scholarly journals Overexpression of PSAT1 Gene is a Favorable Prognostic Marker in Lower-Grade Gliomas and Predicts a Favorable Outcome in Patients with IDH1 Mutations and Chromosome 1p19q Codeletion

Cancers ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 13 ◽  
Author(s):  
Shang-Pen Huang ◽  
Yung-Chieh Chan ◽  
Shang-Yu Huang ◽  
Yuan-Feng Lin
Keyword(s):  
Gene Expression ◽  
Prognostic Marker ◽  
Cancer Metabolism ◽  
Prognostic Significance ◽  
Favorable Outcome ◽  
Lower Grade ◽  
1P19q Codeletion ◽  
Potential Biomarker ◽  
Idh1 Mutations ◽  
Genome Atlas

Patients with lower-grade gliomas (LGGs) have highly diverse clinical outcomes. Although histological features and molecular markers have been used to predict prognosis, the identification of new biomarkers for the accurate prediction of patient outcomes is still needed. The serine synthesis pathway (SSP) is important in cancer metabolism. There are three key regulators, including phosphoglycerate dehydrogenase (PHGDH), phosphoserine phosphatase (PSPH), and phosphoserine aminotransferase 1 (PSAT1), in SSP. However, their clinical importance in LGGs is still unknown. In this study, we used the bioinformatics tool in the Gene Expression Profiling Interactive Analysis (GEPIA) website to examine the prognostic significance of PHGDH, PSPH, and PSAT1 genes in LGGs. PSAT1 gene expression was then identified as a potential biomarker candidate for LGGs. Datasets from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were further used to explore the prognostic role of PSAT1 gene. Our results demonstrated that PSAT1 overexpression is a favorable prognostic marker of LGGs and significantly correlated with patient age ≤40, and a lower WHO histological grade, as well as mutations in IDH1, TP53 and ATRX, but not with chromosome 1p19q codeletions. More importantly, LGG patients with isocitrate dehydrogenase 1 (IDH1) mutations, chromosome 1p19q codeletions, and PSAT1 overexpression may have the best overall survival (five-year survival rate: 100%). Finally, we observed a coordinated biological reaction between IDH1 mutations and PSAT1 overexpression, and suggested overexpression of PSAT1 might enhance the function of mutant IDH1 to promote a favorable outcome in LGG patients. In conclusion, our study confirmed the importance of identifying the overexpression of PSAT1 as a favorable prognostic marker of LGGs, which may compensate for the limitation of IDH1 mutations and chromosome 1p19q codeletion in the prognostication of LGGs.

scholarly journals Metabolic classification of bladder cancer based on multi-omics integrated analysis to predict patient prognosis and treatment response

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chaozhi Tang ◽  
Meng Yu ◽  
Jiakang Ma ◽  
Yuyan Zhu
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Metabolic Activity ◽  
Survival Data ◽  
Cancer Metabolism ◽  
Prognostic Significance ◽  
Integrated Analysis ◽  
Metabolic Characteristics ◽  
Metabolic Genes

Abstract Background Currently, no molecular classification is established for bladder cancer based on metabolic characteristics. Therefore, we conducted a comprehensive analysis of bladder cancer metabolism-related genes using multiple publicly available datasets and aimed to identify subtypes according to distinctive metabolic characteristics. Methods RNA-sequencing data of The Cancer Genome Atlas were subjected to non-negative matrix fractionation to classify bladder cancer according to metabolism-related gene expression; Gene Expression Omnibus and ArrayExpress datasets were used as validation cohorts. The sensitivity of metabolic types to predicted immunotherapy and chemotherapy was assessed. Kaplan–Meier curves were plotted to assess patient survival. Differentially expressed genes between subtypes were identified using edgeR. The differences among identified subtypes were compared using the Kruskal–Wallis non-parametric test. To better clarify the subtypes of bladder cancer, their relationship with clinical characteristics was examined using the Fisher’s test. We also constructed a risk prediction model using the random survival forest method to analyze right-censored survival data based on key metabolic genes. To identify genes of prognostic significance, univariate Cox regression, lasso analysis, and multivariate regression were performed sequentially. Results Three bladder cancer subtypes were identified according to the expression of metabolism-related genes. The M1 subtype was characterized by high metabolic activity, low immunogenicity, and better prognosis. M2 exhibited moderate metabolic activity, high immunogenicity, and the worst prognosis. M3 was associated with low metabolic activity, low immunogenicity, and poor prognosis. M1 showed the best predicted response to immunotherapy, whereas patients with M1 were predicted to be the least sensitive to cisplatin. By contrast, M2 showed the worst predicted response to immunotherapy but was predicted to be more sensitive to cisplatin, doxorubicin, and other first-line anticancer drugs. M3 was the most sensitive to gemcitabine. The risk model based on metabolic genes effectively predicted the prognosis of bladder cancer patients. Conclusions Metabolic classification of bladder cancer has potential clinical value and therapeutic feasibility by inhibiting the associated pathways. This classification can provide valuable insights for developing precise bladder cancer treatment.

The Solute Carrier Family 7 Genes Are Potential Diagnostic and Prognostic Biomarkers in Lower Grade Glioma

2021 ◽  
Author(s):  
Wentao Liu ◽  
Yu Ji ◽  
Rijun Ren ◽  
Gentang Zhang
Keyword(s):  
Gene Expression ◽  
Amino Acid ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Lower Grade ◽  
Lower Grade Glioma ◽  
Family Gene ◽  
Solute Carrier ◽  
Genome Atlas ◽  
Brain Tissues

Abstract Background: The solute carrier (SLC) 7 family genes are a group of cationic amino acid/glycoprotein transporters and of importance to the maintenance of amino acid nutrition and survival of tumour cells. This study was to investigate the diagnostic values of SLC7 family genes and their associations with overall survival (OS) and relapse-free survival (RFS) in Lower grade glioma (LGG). Methods: SLC7 family gene expression and clinical data were retrieved from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas database. The expression difference of SLC7 family genes was compared between 523 LGG and 1141 normal brain tissues. The associations between gene expression, clinicopathologic factors, patients’ OS and RFS were analysed by various statistical methods in the two datasets. Results: As compared to normal brain tissues, SLC7A10 expression was significantly down-regulated, while SLC7A5, SLC7A7 expression was significantly up-regulated in LGG tissues. Multivariate analysis and validation analysis confirmed that increased SLC7A7 expression was associated with increased mortality (P≤0.001, Odd ratio [OR]:2.66, 95% Confidence interval [CI]: 1.56–4.6). While, increased SLC7A4 and SLC7A14 expression was associated with reduced mortality (P=0.02, OR:0.38, 95% CI: 0.16–0.81; P≤0.001, OR:0.38, 95% CI: 0.21–0.67; respectively). Increased SLC7A11 expression was associated with decreased RFS (P=0.01, OR:0.61, 95% CI: 0.43–0.88). Conclusion: SLC7A5, SLC7A7, SLC7A10 might serve as diagnostic biomarkers in LGG. High SLC7A4, SLC7A7 and SLC7A14 expression is significantly associated with OS. SLC7 family gene expression represents a potentially diagnostic and prognostic biomarker to predict survival in LGG.

scholarly journals Molecular classification of IDH-mutant glioblastomas based on gene expression profiles

2019 ◽  
Vol 40 (7) ◽  
pp. 853-860 ◽  
Author(s):  
Fan Wu ◽  
Rui-Chao Chai ◽  
Zhiliang Wang ◽  
Yu-Qing Liu ◽  
Zheng Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Dna Replication ◽  
High Risk ◽  
Molecular Classification ◽  
Lower Grade ◽  
Diffuse Glioma ◽  
Cox Regression Analysis ◽  
Genome Atlas

Abstract Isocitrate dehydrogenase (IDH) mutant glioblastoma (GBM), accounts for ~10% GBMs, arises from lower grade diffuse glioma and preferentially appears in younger patients. Here, we aim to establish a robust gene expression-based molecular classification of IDH-mutant GBM. A total of 33 samples from the Chinese Glioma Genome Atlas RNA-sequencing data were selected as training set, and 21 cases from Chinese Glioma Genome Atlas microarray data were used as validation set. Consensus clustering identified three groups with distinguished prognostic and molecular features. G1 group, with a poorer clinical outcome, mainly contained TERT promoter wild-type and male cases. G2 and G3 groups had better prognosis differed in gender. Gene ontology analysis showed that genes enriched in G1 group were involved in DNA replication, cell division and cycle. On the basis of the differential genes between G1 and G2/G3 groups, a six-gene signature was developed with a Cox proportional hazards model. Kaplan–Meier analysis found that the acquired signature could differentiate the outcome of low- and high-risk cases. Moreover, the signature could also serve as an independent prognostic factor for IDH-mutant GBM in the multivariate Cox regression analysis. Gene ontology and gene set enrichment analyses revealed that gene sets correlated with high-risk group were involved in cell cycle, cell proliferation, DNA replication and repair. These finding highlights heterogeneity within IDH-mutant GBMs and will advance our molecular understanding of this lethal cancer.

scholarly journals Trophinin Is an Important Biomarker and Prognostic Factor in Osteosarcoma: Data Mining from Oncomine and the Cancer Genome Atlas Databases

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Pan Cai ◽  
Yan Lu ◽  
Zhifeng Yin ◽  
Xiuhui Wang ◽  
Xiaoxiao Zhou ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factor ◽  
Prognostic Significance ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Osteosarcoma Cell ◽  
Online Tool ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Osteosarcoma (OS) is a type of bone malignancy with a high rate of treatment failure. To date, few evident biomarkers for the prognostic significance of OS have been established. Oncomine was used to integrate RNA and DNA-seq data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and the published literature. The correlation of the gene Trophinin (TRO) and different types of cancers was generated using the Cancer Cell Line Encyclopedia (CCLE) online tool. Prognostic values of featured Melanoma Antigen Gene (MAGE) members were further assessed by establishing the overall survival using the Kaplan-Meier plotter. Moreover, the online tool, Database for Annotation, Visualization and Integrated Discovery version (DAVID), was used to understand the biological meaning list of the genes. MAGEB10, MAGED2, TRO, MAGEH1, MAGEB18, MAGEB6, MAGEB4, MAGEB1, MAGED4B, MAGED1, MAGEB2, and MAGEB3 were significantly overexpressed in sarcoma. TRO was further demonstrated to be distinctively upregulated in osteosarcoma cell lines and associated with shorter overall survival. TRO may play an important role in the development of OS and may be a promising potential biomarker and prognostic factor.

scholarly journals Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

2020 ◽  
Author(s):  
Han Lin ◽  
Yong Yang ◽  
Chongxian Hou ◽  
Jiantao Zheng ◽  
Guangzhao Lv ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Models ◽  
Normal Brain ◽  
Lower Grade ◽  
Associated Proteins ◽  
Genome Atlas

Abstract BackgroundSynapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. MethodIn this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. ResultData from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. ConclusionOur study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

scholarly journals Analysis of the EGFR Amplification and CDKN2A Deletion Regulated Transcriptomic Signatures Reveals the Prognostic Significance of SPATS2L in Patients With Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Ji Zhang ◽  
Hua Cao
Keyword(s):  
Statistical Analysis ◽  
Prognostic Significance ◽  
Mapk Signaling ◽  
Lower Grade ◽  
Egfr Amplification ◽  
Expression Levels ◽  
Cdkn2a Deletion ◽  
Tumor Types ◽  
Worse Prognosis ◽  
Genome Atlas

Purpose: This study was conducted in order to analyze the prognostic effects of epidermal growth factor receptor (EGFR) and CDKN2A alterations and determine the prognostic significance of EGFR and CDKN2A alterations on regulated genes in patients with glioblastoma (GBM) or lower grade glioma (LGG).Methods: The alteration frequencies of EGFR and CDKN2A across 32 tumor types were derived from cBioPortal based on The Cancer Genome Atlas (TCGA) datasets. The Kaplan–Meier analysis was used to determine the prognostic significance of EGFR and CDKN2A alterations. EGFR and CDKN2A alterations on regulated expression signatures were identified from RNA-seq data in the TCGA GBM datasets. The prognostic significance of EGFR and CDKN2A alterations on regulated genes in patients with glioma was determined using the TCGA and the Chinese Glioma Genome Atlas (CGGA) datasets.Results: Compared with the other 31 tumor types, EGFR amplification and CDKN2A deletion particularly occurred in patients with GBM. GBM patients with EGFR amplification or CDKN2A deletion demonstrated poor prognosis. Statistical analysis showed the coexistence of EGFR alteration and CDKN2A deletion in GBM patients. We identified 864 genes which were commonly regulated by EGFR amplification and CDKN2A deletion, and those genes were highly expressed in brain tissues and associated with the cell cycle, EBRR2, and MAPK signaling pathways. Spermatogenesis-associated serine-rich 2-like gene (SPATS2L) was upregulated in GBM patients with EGFR amplification or CDKN2A alteration. Higher expression levels of SPATS2L were associated with worse prognosis in patients with GBM in both TCGA and CGGA datasets. Moreover, the expression levels of SPATS2L were higher in patients with a mesenchymal subtype of GBM. Statistical analysis also showed that the coexistence of EGFR alteration and CDKN2A deletion was significant in patients with LGG. SPATS2L was upregulated in LGG patients with EGFR amplification or CDKN2A alteration. Furthermore, higher expression levels of SPATS2L were associated with worse prognosis in patients with LGG in both TCGA and CGGA datasets. The expression levels of SPATS2L were higher in patients with an astrocytoma subtype of LGG. Finally, the coexistence and unfavorable prognostic effects of EGFR amplification and CDKN2A alteration were validated using the Memorial Sloan Kettering Cancer Center (MSKCC) glioma datasets.Conclusions: EGFR amplification and CDKN2A deletion of the regulated gene SPATS2L have significant prognostic effects in patients with GBM or LGG.

