Single-Cell Profiling of Cutaneous T-Cell Lymphoma Reveals Underlying Heterogeneity Associated with Disease Progression

Key platelet genes play important roles in predicting the prognosis of sepsis

Sepsis is a life-threatening organ malfunction induced by an imbalanced immunological reaction to infection in the host. Many studies have utilized traditional RNA sequencing (RNA-seq) data to identify important biological targets to predict sepsis prognosis. However, alterations in core cells and functional status cannot be effectively detected in sepsis patients. The goal of this study was to identify key cells through single-cell RNA-seq (scRNA-seq), and combine bulk RNA-seq data and multiple algorithm analysis to construct a stable prognostic model for sepsis. The scRNA-seq and bulk RNA-seq data from sepsis patients were collected from the Gene Expression Omnibus (GEO) database. The R package "Seurat" was used to process the scRNA-seq data. Cell communication was investigated using the R package "CellChat". The pseudo-time of the cells was calculated using the R package "monocle". The R package "limma" was used to identify differentially expressed genes (DEGs) between the sepsis group and the control group. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules. Eight kinds of machine learning and 90 algorithm combinations were used to construct the prognostic model for sepsis. Quantitative real-time PCR (qRT‒PCR) was performed to determine the expression of key genes in the cecal ligation and puncture (CLP)-induced sepsis mouse model. The immunological status and related properties of DEGs were then investigated in the high- and low-risk groups delineated by the model. By combining the scRNA-seq data from nine samples, 13 clusters and 9 cell types were identified. CellChat analysis revealed that the number and strength of interactions between platelets and a variety of cells increased. We identified key platelet genes from the scRNA-seq data and combined these genes and the results of differential analysis and WGCNA of the bulk RNA-seq data. After univariate Cox regression analysis, we calculated the Cindex of the model constructed by the combination of 90 algorithms, and we finally determined the "CoxBoost + Lasso" combination. Multivariate Cox regression was used to construct the final prognostic model. The qRT-PCR results revealed significant differences in five key prognostic genes between the CLP and sham groups. The data was classified into high- and low-risk groups based on the model score. The high-risk group had a poorer survival rate and less immune infiltration. We identified the importance of platelets in sepsis patients through scRNA-seq, and established prognostic models with key genes that were identified via scRNA-seq combined with bulk RNA-seq analysis. The results of this model were closely associated with patient survival rates and immunological status and this model is useful for the prognostic management of sepsis.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM

BACKGROUND

Anoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored.

METHODS

Utilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays.

RESULTS

NMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion.

CONCLUSION

This pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

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.

Identification of Disulfidptosis-Related Genes in Ischemic Stroke by Combining Single-Cell Sequencing, Machine Learning Algorithms, and In Vitro Experiments

BACKGROUND

Ischemic stroke (IS) is a severe neurological disorder with a pathogenesis that remains incompletely understood. Recently, a novel form of cell death known as disulfidptosis has garnered significant attention in the field of ischemic stroke research. This study aims to investigate the mechanistic roles of disulfidptosis-related genes (DRGs) in the context of IS and to examine their correlation with immunopathological features.

METHODS

To enhance our understanding of the mechanistic underpinnings of disulfidptosis in IS, we initially retrieved the expression profile of peripheral blood from human IS patients from the GEO database. We then utilized a suite of machine learning algorithms, including LASSO, random forest, and SVM-RFE, to identify and validate pivotal genes. Furthermore, we developed a predictive nomogram model, integrating multifactorial logistic regression analysis and calibration curves, to evaluate the risk of IS. For the analysis of single-cell sequencing data, we employed a range of analytical tools, such as "Monocle" and "CellChat," to assess the status of immune cell infiltration and to characterize intercellular communication networks. Additionally, we utilized an oxygen-glucose deprivation (OGD) model to investigate the effects of SLC7A11 overexpression on microglial polarization.

RESULTS

This study successfully identified key genes associated with disulfidptosis and developed a reliable nomogram model using machine learning algorithms to predict the risk of ischemic stroke. Examination of single-cell sequencing data showed a robust correlation between disulfidptosis levels and the infiltration of immune cells. Furthermore, "CellChat" analysis elucidated the intricate characteristics of intercellular communication networks. Notably, the TNF signaling pathway was found to be intimately linked with the disulfidptosis signature in ischemic stroke. In an intriguing finding, the OGD model demonstrated that SLC7A11 expression suppresses M1 polarization while promoting M2 polarization in microglia.

CONCLUSION

The significance of our findings lies in their potential to shed light on the pathogenesis of ischemic stroke, particularly by underscoring the pivotal role of disulfidptosis-related genes (DRGs). These insights could pave the way for novel therapeutic strategies targeting DRGs to mitigate the impact of ischemic stroke.

A20 haploinsufficiency disturbs immune homeostasis and drives the transformation of lymphocytes with permissive antigen receptors

Genetic TNFAIP3 (A20) inactivation is a classical somatic lymphoma lesion and the genomic trait in haploinsufficiency of A20 (HA20). In a cohort of 34 patients with HA20, we show that heterozygous TNFAIP3 loss skews immune repertoires toward lymphocytes with classical self-reactive antigen receptors typically found in B and T cell lymphomas. This skewing was mediated by a feed-forward tumor necrosis factor (TNF)/A20/nuclear factor κB (NF-κB) loop that shaped pre-lymphoma transcriptome signatures in clonally expanded B (CD81, BACH2, and NEAT1) or T (GATA3, TOX, and PDCD1) cells. The skewing was reversed by anti-TNF treatment but could also progress to overt lymphoma. Analysis of conditional TNFAIP3 knock-out mice reproduced the wiring of the TNF/A20/NF-κB signaling axis with permissive antigen receptors and suggested a distinct regulation in B and T cells. Together, patients with the genetic disorder HA20 provide an exceptional window into A20/TNF/NF-κB-mediated control of immune homeostasis and early steps of lymphomagenesis that remain clinically unrecognized.

Single-cell RNA and T-cell receptor sequencing unveil mycosis fungoides heterogeneity and a possible gene signature

Background

Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma (CTCL). Comprehensive analysis of MF cells in situ and ex vivo is complicated by the fact that is challenging to distinguish malignant from reactive T cells with certainty.

Methods

To overcome this limitation, we performed combined single-cell RNA (scRNAseq) and T-cell receptor TCR sequencing (scTCRseq) of skin lesions of cutaneous MF lesions from 12 patients. A sufficient quantity of living T cells was obtained from 9 patients, but 2 had to be excluded due to unclear diagnoses (coexisting CLL or revision to a fixed toxic drug eruption).

Results

From the remaining patients we established single-cell mRNA expression profiles and the corresponding TCR repertoire of 18,630 T cells. TCR clonality unequivocally identified 13,592 malignant T cells. Reactive T cells of all patients clustered together, while malignant cells of each patient formed a unique cluster expressing genes typical of naive/memory, such as CD27, CCR7 and IL7R, or cytotoxic T cells, e.g., GZMA, NKG7 and GNLY. Genes encoding classic CTCL markers were not detected in all clusters, consistent with the fact that mRNA expression does not correlate linearly with protein expression. Nevertheless, we successfully pinpointed distinctive gene signatures differentiating reactive malignant from malignant T cells: keratins (KRT81, KRT86), galectins (LGALS1, LGALS3) and S100 genes (S100A4, S100A6) being overexpressed in malignant cells.

Conclusions

Combined scRNAseq and scTCRseq not only allows unambiguous identification of MF cells, but also revealed marked heterogeneity between and within patients with unexpected functional phenotypes. While the correlation between mRNA and protein abundance was limited with respect to established MF markers, we were able to identify a single-cell gene expression signature that distinguishes malignant from reactive T cells.

LAIR1 prevents excess inflammatory tissue damage in S. aureus skin infection and Cutaneous T-cell Lymphoma

Patients with cutaneous T cell lymphoma (CTCL) experience high morbidity and mortality due to S. aureus skin infections and sepsis, but the causative immune defect is unclear. We previously identified high levels of LAIR2, a decoy protein for the inhibitory receptor LAIR1, in advanced CTCL. Mice do not have a LAIR2 homolog, so we used Lair1 knock-out (KO) mice to model LAIR2 overexpression. In a model of subcutaneous S. aureus skin infection, Lair1 KO mice had significantly larger abscesses and areas of dermonecrosis compared to WT. Lair1 KO exhibited a pattern of increased inflammatory responses in infection and sterile immune stimulation, including increased production of proinflammatory cytokines and myeloid chemokines, neutrophil ROS, and collagen/ECM remodeling pathways. Notably, Lair1 KO infected skin had a similar bacterial burden and neutrophils and monocytes had equivalent S. aureus phagocytosis compared to WT. These findings support a model in which lack of LAIR1 signaling causes an excessive inflammatory response that does not improve infection control. CTCL skin lesions harbored similar patterns of increased expression in cytokine and collagen/ECM remodeling pathways, suggesting that high levels of LAIR2 in CTCL recapitulates Lair1 KO, causing inflammatory tissue damage and compromising host defense against S. aureus infection.

Unleashed monocytic engagement in Sézary syndrome during the combination of anti-CCR4 antibody with type I interferon

ABSTRACT

Sézary syndrome (SS) is an aggressive leukemic expansion of skin-derived malignant CD4+ T cells. Drug monotherapy often results in disease relapse because of the heterogenous nature of malignant CD4+ T cells, but how therapies can be optimally combined remains unclear because of limitations in understanding the disease pathogenesis. We identified immunologic transitions that interlink mycosis fungoides with SS using single-cell transcriptome analysis in parallel with high-throughput T-cell receptor sequencing. Nascent peripheral CD4+ T cells acquired a distinct profile of transcription factors and trafficking receptors that gave rise to antigenically mature Sézary cells. The emergence of malignant CD4+ T cells coincided with the accumulation of dysfunctional monocytes with impaired fragment crystallizable γ-dependent phagocytosis, decreased responsiveness to cytokine stimulation, and limited repertoire of intercellular interactions with Sézary cells. Type I interferon supplementation when combined with a monoclonal antibody targeting the chemokine receptor type 4 (CCR4), unleashed monocyte induced phagocytosis and eradication of Sézary cells in vitro. In turn, coadministration of interferon-α with the US Food and Drug Administration-approved anti-CCR4 antibody, mogamulizumab, in patients with SS induced marked depletion of peripheral malignant CD4+ T cells. Importantly, residual CD4+ T cells after Sézary cell ablation lacked any immunologic shifts. These findings collectively unveil an auxiliary role for augmenting monocytic activity during mogamulizumab therapy in the treatment of SS and underscore the importance of targeted combination therapy in this disease.

Deciphering Tumor Cell Evolution in Cutaneous T-Cell Lymphomas: Distinct Differentiation Trajectories in Mycosis Fungoides and Sézary Syndrome

Cutaneous T-cell lymphomas are a heterogeneous group of neoplasms originating in the skin, with mycosis fungoides (MF) and Sézary syndrome (SS) representing the most common variants. The cellular origin of cutaneous lymphomas has remained controversial owing to their immense phenotypic heterogeneity that obfuscates lineage reconstruction on the basis of classical surface biomarkers. To overcome this heterogeneity and reconstruct the differentiation trajectory of malignant cells in MF and SS, TCR sequencing was performed in parallel with targeted transcriptomics at the single-cell resolution among cutaneous samples in MF and SS. Unsupervised lineage reconstruction showed that Sézary cells exist as a population of CD4+ T cells distinct from those in patch, plaque, and tumor MF. Further investigation of malignant cell heterogeneity in SS showed that Sézary cells phenotypically comprised at least 3 subsets on the basis of differential proliferation potentials and expression of exhaustion markers. A T helper 1-polarized cell type, intermediate cell type, and exhausted T helper 2-polarized cell type were identified, with T helper 1- and T helper 2-polarized cells displaying divergent proliferation potentials. Collectively, these findings provide evidence to clarify the relationship between MF and SS and reveal cell subsets in SS that suggest a possible mechanism for therapeutic resistance.

Staphylococcus aureus induces drug resistance in cancer T cells in Sézary syndrome

ABSTRACT

Patients with Sézary syndrome (SS), a leukemic variant of cutaneous T-cell lymphoma (CTCL), are prone to Staphylococcus aureus infections and have a poor prognosis due to treatment resistance. Here, we report that S aureus and staphylococcal enterotoxins (SE) induce drug resistance in malignant T cells against therapeutics commonly used in CTCL. Supernatant from patient-derived, SE-producing S aureus and recombinant SE significantly inhibit cell death induced by histone deacetylase (HDAC) inhibitor romidepsin in primary malignant T cells from patients with SS. Bacterial killing by engineered, bacteriophage-derived, S aureus-specific endolysin (XZ.700) abrogates the effect of S aureus supernatant. Similarly, mutations in major histocompatibility complex (MHC) class II binding sites of SE type A (SEA) and anti-SEA antibody block induction of resistance. Importantly, SE also triggers resistance to other HDAC inhibitors (vorinostat and resminostat) and chemotherapeutic drugs (doxorubicin and etoposide). Multimodal single-cell sequencing indicates T-cell receptor (TCR), NF-κB, and JAK/STAT signaling pathways (previously associated with drug resistance) as putative mediators of SE-induced drug resistance. In support, inhibition of TCR-signaling and Protein kinase C (upstream of NF-κB) counteracts SE-induced rescue from drug-induced cell death. Inversely, SE cannot rescue from cell death induced by the proteasome/NF-κB inhibitor bortezomib. Inhibition of JAK/STAT only blocks rescue in patients whose malignant T-cell survival is dependent on SE-induced cytokines, suggesting 2 distinct ways SE can induce drug resistance. In conclusion, we show that S aureus enterotoxins induce drug resistance in primary malignant T cells. These findings suggest that S aureus enterotoxins cause clinical treatment resistance in patients with SS, and antibacterial measures may improve the outcome of cancer-directed therapy in patients harboring S aureus.

Targeting nucleotide metabolic pathways in colorectal cancer by integrating scRNA-seq, spatial transcriptome, and bulk RNA-seq data

BACKGROUND

Colorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancer METHODS: For single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments.

RESULTS

In both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC.

CONCLUSION

In this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

New Genetic Markers of Skin T-Cell Lymphoma Treatment

AIM

Cutaneous T-cell lymphomas (CTCL) can be described as chronic skin inflammation lesions with the content of malignant T cells and they are considered to be T-cell-mediated skin diseases. CD147 is recognized as a 58-kDa cell surface glycoprotein of the immunoglobulin superfamily; it can induce the synthesis of MMPs (matrix metalloproteinases) on the surface of tumor cells where it was originally identified. It can also function in adjacent tumor fibroblasts using CD147-CD147 interactions. The polymorphism rs8259 T/A is situated in the untranslated region (3'UTR) of the CD147 gene. HLA DRB1*1501 takes part in the process of presentation and recognition of different antigens to T cells. It can be expressed by antigen-presenting cells-macrophages, dendritic cells, and B cells. The aim of the study is to test genotype-phenotype associations of both polymorphisms including therapy in a large cohort of CTCL patients.

MATERIALS AND METHODS

A final total of 104 CTCL patients were enrolled in the study. For the first remission at the clinic department, they were treated by means of local skin-directed therapy, phototherapy, and systemic therapy. Genomic DNA was isolated from peripheral blood leukocytes. A standard technique using proteinase K was applied. The polymorphisms rs8259 T/A (CD147 gene) and rs3135388 (HLA DRB1*1501) were detected through standard PCR-restriction fragment length polymorphism methods.

