Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid

Identification of novel immune-related signatures for keloid diagnosis and treatment: insights from integrated bulk RNA-seq and scRNA-seq analysis

BACKGROUND

Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids.

METHOD

Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibroblast subpopulation differentiation using scRNA-seq. Finally, we used HE and Masson staining, quantitative reverse transcription-PCR, western blotting, immunohistochemical, and Immunofluorescent assay to investigate the dysregulated expression and the mechanism of retinoic acid in keloids.

RESULTS

In the present study, we identified PTGFR, RBP5, and LIF as KHIGs and validated their diagnostic performance. Subsequently, we constructed a novel artificial neural network molecular diagnostic model based on the transcriptome pattern of KHIGs, which is expected to break through the current dilemma faced by molecular diagnosis of keloids in the clinic. Meanwhile, the constructed IG score can also effectively predict keloid risk, which provides a new strategy for keloid prevention. Additionally, we observed that KHIGs were also heterogeneously expressed in the constructed differentiation trajectories of fibroblast subtypes, which may affect the differentiation of fibroblast subtypes and thus lead to dysregulation of the immune microenvironment in keloids. Finally, we found that retinoic acid may treat or alleviate keloids by inhibiting RBP5 to differentiate pro-inflammatory fibroblasts (PIF) to mesenchymal fibroblasts (MF), which further reduces collagen secretion.

CONCLUSION

In summary, the present study provides novel immune signatures (PTGFR, RBP5, and LIF) for keloid diagnosis and treatment, and identifies retinoic acid as potential anti-keloid drugs. More importantly, we provide a new perspective for understanding the interactions between different fibroblast subtypes in keloids and the remodeling of their immune microenvironment.

Global insights into keloid formation: An international systematic review of regional genetic risk factors and commonalities

Keloid disorder is a morbid and disfiguring benign fibroproliferative disease with a higher incidence in groups with darker skin pigmentation. Predicting keloidogenesis in patients is difficult with treatment primarily aimed at preventing further scar expansion and improving aesthetics without addressing their unknown underlying pathophysiology. We aimed to identify potential genetic predispositions to keloid scarring in the literature. A search was conducted on 21 August 2023, by the first and second authors independently from 1985 to August 2023 using PubMed, MEDLINE, Embase, Web of Science, Scopus and CINAHL. The following MeSH terms were used: 'Keloid', 'Risk' and 'Genetic'. Two researchers independently searched for studies based on titles and abstracts and screened filtered articles by reviewing full text. If no agreement could be reached, a third senior author designated whether the article should be included. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement as the basis of our organisation. Human studies with genetic analysis to determine an association of a protein or gene to keloidogenesis were selected for inclusion. Studies in languages other than English, reviews, conference articles, and book chapters were excluded. Fifty studies met inclusion criteria. The human leukocyte antigen (HLA) system was broadly implicated, and the DRB1*15 allele was associated with an increased risk of keloid in three separate ethnic groups. Some HLA Class I alleles were associated with keloid in one population but not in others. Additionally, polymorphisms in the E3 ubiquitin-protein ligase (NEDD4) signal cascade and vitamin D receptor (VDR) have been implicated in diverse groups. No current genetic test can predict keloid risk. Our review identified candidate predisposing genes, including NEDD4, VDR and components of the HLA system. Further studies in heterogeneous populations are needed to identify reliable screening targets.

Analysis of the heterogeneity and complexity of murine extraorbital lacrimal gland via single-cell RNA sequencing

PURPOSE

The lacrimal gland is essential for maintaining ocular surface health and avoiding external damage by secreting an aqueous layer of the tear film. However, a healthy lacrimal gland's inventory of cell types and heterogeneity remains understudied.

METHODS

Here, 10X Genome-based single-cell RNA sequencing was used to generate an unbiased classification of cellular diversity in the extraorbital lacrimal gland (ELG) of C57BL/6J mice. From 43,850 high-quality cells, we produced an atlas of cell heterogeneity and defined cell types using classic marker genes. The possible functions of these cells were analyzed through bioinformatics analysis. Additionally, the CellChat was employed for a preliminary analysis of the cell-cell communication network in the ELG.

