scholarly journals GPX7 is Identified as a Novel Prognostic Indicator for Brain Lower Grade Glioma (LGG): Evidence from a Pan-Cancer Analysis

2021 ◽  
Author(s):  
Qianqian Zhao ◽  
Yin Yang ◽  
Luyu Zhang ◽  
Yingying Wang ◽  
Tianpei Wang ◽  
...  
Keyword(s):  
Glutathione Peroxidase ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Prognostic Indicator ◽  
Lower Grade ◽  
Free Survival ◽  
Multiple Tumors ◽  
Expression Levels ◽  
Lower Grade Glioma ◽  
Pan Cancer

Abstract Background: Glutathione peroxidase-7 (GPX7), a newly discovered non-selenium-containing protein with glutathione peroxidase activity, is located near the endoplasmic reticulum. Various studies have reported the involvement of GPX7 in cancer disease progression. However, the expression patterns of GPX7 and its prognostic potential have not been evaluated from a pan-cancer perspective. Moreover, the relationship between GPX7 and prognosis in Brain Lower Grade Glioma (LGG) patients remains unclear.Methods: Expression levels of GPX7 were evaluated using the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA2) were used to evaluate the effect of GPX7 on clinical prognosis in TCGA tumors. Correlations between GPX7 and cancer immune infiltrates were investigated using the Tumor Immune Estimation Resource (TIMER) site and Estimating the Proportions of Immune and Cancer cells (EPIC) algorithm. In addition, the GEPIA2 and STRING websites were used for enrichment analysis of GPX7-related genes. Finally, we constructed a prognostic Nomogram for LGG to verify the overall survival (OS) outcomes of patients.Results: GPX7 was found to be overexpressed in multiple tumors. Elevated expression levels of GPX7 were associated with poor prognosis regarding OS, disease-free survival (DFS) and progression-free survival (PFS) of LGG patients (OS Hazard ratio (HR) = 1.044, p < 0.0001; DFS HR = 1.035, p < 0.0001; PFS HR = 1.045, p < 0.0001). Concordance index (C-index) of the nomogram for LGG was 0.845 (95% CI, 0.825 to 0.865; p < 0.001). The nomogram exhibited a better predictability. In addition, GPX7 expression and the abundance of Cancer-associated fibroblasts (CAFs) were positively correlated in most cancer types. Enrichment analysis revealed that GPX7 may be involved in the glutathione derivative biosynthetic and glutathione metabolic biological processes.Conclusion: GPX7 was found to be upregulated in multiple tumors, which was correlated with poor prognosis in LGG. Therefore, GPX7 is a potential prognostic indicator for LGG. There is a strong correlation between GPX7 expression levels and glutathione metabolic pathways. GPX7 holds promise for the use of glutathione metabolism for guided therapy in cancer patients.

scholarly journals High KIFC1 expression is associated with poor prognosis in prostate cancer

2021 ◽  
Vol 38 (5) ◽  
Author(s):  
Laurie G. Kostecka ◽  
Athen Olseen ◽  
KiChang Kang ◽  
Gonzalo Torga ◽  
Kenneth J. Pienta ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Poor Prognosis ◽  
Prognostic Indicator ◽  
Tumor Stage ◽  
Ploidy Levels ◽  
Free Survival ◽  
Metastatic Lesions ◽  
High Tumor Stage ◽  
High Ploidy ◽  
Kinesin Family

AbstractKinesins play important roles in the progression and development of cancer. Kinesin family member C1 (KIFC1), a minus end-directed motor protein, is a novel Kinesin involved in the clustering of excess centrosomes found in cancer cells. Recently KIFC1 has shown to play a role in the progression of many different cancers, however, the involvement of KIFC1 in the progression of prostate cancer (PCa) is still not well understood. This study investigated the expression and clinical significance of KIFC1 in PCa by utilizing multiple publicly available datasets to analyze KIFC1 expression in patient samples. High KIFC1 expression was found to be associated with high Gleason score, high tumor stage, metastatic lesions, high ploidy levels, and lower recurrence-free survival. These results reveal that high KIFC1 levels are associated with a poor prognosis for PCa patients and could act as a prognostic indicator for PCa patients as well.