RESULTS

The severity of the disease (patients with parapsoriasis, stages IA and IB, vs patients with stages IIB, IIIA, and IIIB) was associated with the CD147 genotype: the AA variant was 3.38 times more frequent in more severe cases, which reflects the decision on systemic therapy (p = 0.02, specificity 0.965). The AA genotype in the CD147 polymorphism was 12 times more frequent in patients who underwent systemic therapy of CTCL compared to those not treated with this therapy (p = 0.009, specificity 0.976). The same genotype was also associated with radiotherapy-it was observed 14 times more frequently in patients treated with radiotherapy (p = 0.009, specificity 0.959). In patients treated with interferon α therapy, the AA genotype was observed to be 5.85 times more frequent compared to the patients not treated with interferon therapy (p = 0.03, specificity 0.963). The HLA DRB1*1501 polymorphism was associated with local skin-directed therapy of CTCL. The CC genotype of the polymorphism was observed to be 3.57 times more frequent in patients treated with local therapy (p = 0.008, specificity 0.948). When both polymorphisms had been calculated together, even better results were obtained: the AACC double genotype was 11 times more frequent in patients with severe CTCL (p = 0.009, specificity 0.977). The TACT double genotype was associated with local skin-directed therapy (0.09 times lower frequency, p = 0.007, sensitivity 0.982). The AACC genotype was 8.9 times more frequent in patients treated by means of systemic therapy (p = 0.02, specificity 0.976) and as many as 18.8 times more frequent in patients treated with radiotherapy (p = 0.005, specificity 0.969). Thus, the AACC double genotype of CD147 and DRB1*1501 polymorphisms seems to be a clinically highly specific marker of severity, systemic therapy and radiotherapy of patients with T-cell lymphoma.

CONCLUSION

Although genotyping results were not known during the treatment decision and could not modify it, the clinical decision on severity and therapy reflected some aspects of the genetic background of this complicated T-cell-associated disease very well.

Vitamin D in Cutaneous T-Cell Lymphoma

Cutaneous T-cell lymphoma (CTCL) is characterized by the proliferation of malignant T cells in inflamed skin lesions. Mycosis fungoides (MF)-the most common variant of CTCL-often presents with skin lesions around the abdomen and buttocks ("bathing suit" distribution), i.e., in skin areas devoid of sun-induced vitamin D. For decades, sunlight and vitamin D have been connected to CTCL. Thus, vitamin D induces apoptosis and inhibits the expression of cytokines in malignant T cells. Furthermore, CTCL patients often display vitamin D deficiency, whereas phototherapy induces vitamin D and has beneficial effects in CTCL, suggesting that light and vitamin D have beneficial/protective effects in CTCL. Inversely, vitamin D promotes T helper 2 (Th2) cell specific cytokine production, regulatory T cells, tolerogenic dendritic cells, as well as the expression of immune checkpoint molecules, all of which may have disease-promoting effects by stimulating malignant T-cell proliferation and inhibiting anticancer immunity. Studies on vitamin D treatment in CTCL patients showed conflicting results. Some studies found positive effects, others negative effects, while the largest study showed no apparent clinical effect. Taken together, vitamin D may have both pro- and anticancer effects in CTCL. The balance between the opposing effects of vitamin D in CTCL is likely influenced by treatment and may change during the disease course. Therefore, it remains to be discovered whether and how the effect of vitamin D can be tilted toward an anticancer response in CTCL.

GATA-3-dependent Gene Transcription is Impaired upon HDAC Inhibition

PURPOSE

Many peripheral and cutaneous T-cell lymphoma (CTCL) subtypes are poorly responsive to conventional chemotherapeutic agents and associated with dismal outcomes. The zinc finger transcription factor GATA-3 and the transcriptional program it instigates are oncogenic and highly expressed in various T-cell neoplasms. Posttranslational acetylation regulates GATA-3 DNA binding and target gene expression. Given the widespread use of histone deacetylase inhibitors (HDACi) in relapsed/refractory CTCL, we sought to examine the extent to which these agents attenuate the transcriptional landscape in these lymphomas.

EXPERIMENTAL DESIGN

Integrated GATA-3 chromatin immunoprecipitation sequencing and RNA sequencing analyses were performed in complementary cell line models and primary CTCL specimens treated with clinically available HDACi.

RESULTS

We observed that exposure to clinically available HDACi led to significant transcriptional reprogramming and increased GATA-3 acetylation. HDACi-dependent GATA-3 acetylation significantly impaired both its ability to bind DNA and transcriptionally regulate its target genes, thus leading to significant transcriptional reprogramming in HDACi-treated CTCL.

CONCLUSIONS

Beyond shedding new light on the mechanism of action associated with HDACi in CTCL, these findings have significant implications for their use, both as single agents and in combination with other novel agents, in GATA-3-driven lymphoproliferative neoplasms.

Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective.

Methods

The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD.

Results

424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis.

Conclusion

Seven MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) were identified as prognostic genes for LUAD and revealed the mechanisms of MPRGs at the single-cell level.

Leveraging physiology and artificial intelligence to deliver advancements in health care

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.

Microenvironment-dependent growth of Sezary cells in humanized IL-15 mice

Sezary syndrome (SS) is a rare, aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) that lacks adequate therapeutic options and representative small-animal models. Here, we demonstrate that IL-15 is a critical CTCL growth factor. Importantly, an immunodeficient knock-in mouse model genetically engineered to express human IL-15 uniquely supported the growth of SS patient samples relative to conventional immunodeficient mouse strains. SS patient-derived xenograft (PDX) models recapacitated key pathological features of the human disease, including skin infiltration and spread of leukemic cells to the periphery, and maintained the dependence on human IL-15 upon serial in vivo passaging. Detailed molecular characterization of the engrafted cells by single-cell transcriptomic analysis revealed congruent neoplastic gene expression signatures but distinct clonal engraftment patterns. Overall, we document an important dependence of Sezary cell survival and proliferation on IL-15 signaling and the utility of immunodeficient humanized IL-15 mice as hosts for SS - and potentially other T and NK cell-derived hematologic malignancies - PDX model generation. Furthermore, these studies advocate the thorough molecular understanding of the resultant PDX models to maximize their translational impact.

Combining single-cell sequencing and spatial transcriptome sequencing to identify exosome-related features of glioblastoma and constructing a prognostic model to identify BARD1 as a potential therapeutic target for GBM patients

Background

Glioblastoma (GBM) is a malignant primary brain tumor. This study focused on exploring the exosome-related features of glioblastoma to better understand its cellular composition and molecular characteristics.

Methods

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) were used to analyze the heterogeneity of glioblastomas. After data integration, cell clustering, and annotation, five algorithms were used to calculate scores for exosome-related genes(ERGs). Cell trajectory analysis and intercellular communication analysis were performed to explore exosome-related communication patterns. Spatial transcriptome sequencing data were analyzed to validate the findings. To further utilize exosome-related features to aid in clinical decision-making, a prognostic model was constructed using GBM's bulk RNA-seq.

Results

Different cell subpopulations were observed in GBM, with Monocytes/macrophages and malignant cells in tumor samples showing higher exosome-related scores. After identifying differentially expressed ERGs in malignant cells, pseudotime analysis revealed the cellular status of malignant cells during development. Intercellular communication analysis highlighted signaling pathways and ligand-receptor interactions. Spatial transcriptome sequencing confirmed the high expression of exosome-related gene features in the tumor core region. A prognostic model based on six ERGs was shown to be predictive of overall survival and immunotherapy outcome in GBM patients. Finally, based on the results of scRNA-seq and prognostic modeling as well as a series of cell function experiments, BARD1 was identified as a novel target for the treatment of GBM.

Conclusion

This study provides a comprehensive understanding of the exosome-related features of GBM in both scRNA-seq and stRNA-seq, with malignant cells with higher exosome-related scores exhibiting stronger communication with Monocytes/macrophages. In terms of spatial data, highly scored malignant cells were also concentrated in the tumor core region. In bulk RNA-seq, patients with a high exosome-related index exhibited an immunosuppressive microenvironment, which was accompanied by a worse prognosis as well as immunotherapy outcomes. Prognostic models constructed using ERGs are expected to be independent prognostic indicators for GBM patients, with potential implications for personalized treatment strategies for GBM. Knockdown of BARD1 in GBM cell lines reduces the invasive and value-added capacity of tumor cells, and thus BARD1-positively expressing malignant cells are a risk factor for GBM patients.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Molecular techniques drive cutting edge advancements in management of cutaneous T cell lymphoma

Cutaneous 5T cell lymphoma (CTCL), characterized by malignant T cells infiltrating the skin with potential for dissemination, remains a challenging disease to diagnose and treat due to disease heterogeneity, treatment resistance, and lack of effective and standardized diagnostic and prognostic clinical tools. Currently, diagnosis of CTCL practically relies on clinical presentation, histopathology, and immunohistochemistry. These methods are collectively fraught with limitations in sensitivity and specificity. Fortunately, recent advances in flow cytometry, polymerase chain reaction, high throughput sequencing, and other molecular techniques have shown promise in improving diagnosis and treatment of CTCL. Examples of these advances include T cell receptor clonotyping via sequencing to detect CTCL earlier in the disease course and single-cell RNA sequencing to identify gene expression patterns that commonly drive CTCL pathogenesis. Experience with these techniques has afforded novel insights which may translate into enhanced diagnostic and therapeutic approaches for CTCL.

Prognostic implication of cuproptosis related genes associates with immunity in Ewing's sarcoma

Growing evidence demonstrated that cuproptosis play critical roles in human cancers. We aimed to identify the roles of cuproptosis related genes (CRGs) in prognosis and immunity of Ewing's sarcoma. The data of GSE17674 and GSE63156 were obtained from GEO. The expression of 17 CRGs and immune cells were explored, then correlation was analyzed. Based on CRGs, two molecular clusters were identified by consensus clustering algorithm. KM survival and IME features including immune cells, immune response, checkpoint genes between clusters were evaluated. NFE2L2, LIAS, and CDKN2A were screened out as prognostic signatures by univariate, LASSO and step regression. A risk model was established, and validated by KM method with p = 0.0026, and perfect AUC values. The accuracy of risk model was also well validated in external dataset. A nomogram was constructed and evaluated by calibration curves and DCA. Low level of immune cells, immune response, and enriched checkpoint genes were found in high-risk group. GSEA of signatures and GSVA of ES-related pathways revealed the potential molecular mechanism involved in ES progression. Several drugs showed sensitivity to ES samples. DEGs between risk groups were screened out, and function enrichment was conducted. Finally, scRNA analysis of GSE146221 was done. NFE2L2, and LIAS played crucial role in the evolution of ES by pesudotime and trajectory methods. Our study provided new aspects for further research in ES.

Spatially Guided and Single Cell Tools to Map the Microenvironment in Cutaneous T-Cell Lymphoma

Mycosis fungoides (MF) and Sézary syndrome (SS) are two closely related clinical variants of cutaneous T-cell lymphomas (CTCL). Previously demonstrated large patient-to-patient and intra-patient disease heterogeneity underpins the importance of personalized medicine in CTCL. Advanced stages of CTCL are characterized by dismal prognosis, and the early identification of patients who will progress remains a clinical unmet need. While the exact molecular events underlying disease progression are poorly resolved, the tumor microenvironment (TME) has emerged as an important driver. In particular, the Th1-to-Th2 shift in the immune response is now commonly identified across advanced-stage CTCL patients. Herein, we summarize the role of the TME in CTCL evolution and the latest studies in deciphering inter- and intra-patient heterogeneity. We introduce spatially resolved omics as a promising technology to advance immune-oncology efforts in CTCL. We propose the combined implementation of spatially guided and single-cell omics technologies in paired skin and blood samples. Such an approach will mediate in-depth profiling of phenotypic and molecular changes in reactive immune subpopulations and malignant T cells preceding the Th1-to-Th2 shift and reveal mechanisms underlying disease progression from skin-limited to systemic disease that collectively will lead to the discovery of novel biomarkers to improve patient prognostication and the design of personalized treatment strategies.

Single-cell and bulk RNA sequencing identifies T cell marker genes score to predict the prognosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the lethal malignancies, with limited biomarkers identified to predict its prognosis and treatment response of immune checkpoint blockade (ICB). This study aimed to explore the predictive ability of T cell marker genes score (TMGS) to predict their overall survival (OS) and treatment response to ICB by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Multi-omics data of PDAC were applied in this study. The uniform manifold approximation and projection (UMAP) was utilized for dimensionality reduction and cluster identification. The non-negative matrix factorization (NMF) algorithm was applied to molecular subtypes clustering. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was adopted for TMGS construction. The prognosis, biological characteristics, mutation profile, and immune function status between different groups were compared. Two molecular subtypes were identified via NMF: proliferative PDAC (C1) and immune PDAC (C2). Distinct prognoses and biological characteristics were observed between them. TMGS was developed based on 10 T cell marker genes (TMGs) through LASSO-Cox regression. TMGS is an independent prognostic factor of OS in PDAC. Enrichment analysis indicated that cell cycle and cell proliferation-related pathways are significantly enriched in the high-TMGS group. Besides, high-TMGS is related to more frequent KRAS, TP53, and CDKN2A germline mutations than the low-TMGS group. Furthermore, high-TMGS is significantly associated with attenuated antitumor immunity and reduced immune cell infiltration compared to the low-TMGS group. However, high TMGS is correlated to higher tumor mutation burden (TMB), a low expression level of inhibitory immune checkpoint molecules, and a low immune dysfunction score, thus having a higher ICB response rate. On the contrary, low TMGS is related to a favorable response rate to chemotherapeutic agents and targeted therapy. By combining scRNA-seq and bulk RNA-seq data, we identified a novel biomarker, TMGS, which has remarkable performance in predicting the prognosis and guiding the treatment pattern for patients with PDAC.

Integrated transcriptome and trajectory analysis of cutaneous T-cell lymphoma identifies putative precancer populations

The incidence of cutaneous T-cell lymphoma (CTCL) increases with age, and blood involvement portends a worse prognosis. To advance our understanding of the development of CTCL and identify potential therapeutic targets, we performed integrative analyses of paired single-cell RNA and T-cell receptor (TCR) sequencing of peripheral blood CD4+ T cells from patients with CTCL to reveal disease-unifying features. The malignant CD4+ T cells of CTCL showed highly diverse transcriptomic profiles across patients, with most displaying a mature Th2 differentiation and T-cell exhaustion phenotype. TCR-CDR3 peptide prediction analysis suggested limited diversity between CTCL samples, consistent with a role for a common antigenic stimulus. Potential of heat diffusion for affinity-based trajectory embedding transition analysis identified putative precancerous circulating populations characterized by an intermediate stage of gene expression and mutation level between the normal CD4+ T cells and malignant CTCL cells. We further revealed the therapeutic potential of targeting CD82 and JAK that endow the malignant CTCL cells with survival and proliferation advantages.

