Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma
BackgroundRecent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.MethodsIn this study, we comprehensively investigated the expression, prognostic value, and immune significance of FN...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-10-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027154/full |
| _version_ | 1828341849556779008 |
|---|---|
| author | Xiao Wang Xiao Wang Yeping Huang Shanshan Li Hong Zhang |
| author_facet | Xiao Wang Xiao Wang Yeping Huang Shanshan Li Hong Zhang |
| author_sort | Xiao Wang |
| collection | DOAJ |
| description | BackgroundRecent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.MethodsIn this study, we comprehensively investigated the expression, prognostic value, and immune significance of FNDC3B in glioma using several databases and a variety of machine learning algorithms. RNA expression data and clinical information of 529 patients from the Cancer Genome Atlas (TCGA) and 1319 patients from Chinese Glioma Genome Atlas (CGGA) databases were downloaded for further investigation. To evaluate whether FNDC3B expression can predict clinical prognosis of glioma, we constructed a clinical nomogram to estimate long-term survival probabilities. The predicted nomogram was validated by CGGA cohorts. Differentially expressed genes (DEGs) were detected by the Wilcoxon test based on the TCGA-LGG dataset and the weighted gene co-expression network analysis (WGCNA) was implemented to identify the significant module associated with the expression level of FNDC3B. Furthermore, we investigated the correlation between FNDC3B with cancer immune infiltrates using TISIDB, ESTIMATE, and CIBERSORTx.ResultsHigher FNDC3B expression displayed a remarkably worse overall survival and the expression level of FNDC3B was an independent prognostic indicator for patients with glioma. Based on TCGA LGG dataset, a co-expression network was established and the hub genes were identified. FNDC3B expression was positively correlated to the tumor-infiltrating lymphocytes and immune infiltration score, and high FNDC3B expression was accompanied by the increased expression of B7-H3, PD-L1, TIM-3, PD-1, and CTLA-4. Moreover, expression of FNDC3B was significantly associated with infiltrating levels of several types of immune cells and most of their gene markers in glioma.ConclusionThis study demonstrated that FNDC3B may be involved in the occurrence and development of glioma and can be regarded as a promising prognostic and immunotherapeutic biomarker for the treatment of glioma. |
| first_indexed | 2024-04-13T23:20:20Z |
| format | Article |
| id | doaj.art-1d0110bc3c2f4477a61684de9f8fe47c |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-13T23:20:20Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-1d0110bc3c2f4477a61684de9f8fe47c2022-12-22T02:25:15ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-10-011310.3389/fimmu.2022.10271541027154Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in gliomaXiao Wang0Xiao Wang1Yeping Huang2Shanshan Li3Hong Zhang4Department of Nephrology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaShanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, ChinaShanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, ChinaShanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, ChinaShanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, ChinaBackgroundRecent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.MethodsIn this study, we comprehensively investigated the expression, prognostic value, and immune significance of FNDC3B in glioma using several databases and a variety of machine learning algorithms. RNA expression data and clinical information of 529 patients from the Cancer Genome Atlas (TCGA) and 1319 patients from Chinese Glioma Genome Atlas (CGGA) databases were downloaded for further investigation. To evaluate whether FNDC3B expression can predict clinical prognosis of glioma, we constructed a clinical nomogram to estimate long-term survival probabilities. The predicted nomogram was validated by CGGA cohorts. Differentially expressed genes (DEGs) were detected by the Wilcoxon test based on the TCGA-LGG dataset and the weighted gene co-expression network analysis (WGCNA) was implemented to identify the significant module associated with the expression level of FNDC3B. Furthermore, we investigated the correlation between FNDC3B with cancer immune infiltrates using TISIDB, ESTIMATE, and CIBERSORTx.ResultsHigher FNDC3B expression displayed a remarkably worse overall survival and the expression level of FNDC3B was an independent prognostic indicator for patients with glioma. Based on TCGA LGG dataset, a co-expression network was established and the hub genes were identified. FNDC3B expression was positively correlated to the tumor-infiltrating lymphocytes and immune infiltration score, and high FNDC3B expression was accompanied by the increased expression of B7-H3, PD-L1, TIM-3, PD-1, and CTLA-4. Moreover, expression of FNDC3B was significantly associated with infiltrating levels of several types of immune cells and most of their gene markers in glioma.ConclusionThis study demonstrated that FNDC3B may be involved in the occurrence and development of glioma and can be regarded as a promising prognostic and immunotherapeutic biomarker for the treatment of glioma.https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027154/fullFNDC3Bgliomaprognosisimmune infiltrationThe Cancer Genome Atlas (TCGA)Chinese Glioma Genome Atlas (CGGA) |
| spellingShingle | Xiao Wang Xiao Wang Yeping Huang Shanshan Li Hong Zhang Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma Frontiers in Immunology FNDC3B glioma prognosis immune infiltration The Cancer Genome Atlas (TCGA) Chinese Glioma Genome Atlas (CGGA) |
| title | Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| title_full | Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| title_fullStr | Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| title_full_unstemmed | Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| title_short | Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| title_sort | integrated machine learning methods identify fndc3b as a potential prognostic biomarker and correlated with immune infiltrates in glioma |
| topic | FNDC3B glioma prognosis immune infiltration The Cancer Genome Atlas (TCGA) Chinese Glioma Genome Atlas (CGGA) |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027154/full |
| work_keys_str_mv | AT xiaowang integratedmachinelearningmethodsidentifyfndc3basapotentialprognosticbiomarkerandcorrelatedwithimmuneinfiltratesinglioma AT xiaowang integratedmachinelearningmethodsidentifyfndc3basapotentialprognosticbiomarkerandcorrelatedwithimmuneinfiltratesinglioma AT yepinghuang integratedmachinelearningmethodsidentifyfndc3basapotentialprognosticbiomarkerandcorrelatedwithimmuneinfiltratesinglioma AT shanshanli integratedmachinelearningmethodsidentifyfndc3basapotentialprognosticbiomarkerandcorrelatedwithimmuneinfiltratesinglioma AT hongzhang integratedmachinelearningmethodsidentifyfndc3basapotentialprognosticbiomarkerandcorrelatedwithimmuneinfiltratesinglioma |