No association between variant DNA repair genes and prostate cancer risk among men of African descent.

BACKGROUND: Recent reports hypothesize that multiple variant DNA repair gene interactions influence cancer susceptibility. However, studies identifying high-risk cancer-related genes use single gene approaches that lack the statistical rigor to model higher order interactions. METHODS: To address this issue, we systematically evaluated individual and joint modifying effects of commonly studied polymorphic base and nucleotide excision repair genes relative to prostate cancer (PCA) risk using conventional logistic regression models and multifactor dimensionality reduction (MDR). We hypothesized that inheriting two or more compromised DNA repair loci may increase PCA risk due to altered gene product function. Six genetic alterations were evaluated using germ-line DNA samples from 208 PCA cases and 665 disease-free controls via TaqMan polymerase chain reaction. RESULTS: With the exception of XPD 312, no association existed between individual DNA repair single-nucleotide polymorphisms (SNPs) and PCA. Individuals with the XPD 312 Asn/Asn genotype had an 8.6-fold increase in risk (OR = 8.59; 95% CI = 1.81-40.66). We did not observe any significant single gene or gene-gene interactions based on MDR modeling. CONCLUSIONS: Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multilocus interactions in relation to cancer susceptibility.

Angiogenesis-associated sequence variants relative to breast cancer recurrence and survival.

INTRODUCTION: Breast cancer (BrCA) risk stratification using clinico-pathological biomarkers helps improve disease prognosis prediction. However, disease recurrence rates remain unfavorable and individualized clinical management strategies are needed. Consequently, we evaluated the influence of 14 sequence variants detected in IL-10, TGF-ß1, VEGF, and their associated receptors as effective predictors of BrCA clinical outcomes. METHODS: Tumor DNA samples collected from 441 BrCA patients were genotyped using TaqMan-PCR. Most selected targets alter cytokine serum/plasma levels or signaling pathways. Relationships between genetic profiles and recurrence as well as disease-related mortality were evaluated using cumulative incidence curves and competing risk regression models. RESULTS: The VEGF(-2578)C allele was associated with a 1.3- to 1.6-fold increase in BrCA recurrence (HR(trend) = 1.28; 95% CI = 0.96-1.72) and disease-related mortality (HR(trend) = 1.56; 95% CI = 0.93-2.56). Although this marker was marginally significant relative to BrCA outcomes, there were substantial gains in the 5- and 8-year predictive accuracy compared to standard prognostic indicators. Among ER(+)/PR(+) status patients, there was a significant impact of the VEGF(-2578)CC genotype on disease recurrence and predictive accuracy. CONCLUSIONS: Our findings suggest inheritance of the VEGF(-2578)C allele could serve as an independent prognostic indicator of BrCA prognosis. The VEGF(-2578) marker may have clinical implications among a subset of ER(+)/PR(+) patients with an aggressive phenotype. Because the VEGF(-2578)C allele is linked to high VEGF expression, this cytokine is a potential prognostic and targeted clinical management tool.

8q24 sequence variants in relation to prostate cancer risk among men of African descent: a case-control study.

BACKGROUND: Human chromosome 8q24 has been implicated in prostate tumorigenesis. METHODS: Consequently, we evaluated seven 8q24 sequence variants relative to prostate cancer (PCA) in a case-control study involving men of African descent. Genetic alterations were detected in germ-line DNA from 195 incident PCA cases and 531 controls using TaqMan polymerase chain reaction (PCR). RESULTS: Inheritance of the 8q24 rs16901979 T allele corresponded to a 2.5-fold increase in the risk of developing PCA for our test group. These findings were validated using multifactor dimensionality reduction (MDR) and permutation testing (p = 0.038). The remaining 8q24 targets were not significantly related to PCA outcomes. CONCLUSIONS: Although compelling evidence suggests that the 8q24 rs16901979 locus may serve as an effective PCA predictor, our findings require additional evaluation in larger studies.

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among men of African descent: a case-control study.

BACKGROUND: Polymorphisms in glutathione S-transferase (GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected GST genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic GSTs (M1, T1, and P1) alone and combined with cigarette smoking on PCA susceptibility. METHODS: In order to evaluate the effects of GST polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of GSTM1 and GSTT1 gene deletions, GSTP1 105 Val and cigarette smoking on PCA risk. RESULTS: We observed a moderately significant association between risk among men possessing at least one variant GSTP1 105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among GSTM1 (OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and GSTT1 (OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the GSTM1-GSTP1 pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the GSTP1 Val marker. Notably, the GSTM1-GSTP1 axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the GST SNPs and PCA. CONCLUSION: A moderately significant association was observed between PCA risk and men possessing at least one variant GSTP1 105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the GSTP1 (Val/Val) and GSTM1 (*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting GSTP1 105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility.

Whole genome sequencing reveals potential targets for therapy in patients with refractory KRAS mutated metastatic colorectal cancer.

BACKGROUND: The outcome of patients with metastatic colorectal carcinoma (mCRC) following first line therapy is poor, with median survival of less than one year. The purpose of this study was to identify candidate therapeutically targetable somatic events in mCRC patient samples by whole genome sequencing (WGS), so as to obtain targeted treatment strategies for individual patients. METHODS: Four patients were recruited, all of whom had received > 2 prior therapy regimens. Percutaneous needle biopsies of metastases were performed with whole blood collection for the extraction of constitutional DNA. One tumor was not included in this study as the quality of tumor tissue was not sufficient for further analysis. WGS was performed using Illumina paired end chemistry on HiSeq2000 sequencing systems, which yielded coverage of greater than 30X for all samples. NGS data were processed and analyzed to detect somatic genomic alterations including point mutations, indels, copy number alterations, translocations and rearrangements. RESULTS: All 3 tumor samples had KRAS mutations, while 2 tumors contained mutations in the APC gene and the PIK3CA gene. Although we did not identify a TCF7L2-VTI1A translocation, we did detect a TCF7L2 mutation in one tumor. Among the other interesting mutated genes was INPPL1, an important gene involved in PI3 kinase signaling. Functional studies demonstrated that inhibition of INPPL1 reduced growth of CRC cells, suggesting that INPPL1 may promote growth in CRC. CONCLUSIONS: Our study further supports potential molecularly defined therapeutic contexts that might provide insights into treatment strategies for refractory mCRC. New insights into the role of INPPL1 in colon tumor cell growth have also been identified. Continued development of appropriate targeted agents towards specific events may be warranted to help improve outcomes in CRC.

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

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.