Hyperbaric oxygen treatment on keloid tumor immune gene expression

Multi-omics analyses reveal bacteria and catalase associated with keloid disease

BACKGROUND

The pathology of keloid and especially the roles of bacteria on it were not well understood.

METHODS

In this study, multi-omics analyses including microbiome, metaproteomics, metabolomic, single-cell transcriptome and cell-derived xenograft (CDX) mice model were used to explore the roles of bacteria on keloid disease.

FINDINGS

We found that the types of bacteria are significantly different between keloid and healthy skin. The 16S rRNA sequencing and metaproteomics showed that more catalase (CAT) negative bacteria, Clostridium and Roseburia existed in keloid compared with the adjacent healthy skin. In addition, protein mass spectrometry shows that CAT is one of the differentially expressed proteins (DEPs). Overexpression of CAT inhibited the proliferation, migration and invasion of keloid fibroblasts, and these characteristics were opposite when CAT was knocked down. Furthermore, the CDX model showed that Clostridium butyricum promote the growth of patient's keloid fibroblasts in BALB/c female nude mice, while CAT positive bacteria Bacillus subtilis inhibited it. Single-cell RNA sequencing verified that oxidative stress was up-regulated and CAT was down-regulated in mesenchymal-like fibroblasts of keloid.

INTERPRETATION

In conclusion, our findings suggest that bacteria and CAT contribute to keloid disease.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

The Mechanisms of Action of Hyperbaric Oxygen in Restoring Host Homeostasis during Sepsis

The perception of sepsis has shifted over time; however, it remains a leading cause of death worldwide. Sepsis is now recognized as an imbalance in host cellular functions triggered by the invading pathogens, both related to immune cells, endothelial function, glucose and oxygen metabolism, tissue repair and restoration. Many of these key mechanisms in sepsis are also targets of hyperbaric oxygen (HBO2) treatment. HBO2 treatment has been shown to improve survival in clinical studies on patients with necrotizing soft tissue infections as well as experimental sepsis models. High tissue oxygen tension during HBO2 treatment may affect oxidative phosphorylation in mitochondria. Oxygen is converted to energy, and, as a natural byproduct, reactive oxygen species are produced. Reactive oxygen species can act as mediators, and both these and the HBO2-mediated increase in oxygen supply have the potential to influence the cellular processes involved in sepsis. The pathophysiology of sepsis can be explained comprehensively through resistance and tolerance to infection. We argue that HBO2 treatment may protect the host from collateral tissue damage during resistance by reducing neutrophil extracellular traps, inhibiting neutrophil adhesion to vascular endothelium, reducing proinflammatory cytokines, and halting the Warburg effect, while also assisting the host in tolerance to infection by reducing iron-mediated injury and upregulating anti-inflammatory measures. Finally, we show how inflammation and oxygen-sensing pathways are connected on the cellular level in a self-reinforcing and detrimental manner in inflammatory conditions, and with support from a substantial body of studies from the literature, we conclude by demonstrating that HBO2 treatment can intervene to maintain homeostasis.

Revealing the roles of glycosphingolipid metabolism pathway in the development of keloid: a conjoint analysis of single-cell and machine learning

Keloid is a pathological scar formed by abnormal wound healing, characterized by the persistence of local inflammation and excessive collagen deposition, where the intensity of inflammation is positively correlated with the size of the scar formation. The pathophysiological mechanisms underlying keloid formation are unclear, and keloid remains a therapeutic challenge in clinical practice. This study is the first to investigate the role of glycosphingolipid (GSL) metabolism pathway in the development of keloid. Single cell sequencing and microarray data were applied to systematically analyze and screen the glycosphingolipid metabolism related genes using differential gene analysis and machine learning algorithms (random forest and support vector machine), and a set of genes, including ARSA,GBA2,SUMF2,GLTP,GALC and HEXB, were finally identified, for which keloid diagnostic model was constructed and immune infiltration profiles were analyzed, demonstrating that this set of genes could serve as a new therapeutic target for keloid. Further unsupervised clustering was performed by using expression profiles of glycosphingolipid metabolism genes to discover keloid subgroups, immune cells, inflammatory factor differences and the main pathways of enrichment between different subgroups were calculated. The single-cell resolution transcriptome landscape concentrated on fibroblasts. By calculating the activity of the GSL metabolism pathway for each fibroblast, we investigated the activity changes of GSL metabolism pathway in fibroblasts using pseudotime trajectory analysis and found that the increased activity of the GSL metabolism pathway was associated with fibroblast differentiation. Subsequent analysis of the cellular communication network revealed the existence of a fibroblast-centered communication regulatory network in keloids and that the activity of the GSL metabolism pathway in fibroblasts has an impact on cellular communication. This contributes to the further understanding of the pathogenesis of keloids. Overall, we provide new insights into the pathophysiological mechanisms of keloids, and our results may provide new ideas for the diagnosis and treatment of keloids.