RESULTS

Over 37 subclasses of cells were identified, including seven types of glandular epithelial cells, three types of fibroblasts, ten types of myeloid-derived immune cells, at least eleven types of lymphoid-derived immune cells, and five types of vascular-associated cell subsets. The cell-cell communication network analysis revealed that fibroblasts and immune cells play a pivotal role in the dense intercellular communication network within the mouse ELG.

CONCLUSIONS

This study provides a comprehensive transcriptome atlas and related database of the mouse ELG.

Identification of Potential Ferroptosis Biomarkers and Analysis of Immune Cell Infiltration in Psoriasis Using Machine Learning

Background

Ferroptosis is a type of cell death characterized by the accumulation of iron-dependent lethal lipid peroxides, which is associated with various pathophysiological processes. Psoriasis is a chronic autoimmune skin disease accompanied by abnormal immune cell infiltration and excessive production of lipid reactive oxygen species (ROS). Currently, its pathogenesis remains elusive, especially the potential role of ferroptosis in its pathophysiological process.

Methods

The microarrays GSE13355 (58 psoriatic skin specimens versus 122 healthy skin specimens) and the ferroptosis database were employed to identify the common differentially expressed genes (DEGs) associated with psoriasis and ferroptosis. The functions of common DEGs were investigated through functional enrichment analysis and protein-protein interaction analysis. The potential diagnostic markers for psoriasis among the common DEGs were identified using four machine-learning algorithms. DGIdb was utilized to explore potential therapeutic agents for psoriasis. Additionally, CIBERSORT was employed to investigate immune infiltration in psoriasis.

Results

A total of 8 common DEGs associated with psoriasis and ferroptosis were identified, which are involved in intercellular signaling and affect pathways of cell response to stress and stimulation. Four machine-learning algorithms were employed to identify poly (ADP-ribose) polymerase 12 (PARP12), frizzled homolog 7 (FZD7), and arachidonate 15-lipoxygenase (ALOX15B) among the eight common DEGs as potential diagnostic markers for psoriasis. A total of 18 drugs targeting the five common DEGs were identified as potential candidates for treating psoriasis. Additionally, significant changes were observed in the immune microenvironment of patients with psoriasis.

Conclusion

This study has contributed to our enhanced comprehension of ferroptosis-related genes as potential biomarkers for psoriasis diagnosis, as well as the alterations in the immune microenvironment associated with psoriasis. Our findings offer valuable insights into the diagnosis and treatment of psoriasis.

Revisiting roles of mast cells and neural cells in keloid: exploring their connection to disease activity

Background

Mast cells (MCs) and neural cells (NCs) are important in a keloid microenvironment. They might contribute to fibrosis and pain sensation within the keloid. However, their involvement in pathological excessive scarring has not been adequately explored.

Objectives

To elucidate roles of MCs and NCs in keloid pathogenesis and their correlation with disease activity.

Methods

Keloid samples from chest and back regions were analyzed. Single-cell RNA sequencing (scRNA-seq) was conducted for six active keloids (AK) samples, four inactive keloids (IK) samples, and three mature scar (MS) samples from patients with keloids.

Results

The scRNA-seq analysis demonstrated notable enrichment of MCs, lymphocytes, and macrophages in AKs, which exhibited continuous growth at the excision site when compared to IK and MS samples (P = 0.042). Expression levels of marker genes associated with activated and degranulated MCs, including FCER1G, BTK, and GATA2, were specifically elevated in keloid lesions. Notably, MCs within AK lesions exhibited elevated expression of genes such as NTRK1, S1PR1, and S1PR2 associated with neuropeptide receptors. Neural progenitor cell and non-myelinating Schwann cell (nmSC) genes were highly expressed in keloids, whereas myelinating Schwann cell (mSC) genes were specific to MS samples.

