Dataset Information

Comprehensive analysis to identify the relationship between CALD1 and immune infiltration in glioma.

ABSTRACT:

Background

An accumulating number of studies show that CALD1 is associated with a variety of tumor microenvironments (TME) and is closely related to patients' survival. However, to the best of our knowledge, few studies examined the role of CALD1 in the immune microenvironment of glioma. The aim of this study is to investigate the potential correlation between CALD1 and the pathogenesis and progression of glioma, aiming to identify a novel therapeutic target.

Methods

We assessed the role of CALD1 in pan-cancer and investigated the correlation between CALD1 and TME of glioma by bioinformatic analysis and experimental verification.

Results

We found that CALD1 expression in glioma was associated with a variety of infiltrating immune cells. CALD1 can promote the development of glioma by affecting M2 macrophage infiltration. Also, we found that CALD1 was closely associated with tumor mutation burden, microsatellite instability, copy number variation, methylation, and stem cell index. Our clinical correlation study demonstrated that CALD1 was associated with overall survival, progression-free interval, and disease-specific survival in a variety of tumors. We verified the significantly high expression of CALD1 in glioma using quantitative real-time polymerase chain reaction (PCR) and Western blotting. Meanwhile, we also conducted relevant cell experiments to prove that CALD1 can affect the proliferation and migration ability of glioma cells in vitro.

Conclusions

Our results confirmed that CALD1 may be a prognostic marker for glioma and a potential target for immunotherapy in the future.

SUBMITTER: Xia J

PROVIDER: S-EPMC11319977 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Publications

Comprehensive analysis to identify the relationship between CALD1 and immune infiltration in glioma.

Xia Jing J Yang Qiuan Q Wang Chengwei C Sun Zhenwei Z

Translational cancer research 20240726 7

<h4>Background</h4>An accumulating number of studies show that CALD1 is associated with a variety of tumor microenvironments (TME) and is closely related to patients' survival. However, to the best of our knowledge, few studies examined the role of CALD1 in the immune microenvironment of glioma. The aim of this study is to investigate the potential correlation between CALD1 and the pathogenesis and progression of glioma, aiming to identify a novel therapeutic target.<h4>Methods</h4>We assessed t ...[more]

PMID: 39145081

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Project description:Immune dysfunction has been implicated in the pathogenesis of schizophrenia (SZ). Despite previous studies showing a broad link between immune dysregulation and the central nervous system of SZ, the exact relationship has not been completely elucidated. With immune infiltration analysis as an entry point, this study aimed to explore the relationship between schizophrenia and the immune system in more detail from brain regions, immune cells, genes, and pathways. Here, we comprehensively analyzed the hippocampus (HPC), prefrontal cortex (PFC), and striatum (STR) between SZ and control groups. Differentially expressed genes (DEGs) and functional enrichment analysis showed that three brain regions were closely related to the immune system. Compared with PFC and STR, there were 20 immune-related genes (IRGs) and 42 immune pathways in HPC. The results of immune infiltration analysis showed that the differential immune cells in HPC were effector memory T (Tem) cells. The correlation of immune-related DEGs (IDEGs) and immune cells further analysis showed that NPY, BLNK, OXTR, and FGF12, were moderately correlated with Tem cells. Functional pathway analysis indicated that these four genes might affect Tem by regulating the PI3K-AKT pathway and the neuroactive ligand-receptor interaction pathway. The receiver operating characteristic curve (ROC) analysis results indicated that these four genes had a high diagnostic ability (AUC=95.19%). Finally, the disease animal model was successfully replicated, and further validation was conducted using the real-time PCR and the western blot. These results showed that these gene expression changes were consistent with our previous expression profiling. In conclusion, our findings suggested that HPC in SZ may be more closely related to immune disorders and modulate immune function through Tem, PI3K-Akt pathway, and neuroactive ligand-binding receptor interactions. To the best of our knowledge, the Immucell AI tool has been applied for the first time to analyze immune infiltration in SZ, contributing to a better understanding of the role of immune dysfunction in SZ from a new perspective.

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Project description:Oxidative stress refers to the process of reactive oxide species (ROS) increase in human body due to various factors, which leads to oxidative damage in human tissues. Current studies have confirmed that sustained oxidative stress is one of the distinctive features throughout the development of tumors. Numerous reports have shown that lncRNAs can regulate the process of oxidative stress through multiple pathways. However, the relationship between glioma-associated oxidative stress and lncRNAs is not clearly investigated. RNA sequencing data of GBM (glioblastoma) and LGG (low grade glioma) and corresponding clinical data were retrieved from the TCGA database. Oxidative stress related lncRNAs (ORLs) were identified by Pearson correlation analysis. Prognostic models for 6-ORLs were structured in the training cohort by univariate Cox regression analysis, multivariate Cox regression analysis and LASSO regression analysis. We constructed the nomogram and verified its predictive efficacy by Calibration curves and DCA decision curves. The biological functions and pathways of 6-ORLs-related mRNAs were inferred by Gene Set Enrichment Analysis. Immune cell abundance and immune function associated with risk score (RS) were estimated by ssGSEA, CIBERSORT and MCPcounter synthetically. External validation of the signature was completed using the CGGA-325 and CGGA-693 datasets. 6-ORLs signature-AC083864.2, AC107294.1, AL035446.1, CRNDE, LINC02600, and SNAI3-AS1-were identified through our analysis as being predictive of glioma prognosis. Kaplan-Meier and ROC curves indicated that the signature has a dependable predictive efficacy in the TCGA training cohort, validation cohort and CGGA-325/CGGA-693 test cohort. The 6-ORLs signature were verified to be independent prognostic predictors by multivariate cox regression and stratified survival analysis. Nomogram built with risk scores had strong predictive efficacy for patients' overall survival (OS). The outcomes of the functional enrichment analysis revealing potential molecular regulatory mechanisms for the 6-ORLs. Patients in the high-risk subgroup presented a significant immune microenvironment of macrophage M0 and cancer-associated fibroblast infiltration which was associated with a poorer prognosis. Finally, the expression levels of 6-ORLs in U87/U251/T98/U138 and HA1800 cell lines were verified by RT-qPCR. The nomogram in this study has been made available as a web version for clinicians. This 6-ORLs risk signature has the capabilities to predict the prognosis of glioma patients, assist in evaluating immune infiltration, and assess the efficacy of various anti-tumor systemic therapy regimens.

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Project description:BackgroundTumor microenvironment (TME) is closely related to the progression of glioma and the therapeutic effect of drugs on this cancer. The aim of this study was to develop a signature associated with the tumor immune microenvironment using machine learning.MethodsWe downloaded the transcriptomic and clinical data of glioma patients from the Chinese Glioma Genome Atlas (CGGA) databases (mRNAseq_693). The single-sample Gene Set Enrichment Analysis (ssGSEA) database was used to quantify the relative abundance of immune cells. We divided patients into two different infiltration groups via unsupervised clustering analysis of immune cells and then selected differentially expressed genes (DEGs) between the two groups. Survival-related genes were determined using Cox regression analysis. We next randomly divided patients into a training set and a testing set at a ratio of 7 : 3. By integrating the DEGs into least absolute shrinkage and selection operator (LASSO) regression analysis in the training set, we were able to construct a 15-gene signature, which was validated in the testing and total sets. We further validated the signature in the mRNAseq_325 dataset of CGGA.ResultsWe identified 74 DEGs associated with tumor immune infiltration, 70 of which were significantly associated with overall survival (OS). An immune-related gene signature was established, consisting of 15 key genes: adenosine triphosphate (ATP)-binding cassette subfamily C member 3 (ABCC3), collagen type IV alpha 1 chain (COL4A1), podoplanin (PDPN), annexin A1 (ANXA1), COL4A2, insulin-like growth factor binding protein 2 (IGFBP2), serpin family A member 3 (SERPINA3), CXXC-type zinc finger protein 11 (CXXC11), junctophilin 3 (JPH3), secretogranin III (SCG3), secreted protein acidic and rich in cysteine (SPARC)-related modular calcium-binding protein 1 (SMOC1), Cluster of Differentiation 14 (CD14), COL1A1, S100 calcium-binding protein A4 (S100A4), and transforming growth factor beta 1 (TGF-β1). The OS of patients in the high-risk group was worse than that of patients in the low-risk group. GSEA showed that interleukin-6 (IL-6)/Janus kinase (JAK)/signal transducer and activator of transcription (STAT3) signaling, interferon gamma (IFN-γ) response, angiogenesis, and coagulation were more highly enriched in the high-risk group and that oxidative phosphorylation was more highly enriched in the low-risk group.ConclusionWe constructed a stable gene signature associated with immune infiltration to predict the survival rates of glioma patients.

Dataset Information

Comprehensive analysis to identify the relationship between CALD1 and immune infiltration in glioma.

Background

Methods

Results

Conclusions

Publications

Comprehensive analysis to identify the relationship between CALD1 and immune infiltration in glioma.

Similar Datasets

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