Single-cell analysis of Sézary syndrome reveals novel markers and shifting gene profiles associated with treatment

Cutaneous T-cell lymphomas (CTCLs) are a spectrum of diseases with varied clinical courses caused by malignant clonal proliferation of skin-tropic T cells. Most patients have an indolent disease course managed with skin-directed therapies. In contrast, others, especially in advanced stages of disease or with specific forms, have aggressive progression and poor median survival. Sézary syndrome (SS), a leukemic variant of CTCL, lacks highly consistent phenotypic and genetic markers that may be leveraged to prevent the delay in diagnosis experienced by most patients with CTCL and could be useful for optimal treatment selection. Using single-cell mRNA and T-cell receptor sequencing of peripheral blood immune cells in SS, we extensively mapped the transcriptomic variations of nearly 50 000 T cells of both malignant and nonmalignant origins. We identified potential diverging SS cell populations, including quiescent and proliferative populations shared across multiple patients. In particular, the expression of AIRE was the most highly upregulated gene in our analysis, and AIRE protein expression could be observed over a variety of CTCLs. Furthermore, within a single patient, we were able to characterize differences in cell populations by comparing malignant T cells over the course of treatment with histone deacetylase inhibition and photopheresis. New cellular clusters after progression of the therapy notably exhibited increased expression of the transcriptional factor FOXP3, a master regulator of regulatory T-cell function, raising the potential implication of an evolving mechanism of immune evasion.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.

Single-cell RNA-sequencing reveals predictive features of response to pembrolizumab in Sézary syndrome

The PD-1 inhibitor pembrolizumab is effective in treating Sézary syndrome, a leukemic variant of cutaneous T-cell lymphoma. Our purpose was to investigate the effects of pembrolizumab on healthy and malignant T cells in Sézary syndrome and to discover characteristics that predict pembrolizumab response. Samples were analyzed before and after 3 weeks of pembrolizumab treatment using single-cell RNA-sequencing of 118,961 peripheral blood T cells isolated from six Sézary syndrome patients. T-cell receptor clonotyping, bulk RNA-seq signatures, and whole-exome data were integrated to classify malignant T-cells and their underlying subclonal heterogeneity. We found that responses to pembrolizumab were associated with lower KIR3DL2 expression within Sézary T cells. Pembrolizumab modulated Sézary cell gene expression of T-cell activation associated genes. The CD8 effector populations included clonally expanded populations with a strong cytotoxic profile. Expansions of CD8 terminal effector and CD8 effector memory T-cell populations were observed in responding patients after treatment. We observed intrapatient Sézary cell heterogeneity including subclonal segregation of a coding mutation and copy number variation. Our study reveals differential effects of pembrolizumab in both malignant and healthy T cells. These data support further study of KIR3DL2 expression and CD8 immune populations as predictive biomarkers of pembrolizumab response in Sézary syndrome.

Single-cell RNA sequencing unveils the communications between malignant T and myeloid cells contributing to tumor growth and immunosuppression in cutaneous T-cell lymphoma

Cutaneous T cell lymphoma (CTCL) is characterized by the accumulation of malignant T cells in the skin. However, advanced CTCL pathophysiology remains elusive and therapeutic options are limited due to the high intratumoral heterogeneity and complicated tumor microenvironment (TME). By comparing the single-cell RNA-seq (scRNA-seq) data from advanced CTCL patients and healthy controls (HCs), we showed that CTCL had a higher enrichment of T/NK and myeloid cells. Subpopulations of T cells (CXCR3+, GNLY+, CREM+, and MKI67+ T cells), with high proliferation, stemness, and copy number variation (CNV) levels, contribute to the malignancy of CTCL. Besides, CCL13+ monocytes/macrophages and LAMP3+ cDC cells were enriched and mediated the immunosuppression via inhibitory interactions with malignant T cells, such as CD47-SIRPA, MIF-CD74, and CCR1-CCL18. Notably, elevated expressions of S100A9 and its receptor TLR4, as well as the activation of downstream toll-like receptor and NF-κB pathway were observed in both malignant cells and myeloid cells in CTCL. Cell co-culture experiments further confirmed that the interaction between malignant CTCL cells and macrophages contributed to tumor growth via S100A9 upregulation and NF-kb activation. Our results showed that blocking the S100A9-TLR4 interaction using tasquinimod could inactivate the NF-κB pathway and inhibit the growth of CTCL tumor cells, and trigger cell apoptosis. Collectively, our study revealed a landscape of immunosuppressive TME mediated by interactions between malignant T cells and myeloid cells, and provided novel targets and potential treatment strategies for advanced CTCL patients.

Expression of hub genes of endothelial cells in glioblastoma-A prognostic model for GBM patients integrating single-cell RNA sequencing and bulk RNA sequencing

BACKGROUND

This study aimed to use single-cell RNA-seq (scRNA-seq) to discover marker genes in endothelial cells (ECs) and construct a prognostic model for glioblastoma multiforme (GBM) patients in combination with traditional high-throughput RNA sequencing (bulk RNA-seq).

METHODS

Bulk RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA) and The China Glioma Genome Atlas (CGGA) databases. 10x scRNA-seq data for GBM were obtained from the Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) were used for downscaling and cluster identification. Key modules and differentially expressed genes (DEGs) were identified by weighted gene correlation network analysis (WGCNA). A non-negative matrix decomposition (NMF) algorithm was used to identify the different subtypes based on DEGs, and multivariate cox regression analysis to model the prognosis. Finally, differences in mutational landscape, immune cell abundance, immune checkpoint inhibitors (ICIs)-associated genes, immunotherapy effects, and enriched pathways were investigated between different risk groups.

RESULTS

The analysis of scRNA-seq data from eight samples revealed 13 clusters and four cell types. After applying Fisher's exact test, ECs were identified as the most important cell type. The NMF algorithm identified two clusters with different prognostic and immunological features based on DEGs. We finally built a prognostic model based on the expression levels of four key genes. Higher risk scores were significantly associated with poorer survival outcomes, low mutation rates in IDH genes, and upregulation of immune checkpoints such as PD-L1 and CD276.

CONCLUSION

We built and validated a 4-gene signature for GBM using 10 scRNA-seq and bulk RNA-seq data in this work.

Single-cell analyses reveal novel molecular signatures and pathogenesis in cutaneous T cell lymphoma

Sézary syndrome (SS) is a rare and aggressive type of cutaneous T cell lymphoma (CTCL) with a poor prognosis. Intra-tumoral heterogeneity caused by different disease compartments (e.g., skin, blood) and poor understanding of the pathogenesis has created obstacles to the precise diagnosis and targeted treatment of the disease. Here we performed a comprehensive analysis by integrating single-cell transcriptomic data of 40,333 peripheral blood mononuclear cells (PBMCs) and 41,580 skin cells, as well as single-cell chromatin accessibility data of 11,058 PBMCs from an SS patient and matched healthy controls (HCs). Validation and functional investigation were carried out in an independent cohort consisting of SS patients, mycosis fungoides (MF) patients, psoriatic erythroderma patients, and HCs, as well as multiple cell lines. The analysis revealed that skin-derived Sézary cells (SCs) had a shifting trend to more advanced mature phenotypes compared to blood-derived SCs. A series of specific marker genes (TOX, DNM3, KLHL42, PGM2L1, and SESN3) shared in blood- and skin-derived SCs were identified, facilitating the diagnosis and prognosis of MF/SS. Moreover, luciferase reporter assays and gene knockdown assays were used to verify that KLHL42 was transcriptionally activated by GATA3 in SS. Functional assays indicated that KLHL42 silencing significantly inhibited aggressive CTCL cell proliferation and promoted its apoptosis. Therefore, targeting inhibition KLHL42 might serve as a promising therapeutic approach in CTCL.

