Dataset Information

BICD1 expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas.

ABSTRACT: There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by in silico meta-analysis of the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Our results demonstrated that BICD1 expression could predict both prognosis and response to therapy in GBM patients. First, high BICD1 expression was correlated with poor prognosis in the TCGA GBM cohort (n=523) and in the CGGA glioma cohort (n=220). Second, high BICD1 expression predicted poor outcome in patients with TMZ treatment (n=301) and radiation therapy (n=405). Third, multivariable Cox regression analysis confirmed BICD1 expression as an independent factor affecting the prognosis and therapeutic response of TMZ and radiation in GBM patients. Additionally, age, MGMT and BICD1 expression were combinedly utilized to stratify GBM patients into more distinct risk groups, which may provide better outcome assessment. Finally, we observed a strong correlation between BICD1 expression and epithelial-mesenchymal transition (EMT) in GBMs, and proposed a possible mechanism of BICD1-associated survival or therapeutic resistance in GBMs accordingly. In conclusion, our study suggests that high BICD1 expression may result in worse prognosis and could be a predictor of poor response to TMZ and radiation therapies in GBM patients.

SUBMITTER: Huang SP

PROVIDER: S-EPMC5768362 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

<i>BICD1</i> expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas.

Huang Shang-Pen SP Chang Yu-Chan YC Low Qie Hua QH Wu Alexander T H ATH Chen Chi-Long CL Lin Yuan-Feng YF Hsiao Michael M

Oncotarget 20171127 69

There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by <i>in silico</i> meta-analysis of the Cancer Genome Atlas (T ...[more]

PMID: 29371945

Similar Datasets

Project description:Background: Abnormal mucosal inflammation is a critical risk factor for pathogenesis and progression of colorectal cancer (CRC). As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in CRC remains unclear. Methods: A total of 38 pyroptosis-related gene (PRG) expression profiles and clinical information were collected from multiple public datasets. Bioinformatics methods were used to analyze the clinical significance, functional status, immune infiltration, genomic alteration, and drug sensitivity in different subgroups. Whole-genome microarray analysis was performed to analyze the regulation of gut microbiota on the expression of PRGs. Results: Two distinct molecular subtypes were identified and suggested that multilayer PRG alterations were associated with patient clinicopathological features, prognosis, and tumor microenvironment (TME) infiltrating characteristics. Furthermore, we obtained eight PRG signatures by applying differential expression analysis and univariate Cox and Lasso regression analyses. A risk prognosis model was constructed for predicting overall survival (OS) and recurrence-free survival (RFS) based on the PRG signature. There were significant differences in clinical characteristics, 22 immune cells, and immune functions between the high- and low-risk groups. In addition, the PRG signature was significantly associated with the microsatellite instability (MSI), tumor mutation burden (TMB), cancer stem cell (CSC) index, immunotherapeutic characteristics, and chemotherapeutic drug sensitivity. Moreover, the in vitro experiments had shown that Fusobacterium nucleatum (F.n) could affect the CASP6 expression, which was associated with the chemoresistance to 5-fluorouracil (5-Fu) in CRC. Conclusion: Our findings provided a foundation for future research targeting pyroptosis and a new insight into the prognosis and immune cell infiltration of CRC, and they suggested that F.n might influence CRC progression through pyroptosis.

