Xiangyun Li, Yang Liu, Luting Zhou, Jianhua Wang, Xiaoqun Yang
{"title":"Construction and Validation of a Mutation-Related Model in Papillary Renal Cell Carcinoma and Associated Immune Infiltration.","authors":"Xiangyun Li, Yang Liu, Luting Zhou, Jianhua Wang, Xiaoqun Yang","doi":"10.1159/000539096","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>To improve the clinical evaluation of the prognosis of papillary renal cell carcinoma (PRCC), we screened a model to predict the survival of patients with mutations in related genes.</p><p><strong>Methods: </strong>We downloaded RNA sequencing information from all patients with PRCC in TCGA. We first analyzed the differences in genes and the enrichment of these differences. Then, by selecting mutant genes, constructing a protein-protein interaction network, least absolute shrinkage and selection operator regression, and multivariable Cox regression, a prognosis model was constructed. Additionally, the model was validated using external data sets. We analyzed the immune infiltration of PRCC and the correlation between the model and popular targets. Finally, we performed tissue microarray analysis and immunohistochemistry to verify the expression levels of the three genes.</p><p><strong>Results: </strong>We constructed a three-gene (never in mitosis gene A-related kinase 2 [NEK2], centromere protein A [CENPA], and GINS complex subunit 2 [GINS2]) model. The verification results indicated that the model had a good prediction effect. We also developed a visual nomogram. Enrichment analysis revealed the major pathways involved in muscle system processes. Immunoassays showed that the expression level of CENPA was positively correlated with PD-1 and CTLA4 expression levels. Immunohistochemical and tissue microarray results showed that these three genes were highly expressed in PRCC, which was consistent with the predicted results in the database.</p><p><strong>Conclusion: </strong>We constructed and verified a three-gene model to predict the patient survival. The results show that the model has a good prediction effect.</p>","PeriodicalId":17813,"journal":{"name":"Kidney & blood pressure research","volume":" ","pages":"355-367"},"PeriodicalIF":2.3000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kidney & blood pressure research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000539096","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/7 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PERIPHERAL VASCULAR DISEASE","Score":null,"Total":0}
引用次数: 0
Abstract
Background: To improve the clinical evaluation of the prognosis of papillary renal cell carcinoma (PRCC), we screened a model to predict the survival of patients with mutations in related genes.
Methods: We downloaded RNA sequencing information from all patients with PRCC in TCGA. We first analyzed the differences in genes and the enrichment of these differences. Then, by selecting mutant genes, constructing a protein-protein interaction network, least absolute shrinkage and selection operator regression, and multivariable Cox regression, a prognosis model was constructed. Additionally, the model was validated using external data sets. We analyzed the immune infiltration of PRCC and the correlation between the model and popular targets. Finally, we performed tissue microarray analysis and immunohistochemistry to verify the expression levels of the three genes.
Results: We constructed a three-gene (never in mitosis gene A-related kinase 2 [NEK2], centromere protein A [CENPA], and GINS complex subunit 2 [GINS2]) model. The verification results indicated that the model had a good prediction effect. We also developed a visual nomogram. Enrichment analysis revealed the major pathways involved in muscle system processes. Immunoassays showed that the expression level of CENPA was positively correlated with PD-1 and CTLA4 expression levels. Immunohistochemical and tissue microarray results showed that these three genes were highly expressed in PRCC, which was consistent with the predicted results in the database.
Conclusion: We constructed and verified a three-gene model to predict the patient survival. The results show that the model has a good prediction effect.
期刊介绍：
This journal comprises both clinical and basic studies at the interface of nephrology, hypertension and cardiovascular research. The topics to be covered include the structural organization and biochemistry of the normal and diseased kidney, the molecular biology of transporters, the physiology and pathophysiology of glomerular filtration and tubular transport, endothelial and vascular smooth muscle cell function and blood pressure control, as well as water, electrolyte and mineral metabolism. Also discussed are the (patho)physiology and (patho) biochemistry of renal hormones, the molecular biology, genetics and clinical course of renal disease and hypertension, the renal elimination, action and clinical use of drugs, as well as dialysis and transplantation. Featuring peer-reviewed original papers, editorials translating basic science into patient-oriented research and disease, in depth reviews, and regular special topic sections, ''Kidney & Blood Pressure Research'' is an important source of information for researchers in nephrology and cardiovascular medicine.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
