{"title":"PPIB Unveiled: A Comprehensive Pan-Cancer Exploration Unraveling Immunological Signatures and Prognostic Implications","authors":"Ouyang Yan, Qi Dai, Shengming Lai, Haiyan Huang, Yongsheng Huang, Shuwei Ren","doi":"10.34257/gjmrfvol24is1pg1","DOIUrl":null,"url":null,"abstract":"Background: Peptidylprolyl isomerase B (PPIB) has been shown to play an essential role in tumor initiation and progression. However, it lacks systematic analysis and evaluation of the effect of PPIB on pan-cancer.\nMethods: The expression profile and survival analysis of PPIB in tumor tissues were demonstrated by the TIMER2.0, GEPIA2.0, and UALCAN online tools. The cBioportal, GSCA, TISDB, and TIMER2.0 databases were applied to analyze the correlation between PPIB and genetic variation, immune infiltration, and cancer-associated fibroblasts (CAFs), respectively. The STRING, GEPIA2.0, and TIMER2.0 databases were used to identify the co-expressed genes of PPIB. The DAVID online database was used for GO and KEGG pathway analysis.\nResults: PPIB was highly expressed in 20 types of tumors. Upregulation of PPIB was associated with a poor prognosis of 6 types of tumors (P<0.05). In most cancers, the frequency of PPIB genetic variation is relatively low, and the common mutation types are missense mutations and splices.","PeriodicalId":93101,"journal":{"name":"Global journal of medical research","volume":"13 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global journal of medical research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34257/gjmrfvol24is1pg1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Peptidylprolyl isomerase B (PPIB) has been shown to play an essential role in tumor initiation and progression. However, it lacks systematic analysis and evaluation of the effect of PPIB on pan-cancer.
Methods: The expression profile and survival analysis of PPIB in tumor tissues were demonstrated by the TIMER2.0, GEPIA2.0, and UALCAN online tools. The cBioportal, GSCA, TISDB, and TIMER2.0 databases were applied to analyze the correlation between PPIB and genetic variation, immune infiltration, and cancer-associated fibroblasts (CAFs), respectively. The STRING, GEPIA2.0, and TIMER2.0 databases were used to identify the co-expressed genes of PPIB. The DAVID online database was used for GO and KEGG pathway analysis.
Results: PPIB was highly expressed in 20 types of tumors. Upregulation of PPIB was associated with a poor prognosis of 6 types of tumors (P<0.05). In most cancers, the frequency of PPIB genetic variation is relatively low, and the common mutation types are missense mutations and splices.