Conclusions

scRNA-seq analyses of AK, IK, and MS samples unveiled substantial microenvironmental heterogeneity. Such heterogeneity might be linked to disease activity. These findings suggest the potential contribution of MCs and NCs to keloid pathogenesis. Histopathological and molecular features observed in AK and IK samples provide valuable insights into the mechanisms underlying pain and pruritus in keloid lesions.

Transcriptome network analysis of inflammation and fibrosis in keloids

BACKGROUND

Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics.

OBJECTIVE

Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars.

METHODS

In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity.

RESULTS

By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615-5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations.

CONCLUSIONS

Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.

Weighted gene co-expression network analysis and machine learning identified the lipid metabolism-related gene LGMN as a novel biomarker for keloid

The aetiology of keloid formation remains unclear, and existing treatment modalities have not definitively established a successful approach. Therefore, it is necessary to identify reliable and novel keloid biomarkers as potential targets for therapeutic interventions. In this study, we performed differential expression analysis and functional enrichment analysis on the keloid related datasets, and found that multiple metabolism-related pathways were associated with keloid formation. Subsequently, the differentially expressed genes (DEGs) were intersected with the results of weighted gene co-expression network analysis (WGCNA) and the lipid metabolism-related genes (LMGs). Then, three learning machine algorithms (SVM-RFE, LASSO and Random Forest) together identified legumain (LGMN) as the most critical LMGs. LGMN was overexpressed in keloid and had a high diagnostic performance. The protein-protein interaction (PPI) network related to LGMN was constructed by GeneMANIA database. Functional analysis of indicated PPI network was involved in multiple immune response-related biological processes. Furthermore, immune infiltration analysis was conducted using the CIBERSORT method. M2-type macrophages were highly infiltrated in keloid tissues and were found to be significantly and positively correlated with LGMN expression. Gene set variation analysis (GSVA) indicated that LGMN may be related to promoting fibroblast proliferation and inhibiting their apoptosis. Moreover, eight potential drug candidates for keloid treatment were predicted by the DSigDB database. Western blot, qRT-PCR and immunohistochemistry staining results confirmed that LGMN was highly expressed in keloid. Collectively, our findings may identify a new biomarker and therapeutic target for keloid and contribute to the understanding of the potential pathogenesis of keloid.

Tissue RNA Sequencing Reveals Novel Biomarkers Associated with Postoperative Keloid Recurrence

Keloids can be resected through surgery, but they may still recur. The purpose of this study was to explore the biomarkers to predict the postoperative recurrence of keloids. Patients who underwent surgical treatment and postoperative superficial X-ray radiation between January 2019 and December 2020 were recruited with clinical data and keloid samples for RNA-seq. By screening differentially expressed genes (DEGs) between postoperative recurrent and non-recurrent sample groups and constructing a co-expression network via the weighted gene co-expression network analysis (WGCNA), an immunity-related module was chosen for subsequent analysis. By constructing a DEG co-expression network and using the Molecular Complex Detection (MCODE) algorithm, five hub genes were identified in the key module. Receiver Operating Characteristic (ROC) curve analysis showed that the area under the curve (AUC) for the five combined hub genes was 0.776. The result of qRT-PCR showed that CHI3L1, IL1RN, MMP7, TNFAIP3, and TNFAIP6 were upregulated in the recurrent group with statistical significance (p < 0.05). Immune infiltration analysis showed that mast cells, macrophages, and T cells were the major components of the keloid immune microenvironment. This study provides potential biomarkers for predicting keloid recurrence and offers insights into genetic targets for recurrence prevention.

Complex interactions of cellular players in chronic Graft-versus-Host Disease

Chronic Graft-versus-Host Disease is a life-threatening inflammatory condition that affects many patients after allogeneic hematopoietic stem cell transplantation. Although we have made substantial progress in understanding disease pathogenesis and the role of specific immune cell subsets, treatment options are still limited. To date, we lack a global understanding of the interplay between the different cellular players involved, in the affected tissues and at different stages of disease development and progression. In this review we summarize our current knowledge on pathogenic and protective mechanisms elicited by the major involved immune subsets, being T cells, B cells, NK cells and antigen presenting cells, as well as the microbiome, with a special focus on intercellular communication of these cell types via extracellular vesicles as up-and-coming fields in chronic Graft-versus-Host Disease research. Lastly, we discuss the importance of understanding systemic and local aberrant cell communication during disease for defining better biomarkers and therapeutic targets, eventually enabling the design of personalized treatment schemes.

Bioinformatics analysis and experimental validation of a novel autophagy-related signature relevant to immune infiltration for recurrence prediction after curative hepatectomy

Hepatocellular carcinoma (HCC) remains imposing an enormous economic and healthcare burden worldwide. In this present study, we constructed and validated a novel autophagy-related gene signature to predict the recurrence of HCC patients. A total of 29 autophagy-related differentially expressed genes were identified. A five-gene signature (CLN3, HGF, TRIM22, SNRPD1, and SNRPE) was constructed for HCC recurrence prediction. Patients in high-risk groups exhibited a significantly poor prognosis compared with low-risk patients both in the training set (GSE14520 dataset) and the validation set (TCGA and GSE76427 dataset). Multivariate cox regression analysis demonstrated that the 5-gene signature was an independent risk factor for recurrence-free survival (RFS) in HCC patients. The nomograms incorporating 5-gene signature and clinical prognostic risk factors were able to effectively predict RFS. KEGG and GSEA analysis revealed that the high-risk group was enriched with multiple oncology characteristics and invasive-related pathways. Besides, the high-risk group had a higher level of immune cells and higher levels of immune checkpoint-related gene expression in the tumor microenvironment, suggesting that they might be more likely to benefit from immunotherapy. Finally, the immunohistochemistry and cell experiments confirmed the role of SNRPE, the most significant gene in the gene signature. SNRPE was significantly overexpressed in HCC. After SNRPE knockdown, the proliferation, migration and invasion ability of the HepG2 cell line were significantly inhibited. Our study established a novel five-gene signature and nomogram to predict RFS of HCC, which may help in clinical decision-making for individual treatment.

Identification and preliminary validation of synovial tissue-specific genes and their-mediated biological mechanisms in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. It is well known that the formation of positive feedback between synovial hyperplasia and inflammatory infiltration is intimately associated with the occurrence and development of RA. However, the exact mechanisms still remain unknown, making the early diagnosis and therapy of RA difficult. This study was designed to identify prospective diagnostic and therapeutic biomarkers, as well as their-mediated biological mechanisms in RA.

METHODS

Three microarray datasets (GSE36700, GSE77298 and GSE153015) and two RNA-sequencing datasets (GSE89408 and GSE112656) of synovial tissues, as well as three other microarray datasets (GSE101193, GSE134087 and GSE94519) of peripheral blood were downloaded for integrated analysis. The differently expressed genes (DEGs) were identified by "limma" package of R software. Then, weight gene co-expression analysis and gene set enrichment analysis were performed to investigate synovial tissue-specific genes and their-mediated biological mechanisms in RA. The expression of candidate genes and their diagnostic value for RA were verified by quantitative real-time PCR and receiver operating characteristic (ROC) curve, respectively. Relevant biological mechanisms were explored through cell proliferation and colony formation assay. The suggestive anti-RA compounds were discovered by CMap analysis.

RESULTS

We identified a total of 266 DEGs, which were mainly enriched in cellular proliferation and migration, infection and inflammatory immune signaling pathways. Bioinformatics analysis and molecular validation revealed 5 synovial tissue-specific genes, which exhibited excellent diagnostic value for RA. The infiltration level of immune cells in RA synovial tissue was significantly higher than that in control individuals. Moreover, preliminary molecular experiments suggested that these characteristic genes may be responsible for the high proliferation potential of RA fibroblast-like synoviocytes (FLSs). Finally, 8 small molecular compounds with anti-RA potential were obtained.

CONCLUSIONS

We have proposed 5 potential diagnostic and therapeutic biomarkers (CDK1, TTK, HMMR, DLGAP5, and SKA3) in synovial tissues that may contribute to the pathogenesis of RA. These findings may shed light on the early diagnosis and therapy of RA.

Extracellular matrix stiffness-The central cue for skin fibrosis

Skin fibrosis is a physiopathological process featuring the excessive deposition of extracellular matrix (ECM), which is the main architecture that provides structural support and constitutes the microenvironment for various cellular behaviors. Recently, increasing interest has been drawn to the relationship between the mechanical properties of the ECM and the initiation and modulation of skin fibrosis, with the engagement of a complex network of signaling pathways, the activation of mechanosensitive proteins, and changes in immunoregulation and metabolism. Simultaneous with the progression of skin fibrosis, the stiffness of ECM increases, which in turn perturbs mechanical and humoral homeostasis to drive cell fate toward an outcome that maintains and enhances the fibrosis process, thus forming a pro-fibrotic "positive feedback loop". In this review, we highlighted the central role of the ECM and its dynamic changes at both the molecular and cellular levels in skin fibrosis. We paid special attention to signaling pathways regulated by mechanical cues in ECM remodeling. We also systematically summarized antifibrotic interventions targeting the ECM, hopefully enlightening new strategies for fibrotic diseases.

An updated review of the immunological mechanisms of keloid scars

Keloid is a type of disfiguring pathological scarring unique to human skin. The disorder is characterized by excessive collagen deposition. Immune cell infiltration is a hallmark of both normal and pathological tissue repair. However, the immunopathological mechanisms of keloid remain unclear. Recent studies have uncovered the pivotal role of both innate and adaptive immunity in modulating the aberrant behavior of keloid fibroblasts. Several novel therapeutics attempting to restore regulation of the immune microenvironment have shown variable efficacy. We review the current understanding of keloid immunopathogenesis and highlight the potential roles of immune pathway-specific therapeutics.

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.

A pan-cancer analysis of the oncogenic role of ribonucleotide reductase subunit M2 in human tumors

Background

Recent studies have identified ribonucleotide reductase subunit M2 (RRM2) as a putative promoter of tumors. However, no systematic analysis of its carcinogenicity has been conducted.

Methods

The potential functions of RRM2 in various tumor types were investigated using data from the Genotype-Tissue Expression (GTEx), the Clinical Proteomic Tumor Analysis Consortium (CPTAC), the Cancer Genome Atlas (TCGA), the Human Protein Atlas (HPA), cBioPortal, GEPIA, String, and Gene Set Enrichment Analysis (GSEA). We analyzed the difference in mRNA and protein expression, pathological stage, survival, mutation, tumor microenvironment (TME), and immune cell infiltration in relation to RRM2. Meanwhile, using TCGA and the Tumor Immune Estimation Resource 2 (TIMER 2), the associations between RRM2 expression, immune infiltration, and immune-related genes were assessed. Additionally, CCK-8, Edu and RT-PCR assays were used to validate that RRM2 acts as an oncogene in liver cancer cells and its association with HBx. A cohort of liver hepatocellular carcinoma (LIHC) patients (n=154) from Huashan Hospital was analyzed for the expression of RRM2 and the association between RRM2 and immune infiltration.

Results

Using the GTEx and TCGA databases, we discovered that 28 tumors expressed RRM2 at significantly higher levels than the corresponding normal tissues. Increased RRM2 expression may be predictive of a poor overall survival (OS) in patients with seven different cancers. GO, KEGG, and GSEA analyses revealed that the biological process of RRM2 was associated with the regulation of carcinogenic processes and immune pathways in a variety of tumor types. The expression of RRM2 was highly correlated with maker genes involved in immune activation and immunosuppression, immune checkpoints, DNA mismatch repair system (MMR), and the infiltration levels of Tregs and macrophages (TAMs), suggesting that the carcinogenic effect of RRM2 may be achieved by regulating immune related genes. Moreover, as demonstrated by CCK-8 and Edu assays, RRM2 was an oncogene in liver cancer cells. We confirmed for the first time that RRM2 was significantly upregulated by HBx, suggesting that RRM2 may be a key regulator of LIHC induced by HBV. IHC analysis validated the upregulated expression of RRM2 protein and its correlation with immune infiltration makers in a LIHC patient cohort.

Conclusion

RRM2 may be a valuable molecular biomarker for predicting prognosis and immunotherapeutic efficacy in pan-cancer, particularly in LIHC.

Comprehensive bioinformatics analysis and molecular validation of lncRNAs-mediated ceRNAs network in schizophrenia

AIMS

The present study aimed to investigate how Schizophrenia (SCZ)-specific long non-coding RNAs (lncRNAs) served as competing endogenous RNAs (ceRNAs) to modulate the biological functions and pathways involved in the pathogenesis of SCZ.

MAIN METHODS

Microarray dataset (GSE54913) was obtained from Gene Expression Omnibus (GEO) database. Differently expressed (DE) lncRNAs and mRNAs were identified by "limma" package. The binding miRNAs of lncRNAs and target mRNAs of shared miRNAs were predicted by miRcode, miRDB, miRTarbase and targetscan databases. Following the ceRNAs theory, interaction network was established and visualized with the cytoscape. Functional enrichment analysis uncovered the concentrated functions and signaling pathways that may be associated with SCZ progression. Protein-protein interaction (PPI) analysis was utilized to determine hub genes. Quantitative real-time PCR (qRT-PCR) and receiver operating characteristic curve (ROC) were performed to evaluate the expression and diagnostic value of ceRNAs members, respectively.

KEY FINDINGS

DElncRNAs and DEmRNAs were initially screened from GSE54913 to construct the SCZ-related ceRNAs network with 42 nodes and 53 edges. Functional enrichment analysis revealed that ceRNAs members appeared to be highly correlated with transcription factor activation, cell replication and tumor-related pathways. Once validated, a significant ceRNAs subnetwork was proposed as being implicated in the pathogenesis of SCZ. ROC analysis indicated that SCZ-related ceRNAs members may be sensitive diagnostic biomarkers for SCZ.

SIGNIFICANCE

The significant SCZ-related ceRNAs subnetworks (lncRNA-C2orf48A/hsa-miR-20b-5p,-17-5p/KIF23, FOXJ2) may represent promising predictive and diagnostic biomarkers and provide novel insights into the mechanism by which lncRNAs act as microRNA sponges and contribute to the pathogenesis of SCZ.

Conjunctival squamous cell carcinoma with massive apoptosis and immune cell infiltration: A case report

This case reports a rare case of conjunctival squamous cell carcinoma in China. The elderly (86-year-old) female patient was diagnosed and treated effectively after three times of diagnosis. During this period, she was misdiagnosed and ineffective treatment for many times. Therefore, we propose to make an integrated diagnosis based on histopathological diagnosis, combined with a variety of diagnostic methods including MRI and CDFI, supplemented by updated multiple immunohistochemically techniques, so as to achieve the purpose of accurate diagnosis.

Clinical significance for diagnosis and prognosis of POP1 and its potential role in breast cancer: a comprehensive analysis based on multiple databases

Background: Breast cancer (BC) is one of the most common cancers in women. The discovery of available biomarkers is crucial for early diagnosis and improving prognosis. The effect of POP1 in BC remains unrevealed. Our study aims to explore the expression of POP1 in BC and demonstrate its clinical significance and potential molecular mechanisms.

Methods: The Cancer Genome Atlas (TCGA) BC cohort transcriptome data and corresponding clinical information were downloaded. GSE42568 cohort, GSE162228 cohort, GSE7904 cohort, and GSE161533 cohort in the Gene Expression Omnibus (GEO) database were used as verification groups. R software and several web tools were used for statistical analysis. Moreover, the proliferation, transwell, wound healing experiments, and flow cytometry were used for in vitro investigation.

Results: Compared with normal breast tissue, POP1 expression was up-regulated in BC tissue with a higher mutation rate. POP1 had good diagnostic value for BC and could be utilized as a new marker. POP1 was significantly correlated with multiple pathways in BC and played an important role in the immune infiltration of BC. High-POP1 expression patients were more prone to be responded to immunotherapy and had a significantly higher percentage of immunotherapy response rate. Moreover, POP1 promoted proliferation and migration and inhibited apoptosis in BC cells.

Conclusions: POP1 expression was up-regulated in BC and was associated with a poor prognosis. Patients with high-POP1 expression were more likely to be responded to immunotherapy. Our study can provide a potential marker POP1 for BC, which is beneficial in the diagnosis and treatment of BC.

Activation of the NFκB signaling pathway in IL6+CSF3+ vascular endothelial cells promotes the formation of keloids

Background: Keloid is a disease caused by abnormal proliferation of skin fibres, the causative mechanism of which remains unclear.

Method: In this study, endothelial cells of keloids were studied using scRNAseq combined with bulk-RNAseq data from keloids. The master regulators driving keloid development were identified by transcription factor enrichment analysis. The pattern of changes in vascular endothelial cells during keloid development was explored by inferring endothelial cell differentiation trajectories. Deconvolution of bulkRNAseq by CIBERSORTX verified the pattern of keloidogenesis. Immunohistochemistry for verification of the lesion process in keloid endothelial cells.

Results: The endothelial cells of keloids consist of four main cell populations (MMP1+ Endo0, FOS + JUN + Endo1, IL6+CSF3+Endo2, CXCL12 + Endo3). Endo3 is an endothelial progenitor cell, Endo1 is an endothelial cell in the resting state, Endo2 is an endothelial cell in the activated state and Endo0 is an endothelial cell in the terminally differentiated state. Activation of the NFΚB signaling pathway is a typical feature of Endo2 and represents the early skin state of keloids.

Conclusion: We have identified patterns of vascular endothelial cell lesions during keloidogenesis and development, and have found that activation of the NFΚB signaling pathway is an essential feature of keloid formation. These findings are expected to contribute to the understanding of the pathogenesis of keloids and to the development of new targeted therapeutic agents for the lesional characteristics of vascular endothelial cells.

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

Background

One of the most common diseases that have a negative impact on women’s health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-γ is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-γ-related genes and long non-coding RNAs in endometrial cancer, however, is unknown.

Methods

The Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-γ were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-γ gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1).

Results

Based on the transcript expression of IFN-γ-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-γ-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories.

Conclusion

Our findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.

SPINDOC is Highly Expressed in Pan-Cancer Samples and Can Promote the Proliferation, Invasion and Migration of Hepatocellular Carcinoma Cells by Activating Wnt/β-Catenin Signaling Pathway

Purpose

Methods

Results

Conclusion

Noncoding-RNA mediated high expression of zinc finger protein 268 suppresses clear cell renal cell carcinoma progression by promoting apoptosis and regulating immune cell infiltration

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant kidney tumors with a poor prognosis. Accumulating evidence proves that zinc finger protein 268 (ZNF268) is associated with tumor progression, but the detailed regulatory functions of ZNF268 in ccRCC require further exploration. Thus, here we aim to characterize the role of ZNF268 in ccRCC. The clinical significance of ZNF268 was evaluated using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Subsequently, tumor-infiltrating immune cells, as well as upstream noncoding RNAs (ncRNAs) related to the tumor-suppressing function of ZNF268, were identified by in silico analyses. The expression of ZNF268 was significantly decreased in ccRCC samples compared with adjacent normal tissues. In addition, ZNF268 expression was negatively correlated with tumor progression and positively correlated with overall and disease-specific survival. TCGA and GTEx databases proved the potential tumor-suppressing function, which was measured both in vitro and in vivo after ZNF268 over-expression. Overexpression of ZNF268 effectively inhibited the proliferation, migration, invasion and promotied apoptosis of the Caki-1. The level of ZNF268 was positively related to the immune cell infiltration in the tumor. Moreover, we determined that the AC093157.1/miR-27a-3p axis can potentially regulate ZNF268 function in ccRCC. Our work describes a novel ncRNA-mediated ZNF268 function in ccRCC. ZNF268 acts as a tumor suppressor, and it is associated with apoptosis and immune cell infiltration in ccRCC.