Comprehensive Analysis of Prognostic Value and Immune Infiltration of IGFBP Family Members in Glioblastoma

Zhong, Zhenglan; Xu, Xiaoping; Han, Shiguo; Shao, Yongxiang; Ye, Yi

doi:10.1155/2022/2929695

Cited by 7 publications

(6 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, we inferred that the high-risk effect of RAB6C in UVM may be related to BAP1 mutation. IGFBP4 plays an oncogenic role in glioblastoma and renal cell carcinoma ( 31 - 33 ). The oncogenic role of IGFBP4 is induced by the Wnt/beta-catenin pathway in renal cell carcinoma ( 32 ).…”

Section: Discussionmentioning

confidence: 99%

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Yu,

Guo,

et al. 2024

Transl Cancer Res

View full text Add to dashboard Cite

Background Centrosome aberration (CA) plays a vital role in tumorigenesis and metastasis under pathophysiological conditions. The existence of CA was first reported in uveal melanoma (UVM) recently. Our study aimed to investigate the association of centrosome-related genes with UVM prognosis. Methods The Cancer Genome Atlas (TCGA)-UVM and Gene Expression Omnibus series (GSE) 22138 were included in the study. Least absolute shrinkage and selection operator (LASSO) and Cox regression were combined to screen out key genes and construct a centrosome-related gene signature. Kaplan-Meier (KM) survival curves were used to evaluate the survival differences between the 2 groups. Gene enrichment, immune infiltration, and mutation profile were used to explore the underlying mechanism. Results A centrosome-related gene signature was constructed: Risk score =−3.27071 × MAP6 − 5.03735 × CCDC40 − 2.68459 × PRKCD + 1.826349 × IGFBP4 + 11.66582 × RAB6C − 4.86899 × CCND3. The survival possibilities of the two groups were significantly different. The high-risk group showed cancer progression, inflammation, and immune restriction characteristics when compared with the low-risk group. BAP1 mutation was associated with high risk and SF3B1 mutation was associated with low risk according to the signature. Conclusions Our study first investigated the role of centrosome-related genes in UVM overall survival (OS). We then constructed a centrosome-related gene signature for UVM, which provides new insights into the role of CA in UVM and identifies novel centrosome-related biomarkers.

show abstract

Section: Discussionmentioning

confidence: 99%

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Yu,

Guo,

et al. 2024

Transl Cancer Res

View full text Add to dashboard Cite

show abstract

“…The six prognostic genes directly and indirectly participated in the immune response in numerous tumors, for instance, LGALS2 in triple-negative breast cancer ( 37 ), LAMP3 + dendritic cells in nasopharyngeal carcinomas ( 38 ), ICOS in the generation of Tregs in follicular lymphoma ( 35 ), FCAMR in lung squamous cell carcinoma ( 39 ), IGFBP4 in ewing’s sarcoma ( 40 ), C1QA in skin cutaneous melanoma ( 41 ). A previous study has suggested that IGFBP4 is associated with poor outcomes in glioblastoma ( 42 ). Interestingly, in diffuse large B cell lymphoma (DLBCL) patients, the C1qA [276] polymorphism of the A/A allele is an independent favorable prognostic factor for rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) as first-line therapy ( 43 ), while the expression level of LGALS2 was not associated with OS but was lower in tumors than in normal samples ( 44 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of immune-related genes and development of a prognostic model in mantle cell lymphoma

Zhang¹,

Shi²,

Wang³

et al. 2022

Ann Transl Med

View full text Add to dashboard Cite

Background: The immune landscape, prognostic model, and molecular variations of mantle cell lymphoma (MCL) remain unclear. Hence, an integrated bioinformatics analysis of MCL datasets is required for the development of immunotherapy and the optimization of targeted therapies.Methods: Data were obtained from the Gene Expression Omnibus (GEO) database (GSE32018, GSE45717 and GSE93291). The differentially expressed immune-related genes were selected, and the hub genes were screened by three machine learning algorithms, followed by enrichment and correlation analyses. Next, MCL molecular clusters based on the hub genes were identified by K-Means clustering, the probably approximately correct (PAC) algorithm, and principal component analysis (PCA). The landscape of immune cell infiltration and immune checkpoint molecules in distinct clusters was explored by single-sample gene-set enrichment analysis (ssGSEA) as well as the CIBERSORT and xCell algorithms. The prognostic genes and prognostic risk score model for MCL clusters were identified by least absolute shrinkage and selection operator (LASSO)-Cox analysis and cross-validation for lambda. Correlation analysis was performed to explore the correlation between the screened prognostic genes and immune cells or immune checkpoint molecules.Results: Four immune-related hub genes (CD247, CD3E, CD4, and GATA3) were screened in MCL, mainly enriched in the T-cell receptor signaling pathway. Based on the hub genes, two MCL molecular clusters were recognized. The cluster 2 group had a significantly worse overall survival (OS), with downregulated hub genes, and a variety of activated immune effector cells declined. The majority of immune checkpoint molecules had also decreased. An efficient prognostic model was established, including six prognostic genes (LGALS2, LAMP3, ICOS, FCAMR, IGFBP4, and C1QA) differentially expressed between two MCL clusters. Patients with a higher risk score in the prognostic model had a poor prognosis.Furthermore, most types of immune cells and a range of immune checkpoint molecules were positively correlated with the prognostic genes.Conclusions: Our study identified distinct molecular clusters based on the immune-related hub genes, and showed that the prognostic model affected the prognosis of MCL patients. These hub genes, modulated immune cells, and immune checkpoint molecules might be involved in oncogenesis and could be potential prognostic biomarkers in MCL.