scholarly journals Integrated Analysis Reveals Prognostic Value and Immune Correlates of CD86 Expression in Lower Grade Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Huaide Qiu ◽  
Wei Tian ◽  
Yikang He ◽  
Jiahui Li ◽  
Chuan He ◽  
...  
Keyword(s):  
Immune Response ◽  
Overall Survival ◽  
Prognostic Factor ◽  
Prognostic Value ◽  
Integrated Analysis ◽  
Lower Grade ◽  
Qrt Pcr ◽  
Lower Grade Glioma ◽  
Pan Cancer ◽  
Genome Atlas

BackgroundCD86 has great potential to be a new target of immunotherapy by regulating cancer immune response. However, it remains unclear whether CD86 is a friend or foe in lower-grade glioma (LGG).MethodsThe prognostic value of CD86 expression in pan-cancer was analyzed using Cox regression and Kaplan-Meier analysis with data from the cancer genome atlas (TCGA). Cancer types where CD86 showed prognostic value in overall survival and disease-specific survival were identified for further analyses. The Chinese Glioma Genome Atlas (CGGA) dataset were utilized for external validation. Quantitative real-time PCR (qRT-PCR), Western blot (WB), and Immunohistochemistry (IHC) were conducted for further validation using surgical samples from Jiangsu Province hospital. The correlations between CD86 expression and tumor immunity were analyzed using the Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm, Tumor IMmune Estimation Resource (TIMER) database, and expressions of immune checkpoint molecules. Gene Set Enrichment Analysis (GSEA) was performed using clusterprofiler r package to reveal potential pathways.ResultsPan-cancer survival analysis established CD86 expression as an unfavorable prognostic factor in tumor progression and survival for LGG. CD86 expression between Grade-II and Grade-III LGG was validated using qRT-PCR and WB. Additionally, CD86 expression in LGG with unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter was significantly higher than those with methylated MGMT (P&lt;0.05), while in LGG with codeletion of 1p/19q it was significantly downregulated as opposed to those with non-codeletion (P&lt;2.2*10-16). IHC staining validated that CD86 expression was correlated with MGMT status and X1p/19q subtypes, which was independent of tumor grade. Multivariate regression validated that CD86 expression acts as an unfavorable prognostic factor independent of clinicopathological factors in overall survival of LGG patients. Analysis of tumor immunity and GSEA revealed pivotal role of CD86 in immune response for LGG.ConclusionsIntegrated analysis shows that CD86 is an unfavorable prognostic biomarker in LGG patients. Targeting CD86 may become a novel approach for immunotherapy of LGG.

scholarly journals T-Cell Exhaustion Status Under High and Low Levels of Hypoxia-Inducible Factor 1α Expression in Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuai Liu ◽  
Xing Liu ◽  
Chuanbao Zhang ◽  
Wei Shan ◽  
Xiaoguang Qiu
Keyword(s):  
T Cells ◽  
T Cell ◽  
Immune Cells ◽  
Hypoxia Inducible Factor ◽  
Lower Grade ◽  
T Cell Exhaustion ◽  
Expression Levels ◽  
Cell Exhaustion ◽  
Lower Grade Glioma ◽  
Genome Atlas

