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Thioredoxin and thioredoxin-interacting protein as prognostic markers for gastric cancer recurrence.

ABSTRACT: To evaluate the potential of thioredoxin (TXN) and thioredoxin-interacting protein (TXNIP) expression as biomarkers for predicting gastric cancer recurrence.TXN and TXNIP expression levels were acquired from gene expression microarray data for 65 human gastric cancer tissues. We determined whether each gene expression level was associated with cancer recurrence and investigated the relationship between the two genes. For validation, the expression levels of TXN and TXNIP were measured by quantitative real-time reverse transcription polymerase chain reaction in 68 independent stage III gastric cancer patients. The correlation between gene expression and cancer prognosis was evaluated. Immunohistochemical staining was performed to investigate the protein expression levels of TXN and TXNIP and to characterize the expression patterns of each protein.TXN was a prognosis-related gene (P = 0.009), whereas TXNIP, a TXN inhibitor, demonstrated a negative correlation with TXN in the gene expression microarray data. In the 68 stage III patients, the expression levels of both TXN and TXNIP had a statistically significant effect on recurrence-free survival (RFS, P = 0.008 and P = 0.036, respectively). The low TXN and high TXNIP expression group exhibited a better prognosis than the other groups, and the high TXN and low TXNIP expression group exhibited a poorer prognosis (P < 0.001 for RFS and P = 0.001 for overall survival). More than half of the patients in the simultaneously high TXN and low TXNIP expression group experienced a recurrence within 1 year after curative surgery, and the 5-year survival rate of the patients in this group was 29%, compared with 89% in the low TXN and high TXNIP expression group. The TXN protein was overexpressed in 65% of the gastric cancer tissues, whereas the TXNIP protein was underexpressed in 85% of the cancer cells. In a correlation analysis, TXN and TXNIP were highly correlated with many oncogenes and tumor suppressors as well as with genes related to energy, protein synthesis and autophagy.TXN and TXNIP are promising prognostic markers for gastric cancer, and performing personalized adjuvant treatment based on TXN and TXNIP expression levels would be an effective practice in the treatment of gastric cancer.

SUBMITTER: Lim JY

PROVIDER: S-EPMC3482645 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Thioredoxin and thioredoxin-interacting protein as prognostic markers for gastric cancer recurrence.

Lim Jae Yun JY Yoon Sun Och SO Hong Soon Won SW Kim Jong Won JW Choi Seung Ho SH Cho Jae Yong JY

World journal of gastroenterology 20121001 39

<h4>Aim</h4>To evaluate the potential of thioredoxin (TXN) and thioredoxin-interacting protein (TXNIP) expression as biomarkers for predicting gastric cancer recurrence.<h4>Methods</h4>TXN and TXNIP expression levels were acquired from gene expression microarray data for 65 human gastric cancer tissues. We determined whether each gene expression level was associated with cancer recurrence and investigated the relationship between the two genes. For validation, the expression levels of TXN and TX ...[more]

PMID: 23112551

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Project description:BackgroundProstate cancer (PCa) is an immune-responsive disease. The current study sought to explore a robust immune-related prognostic gene signature for PCa.MethodsData were retrieved from the tumor Genome Atlas (TCGA) database and GSE46602 database for performing the least absolute shrinkage and selection operator (LASSO) cox regression model analysis. Immune related genes (IRGs) data were retrieved from ImmPort database.ResultsThe weighted gene co-expression network analysis (WGCNA) showed that nine functional modules are correlated with the biochemical recurrence of PCa, including 259 IRGs. Univariate regression analysis and survival analysis identified 35 IRGs correlated with the prognosis of PCa. LASSO Cox regression model analysis was used to construct a risk prognosis model comprising 18 IRGs. Multivariate regression analysis showed that risk score was an independent predictor of the prognosis of PCa. A nomogram comprising a combination of this model and other clinical features showed good prediction accuracy in predicting the prognosis of PCa. Further analysis showed that different risk groups harbored different gene mutations, differential transcriptome expression and different immune infiltration levels. Patients in the high-risk group exhibited more gene mutations compared with those in the low-risk group. Patients in the high-risk groups showed high-frequency mutations in TP53. Immune infiltration analysis showed that M2 macrophages were significantly enriched in the high-risk group implying that it affected prognosis of PCa patients. In addition, immunostimulatory genes were differentially expressed in the high-risk group compared with the low-risk group. BIRC5, as an immune-related gene in the prediction model, was up-regulated in 87.5% of prostate cancer tissues. Knockdown of BIRC5 can inhibit cell proliferation and migration.ConclusionIn summary, a risk prognosis model based on IGRs was developed. A nomogram comprising a combination of this model and other clinical features showed good accuracy in predicting the prognosis of PCa. This model provides a basis for personalized treatment of PCa and can help clinicians in making effective treatment decisions.

Dataset Information

Thioredoxin and thioredoxin-interacting protein as prognostic markers for gastric cancer recurrence.

Publications

Thioredoxin and thioredoxin-interacting protein as prognostic markers for gastric cancer recurrence.

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