Project description:PurposeImmune checkpoint therapy (ICT) provides a new idea for the treatment of advanced clear cell renal cell carcinoma (ccRCC), which can bring significant benefits to patients. However, the clinical application of ICT is limited because of the lack of predictive biomarkers to select potential responders. This study aims to propose a new biomarker to predict the response to Nivolumab in patients with ccRCC.Materials and methodsThe genes that significantly improve the prognosis of ccRCC were retrieved from The Cancer Genome Atlas (TCGA) database. The genomic and clinical data were from patients that had been registered in prospective clinical trials (CheckMate 009, CheckMate 010 and CheckMate 025). TCGA, Gene Expression Omnibus (GEO), and The Human Protein Atlas database were used to analyze the gene and protein expression of WD repeat-containing protein 72 (WDR72) in ccRCC. Gene Ontology (GO) & The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to dig relevant mechanisms of WDR72. Single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the role of WDR72 in immune infiltration. Cell proliferation assay, FAO and ATP quantification were used to explore and verify the molecular mechanisms. The expression of WDR72, FOXP3, CD8, and CPT1A was examined by IHC in 20 advanced ccRCC tissue samples at the Urology Department of our hospital. The MethSurv was used to identify PBRM1 and WDR72 gene methylation and its effect on prognosis of ccRCC.ResultsWDR72 is the most significant gene for improving overall survival (OS) in ccRCC. In all three checkmates, OS and progression free survival (PFS) were found to be significantly higher in WDR72 high expression group than that in WDR72 low expression group (P=0.040 and P=0.012, respectively), and similar conclusions could be drawn from the PBRM1-mutation (MUT) compared with the PBRM1-wildtype (WT) (P=0.007 and P=0.006, respectively). What's more, high expression of WDR72 plus PBRM1-MUT as a combinatorial biomarker showed improved OS (HR=0.388, P=0.0026) and PFS (HR=0.39, P=0.0066) compared to low expression of WDR72 plus PBRM1-WT. Functional enrichment analysis showed that WDR72 was closely positively related to fatty acid degradation and fatty acid beta oxidation pathway in ccRCC. In vitro experiments showed that high expression of WDR72 can promote fatty acids oxidation and inhibit the proliferation of ccRCC cells. Immune analysis revealed that WDR72 high expression was associated with decreased infiltration of Treg cells and low ssGSEA score of check-point. IHC results showed that WDR72 was negatively correlated with FOXP3 expression (r=-0.506, P=0.023) and positively correlated with CPT1A expression (r=0.529, P=0.017).ConclusionsThe present study indicated that high expression of WDR72 may indicate a good prognosis of patients treated with Nivolumab and WDR72 expression combined with PBRM1 mutation could be more persuasive to predict the response for ICT in ccRCC patients.

Project description:BackgroundOur previous studies have found that single nucleotide polymorphisms (SNPs) of tribbles homolog 3 (TRIB3) are related to the hypotensive effects of calcium-channel blockers (CCBs) and angiotensin-converting enzyme (ACE) inhibitors. In this study, we aimed at exploring and validating the effect of TRIB3 polymorphism on antihypertensive drugs responses.MethodsA total of 830 hypertensive patients, who were administered with open-labeled hydrochlorothiazide (12.5 mg once daily) and randomly assigned to off-labeled felodipine (5 mg) or a matched placebo combination treatment (1:1), were selected from the Felodipine Event Reduction (FEVER) study. A strategy of screening 259 samples and validating the remaining 531 samples was implemented. Four functional SNPs were selected (rs2295490, rs11470129, rs4815567 and rs6037475 in TRIB3). A mixed linear model was performed to analyze the effects of TRIB3 SNPs on antihypertensive drugs responses.ResultsWe found that TRIB3 rs6037475 CC genotype was associated with a reduction of diastolic blood pressure (DBP) (P=6.3×10-3) in the felodipine treatment group of screening set, and was also associated with a reduction of systolic blood pressure (SBP) (P=0.021), DBP (P=6.0×10-3) and mean arterial pressure (MAP) (P=0.021) in the felodipine treatment group of the validation set. As for the reductions influenced by the rs2295490, rs11470129 and rs4815567 genetic variations, however, the adjusted P-value did not reach statistical significance. Combined screening and validation set analysis found that patients with TRIB3 rs6037475 CC genotype had a significant higher mean SBP, DBP and MAP than those with TT genotype in the felodipine treatment group (CC vs. TT -10.2±0.74 vs. -17.8±0.21, P=7.8×10-3; -4.6±0.50 vs. -10.2±0.23, P=3.0×10-4; -6.5±0.54 vs. -12.7±0.14, P=3.0×10-4, respectively).ConclusionsThese results suggest that TRIB3 rs6037475 genetic variation can be useful as a bio-marker for predicting felodipine drug response in Chinese patients with hypertension.

Dataset Information

BICD1 expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas.

Publications

<i>BICD1</i> expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets