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Genetic interaction analysis of TCF7L2 for biochemical recurrence after radical prostatectomy in localized prostate cancer.

ABSTRACT: Backgroud: Accumulated evidence has demonstrated a significant role of the Wnt pathway in human prostate cancer. We hypothesize that genetic variants in the Wnt pathway effector, Transcription factor 7-like 2 (TCF7L2), may influence clinical outcomes in prostate cancer.We comprehensively selected 12 tagged single-nucleotide polymorphisms (SNPs) to capture majority of common variants across TCF7L2, and genotyped in 458 localized prostate cancer patients treated with radical prostatectomy (RP). Kaplan-Meier analysis, Cox proportional hazard model, and survival tree analyses were performed to identify significant SNPs that correlated with biochemical recurrence (BCR) after surgery.A higher-order SNP-SNP interaction profile consisting of TCF7L2 rs7094463, rs10749127, and rs11196224 was significantly associated with BCR (P trend = 0.001). After adjusting for possible confounders, the genetic profile remained significant (P trend = 0.007). None of the studied SNPs were individually associated with BCR.Our results support a genetic interaction in the TCF7L2 SNPs as a predictor of disease recurrence after curative RP in localized prostate cancer patients.

SUBMITTER: Chen CS

PROVIDER: S-EPMC4323362 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Genetic interaction analysis of TCF7L2 for biochemical recurrence after radical prostatectomy in localized prostate cancer.

Chen Chien-Shu CS Huang Chao-Yuan CY Huang Shu-Pin SP Lin Victor C VC Yu Chia-Cheng CC Chang Ta-Yuan TY Bao Bo-Ying BY

International journal of medical sciences 20150205 3

<h4>Unlabelled</h4>Backgroud: Accumulated evidence has demonstrated a significant role of the Wnt pathway in human prostate cancer. We hypothesize that genetic variants in the Wnt pathway effector, Transcription factor 7-like 2 (TCF7L2), may influence clinical outcomes in prostate cancer.<h4>Methods</h4>We comprehensively selected 12 tagged single-nucleotide polymorphisms (SNPs) to capture majority of common variants across TCF7L2, and genotyped in 458 localized prostate cancer patients treated ...[more]

PMID: 25678841

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Project description:Accurate estimation of recurrence risk is needed for optimal treatment of clinically localized prostate cancer (PCa) patients. We combined classical clinicopathological predictors of biochemical recurrence (BCR) and molecular markers into a new risk score for predicting BCR after radical prostatectomy (RP). A retrospective study which included 122 PCa patients who attended our department between 2000 and 2007 was conducted. Total RNA was isolated from formalin-fixed paraffin embedded PCa tissue. Gene expression patterns were analyzed in 21 selected samples from 7 localized, 6 locally advanced, and 8 metastatic PCa patients using Illumina microarrays. Expression levels of 41 genes were validated by quantitative PCR in an independent retrospective series of 101 patients with ≥ 10 years follow-up who underwent RP for clinically localized PCa. Univariate and multivariate logistic regression analysis were used to identify individual predictors of BCR. A risk score (RS) for predicting BCR including clinicopathological and gene expression data was developed and Kaplan-Meier curves were generated. Interaction networks between the genes of the model were built by GeneMANIA Cytoscape plugin. In a median follow-up of 120 months (range 3-190), 37 patients developed BCR (36.6%). Expression levels of 7,930 transcripts differed between clinically localized and locally advanced-metastatic PCa groups (FDR<0.1). A set of 41 genes were validated by quantitative PCR. Regression analysis showed that expression of ASF1B and MCL1 as well as Gleason score, extracapsular extension, seminal vesicle invasion and positive margins were independent prognostic factors of BCR. A RS generated using these gene expression and clinicopathological variables was able to discriminate between two groups of patients with a significantly different probability of BCR (HR 6.24; CI 3.23-12.4, p<0.01), improving the individual discriminative performance of each of these variables on their own. Direct interactions between the two genes of the model were not found. In conclusion, identification of new gene expression patterns associated with a high probability of BCR in clinically localized PCa patients treated with RP, and their combination with clinicopathological variables in a robust, easy-to-use and reliable classifier may contribute to improve PCa risk stratification and, consequently, to tailor treatment and surveillance strategies in these patients.