Bioinformatics analysis and identification of dysregulated POSTN in the pathogenesis of keloid

Keloid is a benign fibro-proliferative dermal tumour formed by an abnormal scarring response to injury and characterised by excessive collagen accumulation and invasive growth. The pathophysiology of keloids is complex, and the treatment for keloids is still an unmet medical need. Here, we investigated the transcriptional gene that influences keloid development by comparing keloid, non-lesioned keloid skin and normal skin as well as keloid fibroblast and normal fibroblast (GSE83286, GSE92566, GSE44270). Based on the analysis, 146 up-regulated genes and 48 down-regulated genes were found in keloid tissue compared with normal skin and keloid no-lesioned skin. Eleven genes were further identified by overlapping the DEGs from keloid tissue described previously with DEGs in keloid fibroblast. The overlapped genes included PRR16, SFRP2, EDIL3, GERM1, POSTN, PDE3A, GALNT5, F2RL2, EYA4, ZFHX4, and AIM2. POSTN is the most crucial node in PPI network, which mainly correlate to collagen-related genes. Moreover, siRNA knockdown identified POSTN is a crucial regulatory gene that regulates keloid fibroblast migration and collagen I, collagen III expression level. In conclusion, our study identified 11 hub genes that play crucial role in keloid formation and provided insights for POSTN to be the therapeutic target for keloid through bioinformatic analysis of three datasets. Additionally, our results would support the development of future therapeutic strategies.

Skin endothelial cell and microcirculation function study in recurred keloids patients after keloid surgery and radiotherapy

BACKGROUND

Keloid is a type of benign tumor of the skin with abnormal proliferation of fibrous tissue. We sought to observe the changes in skin microcirculation and endothelial cell function around the recurred keloid and explore the skin microcirculation characters in recurred keloid patients.

METHODS

Six patients with recurred keloid were treated with keloid surgery and radiotherapy for the second time. Microcirculation of recurred keloids and their surrounding normal skin tissue was observed with laser Doppler flowmeter before operation. Expression of vascular endothelial growth factor (VEGF), CD31, and HIF-1α were identified by several assay.

RESULTS

The local blood flow of group RN was enhanced. The average strength of group N is 0.87. The average strength of group RN is 2.08. The expression of VEGF, CD31, and hypoxia inducible factor-1α (HIF-1α) protein in the keloid-recurred skin (RN) group was higher than the normal skin group via immunohistochemistry (IHC) and Western blotting analysis. The relative expression of VEGF and CD31 mRNA was significantly increased in RN group samples (P < .05).

CONCLUSIONS

There are significant differences in the expression of VEGF, CD31, and HIF-1α in the recurred keloid skin after radiotherapy and normal skin. They may be used as potential biomarkers and targets for future research on keloid recurrence.

