Qingyuan Lin, Jinchao Zhu, Jun Chen, Shouqiang Jia, Shengdong Nie
{"title":"银屑病相关基因在银屑病诊断和分型中的意义。","authors":"Qingyuan Lin, Jinchao Zhu, Jun Chen, Shouqiang Jia, Shengdong Nie","doi":"10.3389/fmolb.2023.1115091","DOIUrl":null,"url":null,"abstract":"<p><p>Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"10 ","pages":"1115091"},"PeriodicalIF":3.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119406/pdf/","citationCount":"0","resultStr":"{\"title\":\"Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.\",\"authors\":\"Qingyuan Lin, Jinchao Zhu, Jun Chen, Shouqiang Jia, Shengdong Nie\",\"doi\":\"10.3389/fmolb.2023.1115091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis.</p>\",\"PeriodicalId\":12465,\"journal\":{\"name\":\"Frontiers in Molecular Biosciences\",\"volume\":\"10 \",\"pages\":\"1115091\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10119406/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Molecular Biosciences\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.3389/fmolb.2023.1115091\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Molecular Biosciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fmolb.2023.1115091","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.
Cuproptosis is a novel form of cell death linked to mitochondrial metabolism and is mediated by protein lipoylation. The mechanism of cuproptosis in many diseases, such as psoriasis, remains unclear. In this study, signature diagnostic markers of cuproptosis were screened by differential analysis between psoriatic and non-psoriatic patients. The differentially expressed cuproptosis-related genes (CRGs) for patients with psoriasis were screened using the GSE178197 dataset from the gene expression omnibus database. The biological roles of CRGs were identified by GO and KEGG enrichment analyses, and the candidates of cuproptosis-related regulators were selected from a nomogram model. The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. Finally, latent diagnostic markers and drug sensitivity were analyzed using the pRRophetic R package. The differential analysis revealed that CRGs (MTF1, ATP7B, and SLC31A1) are significantly expressed in psoriatic patients. GO and KEGG enrichment analyses showed that the biological functions of CRGs were mainly related to acetyl-CoA metabolic processes, the mitochondrial matrix, and acyltransferase activity. Compared to the machine learning method used, the random forest model has higher accuracy in the occurrence of cuproptosis. However, the decision curve of the candidate cuproptosis regulators analysis showed that patients can benefit from the nomogram model. The consensus clustering analysis showed that psoriasis can be grouped into three patterns of cuproptosis (clusterA, clusterB, and clusterC) based on selected important regulators of cuproptosis. In advance, we analyzed the immune characteristics of patients and found that clusterA was associated with T cells, clusterB with neutrophil cells, and clusterC predominantly with B cells. Drug sensitivity analysis showed that three cuproptosis regulators (ATP7B, SLC31A1, and MTF1) were associated with the drug sensitivity. This study provides insight into the specific biological functions and related mechanisms of CRGs in the development of psoriasis and indicates that cuproptosis plays a non-negligible role. These results may help guide future treatment strategies for psoriasis.
期刊介绍:
Much of contemporary investigation in the life sciences is devoted to the molecular-scale understanding of the relationships between genes and the environment — in particular, dynamic alterations in the levels, modifications, and interactions of cellular effectors, including proteins. Frontiers in Molecular Biosciences offers an international publication platform for basic as well as applied research; we encourage contributions spanning both established and emerging areas of biology. To this end, the journal draws from empirical disciplines such as structural biology, enzymology, biochemistry, and biophysics, capitalizing as well on the technological advancements that have enabled metabolomics and proteomics measurements in massively parallel throughput, and the development of robust and innovative computational biology strategies. We also recognize influences from medicine and technology, welcoming studies in molecular genetics, molecular diagnostics and therapeutics, and nanotechnology.
Our ultimate objective is the comprehensive illustration of the molecular mechanisms regulating proteins, nucleic acids, carbohydrates, lipids, and small metabolites in organisms across all branches of life.
In addition to interesting new findings, techniques, and applications, Frontiers in Molecular Biosciences will consider new testable hypotheses to inspire different perspectives and stimulate scientific dialogue. The integration of in silico, in vitro, and in vivo approaches will benefit endeavors across all domains of the life sciences.