Combined High-Throughput Approaches Reveal the Signals Driven by Skin and Blood Environments and Define the Tumor Heterogeneity in Sézary Syndrome

Simple Summary

Sézary syndrome (SS) is a leukemic and incurable variant of cutaneous T-cell lymphoma characterized by the accumulation of neoplastic CD4+ lymphocytes in the blood, lymph nodes, and skin. With the exception of allogenic transplantation, no curative chance is available to treat SS, and it is a priority to find new therapies that target SS cells within all disease compartments. This review aims to summarize the more recent analyses conducted on skin- and blood-derived SS cells concurrently obtained from the same SS patients. The results highlighted that skin-SS cells were more active/proliferating with respect to matched blood SS cells that instead appeared quiescent. These data shed the light on the possibility to treat blood and skin SS cells with different compounds, respectively. Moreover, this review recaps the more recent findings on the heterogeneity of circulating SS cells that presented a series of novel markers that could improve diagnosis, prognosis and therapy of this lymphoma.

Abstract

Sézary syndrome (SS) is an aggressive variant of cutaneous t-cell lymphoma characterized by the accumulation of neoplastic CD4+ lymphocytes—the SS cells—mainly in blood, lymph nodes, and skin. The tumor spread pattern of SS makes this lymphoma a unique model of disease that allows a concurrent blood and skin sampling for analysis. This review summarizes the recent studies highlighting the transcriptional programs triggered by the crosstalk between SS cells and blood–skin microenvironments. Emerging data proved that skin-derived SS cells show consistently higher activation/proliferation rates, mainly driven by T-cell receptor signaling with respect to matched blood SS cells that instead appear quiescent. Biochemical analyses also demonstrated an hyperactivation of PI3K/AKT/mTOR, a targetable pathway by multiple inhibitors currently in clinical trials, in skin SS cells compared with a paired blood counterpart. These results indicated that active and quiescent SS cells coexist in this lymphoma, and that they could be respectively treated with different therapeutics. Finally, this review underlines the more recent discoveries into the heterogeneity of circulating SS cells, highlighting a series of novel markers that could improve the diagnosis and that represent novel therapeutic targets (GPR15, PTPN13, KLRB1, and ITGB1) as well as new genetic markers (PD-1 and CD39) able to stratify SS patients for disease aggressiveness.

Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma

ABSTRACT

Cutaneous T-cell lymphoma (CTCL) is a rare cancer of skin-homing T cells. A subgroup of patients develops large cell transformation with rapid progression to an aggressive lymphoma. Here, we investigated the transformed CTCL (tCTCL) tumor ecosystem using integrative multiomics spanning whole-exome sequencing (WES), single-cell RNA sequencing, and immune profiling in a unique cohort of 56 patients. WES of 70 skin biopsies showed high tumor mutation burden, UV signatures that are prognostic for survival, exome-based driver events, and most recurrently mutated pathways in tCTCL. Single-cell profiling of 16 tCTCL skin biopsies identified a core oncogenic program with metabolic reprogramming toward oxidative phosphorylation (OXPHOS), cellular plasticity, upregulation of MYC and E2F activities, and downregulation of MHC I suggestive of immune escape. Pharmacologic perturbation using OXPHOS and MYC inhibitors demonstrated potent antitumor activities, whereas immune profiling provided in situ evidence of intercellular communications between malignant T cells expressing macrophage migration inhibitory factor and macrophages and B cells expressing CD74.

SIGNIFICANCE

Our study contributes a key resource to the community with the largest collection of tCTCL biopsies that are difficult to obtain. The multiomics data herein provide the first comprehensive compendium of genomic alterations in tCTCL and identify potential prognostic signatures and novel therapeutic targets for an incurable T-cell lymphoma. This article is highlighted in the In This Issue feature, p. 1171.

Mass Cytometric Analysis of Early-Stage Mycosis Fungoides

Mycosis fungoides (MF) is the most common subtype of cutaneous T-cell lymphoma. Early-stage disease is characterized by superficial infiltrates of small- to medium-sized atypical epidermotropic T lymphocytes that are clonal related. Nevertheless, the percentage of atypical T cells is low with many admixed reactive immune cells. Despite earlier studies, the composition and spatial characteristics of the cutaneous lymphocytic infiltrate has been incompletely characterized. Here, we applied mass cytometry to profile the immune system in skin biopsies of patients with early-stage MF and in normal skin from healthy individuals. Single-cell suspensions were prepared and labeled with a 43-antibody panel, and data were acquired on a Helios mass cytometer. Unbiased hierarchical clustering of the data identified the major immune lineages and heterogeneity therein. This revealed patient-unique cell clusters in both the CD4⁺ and myeloid cell compartments but also phenotypically distinct cell clusters that were shared by most patients. To characterize the immune compartment in the tissue context, we developed a 36-antibody panel and performed imaging mass cytometry on MF skin tissue. This visualized the structure of MF skin and the distribution of CD4⁺ T cells, regulatory T cells, CD8⁺ T cells, malignant T cells, and various myeloid cell subsets. We observed clusters of CD4⁺ T cells and multiple types of dendritic cells (DCs) identified through differential expression of CD11c, CD1a, and CD1c in the dermis. These results indicated substantial heterogeneity in the composition of the local immune infiltrate but suggest a prominent role for clustered CD4-DC interactions in disease pathogenesis. Probably, the local inhibition of such interactions may constitute an efficient treatment modality.

Single-cell transcriptomics links malignant T cells to the tumor immune landscape in cutaneous T cell lymphoma

Cutaneous T cell lymphoma (CTCL) represents a heterogeneous group of non-Hodgkin lymphoma distinguished by the presence of clonal malignant T cells. The heterogeneity of malignant T cells and the complex tumor microenvironment remain poorly characterized. With single-cell RNA analysis and bulk whole-exome sequencing on 19 skin lesions from 15 CTCL patients, we decipher the intra-tumor and inter-lesion diversity of CTCL patients and propose a multi-step tumor evolution model. We further establish a subtyping scheme based on the molecular features of malignant T cells and their pro-tumorigenic microenvironments: the T_CyEM group, demonstrating a cytotoxic effector memory T cell phenotype, shows more M2 macrophages infiltration, while the T_CM group, featured by a central memory T cell phenotype and adverse patient outcome, is infiltrated by highly exhausted CD8⁺ reactive T cells, B cells and Tregs with suppressive activities. Our results establish a solid basis for understanding the nature of CTCL and pave the way for future precision medicine for CTCL patients.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing Data to Establish and Validate a Prognostic Model for Patients With Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) remains a lethal disease worldwide, with numerous studies exploring its potential prognostic markers using traditional RNA sequencing (RNA-seq) data. However, it cannot detect the exact cellular and molecular changes in tumor cells. This study aimed to construct a prognostic model for LUAD using single-cell RNA-seq (scRNA-seq) and traditional RNA-seq data.

Methods: Bulk RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) database. LUAD scRNA-seq data were acquired from Gene Expression Omnibus (GEO) database. The uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Weighted Gene Correlation Network Analysis (WGCNA) was utilized to identify key modules and differentially expressed genes (DEGs). The non-negative Matrix Factorization (NMF) algorithm was used to identify different subtypes based on DEGs. The Cox regression analysis was used to develop the prognostic model. The characteristics of mutation landscape, immune status, and immune checkpoint inhibitors (ICIs) related genes between different risk groups were also investigated.

Results: scRNA-seq data of four samples were integrated to identify 13 clusters and 9cell types. After applying differential analysis, NK cells, bladder epithelial cells, and bronchial epithelial cells were identified as significant cell types. Overall, 329 DEGs were selected for prognostic model construction through differential analysis and WGCNA. Besides, NMF identified two clusters based on DEGs in the TCGA cohort, with distinct prognosis and immune characteristics being observed. We developed a prognostic model based on the expression levels of six DEGs. A higher risk score was significantly correlated with poor survival outcomes but was associated with a more frequent TP53 mutation rate, higher tumor mutation burden (TMB), and up-regulation of PD-L1. Two independent external validation cohorts were also adopted to verify our results, with consistent results observed in them.