Background: Hypoxia-inducible factor 1α (HIF1A), the principal regulator of hypoxia, is involved in the suppression of antitumor immunity. We aimed to describe the T-cell exhaustion status of gliomas under different levels of HIF1A expression.Methods: In this study, 692 patients, whose data were collected from the Chinese Glioma Genome Atlas (CGGA) database, and 669 patients, whose data were collected from The Cancer Genome Atlas database, were enrolled. We further screened the data of a cohort of paired primary and recurrent patients from the CGGA dataset (n = 50). The abundance of immune cells was calculated using the transcriptome data. The association between HIF1A and T-cell exhaustion-related genes and immune cells was investigated.Results: According to the median value of HIF1A expression, gliomas were classified into low-HIF1A-expression and high-HIF1A-expression groups. The expression levels of PDL1 (CD274), FOXO1, and PRDM1 in the high-HIF1A-expression group were significantly higher in both glioblastoma (GBM) and lower-grade glioma. The abundance of exhausted T cells and B cells was significantly higher in the high-HIF1A-expression group, while that of macrophage, monocyte, and natural killer cell was significantly higher in the low-HIF1A-expression group in both GBM and lower-grade glioma. After tumor recurrence, the expression of HIF1A significantly increased, and the correlation between HIF1A expression levels and exhausted T cells and induced regulatory T cells became stronger.Conclusion: In diffuse gliomas, the levels of T-cell exhaustion-associated genes and the abundance of immune cells were elevated under high HIF1A expression. Reversing hypoxia may improve the efficacy of immunotherapy.

Development and validation of an immune-related gene pairs signature in lower-grade glioma

2020 ◽  
Author(s):  
Xu Zhang ◽  
Shuai Ping ◽  
Rui Zhang ◽  
Can Li ◽  
Caibin Gao ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Related Gene ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Immune Related Gene ◽  
Lower Grade Glioma ◽  
Functional Pathways ◽  
Genome Atlas

Abstract Background Lower-grade gliomas (LGG) are the prevalent primary intracerebral malignancy tumor. Increasing evidence indicated an association between immune signature and LGG prognosis. Thus, we aim to develop an immune-related gene pairs (IRGPs) signature that can predict prognosis for LGG. Method: Gene expression levels and clinical information of LGG patients (LGGs) were collected from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. The two databases were divided into training cohort (n = 515) and an independent validation cohort (n = 604). IGRPs significantly associated with prognosis were selected by Cox regression. Gene set enrichment analysis and filtration were performed on IGRPs. Results Within 1991 immune genes, an 8 IRGPs signature including 15 unique genes was constructed, which had a significant association with survival. In the validation dataset, the IRGPs signature significantly stratified LGGs into low- and high-risk groups (P < 0.001), and it remained an independent prognostic factor in univariate and multivariate analyses (P < 0.001). Additionally, 26 functional pathways were filtrated through the intersection of Gene set enrichment analysis (GSEA) and gene ontology (GO) enrichment analysis. Conclusion The IGRPs signature demonstrated good prognostic value in lower-grade glioma, which may provide new insights into individual treatment for glioma patients. And the IGRPs might take effect through these filtrated 26 functional pathways.

scholarly journals Identification and Verification on Prognostic Index of Lower-Grade Glioma Immune-Related LncRNAs

2020 ◽  
Vol 10 ◽  
Author(s):  
Jing Wen ◽  
Youjun Wang ◽  
Lili Luo ◽  
Lu Peng ◽  
Caixia Chen ◽  
...  
Keyword(s):  
Risk Score ◽  
Immune Cells ◽  
Risk Group ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Validation Data ◽  
Lower Grade Glioma ◽  
Immune Group

Previous studies have shown that the prognosis of patients with lower-grade glioma (LGG) is closely related to the infiltration of immune cells and the expression of long non-coding RNAs (lncRNAs). In this paper, we applied single-sample gene set enrichment analysis (ssGSEA) algorithm to evaluate the expression level of immune genes from tumor tissues in The Cancer Genome Atlas (TCGA) database, and divided patients into the high immune group and the low immune group, which were separately analyzed for differential expression. Venn analysis was taken to select 36 immune-related lncRNAs. To construct a prognostic model of LGG based on immune-related lncRNAs, we divided patients into a training set and a verification set at a ratio of 2:1. Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to select 11 immune-related lncRNAs associated with the prognosis of LGG, and based on these selected lncRNAs, the risk scoring model was constructed. Through Kaplan-Meier analysis, the overall survival (OS) of patients in the high-risk group was significantly lower than that of the low-risk group. Then, established a nomogram including age, gender, neoplasm histologic grade, and risk score. Meanwhile, the predictive performance of the model was evaluated by calculating the C-index, drawing the calibration chart, the clinical decision curve as well as the Receiver Operating Characteristic (ROC) curve. Similar results were obtained by utilizing the validation data to verify the above consequences. Based on the TIMER database, the correlation analysis showed that the 11 immune-related lncRNAs risk score of LGG were in connection with the infiltration of the subtypes of immune cells. Subsequently, we performed enrichment analysis, whose results showed that these immune-related lncRNAs played important roles in the progress of LGG. In conclusion, these 11 immune-related lncRNAs have the potential to predict the prognosis of patients with LGG, which may play a key role in the development of LGG.

