility and Smad3 DNA binding leading to a transcriptional program of RhoGEFs that facilitate nMRTF activity. Importantly, small molecule AP-1 inhibitors selectively target LYPD3+/TACSTD2+/LY6D+ nMRTF human BCCs ex vivo, opening an avenue for improving combinatorial therapies.