Conclusion: This study constructed and validated a prognostic model for LUAD by integrating 10× scRNA-seq and bulk RNA-seq data. Besides, we observed two distinct subtypes in this population, with different prognosis and immune characteristics.

Transcriptional Heterogeneity and the Microbiome of Cutaneous T-Cell Lymphoma

Cutaneous T-Cell Lymphomas (CTCL) presents with substantial clinical variability and transcriptional heterogeneity. In the recent years, several studies paved the way to elucidate aetiology and pathogenesis of CTCL using sequencing methods. Several T-cell subtypes were suggested as the source of disease thereby explaining clinical and transcriptional heterogeneity of CTCL entities. Several differentially expressed pathways could explain disease progression. However, exogenous triggers in the skin microenvironment also seem to affect CTCL status. Especially Staphylococcus aureus was shown to contribute to disease progression. Only little is known about the complex microbiome patterns involved in CTCL and how microbial shifts might impact this malignancy. Nevertheless, first hints indicate that the microbiome might at least in part explain transcriptional heterogeneity and that microbial approaches could serve in diagnosis and prognosis. Shaping the microbiome could be a treatment option to maintain stable disease. Here, we review current knowledge of transcriptional heterogeneity of and microbial influences on CTCL. We discuss potential benefits of microbial applications and microbial directed therapies to aid patients with CTCL burden.

Mogamulizumab induces long term immune restoration and reshapes tumor heterogeneity in Sézary syndrome

BACKGROUND

Mogamulizumab, an anti-CCR4 monoclonal antibody, has been shown to increase progression-free survival in cutaneous T-cell lymphoma.

OBJECTIVES

We hypothesized that besides the targeted depletion of Sézary cells (SCs), mogamulizumab may reshape the immune tumor microenvironment.

METHODS

Both malignant and benign compartments from 26 Sézary patients with B2 stage before mogamulizumab initiation were prospectively analyzed using KIR3DL2 and TCR-Vβ markers, serological markers and molecular assessments of clonality.

RESULTS

Prior to mogamulizumab, the benign subset of CD4+ T-cells displayed exhausted phenotypes, with an increased gradient in PD1/TIGIT/DNAM/CD27/CD28 and CD70 expression from age- matched controls to patient benign CD4+T cells and to SCs. All patients presented SCs with heterogeneous phenotypes and differential expression of individual markers were found within distinct malignant subsets. Early complete blood response was observed in 17/26 patients and was associated to a higher baseline CCR4 expression. A drastic decrease in benign T cells and activated Treg counts was observed during the first 4 weeks. Long-term follow-up revealed the emergence of an immune restoration involving CD8+, naive and stem-memory CD4+T cells, with almost complete disappearance of exhausted lymphocytes. Development of resistance/tumor escape to mogamulizumab was associated to the emergence of CCR4- SCs in blood and skin, displaying significant changes in their heterogeneity patterns, and not univocally explained by mutations within CCR4 coding regions.

CONCLUSIONS

Mogamulizumab is likely contributing to the restoration of an efficient immunity and reshapes not only the malignant lymphocyte subset but also the benign subset. These results have potential implications for optimal therapeutic sequences and/or combinations.

Natural Barcodes for Longitudinal Single Cell Tracking of Leukemic and Immune Cell Dynamics

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.

Pathogenesis of cutaneous T cell lymphoma: Involvement of Staphylococcus aureus

Mycosis fungoides (MF) and Sézary syndrome (SS) are representative cutaneous lymphomas. In their early stage, a small number of tumor cells and a large number of non-malignant cells form a Th1-dominant tumor microenvironment. Increase in malignant T cells is accompanied by a decrease in CD8-positive T cells, with a shift toward a Th2-dominant milieu in advanced-stage lesions. The etiologies of MF/SS are diverse, and the underlying pathogenetic mechanisms are yet to be elucidated. Advanced MF/SS is known to be highly sensitive to Staphylococcus aureus, and the majority of deaths are caused by severe infections. The susceptibility to infection is associated with barrier dysfunction and immunosuppression, which are the main symptoms of MF. In recent years, skin-colonizing S. aureus has been identified to not only cause severe infections but also play an important role in the pathogenesis of MF/SS. Staphylococcal superantigens activate the proliferation of tumor cells and induce CD25 upregulation, FOXP3 expression, IL-17 expression, and miR-155 expression. Alpha-toxin eliminates non-neoplastic CD4-positive cells and CD8-positive cells and plays a major role in tumor cell selection. Lipoprotein may also be associated with the induction of Th2-dominant milieu. Antibiotic therapy for S. aureus eradication has been reported to cause considerable clinical improvement in the majority of individuals with advanced cutaneous T-cell lymphoma. Therefore, S. aureus may be a novel target for the treatment of advanced-stage MF/SS in the future.

High Expression of IKZF2 in Malignant T Cells Promotes Disease Progression in Cutaneous T Cell Lymphoma

Cutaneous T cell lymphoma is a generally indolent disease derived from skin-homing mature T cells. However, in advanced stages, cutaneous T cell lymphoma may manifest aggressive clinical behaviour and lead to a poor prognosis. The mechanism of disease progression in cutaneous T cell lymphoma remains unknown. This study, based on a large clinical cohort, found that IKZF2, an essential transcription factor during T cell development and differentiation, showed stage-dependent overexpression in the malignant T cells in mycosis fungoides lesions. IKZF2 is specifically over-expressed in advanced-stage mycosis fungoides lesions, and correlates with poor prognosis. Mechanistically, overexpression of IKZF2 promotes cutaneous T cell lymphoma progression via inhibiting malignant cell apoptosis and may contribute to tumour immune escape by downregulating major histocompatibility complex II molecules and up-regulating the production of anti-inflammatory cytokine interleukin-10 by malignant T cells. These results demonstrate the important role of IKZF2 in high-risk cutaneous T cell lymphoma and pave the way for future targeted therapy.

Malignant and Benign T Cells Constituting Cutaneous T-Cell Lymphoma

Cutaneous T-cell lymphoma (CTCL) is a heterogeneous group of non-Hodgkin lymphoma, including various clinical manifestations, such as mycosis fungoides (MF) and Sézary syndrome (SS). CTCL mostly develops from CD4 T cells with the skin-tropic memory phenotype. Malignant T cells in MF lesions show the phenotype of skin resident memory T cells (T_RM), which reside in the peripheral tissues for long periods and do not recirculate. On the other hand, malignant T cells in SS represent the phenotype of central memory T cells (T_CM), which are characterized by recirculation to and from the blood and lymphoid tissues. The kinetics and the functional characteristics of malignant cells in CTCL are still unclear due, in part, to the fact that both the malignant cells and the T cells exerting anti-tumor activity possess the same characteristics as T cells. Capturing the features of both the malignant and the benign T cells is necessary for understanding the pathogenesis of CTCL and would lead to new therapeutic strategies specifically targeting the skin malignant T cells or benign T cells.

Clinical Response to Anti-CD47 Immunotherapy Is Associated with Rapid Reduction of Exhausted Bystander CD4+ BTLA+ T Cells in Tumor Microenvironment of Mycosis Fungoides

Simple Summary

The identification of the events that accompany cancer progression is essential for developing new therapies. We have used mycosis fungoides, the most common type of cutaneous lymphoma, as a model for our study. We have shown that cancer progression is accompanied by the expansion of exhausted immune cells around malignant cells. Those exhausted cells prevent immune activation, blocking cancer clearance by the immune system. Furthermore, we have demonstrated that novel anti-CD47 immunotherapy with mycosis fungoides leads to the reduction of exhausted T cells accompanied by the expansion of NK and CD8⁺ T cells. These therapeutic benefits of CD47 blockade were further facilitated by interferon-α, which stimulates cytotoxic cells. Thus, we showed that CD47 might serve as an effective therapeutic target in treating mycosis fungoides.

