Single-Cell and Bulk Transcriptome Data Integration Reveals Dysfunctional Cell Types and Aberrantly Expressed Genes in Hypertrophic Scar

Zhang, Shunuo; Zhang, Yixin; Min, Peiru

doi:10.3389/fgene.2021.806740

Cited by 7 publications

(9 citation statements)

References 46 publications

(57 reference statements)

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“…Upregulation of numerous genes, previously described to be increased in scar tissue (7,50,51), was significantly inhibited after PBMCsec-application.…”

Section: Pbmcsec Induces Significant Changes Of the Transcriptome Aft...mentioning

confidence: 74%

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The secretome of irradiated peripheral mononuclear cells attenuates hypertrophic skin scarring

Vorstandlechner

Copic

Klas

et al. 2022

Preprint

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Background Hypertrophic scars can cause pain, movement restrictions, and reduction of quality of life. Despite numerous options to tackle hypertrophic scarring, efficient therapies are still scarce, and cellular mechanisms are not well understood. Secreted factors from peripheral blood mononuclear cells (PBMCsec) were previously described for their beneficial effects in tissue regeneration. Here, we investigated the effects of PBMCsec on skin scarring in mouse models and human scar explant cultures at single cell resolution (scRNAseq). Methods Mouse wounds and scars were treated with PBMCsec either intradermally or topically. Human mature scars were treated with PBMCsec ex vivo in explant cultures. All experimental settings were analyzed by single cell RNA sequencing (scRNAseq). A variety of bioinformatics approaches were used to decipher gene regulation in the scRNAseq data sets. Components of the extracellular matrix (ECM) were investigated in situ by immunofluorescence. The effect of PBMCsec on myofibroblast differentiation and elastin expression was investigated by stimulating human primary fibroblasts with TGFβ. Findings Topical and intradermal application of PBMCsec regulated the expression of a variety of genes involved in pro-fibrotic processes and tissue remodeling. Our bioinformatics approach identified elastin as a common linchpin of antifibrotic action in both, the mouse and human experimental setting. In vitro, we found that PBMCsec prevents TGFβ-mediated myofibroblast-differentiation and attenuates abundant elastin expression through non-canonical signaling inhibition. Furthermore, TGFβ-induced breakdown of elastic fibers was strongly inhibited by addition of PBMCsec. Interpretation Together, we showed anti-fibrotic effect of PBMCsec on cutaneous scars in mouse and human experimental settings, suggesting PBMCsec as a novel therapeutic option to treat skin scarring.

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“…Upregulation of numerous genes, previously described to be increased in scar tissue (7,50,51), was significantly inhibited after PBMCsec-application.…”

Section: Pbmcsec Induces Significant Changes Of the Transcriptome Aft...mentioning

confidence: 74%

“…To provide an impression of the overall regulation in all celltypes, the top 50 DEGs per clustergroup are shown in Figure S3A-I. Upregulation of numerous genes, previously described to be increased in scar tissue (7, 50, 51), was significantly inhibited after PBMCsec-application.…”

Section: Resultsmentioning

confidence: 99%

The secretome of irradiated peripheral mononuclear cells attenuates hypertrophic skin scarring

Vorstandlechner

Copic

Klas

et al. 2022

Preprint

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“…We further analyzed the regulatory activity of transcription factors in skin fibroblasts and found that NFIA regulatory activity was highest in normal skin fibroblasts, and it has been shown that most DM rats developed retinopathy and lens fibrosis after inhibition of NFIA gene expression using RNA silencing ( 39 ). In HS fibroblasts, CREB3L1 regulatory activity was highest and CREB3L1 has been identified as a key transcription factor involved in HS myofibroblasts ( 21 ). The correlation between transcription factors with high activity in skin fibroblasts and CRGs was explored and from our results we know that CRGs are strongly positively and negatively correlated with a large number of transcription factors.…”

Section: Discussionmentioning

confidence: 99%

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques

et al. 2023

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Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment.

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“…Recently, several studies have illustrated CREB3L1 expression and functions in different cell lineages development through conducting single-cell RNA sequencing (scRNA-seq) analysis. It has been found that FB-1 cells, a major type of fibroblast in hypertrophic scar samples have higher transcriptional activities of CREB3L1 than those in normal samples, and hypertrophic scar samples have a higher proportion of the FB-1 cells expressing CREB3L1 through investigating online scRNA-seq data, suggesting that CREB3LI may be critically involved in hypertrophic scar formation ( Zhang et al, 2021a ). In addition, a recent study conducting scRNA-seq analysis has revealed the critical biomarkers and process of the differentiation of fibroblasts into myofibroblasts in systemic sclerosis, and CREB3L1 may be a critical upstream transcription factor in promoting systemic sclerosis myofibroblast differentiation ( Tabib et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy

Lin

Xiao

et al. 2022

Front. Genet.

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Background: CAMP response element binding protein 3-like 1 (CREB3L1) has been indicated as a critical biomarker and can modulate multifaced behaviors of tumor cells in diverse cancers. However, a systematic assessment of CREB3L1 in pan-cancer is of absence, and the predictive value of CREB3L1 in cancer prognosis, the tumor immune microenvironment and the efficacy of immunotherapy remains unexplored.Methods: CREB3L1 expression in 33 different cancer types was investigated using RNAseq data from The Cancer Genome Atlas (TCGA) database. The characteristics of CREB3L1 alternations were illustrated in cBioPortal database. The prognostic and clinicopathological value of CREB3L1 was analyzed through clinical data downloaded from the TCGA database. The potential role of CREB3L1 in the tumor immune microenvironment was illustrated by utilizing CIBERSORT and ESTIMATE algorithms, and TISIDB online database. The associations between CREB3L1 expression and tumor mutation burden (TMB), and microsatellite instability (MSI) were assessed by spearman’s rank correlation coefficient. Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. The correlations of CREB3L1 expression with PD-1/PD-L1 inhibitors efficacy and drug sensitivity were also investigated.Results: The expression of CREB3L1 was abnormally high or low in several different cancer types, and was also strictly associated with the prognosis of cancer patients. CREB3L1 expression levels have a strong relationship with infiltrating immune cells, including regulatory T cells, CD8+ T cells, macrophages, B naïve cells, dendritic cells and mast cells. CREB3L1 expression was also correlated with the expression of multiple immune-related biomolecules, TMB, and MSI in several cancers. Moreover, CREB3L1 had promising applications in predicting the immunotherapeutic benefits and drug sensitivity in cancer management.Conclusions: Our results highlight the value of CREB3L1 as a predictive biomarker for the prognosis and immunotherapy efficacy in multiple cancers, and CREB3L1 seems to play key roles in the tumor immune microenvironment, suggesting the role of CREB3L1 as a promising biomarker for predicting the prognosis and immune-related signatures in diverse cancers.

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Single-Cell and Bulk Transcriptome Data Integration Reveals Dysfunctional Cell Types and Aberrantly Expressed Genes in Hypertrophic Scar

Cited by 7 publications

References 46 publications

The secretome of irradiated peripheral mononuclear cells attenuates hypertrophic skin scarring

The secretome of irradiated peripheral mononuclear cells attenuates hypertrophic skin scarring

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques

Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy

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