scholarly journals A pan-cancer perspective analysis reveals the opposite prognostic significance of CD133 in lower grade glioma and papillary renal cell carcinoma

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110109
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Ji Zhang ◽  
Hua Cao
Keyword(s):  
Prognostic Factor ◽  
Prognostic Significance ◽  
Papillary Renal Cell Carcinoma ◽  
High Expression ◽  
Lower Grade ◽  
Cd133 Expression ◽  
The Poor ◽  
Lower Grade Glioma ◽  
Pan Cancer ◽  
Perspective Analysis

CD133 is a valuable prognostic marker in multiple types of cancer. However, the expression, methylation levels, and prognostic relevance of CD133 have not been evaluated in a pan-cancer perspective. The expression and methylation levels of CD133 across different types of cancer were determined using The Cancer Genome Atlas (TCGA) dataset. Univariate cox regression and Kaplan-Meier survival were used to determine the prognostic significance of CD133 expression and methylation. CD133 was highly expressed in papillary renal cell carcinoma (PRCC) or pancreatic adenocarcinoma (PAAD). Correspondingly, PAAD and PRCC had low CD133 methylation levels. Through pan-cancer perspective analysis, we found that CD133 high expression was a poor prognostic factor in lower grade glioma (LGG), while, CD133 high expression was a good prognostic factor in PRCC. Moreover, genes positively correlated with CD133 expression were associated with the poor clinical outcomes of LGG. In PRCC, genes negatively correlated with CD133 expression were correlated with the poor overall survival. Furthermore, CD133 expression levels were highly correlated with the CD133 methylation levels in LGG or PRCC. Correspondingly, CD133 hypermethylation was a good prognostic factor in LGG. On the contrary, CD133 hypomethylation was a good prognostic factor in PRCC. We also found that CD133 was highly expressed and hypomethylated in wild type IDH subgroup of LGG. CD133 was highly expressed and hypomethylated in low stages and type1 of PRCC. CD133 high expression and hypomethylation were bad prognostic factors in LGG, while, CD133 high expression and hypomethylation were good prognostic factors in PRCC.

scholarly journals Decreased Expression of ACADSB Predicts Poor Prognosis in Clear Cell Renal Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Xianhui Liu ◽  
Weiyu Zhang ◽  
Huanrui Wang ◽  
Lin Zhu ◽  
Kexin Xu
Keyword(s):  
Poor Prognosis ◽  
Clear Cell ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Clinicopathological Parameters ◽  
Pathway Enrichment ◽  
Gene Sets ◽  
Branched Chain ◽  
Spearman’S Correlation ◽  
Pan Cancer

BackgroundPrevious reports have shown that short/branched chain acyl-CoA dehydrogenase (ACADSB) plays an important role in glioma, but its role in clear cell renal carcinoma (ccRCC) has not been reported.MethodsThe TIMER and UALCAN databases were used for pan-cancer analysis. RNA sequencing and microarray data of patients with ccRCC were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus database. The differential expression of ACADSB in ccRCC and normal kidney tissues was tested. Correlations between ACADSB expression and clinicopathological parameters were assessed using the Wilcoxon test. The influences of ACADSB expression and clinicopathological parameters on overall survival were assessed using Cox proportional hazards models. Gene set enrichment analysis (GSEA) was performed to explore the associated gene sets enriched in different ACADSB expression phenotypes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on genes with similar expression patterns to ACADSB. Correlations between ACADSB and ferroptosis-related genes were assessed using Spearman’s correlation analysis.ResultsPan-cancer analysis revealed that ACADSB is down-regulated in multiple cancers, and decreased expression of ACADSB correlates with poor prognosis in certain types of cancer. Differential expression analyses revealed that ACADSB was down-regulated in ccRCC, indicating that ACADSB expression could be a single significant parameter to discriminate between normal and tumor tissues. Clinical association analysis indicated that decreased ACADSB expression was associated with high tumor stage and grade. The Cox regression model indicated that low ACADSB expression was an independent risk factor for the overall survival of patients with ccRCC. GSEA showed that 10 gene sets, including fatty acid (FA) metabolism, were differentially enriched in the ACADSB high expression phenotype. GO and KEGG pathway enrichment analysis revealed that ACADSB-related genes were significantly enriched in categories related to FA metabolism, branched-chain amino acid (BCAA) metabolism, and iron regulation. Spearman’s correlation analysis suggested that the expression of ACADSB was positively correlated with the expression of ferroptosis driver genes.ConclusionsACADSB showed good diagnostic and prognostic abilities for ccRCC. The downregulation of ACADSB might promote tumorigenesis and tumor progression by inhibiting FA catabolism, BCAA catabolism, and ferroptosis in ccRCC.

scholarly journals Comprehensive Pan-Cancer Analysis and the Regulatory Mechanism of ASF1B, a Gene Associated With Thyroid Cancer Prognosis in the Tumor Micro-Environment

2021 ◽  
Vol 11 ◽  
Author(s):  
Jing Ma ◽  
Wei Han ◽  
Kai Lu
Keyword(s):  
Gene Expression ◽  
Survival Analysis ◽  
Thyroid Cancer ◽  
Prognostic Marker ◽  
Enrichment Analysis ◽  
Differential Analysis ◽  
Expression Levels ◽  
Multiple Cancers ◽  
Mtorc1 Signaling ◽  
Pan Cancer

BackgroundThe incidence of thyroid cancer, whose local recurrence and metastasis lead to death, has always been high and the pathogenesis of papillary thyroid carcinoma (PTC) has not been clearly elucidated. Therefore, the research for more accurate prognosis-related predictive biomarkers is imminent, and a key gene can often be a prognostic marker for multiple tumors.MethodsGene expression profiles of various cancers in the TCGA and GTEx databases were downloaded, and genes significantly associated with the prognosis of THCA were identified by combining differential analysis with survival analysis. Then, a series of bioinformatics tools and methods were used to analyze the expression of the gene in each cancer and the correlation of each expression with prognosis, tumor immune microenvironment, immune neoantigens, immune checkpoints, DNA repair genes, and methyltransferases respectively. The possible biological mechanisms were also investigated by GSEA enrichment analysis.Results656 differentially expressed genes were identified from two datasets and 960 DEGs that were associated with disease-free survival in THCA patients were screened via survival analysis. The former and the latter were crossed to obtain 7 key genes, and the gene with the highest risk factor, ASF1B, was selected for this study. Differential analysis of multiple databases showed that ASF1B was commonly and highly expressed in pan-cancer. Survival analysis showed that high ASF1B expression was significantly associated with poor patient prognosis in multiple cancers. In addition, ASF1B expression levels were found to be associated with tumor immune infiltration in THCA, KIRC, LGG, and LIHC, and with tumor microenvironment in BRCA, LUSC, STAD, UCEC, and KIRC. Further analysis of the relationship between ASF1B expression and immune checker gene expression suggested that ASF1B may regulate tumor immune patterns in most tumors by regulating the expression levels of specific immune checker genes. Finally, GSEA enrichment analysis showed that ASF1B high expression was mainly enriched in cell cycle, MTORC1 signaling system, E2F targets, and G2M checkpoints pathways.ConclusionsASF1B may be an independent prognostic marker for predicting the prognosis of THCA patients. The pan-cancer analysis suggested that ASF1B may play an important role in the tumor micro-environment and tumor immunity and it has the potential of serving as a predictive biomarker for multiple cancers.

scholarly journals Integrative Analysis of a Novel Eleven-Small Nucleolar RNA Prognostic Signature in Patients With Lower Grade Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Teng Deng ◽  
Yizhen Gong ◽  
Xiwen Liao ◽  
Xiangkun Wang ◽  
Xin Zhou ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Comprehensive Analysis ◽  
Integrative Analysis ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Rna Seq ◽  
Prognostic Signature ◽  
Immune Microenvironment ◽  
Immune Infiltration ◽  
Lower Grade Glioma

ObjectiveThe present study used the RNA sequencing (RNA-seq) dataset to identify prognostic snoRNAs and construct a prognostic signature of The Cancer Genome Atla (TCGA) lower grade glioma (LGG) cohort, and comprehensive analysis of this signature.MethodsRNA-seq dataset of 488 patients from TCGA LGG cohort were included in this study. Comprehensive analysis including function enrichment, gene set enrichment analysis (GSEA), immune infiltration, cancer immune microenvironment, and connectivity map (CMap) were used to evaluate the snoRNAs prognostic signature.ResultsWe identified 21 LGG prognostic snoRNAs and constructed a novel eleven-snoRNA prognostic signature for LGG patients. Survival analysis suggests that this signature is an independent prognostic risk factor for LGG, and the prognosis of LGG patients with a high-risk phenotype is poor (adjusted P = 0.003, adjusted hazard ratio = 2.076, 95% confidence interval = 1.290–3.340). GSEA and functional enrichment analysis suggest that this signature may be involved in the following biological processes and signaling pathways: such as cell cycle, Wnt, mitogen-activated protein kinase, janus kinase/signal transducer and activator of tran-ions, T cell receptor, nuclear factor-kappa B signaling pathway. CMap analysis screened out ten targeted therapy drugs for this signature: 15-delta prostaglandin J2, MG-262, vorinostat, 5155877, puromycin, anisomycin, withaferin A, ciclopirox, chloropyrazine and megestrol. We also found that high- and low-risk score phenotypes of LGG patients have significant differences in immune infiltration and cancer immune microenvironment.ConclusionsThe present study identified a novel eleven-snoRNA prognostic signature of LGG and performed a integrative analysis of its molecular mechanisms and relationship with tumor immunity.

scholarly journals Fam20C Overexpression Predicts Poor Outcomes and is a Diagnostic Biomarker in Lower-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jing Feng ◽  
Jinping Zhou ◽  
Lin Zhao ◽  
Xinpeng Wang ◽  
Danyu Ma ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Research Field ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Kaplan Meier ◽  
Lower Grade Glioma ◽  
Poor Outcomes

Glioma is a relatively low aggressive brain tumor. Although the median survival time of patients for lower-grade glioma (LGG) was longer than that of patients for glioblastoma, the overall survival was still short. Therefore, it is urgent to find out more effective molecular prognostic markers. The role of the Fam20 kinase family in different tumors was an emerging research field. However, the biological function of Fam20C and its prognostic value in brain tumors have rarely been reported. This study aimed to evaluate the value of Fam20C as a potential prognostic marker for LGG. A total of 761 LGG samples (our cohort, TCGA and CGGA) were included to investigate the expression and role of Fam20C in LGG. We found that Fam20C was drastically overexpressed in LGG and was positively associated with its clinical progression. Kaplan-Meier analysis and a Cox regression model were employed to evaluate its prognostic value, and Fam20C was found as an independent risk factor in LGG patients. Gene set enrichment analysis also revealed the potential signaling pathways associated with Fam20C gene expression in LGG; these pathways were mainly enriched in extracellular matrix receptor interactions, cell adhesion, cell apoptosis, NOTCH signaling, cell cycle, etc. In summary, our findings provide insights for understanding the potential role of Fam20C and its application as a new prognostic biomarker for LGG.

Sign in / Sign up

Export Citation Format

Share Document