PageRank analysis reveals topologically expressed genes correspond to psoriasis and their functions are associated with apoptosis resistance

PRRGO: A Tool for Visualizing and Mapping Globally Expressed Genes in Public Gene Expression Omnibus RNA-Sequencing Studies to PageRank-scored Gene Ontology Terms

We herein report PageRankeR Gene Ontology (PRRGO), a downloadable web application that can integrate differentially expressed gene (DEG) data from the gene expression omnibus (GEO) GEO2R web tool with the gene ontology (GO) database [1]. Unlike existing tools, PRRGO computes the PageRank for the entire GO network and can generate both interactive GO networks on the web interface and comma-separated values (CSV) files containing the DEG statistics categorized by GO term. These hierarchical and tabular GO-DEG data are especially conducive to hypothesis generation and overlap studies with the use of PageRank data, which can provide a metric of GO term centrality. We verified the tool for accuracy and reliability across nine independent heat shock (HS) studies for which the RNA-seq data was publicly available on GEO and found that the tool produced increasing concordance between study DEGs, GO terms, and select HS-specific GO terms.

Metabolomics Reveals Molecular Signatures for Psoriasis Biomarkers and Drug Targets Discovery

Purpose

Psoriasis is a chronic, multi-system skin disease that can be influenced by immunological, environmental, and genetic factors. Plasma metabolomic analysis can provide a great deal of information on potential diagnostic biomarkers, pathogenesis and personalized treatment. However, the role of metabolites in psoriasis is unknown.

Patients and Methods

We performed an untargeted metabolomic analysis of plasma based on high-resolution liquid chromatography mass spectrometry from 10 plaque psoriasis patients and 10 healthy controls.

Results

A total of 301 differential metabolites were detected, of which 10 metabolites were possible potential biomarkers, including vitamins, amino acids, and lipids. At the same time, KEGG pathway enrichment analysis was performed for all detected differential metabolites, and it was found that protein digestion and absorption, amino acid metabolism and lipid metabolism may be jointly involved in regulating the pathogenesis of psoriasis. In addition, the proteins ESR1, OPRM1 and HSD11B1 were identified as possible potential topical therapeutic targets for psoriasis through analysis of the metabolite-protein interaction network.

Conclusion

In this study, we identified 10 differential metabolites as possible potential combinatorial biomarkers for the diagnosis of psoriasis. 12 metabolic pathways were significantly enriched that may be closely related to the occurrence and development of psoriasis. Three proteins, ESR1, OPRM1, and HSD11B1, were identified as possible potential therapeutic targets for psoriasis.

Single-atom catalysts-based catalytic ROS clearance for efficient psoriasis treatment and relapse prevention via restoring ESR1

Psoriasis is a common inflammatory disease of especially high recurrence rate (90%) which is suffered by approximately 3% of the world population. The overexpression of reactive oxygen species (ROS) plays a critical role in psoriasis progress. Here we show that biomimetic iron single-atom catalysts (FeN4O2-SACs) with broad-spectrum ROS scavenging capability can be used for psoriasis treatment and relapse prevention via related gene restoration. FeN4O2-SACs demonstrate attractive multiple enzyme-mimicking activities based on atomically dispersed Fe active structures, which are analogous to those of natural antioxidant enzymes, iron superoxide dismutase, human erythrocyte catalase, and ascorbate peroxidase. Further, in vitro and in vivo experiments show that FeN4O2-SACs can effectively ameliorate psoriasis-like symptoms and prevent the relapse with augmented efficacy compared with the clinical drug calcipotriol. Mechanistically, estrogen receptor 1 (ESR1) is identified as the core protein upregulated in psoriasis treatment through RNA sequencing and bioinformatic analysis. Together, this study provides a proof of concept of psoriasis catalytic therapy (PCT) and multienzyme-inspired bionics (MIB).

Identification of key apoptosis-related genes and immune infiltration in the pathogenesis of psoriasis

Background

Psoriasis is a condition in which skin cells build up and form itchy scales and dry patches. It is also considered a common lifelong disease with an unclear pathogenesis. Furthermore, an effective cure for psoriasis is still unavailable. Reductive apoptosis of keratinocytes and immune infiltration are common in psoriasis. This study aimed to explore underlying functions of key apoptosis-related genes and the characteristics of immune infiltration in psoriasis. We used GSE13355 and GSE30999 to screen differentially expressed apoptosis related genes (DEARGs) in our study. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and gene set enrichment analysis (GSEA) were performed using clusterProfiler package. Protein–protein interaction (PPI) network was constructed to acquire key DEARGs. Transcription factor (TF)–target and miRNA–mRNA network analyses, drug sensitivity prediction, and immune infiltration were applied. Key DEARGs were validated using real-time quantitative PCR (RT-qPCR).

Results

We identified 482 and 32 DEARGs from GSE13355 and GSE30999, respectively. GO analysis showed that DEARGs were commonly enriched in cell chemotaxis, receptor ligand activity, and signaling receptor activator activity. KEGG pathway analysis indicated that viral protein interaction with cytokine and cytokine receptor was maximally enriched pathway. The GSEA analysis of GSE13355 and GSE30999 demonstrated a high consistency degree of enriched pathways. Thirteen key DEARGs with upregulation were obtained in the PPI network. Eleven key DEARGs were confirmed using RT-qPCR. Additionally, 5 TFs and 553 miRNAs were acquired, and three novel drugs were predicted. Moreover, Dendritic.cells.activated exhibited high levels of immune infiltration while Mast.cells.resting showed low levels of immune infiltration in psoriasis groups.

Conclusion

Results of this study may reveal some insights into the underlying molecular mechanism of psoriasis and provide novel targeted drugs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00233-0.

Mining Important Herb Combinations of Traditional Chinese Medicine against Hypertension Based on the Symptom-Herb Network Combined with Network Pharmacology

Although data mining methods are extensively used in the rule analysis of famous old traditional Chinese medicine (TCM) experts' prescriptions for the treatment of hypertension, most of them only mine the association between herbs and herbs, ignoring the importance of symptoms in the disease. This study collected 439 cases of hypertension treated by famous old TCM experts from the FangNet platform. Using the structure network algorithm, the symptom-herb network was constructed, which redefined the importance of herb in disease. Based on the network, 21 driver herbs, 76 herb pairs, and 41 symptom-herb associations were mined. Finally, the basic prescription composed of Gouteng (Uncariae Ramulus cum Uncis), Huanglian (Coptidis Rhizoma), Chuanxiong (Chuanxiong Rhizoma), Gegen (Puerariae Lobatae Radix), Danggui (Angelicae Sinensis Radix), and Huangqin (Scutellariae Radix) was found. These herbs are the most significant among all herbs, and they have a potential correlation with each other. To further verify the rationality of the data mining results, we adopted the network pharmacology method. Network pharmacological analysis shows that the five core targets in the basic prescription include IL6, VEGFA, TNF, TP53, and EGF, which link 10 significant active compounds and 7 important KEGG pathways. It was predicted that anti-inflammatory, antioxidant, vascular endothelial protection, emotion regulation, and ion channel intervention might be the main mechanisms of the basic prescription against hypertension. This study reveals the prescription rule of famous old TCM experts for treating hypertension from a new perspective, which provides a new approach to inherit the academic experience of famous old TCM experts and develop new drugs.

The S100A7 nuclear interactors in autoimmune diseases: a coevolutionary study in mammals

