Dataset Information

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer.

ABSTRACT: BACKGROUND:Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohibitive amount of data needed to account for multiple hypothesis testing. METHODS:To address this issue, we systematically prioritized and evaluated individual effects and complex interactions among 172 apoptotic SNPs in relation to PCA risk and aggressive disease (i.e., Gleason score ? 7 and tumor stages III/IV). Single and joint modifying effects on PCA outcomes among European-American men were analyzed using statistical epistasis networks coupled with multi-factor dimensionality reduction (SEN-guided MDR). The case-control study design included 1,175 incident PCA cases and 1,111 controls from the prostate, lung, colo-rectal, and ovarian (PLCO) cancer screening trial. Moreover, a subset analysis of PCA cases consisted of 688 aggressive and 488 non-aggressive PCA cases. SNP profiles were obtained using the NCI Cancer Genetic Markers of Susceptibility (CGEMS) data portal. Main effects were assessed using logistic regression (LR) models. Prior to modeling interactions, SEN was used to pre-process our genetic data. SEN used network science to reduce our analysis from > 36 million to < 13,000 SNP interactions. Interactions were visualized, evaluated, and validated using entropy-based MDR. All parametric and non-parametric models were adjusted for age, family history of PCA, and multiple hypothesis testing. RESULTS:Following LR modeling, eleven and thirteen sequence variants were associated with PCA risk and aggressive disease, respectively. However, none of these markers remained significant after we adjusted for multiple comparisons. Nevertheless, we detected a modest synergistic interaction between AKT3 rs2125230-PRKCQ rs571715 and disease aggressiveness using SEN-guided MDR (p = 0.011). CONCLUSIONS:In summary, entropy-based SEN-guided MDR facilitated the logical prioritization and evaluation of apoptotic SNPs in relation to aggressive PCA. The suggestive interaction between AKT3-PRKCQ and aggressive PCA requires further validation using independent observational studies.

SUBMITTER: Lavender NA

PROVIDER: S-EPMC3355002 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer.

Lavender Nicole A NA Rogers Erica N EN Yeyeodu Susan S Rudd James J Hu Ting T Zhang Jie J Brock Guy N GN Kimbro Kevin S KS Moore Jason H JH Hein David W DW Kidd La Creis R LC

BMC medical genomics 20120430

<h4>Background</h4>Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohib ...[more]

PMID: 22546513

Similar Datasets

Project description:Background: There is an urgent need for the detection of aggressive prostate cancer. Glycoproteins play essential roles in cancer development, while urine is a noninvasive and easily obtainable biological fluid that contains secretory glycoproteins from the urogenital system. Therefore, here we aimed to identify urinary glycoproteins that are capable of differentiating aggressive from non-aggressive prostate cancer. Methods: Quantitative mass spectrometry data of glycopeptides from a discovery cohort comprised of 74 aggressive (Gleason score ≥8) and 68 non-aggressive (Gleason score = 6) prostate cancer urine specimens were acquired via a data independent acquisition approach. The glycopeptides showing distinct expression profiles in aggressive relative to non-aggressive prostate cancer were further evaluated for their performance in distinguishing the two groups either individually or in combination with others using repeated 5-fold cross validation with logistic regression to build predictive models. Predictive models showing good performance from the discovery cohort were further evaluated using a validation cohort. Results: Among the 20 candidate glycoproteins, urinary ACPP outperformed the other candidates. Urinary ACPP can also serve as an adjunct to serum PSA to further improve the discrimination power for aggressive prostate cancer (AUC= 0.82, 95% confidence interval 0.75 to 0.89). A three-signature panel including urinary ACPP, urinary CLU, and serum PSA displayed the ability to distinguish aggressive prostate cancer from non-aggressive prostate cancer with an AUC of 0.86 (95% confidence interval 0.8 to 0.92). Another three-signature panel containing urinary ACPP, urinary LOX, and serum PSA also demonstrated its ability in recognizing aggressive prostate cancer (AUC=0.82, 95% confidence interval 0.75 to 0.9). Moreover, consistent performance was observed from each panel when evaluated using a validation cohort. Conclusion: We have identified glycopeptides of urinary glycoproteins associated with aggressive prostate cancer using a quantitative mass spectrometry-based glycoproteomic approach and demonstrated their potential to serve as noninvasive urinary glycoprotein biomarkers worthy of further validation by a multi-center study.

Project description:BackgroundMajority of prostate cancer (PCa) deaths are attributed to localized high-grade aggressive tumours which progress rapidly to metastatic disease. A critical unmet need in clinical management of PCa is discovery and characterization of the molecular drivers of aggressive tumours. The development and progression of aggressive PCa involve genetic and epigenetic alterations occurring in the germline, somatic (tumour), and epigenomes. To date, interactions between genes containing germline, somatic, and epigenetic mutations in aggressive PCa have not been characterized. The objective of this investigation was to elucidate the genomic-epigenomic interaction landscape in aggressive PCa to identify potential drivers aggressive PCa and the pathways they control. We hypothesized that aggressive PCa originates from a complex interplay between genomic (both germline and somatic mutations) and epigenomic alterations. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect gene expression, molecular networks, and signaling pathways which in turn drive aggressive PCa.MethodsWe addressed these hypotheses by performing integrative data analysis combining information on germline mutations from genome-wide association studies with somatic and epigenetic mutations from The Cancer Genome Atlas using gene expression as the intermediate phenotype.ResultsThe investigation revealed signatures of genes containing germline, somatic, and epigenetic mutations associated with aggressive PCa. Aberrant DNA methylation had effect on gene expression. In addition, the investigation revealed molecular networks and signalling pathways enriched for germline, somatic, and epigenetic mutations including the STAT3, PTEN, PCa, ATM, AR, and P53 signalling pathways implicated in aggressive PCa.ConclusionsThe study demonstrated that integrative analysis combining diverse omics data is a powerful approach for the discovery of potential clinically actionable biomarkers, therapeutic targets, and elucidation of oncogenic interactions between genomic and epigenomic alterations in aggressive PCa.

Project description:BackgroundTelomeres play important roles in cancer initiation and progression. The aim of this study is to investigate whether leukocyte telomere length (LTL) is associated with aggressive prostate cancer (PCa).MethodsWe measured relative LTL in a cohort of 1,889 white PCa patients who were treated and followed up at the University of Texas MD Anderson Cancer Center and assessed its associations with aggressive disease characteristics at diagnosis and biochemical recurrence (BCR) after active treatments (radical prostatectomy and radiotherapy). We further used a Mendelian randomization (MR) approach to compute a weighted genetic risk score (GRS) predictive of LTL using 10 established LTL-associated genetic variants and determined whether this GRS is associated with aggressive PCa.FindingsLTL was significantly shorter in patients with higher Gleason scores at diagnosis. Dichotomized at the median value of LTL, patients with short LTL exhibited a 2.74-fold (95% confidence interval, 1.79-4.18, P = 3.11 × 10-6) increased risk of presenting with GS≥8 disease than those with long LTL in multivariate logistic regression analysis. Moreover, shorter LTL was significantly associated with an increased risk of BCR (hazard ratio = 1.53, 95% confidence interval, 1.01-2.34) compared to longer LTL in localized patients receiving prostatectomy or radiotherapy with a significant dose-response association (P for trend = 0.017) in multivariate Cox proportional hazards regression analysis. In MR analysis, genetically predicted short LTL was also associated with an increased risk of BCR (HR=1.73, 95% CI, 1.08-2.78).InterpretationOur results showed for the first time that LTL was shorter in PCa patients with high Gleason scores and that short LTL and genetically predicted short LTL are associated with worse prognosis in PCa patients receiving prostatectomy or radiotherapy.FundingCancer Prevention and Research Institute of Texas (CPRIT) grant (RP140556), National Cancer Institute Specialized Program of Research Excellence (SPORE) grant (CA140388), and MD Anderson Cancer Center start-up fund.

Dataset Information

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer.

Publications

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets