PPIB Unveiled: A Comprehensive Pan-Cancer Exploration Unraveling Immunological Signatures and Prognostic Implications

Article ID

2R9X9

Unraveling Immuno Signatures in Diseases.

PPIB Unveiled: A Comprehensive Pan-Cancer Exploration Unraveling Immunological Signatures and Prognostic Implications

Yan Ouyang
Yan Ouyang Sun Yat-Sen University,
Qi Dai
Qi Dai
Shengming Lai
Shengming Lai
Haiyan Huang
Haiyan Huang
Yongsheng Huang
Yongsheng Huang
Shuwei Ren
Shuwei Ren
DOI

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

PPIB Unveiled: A Comprehensive Pan-Cancer Exploration Unraveling Immunological Signatures and Prognostic Implications

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.

Yan Ouyang
Yan Ouyang Sun Yat-Sen University,
Qi Dai
Qi Dai
Shengming Lai
Shengming Lai
Haiyan Huang
Haiyan Huang
Yongsheng Huang
Yongsheng Huang
Shuwei Ren
Shuwei Ren

No Figures found in article.

Yan Ouyang. 2026. “. Global Journal of Medical Research – F: Diseases GJMR-F Volume 24 (GJMR Volume 24 Issue F1): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjmra

Print ISSN 0975-5888

e-ISSN 2249-4618

Classification
Not Found
Keywords
Article Matrices
Total Views: 988
Total Downloads: 22
2026 Trends
Research Identity (RIN)
Related Research
Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

PPIB Unveiled: A Comprehensive Pan-Cancer Exploration Unraveling Immunological Signatures and Prognostic Implications

Yan Ouyang
Yan Ouyang Sun Yat-Sen University,
Qi Dai
Qi Dai
Shengming Lai
Shengming Lai
Haiyan Huang
Haiyan Huang
Yongsheng Huang
Yongsheng Huang
Shuwei Ren
Shuwei Ren

Research Journals