Project description:We have previously demonstrated a significant correlative relationship between PTEN deletion and ERG rearrangement, both in the development of clinically localized prostate cancers and metastases. Herein, we evaluate the cooperative role of ERG and PTEN in oncological outcomes after radical prostatectomy for clinically localized prostate cancer. We evaluated ERG and PTEN status using three previously described cohorts. The first cohort included 235 clinically localized prostate cancer cases represented on tissue microarrays (TMA), evaluated using previously validated FISH assays for ERG and PTEN. The second cohort included 167 cases of clinically localized prostate cancer on TMAs evaluated for PTEN by FISH, and for PTEN and ERG by dual IHC. The third cohort comprised 59 clinically localized prostate cancer cases assessed by array comparative genomic hybridization (aCGH). Kaplan-Meir plots and long rank tests were used to assess the association of ERG and PTEN status with biochemical recurrence after radical prostatectomy for clinically localized prostate cancer. Of the 317 cases eligible for analyses with evaluable ERG and PTEN status, 88 (27.8%) patients developed biochemical recurrence over a median follow-up of 5.7 years. Overall, 45% (142/317) of cases demonstrated ERG rearrangement and 20% (62/317) of cases demonstrated PTEN loss. Hemizygous and homozygous deletion of PTEN was seen in 10% (18/175) and 3% (5/175) of ERG-negative cases, respectively. In contrast, hemizygous and homozygous deletion of PTEN was seen in 11% (15/142) and 17% (24/123) of ERG-positive cases, respectively. PTEN loss (heterozygous or homozygous) was significantly associated with shorter time to biochemical recurrence compared to no PTEN loss (p < 0.001). However, ERG rearrangement versus no rearrangement was not associated with time to PSA recurrence (p = 0.15). Patients who exhibited ERG rearrangement and loss of PTEN had no significant difference in time to recurrence compared to patients with wild-type ERG and loss of PTEN (p = 0.30). Our findings confirm a mutual cooperative role of ERG and PTEN in the pathogenesis of prostate cancer, particularly for homozygous PTEN deletion. ERG did not stratify outcome either alone or in combination with PTEN in this cohort.

Project description:Background: Nowadays, predictions of biochemical recurrence (BCR) in localized prostate cancer (PCa) patients after radical prostatectomy (RP) are mainly based on clinical parameters with a low predictive accuracy. Given the critical role of apoptosis in PCa occurrence and progression, we aimed to establish a novel predictive model based on apoptosis-related gene signature and clinicopathological parameters that can improve risk stratification for BCR and assist in clinical decision-making. Methods: Expression data and corresponding clinical information were obtained from four public cohorts, one from The Cancer Genome Atlas (TCGA) dataset and three from the Gene Expression Omnibus (GEO) dataset. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate modules closely correlated to BCR, and univariate and multivariate Cox regression analyses were utilized to build the gene signature. Time-dependent receiver operating curve (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic value. Finally, we analyzed the expression of genes in the signature and validated the results using quantitative real-time PCR (qRT-PCR). Results: The novel gene signature we established exhibited a high prognostic value and was able to act as an independent risk factor for BCR [Training set: P < 0.001, hazard ratio (HR) = 7.826; Validation set I: P = 0.006, HR = 2.655; Validation set II: P = 0.003, HR = 4.175; Validation set III: P < 0.001, HR = 3.008]. Nomogram based on the gene signature and clinical parameters was capable of distinguishing high-risk BCR patients. Additionally, functional enrichment analysis showed several enriched pathways and biological processes, which might help reveal the underlying mechanism. The expression results of qRT-PCR were consistent with TCGA results. Conclusion: The apoptosis-related gene signature could serve as a powerful predictor and risk factor for BCR in localized PCa patients after RP.

Project description:Background: Decision-making regarding biochemical recurrence (BCR) in localized prostate cancer (PCa) patients after radical prostatectomy (RP) mainly relies on clinicopathological parameters with a low predictive accuracy. Currently, accumulating evidence suggests that immune-associated genes (IAGs) play irreplaceable roles in tumorigenesis, progression and metastasis. Considering the critical role of immune in PCa, we therefore attempted to identify the novel IAGs signature and validate its prognostic value that can better forecast the risk for BCR and guide clinical treatment. Methods: RNA-sequencing and corresponding clinicopathological data were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA) was utilized to screen out the candidate module closely related to BCR, and univariate and LASSO Cox regression analyses were performed to build the gene signature. Kaplan-Meier (KM) survival analysis, time-dependent receiver operating curve (ROC), independent prognostic analysis and nomogram were also applied to evaluate the prognostic value of the signature. Besides, Gene ontology analysis (GO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore potential biological pathways. Results: A total of six IAGs (SSTR1, NFATC3, NRP1, TUBB3, IL1R1, GDF15) were eventually identified and used to establish a novel IAGs signature. The Kaplan-Meier analysis revealed that patients with low-risk scores had longer recurrence-free survival (RFS) than those with high-risk scores in both GSE70769 and TCGA cohorts. Further, our signature was also proven to be a valuable independent prognostic factor for BCR. We also constructed a nomogram based on the gene signature and related clinicopathologic features, which excellently predict 1-year, 3-year and 5-year prognosis of localized PCa patients after RP. Moreover, functional enrichment analysis demonstrated the vital biological processes, and stratified GSEA revealed that a crucial immune-related pathway (T cell receptor signaling pathway) was notably enriched in the high-risk group. Conclusions: We successfully developed a novel robust IAGs signature that is powerful in BCR prediction in localized PCa patients after RP, and created a prognostic nomogram. In addition, the signature might help clinicians in selecting high-risk subpopulation, predicting survival status of patients and promoting more individualized therapies than traditional clinical factors.

Dataset Information

Genetic interaction analysis of TCF7L2 for biochemical recurrence after radical prostatectomy in localized prostate cancer.

Publications

Genetic interaction analysis of TCF7L2 for biochemical recurrence after radical prostatectomy in localized prostate cancer.

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