S100A7, a member of the S100A family of Ca²⁺-binding proteins, is considered a key effector in immune response. In particular, S100A7 dysregulation has been associated with several diseases, including autoimmune disorders. At the nuclear level, S100A7 interacts with several protein-binding partners which are involved in transcriptional regulation and DNA repair. By using the BioGRID and GAAD databases, S100A7 nuclear interactors with a putative involvement in autoimmune diseases were retrieved. We selected fatty acid-binding protein 5 (FABP5), autoimmune regulator (AIRE), cystic fibrosis transmembrane conductance regulator (CFTR), chromodomain helicase DNA-binding protein 4 (CHD4), epidermal growth factor receptor (EGFR), estrogen receptor 1 (ESR1), histone deacetylase 2 (HDAC2), v-myc avian myelocytomatosis viral oncogene homolog (MYC), protection of telomeres protein 1 (POT1), telomeric repeat-binding factor (NIMA-interacting) 1 (TERF1), telomeric repeat-binding factor 2 (TERF2), and Zic family member 1 (ZIC1). Linear correlation coefficients between interprotein distances were calculated with MirrorTree. Coevolution clusters were also identified with the use of a recent version of the Blocks in Sequences (BIS2) algorithm implemented in the BIS2Analyzer web server. Analysis of pair positions identified interprotein coevolving clusters between S100A7 and the binding partners CFTR and TERF1. Such findings could guide further analysis to better elucidate the function of S100A7 and its binding partners and to design drugs targeting for these molecules in autoimmune diseases.

Identification of Six Prognostic Genes in EGFR-Mutant Lung Adenocarcinoma Using Structure Network Algorithms

This study aims to determine hub genes related to the incidence and prognosis of EGFR-mutant (MT) lung adenocarcinoma (LUAD) with weighted gene coexpression network analysis (WGCNA). From The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we used 253 EGFR-MT LUAD samples and 38 normal lung tissue samples. At the same time, GSE19188 was additionally included to verify the accuracy of the predicted gene. To discover differentially expressed genes (DEGs), the R package “limma” was used. The R packages “WGCNA” and “survival” were used to perform WGCNA and survival analyses, respectively. The functional analysis was carried out with the R package “clusterProfiler.” In total, 1450 EGFR-MT–specific DEGs were found, and 7 tumor-related modules were marked with WGCNA. We found 6 hub genes in DEGs that overlapped with the tumor-related modules, and the overexpression level of B3GNT3 was significantly associated with the worse OS (overall survival) of the EGFR-MT LUAD patients (p < 0.05). Functional analysis of the hub genes showed the metabolism and protein synthesis–related terms added value. In conclusion, we used WGCNA to identify hub genes in the development of EGFR-MT LUAD. The established prognostic factors could be used as clinical biomarkers. To confirm the mechanism of those genes in EGFR-MT LUAD, further molecular research is required.

Systems Pharmacology Approach and Experiment Evaluation Reveal Multidimensional Treatment Strategy of LiangXueJieDu Formula for Psoriasis

Clinical studies have demonstrated the anti-psoriatic effect of the LiangXueJieDu (LXJD) herbal formula. However, the systemic mechanism and the targets of the LXJD formula have not yet been elucidated. In the present study, a systems pharmacology approach, metabolomics, and experimental evaluation were employed. First, by systematic absorption-distribution-metabolism-excretion (ADME) analysis, 144 active compounds with satisfactory pharmacokinetic properties were identified from 12 herbs of LXJD formula using the TCMSP database. These active compounds could be linked to 125 target proteins involved in the pathological processes underlying psoriasis. Then, the networks constituting the active compounds, targets, and diseases were constructed to decipher the pharmacological actions of this formula, indicating its curative effects in psoriasis treatment and related complications. The psoriasis-related pathway comprising several regulatory modules demonstrated the synergistic mechanisms of LXJD formula. Furthermore, the therapeutic effect of LXJD formula was validated in a psoriasis-like mouse model. Consistent with the systems pharmacology analysis, LXJD formula ameliorated IMQ-induced psoriasis-like lesions in mice, inhibited keratinocyte proliferation, improved keratinocyte differentiation, and suppressed the infiltration of CD3+ T cells. Compared to the model group, LXJD formula treatment remarkably reduced the expression of inflammatory cytokines and factors, such as IL-1β, IL-6, TNF-α, Cox2, and inhibited the phosphorylation of p-P65, p-IқB, p-ERK, p-P38, p-PI3K, p-AKT, indicating that LXJD formula exerts its therapeutic effect by inhibiting the MAPK, PI3K/AKT, and NF-қB signaling pathways. The metabolic changes in the serum of psoriasis patients were evaluated by liquid chromatography coupled with orbitrap mass spectrometry (LC-MS). The LXJD formula improved two perturbed metabolic pathways of glycerophospholipid metabolism and steroid hormone biosynthesis. Overall, this study revealed the complicated anti-psoriatic mechanism of LXJD formula and also offered a reliable strategy to elucidate the complex therapeutic mechanism of this Chinese herbal formula in psoriasis from a holistic perspective.

FangNet: Mining herb hidden knowledge from TCM clinical effective formulas using structure network algorithm

The use of herbs to treat various human diseases has been recorded for thousands of years. In Asia's current medical system, numerous herbal formulas have been repeatedly verified to confirm their effectiveness in different periods, which is a great resource for drug innovation and discovery. Through the mining of these clinical effective formulas by network pharmacology and bioinformatics analysis, important biologically active ingredients derived from these natural products might be discovered. As modern medicine requires a combination of multiple drugs for the treatment of complex diseases, previously clinical formulas are also combinations of various herbs according to the main causes and accompanying symptoms. However, the herbs that play a major role in the treatment of diseases are always unclear. Therefore, how to rank each herb's relative importance and determine the core herbs, is the first step to assisting herb selection for active ingredients discovery. To solve this problem, we built the platform FangNet, which ranks all herbs on their relative topological importance using the PageRank algorithm, based on the constructed symptom-herb network from a collection of clinical empirical prescriptions. Three types of herb hidden knowledge, including herb importance rank, herb-herb co-occurrence, and associations to symptoms, were provided in an interactive visualization. Moreover, FangNet has designed role-based permission for teams to store, analyze, and jointly interpret their clinical formulas, in an easy and secure collaboration environment, aiming at creating a central hub for massive symptom-herb connections. FangNet can be accessed at http://fangnet.org or http://fangnet.herb.ac.cn.

Review-Current Concepts in Inflammatory Skin Diseases Evolved by Transcriptome Analysis: In-Depth Analysis of Atopic Dermatitis and Psoriasis

During the last decades, high-throughput assessment of gene expression in patient tissues using microarray technology or RNA-Seq took center stage in clinical research. Insights into the diversity and frequency of transcripts in healthy and diseased conditions provide valuable information on the cellular status in the respective tissues. Growing with the technique, the bioinformatic analysis toolkit reveals biologically relevant pathways which assist in understanding basic pathophysiological mechanisms. Conventional classification systems of inflammatory skin diseases rely on descriptive assessments by pathologists. In contrast to this, molecular profiling may uncover previously unknown disease classifying features. Thereby, treatments and prognostics of patients may be improved. Furthermore, disease models in basic research in comparison to the human disease can be directly validated. The aim of this article is not only to provide the reader with information on the opportunities of these techniques, but to outline potential pitfalls and technical limitations as well. Major published findings are briefly discussed to provide a broad overview on the current findings in transcriptomics in inflammatory skin diseases.

Association Study of the Caspase Gene Family and Psoriasis Vulgaris Susceptibility in Northeastern China

Background

Abnormal apoptosis of keratinocytes is one of the pathological changes of psoriasis. Caspases (CASPs) are the central engines of apoptosis. Studies to date have shown that some SNPs alter the expression of related genes and lead to changes in disease risk. However, no studies have investigated the associations between gene polymorphisms and the risk of psoriasis in Han population in northeast China. Therefore, we conducted a case-control study to explore this question in Han population of northeastern China.

Methods

540 patients with PsV and 612 healthy age- and sex-matched controls were enrolled in this study. We determined the genotypes of 17 single nucleotide polymorphisms (SNPs) from 11 genes of caspase family by the improved multiplex ligation detection reaction (iMLDR) method. A model-based single SNP frequentist test and haplotype association studies were performed to evaluate the association between SNPs and PsV.

Results

In the single SNP tests, rs6704688 in CASP8 was significantly associated with psoriasis vulgaris (PsV) in Han population of northeastern China (P = 0.0169, P' = 0.0179 under the additive model; P = 0.0126, P' = 0.0149 under the heterozygous model). In haplotype analyses, the CASP7 haplotype GC was found to be associated with PsV risk (case group versus control group, 47.2% versus 54.4%, respectively, p = 0.0149).

Conclusions

Our study presented that the gene polymorphisms of CASP7 and CASP8 were significantly associated with PsV in Han population of northeastern China, which implied the functional relationship between PsV and caspase genes. CASP8 and CASP7 SNPs could be new potential biomarkers for risk stratification and prevention of PsV.

Inhibitory effects of TGP on KGF‑induced hyperproliferation of HaCaT cells via suppression of the p38 MAPK/NF‑κB p65 pathway

Psoriasis is a chronic inflammatory skin disease, primarily caused by overgrowth and abnormal differentiation of epidermal keratinocytes. Studies have suggested that keratinocyte growth factor (KGF) may be involved in the regulation of differentiation and development of keratinocytes. Total glucosides of peony (TGP) have been widely used for the treatment of psoriasis. The present study aimed to determine whether the therapeutic effect of TGP on psoriasis is mediated by modulation of the p38 mitogen‑activated protein kinase (p38 MAPK)/nuclear factor (NF)‑κB p65 signaling pathways. Cell proliferation was evaluated by CCK‑8 and cell cycle was assessed by flow cytometry assay. Protein and mRNA expression of genes were determined by western blot and reverse transcription‑quantitative polymerase chain reaction, respectively. The results of the present study demonstrated that KGF can promote proliferation of HaCaT cells in a dose‑dependent manner. In addition, it was demonstrated that TGP may suppress the hyperproliferation of HaCaT cells stimulated by KGF by inducing arrest of the cell cycle at the G1 phase. The expression levels of the proinflammatory cytokines interleukin (IL)‑22 and vascular endothelial growth factor (VEGF) were markedly elevated in cells treated with KGF, whereas they were downregulated in cells treated with TGP. Furthermore, combination treatments with p38 MAPK inhibitor SB203580 and KGF, or TGP and KGF suppressed the mRNA and protein expression levels of IL‑22 and VEGF, compared with cells treated with KGF alone. Furthermore, the expression profiles of phosphorylated‑p38 MAPK and NF‑κB p65 were similar to those of IL‑22 and VEGF. The results of the present study suggested that the therapeutic effect of TGP on psoriasis may be mediated by modulation of the p38 MAPK/NF‑κB p65 signaling pathway. The results of the present study contribute to the understanding of the role of TGP in the treatment of psoriasis. The present study provides insights suggesting that p38 MAPK may be a novel regulatory signaling pathway for the treatment of psoriasis.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

p75 Neurotrophin Receptor in the Skin: Beyond Its Neurotrophic Function

p75 neurotrophin receptor (p75^NTR), also known as CD271, is the low-affinity receptor that, together with the tyrosine kinase receptor tropomyosin-receptor kinase (Trk), mediate neurotrophin (NT) functions. Beside their classic role in skin innervation, NT and their receptors constitute a complex cutaneous network associated with a number of autocrine and paracrine activities. In this context, the role of p75^NTR is becoming more and more important. This review will focus on the intriguing functions of p75^NTR in healthy and diseased skin. First, p75^NTR counterbalances the proliferative and survival activities of its cognate receptor Trk by inducing keratinocyte apoptosis. In addition, p75^NTR identifies an early transit-amplifying (TA) keratinocyte population and plays a critical role in keratinocyte stem cell transition to its progeny as well as in epidermal differentiation. p75^NTR is absent in psoriatic TA cells, thus rendering these cells resistant to apoptosis. On the other hand, p75^NTR infection restores NT-induced apoptosis in psoriatic keratinocytes. Taken together, these results provide evidence for a critical role of p75^NTR in epidermal homeostasis, while its lack may account for the TA defect in psoriasis. While the issue of p75^NTR as a marker of melanoma initiating cells is still to be solved, there is strong evidence that downregulation of this receptor is a precondition to melanoma invasion and metastasis in vitro and in vivo. All in all, this review points to p75^NTR as a major actor in both physiologic and pathologic conditions at the skin level.