Abstract

Cancer progression in mycosis fungoides, the most common form of cutaneous T-cell lymphoma, occurs in a predictable, sequential pattern that starts from patches and that evolves to plaques and later to tumors. Therefore, unlocking the relationship between the microarchitecture of mycosis fungoides and the clinical counterparts of that microstructure represents important steps for the design of targeted therapies. Using multispectral fluorescent imaging, we show that the progression of mycosis fungoides from plaque to tumor parallels the cutaneous expansion of the malignant CD4⁺ T cells that express TOX. The density of exhausted BTLA⁺ CD4⁺ T cells around malignant CD4⁺TOX⁺ cells was higher in tumors than it was in plaques, suggesting that undesired safeguards are in place within the tumor microenvironment that prevent immune activation and subsequent cancer eradication. Overriding the CD47 checkpoint with an intralesional SIRPαFc fusion decoy receptor induced the resolution of mycosis fungoides in patients that paralleled an amplified expansion of NK and CD8⁺ T cells in addition to a reduction of the exhausted BTLA⁺ CD4⁺ T cells that were engaged in promiscuous intercellular interactions. These therapeutic benefits of the CD47 blockade were further unleashed by adjuvant interferon-α, which stimulates cytotoxic cells, underscoring the importance of an inflamed microenvironment in facilitating the response to immunotherapy. Collectively, these findings support CD47 as a therapeutic target in treating mycosis fungoides and demonstrate a synergistic role of interferon-α in exploiting these clinical benefits.

Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma

Cutaneous T cell lymphomas (CTCL) are rare but aggressive cancers without effective treatments. While a subset of patients derive benefit from PD-1 blockade, there is a critically unmet need for predictive biomarkers of response. Herein, we perform CODEX multiplexed tissue imaging and RNA sequencing on 70 tumor regions from 14 advanced CTCL patients enrolled in a pembrolizumab clinical trial (NCT02243579). We find no differences in the frequencies of immune or tumor cells between responders and non-responders. Instead, we identify topographical differences between effector PD-1⁺ CD4⁺ T cells, tumor cells, and immunosuppressive Tregs, from which we derive a spatial biomarker, termed the SpatialScore, that correlates strongly with pembrolizumab response in CTCL. The SpatialScore coincides with differences in the functional immune state of the tumor microenvironment, T cell function, and tumor cell-specific chemokine recruitment and is validated using a simplified, clinically accessible tissue imaging platform. Collectively, these results provide a paradigm for investigating the spatial balance of effector and suppressive T cell activity and broadly leveraging this biomarker approach to inform the clinical use of immunotherapies.

The Single-Cell Sequencing: A Dazzling Light Shining on the Dark Corner of Cancer

Tumorigenesis refers to the process of clonal dysplasia that occurs due to the collapse of normal growth regulation in cells caused by the action of various carcinogenic factors. These “successful” tumor cells pass on the genetic templates to their generations in evolutionary terms, but they also constantly adapt to ever-changing host environments. A unique peculiarity known as intratumor heterogeneity (ITH) is extensively involved in tumor development, metastasis, chemoresistance, and immune escape. An understanding of ITH is urgently required to identify the diversity and complexity of the tumor microenvironment (TME), but achieving this understanding has been a challenge. Single-cell sequencing (SCS) is a powerful tool that can gauge the distribution of genomic sequences in a single cell and the genetic variability among tumor cells, which can improve the understanding of ITH. SCS provides fundamental ideas about existing diversity in specific TMEs, thus improving cancer diagnosis and prognosis prediction, as well as improving the monitoring of therapeutic response. Herein, we will discuss advances in SCS and review SCS application in tumors based on current evidence.

Multimodal single-cell analysis of cutaneous T-cell lymphoma reveals distinct subclonal tissue-dependent signatures

Cutaneous T-cell lymphoma (CTCL) is a heterogeneous group of mature T-cell neoplasms characterized by the accumulation of clonal malignant CD4+ T cells in the skin. The most common variant of CTCL, mycosis fungoides (MF ), is confined to the skin in early stages but can be accompanied by extracutaneous dissemination of malignant T cells to the blood and lymph nodes in advanced stages of disease. Sézary syndrome (SS), a leukemic form of disease, is characterized by significant blood involvement. Little is known about the transcriptional and genomic relationship between skin- and blood-residing malignant T cells in CTCL. To identify and interrogate malignant clones in matched skin and blood from patients with leukemic MF and SS, we combine T-cell receptor clonotyping with quantification of gene expression and cell surface markers at the single cell level. Our data reveal clonal evolution at a transcriptional and genetic level within the malignant populations of individual patients. We highlight highly consistent transcriptional signatures delineating skin- and blood-derived malignant T cells. Analysis of these 2 populations suggests that environmental cues, along with genetic aberrations, contribute to transcriptional profiles of malignant T cells. Our findings indicate that the skin microenvironment in CTCL promotes a transcriptional response supporting rapid malignant expansion, as opposed to the quiescent state observed in the blood, potentially influencing efficacy of therapies. These results provide insight into tissue-specific characteristics of cancerous cells and underscore the need to address the patients' individual malignant profiles at the time of therapy to eliminate all subclones.

Clinical Guidelines and New Molecular Targets for Cutaneous Lymphomas

Primary cutaneous lymphomas are heterogenous lymphoproliferative disorders. Some patients show rapid progression and the need for treatment of advanced disease is still unmet. The frequency of each subtype of cutaneous lymphoma varies among different ethnic groups, as do the medical systems found in different countries. It is important to know the differences in clinical guidelines in different areas of the world. Although current monochemotherapy with gemcitabine or pegylated liposomal doxorubicin is temporarily effective for mycosis funogides (MF) and Sézary syndrome (SS)-representative types of cutaneous lymphomas-the duration of response is usually limited. Therefore, treatment strategies targeting tumor-specific molecules have been developed. Molecular targets for MS/SS are currently CD30, CCR4, CD25, CD52, and histone deacetylases, most of which are surface molecules specifically expressed on tumor cells. As a result of advances in research techniques, different kinds of genomic alterations in MF/SS have been revealed. Molecular targets for MS/SS in the near future would be CD158k, JAK, PIK3, the mammalian target of rapamycin, and microRNAs, most of which mediate intracellular signaling pathways. Personalized therapy based on the detection of the genetic signatures of tumors and inhibition of the most suitable target molecules constitutes a future treatment strategy for MF/SS.

Single-cell RNA sequencing reveals markers of disease progression in primary cutaneous T-cell lymphoma

Background

In early-stage mycosis fungoides (MF), the most common primary cutaneous T-cell lymphoma, limited skin involvement with patches and plaques is associated with a favorable prognosis. Nevertheless, approximately 20–30% of cases progress to tumors or erythroderma, resulting in poor outcome. At present, factors contributing to this switch from indolent to aggressive disease are only insufficiently understood.

Methods

In patients with advanced-stage MF, we compared patches with longstanding history to newly developed plaques and tumors by using single-cell RNA sequencing, and compared results with early-stage MF as well as nonlesional MF and healthy control skin.

Results

Despite considerable inter-individual variability, lesion progression was uniformly associated with downregulation of the tissue residency markers CXCR4 and CD69, the heat shock protein HSPA1A, the tumor suppressors and immunoregulatory mediators ZFP36 and TXNIP, and the interleukin 7 receptor (IL7R) within the malignant clone, but not in benign T cells. This phenomenon was not only found in conventional TCR-αβ MF, but also in a case of TCR-γδ MF, suggesting a common mechanism across MF subtypes. Conversely, malignant cells in clinically unaffected skin from MF patients showed upregulation of these markers.

Conclusions

Our data reveal a specific panel of biomarkers that might be used for monitoring MF disease progression. Altered expression of these genes may underlie the switch in clinical phenotype observed in advanced-stage MF.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-021-01419-2.