Dataset Information

Thioredoxin System Protein Expression Is Associated with Poor Clinical Outcome in Adult and Paediatric Gliomas and Medulloblastomas.

ABSTRACT: The thioredoxin (Trx) system is an important enzyme family that regulates cellular redox homeostasis. Protein expression of Trx system family members has been assessed in various cancers and linked to various clinicopathological variables, disease progression, treatment response and survival outcomes but information is lacking in brain tumours. Expression of the system was therefore examined, by immunohistochemistry in different brain tumour types, adult and paediatric cases, to determine if expression was of importance to clinical outcome. Trx system proteins were expressed, to variable levels, across all brain tumour types with significant variations in expression between different tumour types/grades/regions. High Trx reductase (TrxR) expression was linked to worse prognosis across all cohorts. High cytoplasmic TrxR expression was significantly associated with adverse overall survival (OS) in adult glioblastoma (P =?0.027) and paediatric low-grade glioma (LGG) patients (P =?0.012). High expression of nuclear TrxR, cytoplasmic and nuclear Trx and Trx-interacting protein (TxNIP) was associated with improved OS in paediatric LGGs (P =?0.031, P

SUBMITTER: Yao A

PROVIDER: S-EPMC7320063 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Thioredoxin System Protein Expression Is Associated with Poor Clinical Outcome in Adult and Paediatric Gliomas and Medulloblastomas.

Yao Anqi A Storr Sarah J SJ Al-Hadyan Khaled K Rahman Ruman R Smith Stuart S Grundy Richard R Paine Simon S Martin Stewart G SG

Molecular neurobiology 20200516 7

The thioredoxin (Trx) system is an important enzyme family that regulates cellular redox homeostasis. Protein expression of Trx system family members has been assessed in various cancers and linked to various clinicopathological variables, disease progression, treatment response and survival outcomes but information is lacking in brain tumours. Expression of the system was therefore examined, by immunohistochemistry in different brain tumour types, adult and paediatric cases, to determine if exp ...[more]

PMID: 32418115

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Project description:Molecular subtypes of medulloblastoma [Sonic Hedgehog (SHH), Wingless/INT (WNT), Group 3, and Group 4] are defined by common patterns of gene expression. These differential gene expression patterns appear to result in different histomorphology and prognosis. Quantitative histomorphometry is a well-known method of computer-aided pathology image analysis. The hypotheses we sought to examine in this preliminary proof of concept study were whether computer extracted nuclear morphological features of medulloblastomas from digitized tissue slide images could independently: (1) distinguish between molecularly determined subgroups and (2) identify patterns within these subgroups that correspond with clinical outcome. Our dataset was composed of 46 medulloblastoma patients: 16 SHH (5 dead, 11 survived), 3 WNT (0 dead, 3 survived), 12 Group 3 (4 dead, 8 survived), and 15 were Group 4 (5 dead, 10 survived). A watershed-based thresholding scheme was used to automatically identify individual nuclei within digitized whole slide hematoxylin and eosin tissue images. Quantitative histomorphometric features corresponding to the texture (variation in pixel intensity), shape (variations in size, roundness), and architectural rearrangement (distances between, and number of connected neighbors) of nuclei were subsequently extracted. These features were ranked using feature selection schemes and these top-ranked features were then used to train machine-learning classifiers via threefold cross-validation to separate patients based on: (1) molecular subtype and (2) disease-specific outcomes within the individual molecular subtype groups. SHH and WNT tumors were separated from Groups 3 and 4 tumors with a maximum area under the receiver operating characteristic curve (AUC) of 0.7, survival within Group 3 tumors was predicted with an AUC of 0.92, and Group 3 and 4 patients were separated into high- and low-risk groups with p = 0.002. Model prediction was quantitatively compared with age, stage, and histological subtype using univariate and multivariate Cox hazard ratio models. Age was the most statistically significant variable for predicting survival in Group 3 and 4 tumors, but model predictions had the highest hazard ratio value. Quantitative nuclear histomorphometry can be used to study medulloblastoma genetic expression phenotypes as it may distinguish meaningful features of disease pathology.

Project description:Background: Glioma is the most common primary tumor of the central nervous system and is associated with poor overall survival, creating an urgent need to identify survival-associated biomarkers. C1ORF112, an alpha-helical protein, is overexpressed in some cancers; however, its prognostic role has not yet been explored in gliomas. Thus, in this study, we attempted to address this by determining the prognostic value and potential function of C1ORF112 in low-grade gliomas (LGGs). Methods: The expression of C1ORF112 in normal and tumor tissues was analyzed using data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Oncomine, and Rembrandt databases. The genetic changes of C1ORF112 in LGG were analyzed using cBioPortal. Survival analysis was used to evaluate the relationship between C1ORF112 expression and survival in patients with LGG. Correlation between immune infiltration and C1ORF112 expression was determined using Timer software. Additionally, data from three online platforms were integrated to identify the co-expressed genes of C1ORF112. The potential biological functions of C1ORF112 were investigated by enrichment analysis. Results: C1ORF112 mRNA was highly expressed in LGGs (p < 0.01). Area under the ROC curve (AUC) showed that the expression of C1ORF112 in LGG was 0.673 (95% confidence interval [CI] = 0.618-0.728). Kaplan-Meier survival analysis showed that patients with high C1ORF112 expression had lower OS than patients with low C1ORF112 expression (p < 0.05). Multivariate analysis showed that high expression of C1ORF112 was an independent prognostic factor for the overall survival in patients from TCGA and CGGA databases. C1ORF112 expression was positively correlated with six immunoinfiltrating cells (all p < 0.001). The enrichment analysis suggested the enrichment of C1ORF112 and co-expressed genes in cell cycle and DNA replication. Conclusion: This study suggested that C1ORF112 may be a prognostic biomarker and a potential immunotherapeutic target for LGG.

Dataset Information

Thioredoxin System Protein Expression Is Associated with Poor Clinical Outcome in Adult and Paediatric Gliomas and Medulloblastomas.

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Thioredoxin System Protein Expression Is Associated with Poor Clinical Outcome in Adult and Paediatric Gliomas and Medulloblastomas.

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