The Role of CD28 and CD8+ T Cells in Keloid Development

Background: A keloid is a benign skin tumor that extends beyond the initial injury area, and its pathologic mechanism remains unclear. Method: High-throughput sequencing data were obtained from normal skin tissue of patients with keloids (Group N) and healthy controls (Group C). Important genes were mined by bioinformatics analysis and identified by RT−qPCR, Western blotting, immunohistochemistry and immunofluorescence assays. The CIBERSORT algorithm was used to convert gene expression information into immune cell information. Flow cytometry was used to verify the key immune cells. Fluorescence-activated cell sorting coculture and CCK8 experiments were used to explore the effect of CD8+ T cells on keloid-associated fibroblasts. Neural network models were used to construct associations among CD28, CD8+ T cells and the severity of keloids and to identify high-risk values. Result: The expression levels of costimulatory molecules (CD28, CD80, CD86 and CD40L) in the skin tissue of patients with keloids were higher than the levels in healthy people (p < 0.05). The number of CD8+ T cells was significantly higher in Group N than in Group C (p < 0.05). The fluorescence intensities of CD28 and CD8+ T cells in Group N were significantly higher than those in Group C (p = 0.0051). The number and viability of fibroblasts cocultured with CD8+ T cells were significantly reduced compared with those of the control (p < 0.05). The expression of CD28 and CD8+ T cells as the input layer may be predictors of the severity of keloids with mVSS as the output layer. The high-risk early warning indicator for CD28 is 10−34, and the high-risk predictive indicator for CD8+ T cells is 13−28. Conclusions: The abnormal expression of costimulatory molecules may lead to the abnormal activation of CD8+ T cells. CD8+ T cells may drive keloid-associated immunosuppression. The expression of CD28 and CD8+ T cells as an input layer may be a predictor of keloid severity. CD28 and CD8+ T cells play an important role in the development of keloids.

Single-cell RNA sequencing reveals distinct immunology profiles in human keloid

Keloids, characterized by skin fibrosis and excessive accumulation of extracellular matrix, remain a therapeutic challenge. In this study, we systematically capture the cellular composition of keloids by the single-cell RNA sequencing technique. Our results indicated that there are significant differences in most cell types present between 12 pairs of keloid and adjacent normal tissue. We found that fibroblasts, endothelial cells, mast cells, mural cells, and Schwann cells increased significantly in keloid. The proportion of mesenchymal fibroblast subpopulations in keloids was markedly higher than those in the surrounding normal skin tissue. Furthermore, we found that the immune profiles between two groups varied significantly. The proportion of macrophages in the keloid was significantly elevated compared to the surrounding normal tissue, while cDC2 cells significantly decreased. Hotspot and pseudotime trajectory analysis indicated two modules of macrophage cells (Module2: highly expresses RNASE1, C1QA, CD163, CD14, C1QC, FCGRT, MS4A7; Module10: highly expresses APOC1, CTSB, CTSL, TYROBP), which exhibited the characteristics of tumor-associated macrophages, were upregulated in more-advanced keloid cells. Subsequently, the analysis of cellular communication networks suggested that a macrophage-centered communication regulatory network may exist in keloids and that fibroblasts in keloids may facilitate the transition and proliferation of M2 macrophages, which contributes to further comprehension of the immunological features of keloids. Overall, we delineate the immunology landscape of keloids and present new insights into the mechanisms involved in its formation in this study.

Identification of a Diagnostic Signature and Immune Cell Infiltration Characteristics in Keloids

Background: Keloid disorder is a recurrent fibroproliferative cutaneous tumor. Due to the lack of early identification of keloid patients before the formation of keloids, it is impossible to carry out pre-traumatic intervention and prevention for these patients. This led us to identify and determine signatures with diagnostic significance for keloids.

Methods: Public series of matrix files were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were calculated from expression profiling data, and the diagnostic signature was identified by constructing a protein-protein interaction (PPI) network. The diagnostic efficacy of the screened signature was assessed by employing receiver operating characteristic (ROC) curves. Furthermore, we calculated the proportion of different immune cells in the gene expression matrix microenvironment by the “ssGSEA” algorithm, and assessed the difference in immune cell abundance between keloids and control groups and the relationship between the signature and immune cell infiltration. Clinical keloid and normal skin tissues were collected, and the expression of the screened diagnostic signature was validated by RT-qPCR and immunohistochemical assay.

Results: By screening the key genes in PPI, TGM2 was recognized and validated as a diagnostic signature and the infiltrating abundance of 10 immune cells was significantly correlated with TGM2 expression. Gene ontology enrichment analysis demonstrated that TGM2 and molecules interacting with it were mainly enriched in processes involving wound healing and collagen fiber organization. TGM2 correlated positively with HIF-1A (R = 0.82, p-value = 1.4e-05), IL6 (R = 0.62, p-value = 0.0053), and FN1 (R = 0.66, p-value = 0.0019). Besides, TGM2 was significantly upregulated in clinical keloid samples compared to normal skin tissues.

Conclusion: TGM2 may serve as an auxiliary diagnostic indicator for keloids. However, the role of TGM2 in keloids has not been adequately reported in the current literature, which may provide a new direction for molecular studies of keloids.