title: 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.
authors.affiliation: Department of Pharmacology & Toxicology, School of Medicine, University of Louisville-UofL, Louisville, KY, USA.
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Lavender
authors.forename: Erica N
authors.initials: EN
authors.lastname: Rogers
authors.forename: Susan
authors.initials: S
authors.lastname: Yeyeodu
authors.forename: James
authors.initials: J
authors.lastname: Rudd
authors.forename: Ting
authors.initials: T
authors.lastname: Hu
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.forename: Guy N
authors.initials: GN
authors.lastname: Brock
authors.forename: Kevin S
authors.initials: KS
authors.lastname: Kimbro
authors.forename: Jason H
authors.initials: JH
authors.lastname: Moore
authors.forename: David W
authors.initials: DW
authors.lastname: Hein
authors.forename: La Creis R
authors.initials: LC
authors.lastname: Kidd
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017209:Apoptosis / Q000235:genetics*; D016022:Case-Control Studies; D019277:Entropy; D014644:Genetic Variation; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D058011:Multifactor Dimensionality Reduction; D009367:Neoplasm Staging; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D051057:Proto-Oncogene Proteins c-akt / Q000235:genetics; D012307:Risk Factors
chemical_list: D051057:Proto-Oncogene Proteins c-akt