scholarly journals BICD Cargo Adaptor 1 (BICD1) Downregulation Correlates with a Decreased Level of PD-L1 and Predicts a Favorable Prognosis in Patients with IDH1-Mutant Lower-Grade Gliomas

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 701
Author(s):  
Shang-Pen Huang ◽  
Chien-Hsiu Li ◽  
Wei-Min Chang ◽  
Yuan-Feng Lin
Keyword(s):  
The Cancer Genome Atlas ◽  
World Health ◽  
Egfr Mutations ◽  
Lower Grade ◽  
Karnofsky Performance Score ◽  
Wild Type ◽  
Who Grade ◽  
Favorable Prognosis ◽  
Potential Biomarker ◽  
Genome Atlas

Although several biomarkers have been identified to predict the prognosis of lower-grade (Grade II/III) gliomas (LGGs), we still need to identify new markers to facilitate those well-known markers to obtain more accurate prognosis prediction in LGGs. Bioinformatics data from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and the Cancer Cell Line Encyclopedia (CCLE) datasets were used as the research materials. In total, 34 genes associated with the HIF1A pathway were analyzed using the hierarchical method to search for the most compatible gene. The BICD cargo adaptor 1 (BICD1) gene (BICD1) was shown to be significantly correlated with The hypoxic inducible factor 1A (HIF1A) expression, the World Health Organization (WHO) grade, and IDH1 mutation status. In addition, BICD1 downregulation was significantly correlated with a higher Karnofsky performance score (KPS), IDH1/TP53/ATRX mutations, wild-type EGFR, and younger patient age in the enrolled LGG cohort. Moreover, BICD1 expression was significantly upregulated in wild-type IDH1 LGGs with EGFR mutations. Kaplan–Meier survival analysis revealed that BICD1 downregulation predicts a favorable overall survival (OS) in LGG patients, especially in those with IDH1 mutations. Intriguingly, we found a significant correlation between BICD1 downregulation and a decreased level of CD274, GSK3B, HGF, or STAT3 in LGGs. Our findings suggest that BICD1 downregulation could be a potential biomarker for a favorable prognosis of LGGs.

scholarly journals Prognostic and Predictive Value of Immune-Related Gene Pair Signature in Primary Lower-Grade Glioma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Kunjian Lei ◽  
Jingying Li ◽  
Zewei Tu ◽  
Feng Liu ◽  
Minhua Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Cox Regression ◽  
Low Risk ◽  
Lower Grade ◽  
Related Gene ◽  
Immune Related Gene ◽  
Lower Grade Glioma ◽  
Tcga Dataset ◽  
Genome Atlas

Immune-related gene pairs (IRGPs) have been associated with prognosis in various cancer types, but few studies have examined their prognostic capabilities in glioma patients. Here, we gathered the gene expression and clinical profile data of primary lower-grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA, containing CGGAseq1 and CGGAseq2), the Gene Expression Omnibus (GEO: GSE16011), and Rembrandt datasets. In the TCGA dataset, univariate Cox regression was performed to detect overall survival (OS)-related IRGs, Lasso regression, and multivariate Cox regression were used to screen robust prognosis-related IRGs, and 19 IRGs were selected for the construction of an IRGP prognostic signature. All patients were allotted to high- and low-risk subgroups based on the TCGA dataset median value risk score. Validation analysis indicated that the IRGP signature returned a stable prognostic value among all datasets. Univariate and multivariate Cox regression analyses indicated that the IRG -signature could efficiently predict the prognosis of primary LGG patients. The IRGP-signature-based nomogram model was built, revealing the reliable ability of the IRGP signature to predict clinical prognosis. The single-sample gene set enrichment analysis (ssGSEA) suggested that high-risk samples contained higher numbers of immune cells but featured lower tumor purity than low-risk samples. Finally, we verified the prognostic ability of the IRGP signature using experiments performed in LGG cells. These results indicated that the IRGP signature could be regarded as a stable prognostic assessment predictor for identifying high-risk primary LGG patients.

scholarly journals Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

2020 ◽  
Author(s):  
Han Lin ◽  
Yong Yang ◽  
Chongxian Hou ◽  
Jiantao Zheng ◽  
Guangzhao Lv ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Models ◽  
Normal Brain ◽  
Lower Grade ◽  
Associated Proteins ◽  
Genome Atlas

Abstract Background: Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. Method: In this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. Result: Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas.Conclusion: Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

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