show abstract

“…The IGF-dependent pathways for IGFBP-3:The binding of IGFBP-3 to IGF leads to the opening of the corresponding signaling pathway, which has been con rmed to be involved in the progression of glioma [19] ,Elevated serum IGF-1 is regarded as one of the recognized diagnostic markers of different tumors, especially brain malignant tumors.Ye Yun et al [20] detected the changes of IGF-1 and IGFBP-3 in normal brain tissue and glioma tissue by immunohistochemical staining,and were positively correlated with the pathological grade of glioma, suggesting that IGFBP-3 may be Enhanced the pro-tumor proliferative effect of IGF-1.…”

Section: The Pathway Of Action Of Igfbp-3 In Brain Tumormentioning

confidence: 99%

“…IGFBP-3 and Immune Cells:In the glioma microenvironment, immune cells activate corresponding signaling pathways to stimulate the expression of certain cytokines [25] .Scully et al [26] found that high expression of IGFBP-3 in tumor cell interstitium was positively correlated with tumor proliferation under high-fat environment;At the same time, increased CD8 was detected by immunohistochemistry, indicating that knockdown of IGFBP-3 caused CD8+T cell aggregation, which disappeared when knockdown of IGFBP-3 mice were fed a high-fat diet.This indicates that the presence of IGFBP-3 and high-fat environment will limit the anti-tumor proliferation effect of CD8+T and other immune cells.Wolf et al [27] found that the impaired immune function caused by severe burns leads to a weakened Th1 cell response and an increased Th2 cell response;Although there are still limited reports on IGFBP-3 and immune cells in brain tumors, this brings some enlightenment to study the relationship between IGFBP-3 and immune cells in brain tumors.…”

Section: The Relationship Between Igfbp-3 and The Brain Tumor Microen...mentioning

confidence: 99%

Bioinformatics analysis of IGFBP-3 and research advances in brain tumors Running title：Protein structure and biological function

Fan

Aili

et al. 2022

Preprint

View full text Add to dashboard Cite

OBJECTIVE：Bioinformatics analysis of human insulin-like growth factor-binding protein-3 (IGFBP-3) molecules and genes, and review of the pathways and regulatory mechanisms of IGFBP-3 in brain tumors ( especially gliomas ) . METHODS：Analysis of IGFBP-3 protein open reading frame（ORF）and physicochemical properties, secondary structure, tertiary structure, signal peptide and nuclear localization signal, transmembrane structure, domain, phosphorylation and glycosylation of IGFBP-3 protein using molecular biology tools Sites, proteins and biological functions that interact with IGFBP-3 proteins. RESULTS：The molecular formula of IGFBP-3 protein is C1390H2230N418O422S21. 104 ORFs were found in the mRNA sequence of IGFBP-3. The longest ORF is ORF2, which is 519 bp in total and can encode 172 amino acids.It is an unstable hydrophilic secreted protein, the secondary structure is mainly ring structure and helical structure, containing 67 phosphorylation sites and 3 N-glycosylation sites, no transmembrane region, 3 main domains, Having nuclear localization signals exerts biological effects in the nucleus. IGFBP-3 can participate in biological functions such as apoptosis, negative regulation of cell proliferation, negative regulation of signal transduction, and regulation of insulin-like growth factor receptor signaling pathway. CONCLUSIONS：The predicted results provide a basis for further research on the structure and biological function of IGFBP-3 gene and its encoded protein.

show abstract

Comprehensive Analysis of Prognostic Value and Immune Infiltration of IGFBP Family Members in Glioblastoma

Cited by 7 publications

References 58 publications

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

A centrosome-related gene signature for predicting the overall survival of uveal melanoma

Identification of immune-related genes and development of a prognostic model in mantle cell lymphoma

Bioinformatics analysis of IGFBP-3 and research advances in brain tumors Running title：Protein structure and biological function

Contact Info

Product

Resources

About