Faculty Bibliography

Genetic polymorphisms in vitamin D metabolism and signaling genes have been inconsistently associated with risk of breast cancer, though few studies have examined SNPs in vitamin D-related genes other than the vitamin D receptor (VDR) gene and particularly have not examined the association with the retinoid X receptor alpha (RXRA) gene which may be a key vitamin D pathway gene. We conducted a nested case-control study of 734 cases and 1435 individually matched controls from a population-based prospective cohort study, the Northern Sweden Mammary Screening Cohort. Tag and functional SNPs were genotyped for the VDR, cytochrome p450 24A1 (CYP24A1), and RXRA genes. We also genotyped specific SNPs in four other genes related to vitamin D metabolism and signaling (GC/VDBP, CYP2R1, DHCR7, and CYP27B1). SNPs in the CYP2R1, DHCR7, and VDBP gene regions that were associated with circulating 25(OH)D concentration in GWAS were also associated with plasma 25(OH)D in our study (p-trend <0.005). After taking into account the false discovery rate, these SNPs were not significantly associated with breast cancer risk, nor were any of the other SNPs or haplotypes in VDR, RXRA, and CYP24A1. We observed no statistically significant associations between polymorphisms or haplotypes in key vitamin D-related genes and risk of breast cancer. These results, combined with the observation in this cohort and most other prospective studies of no association of circulating 25(OH)D with breast cancer risk, do not support an association between vitamin D and breast cancer risk.

Recent whole genome melanoma sequencing studies have identified recurrent mutations in the gene encoding the catalytic subunit of serine/threonine phosphatase 6 (PPP6C/PP6C). However, the biochemical, functional, and clinical ramifications of these mutations are unknown. Sequencing PP6C from patients with melanoma (233 primary and 77 metastatic specimens) with extended prospective clinical outcome revealed a large number of hotspot mutations in patients with both primary and metastatic melanoma. Despite minimal association between stage and presence of PP6C mutations in patients with primary melanoma, a subpopulation of cells within each tumor did contain PP6C mutations, suggesting PP6C mutation is an early, but non-tumor-initiating event in melanoma. Among patients with primary melanoma with PP6C mutations, patients with stop mutations had significantly shorter recurrence-free survival compared with patients without stop mutations. In addition, PP6C mutations were independent of commonly observed BRAF and NRAS mutations. Biochemically, PP6C mutations could be classified as those that interact with PP6C regulatory subunits and those that do not. Mutations that did not bind to PP6C regulatory subunits were associated with increased phosphorylation of Aurora kinase, a PP6C substrate, and mitotic defects. However, both classes of PP6C mutations led to increased sensitivity to Aurora kinase inhibition. Together, these data support for the first time that PP6C mutations are molecularly, biochemically, and clinically heterogeneous. Implications: PP6C mutations have distinct functional and clinical consequences in melanoma, and confer sensitivity to Aurora A kinase inhibitors. Mol Cancer Res; 12(3); 433-9. (c)2013 AACR.

Molecular and genetic evidence suggests that DNA repair pathways may contribute to lymphoma susceptibility. Several studies have examined the association of DNA repair genes with lymphoma risk, but the findings from these reports have been inconsistent. Here we provide the results of a focused analysis of genetic variation in DNA repair genes and their association with the risk of non-Hodgkin's lymphoma (NHL). With a population of 1,297 NHL cases and 1,946 controls, we have performed a two-stage case/control association analysis of 446 single nucleotide polymorphisms (SNPs) tagging the genetic variation in 81 DNA repair genes. We found the most significant association with NHL risk in the ATM locus for rs227060 (OR = 1.27, 95% CI: 1.13-1.43, p = 6.77x10-5), which remained significant after adjustment for multiple testing. In a subtype-specific analysis, associations were also observed for the ATM locus among both diffuse large B-cell lymphomas (DLBCL) and small lymphocytic lymphomas (SLL), however there was no association observed among follicular lymphomas (FL). In addition, our study provides suggestive evidence of an interaction between SNPs in MRE11A and NBS1 associated with NHL risk (OR = 0.51, 95% CI: 0.34-0.77, p = 0.0002). Finally, an imputation analysis using the 1,000 Genomes Project data combined with a functional prediction analysis revealed the presence of biologically relevant variants that correlate with the observed association signals. While the findings generated here warrant independent validation, the results of our large study suggest that ATM may be a novel locus associated with the risk of multiple subtypes of NHL.

BACKGROUND: Steadily high melanoma mortality rates urge for the availability of novel biomarkers with a more personalized ability to predict melanoma clinical outcomes. Germline risk variants are promising candidates for this purpose; however, their prognostic potential in melanoma has never been systematically tested. METHODS: We examined the effect of 108 melanoma susceptibility single nucleotide polymorphisms (SNPs), associated in recent GWAS with melanoma and melanoma-related phenotypes, on recurrence-free survival (RFS) and overall survival (OS), in 891 prospectively accrued melanoma patients. Cox proportional hazards models (Cox PH) were used to test the associations between 108 melanoma risk SNPs and RFS and OS adjusted by age at diagnosis, gender, tumor stage, histological subtype and other primary tumor characteristics. RESULTS: We identified significant associations for rs7538876 (RCC2) with RFS (HR = 1.48, 95% CI = 1.20-1.83, p = 0.0005) and rs9960018 (DLGAP1) with both RFS and OS (HR = 1.43, 95% CI = 1.07-1.91, p = 0.01, HR = 1.52, 95% CI = 1.09-2.12, p = 0.01, respectively) using multivariable Cox PH models. In addition, we developed a logistic regression model that incorporates rs7538876, rs9960018, primary tumor histological type and stage at diagnosis that has an improved discriminatory ability to classify 3-year recurrence (AUC = 82%) compared to histological type and stage alone (AUC = 78%). CONCLUSIONS: We identified associations between melanoma risk variants and melanoma outcomes. The significant associations observed for rs7538876 and rs9960018 suggest a biological implication of these loci in melanoma progression. The observed predictive patterns of associated variants with clinical end-points suggest for the first time the potential for utilization of genetic risk markers in melanoma prognostication.

Background: Small reported studies have provided some evidence implicating immune related genes in melanoma susceptibility and prognosis; however candidate selection of these prior efforts has been limited. In this study, we performed an analysis of germline variants in immuno-modulatory genes for their association with melanoma survival in a well characterized cohort of prospectively accrued melanoma patients. Methods: Germline DNA isolated from blood samples of 817 melanoma patients was genotyped for 94 SNPs tagging 55 immuno-modulatory genes using Sequenom iPLEX. Cox models were used to test associations between each SNP and recurrence-free and overall survival (RFS and OS), with adjustments for age, gender, subtype, thickness, ulceration, and anatomic site. ROC curves were constructed from different SNP/clinical covariate combinations and the area under the curve (AUC) was used to assess their utility in the classification of 3-year recurrence. Results: The SNP rs2796817 in TGFB2 had strong associations with both RFS (HR=3.8, CI 95%: 1.3-11, p=0.02) and OS (HR=5.5, CI 95%: 1.6-19, p=0.029). Other interesting associations with OS came from IRF8 (rs4843861, HR=0.62, CI 95%: 0.39-0.99, p=0.017), CCL5 (rs4796120, HR=7.6, CI 95%: 2.3-25, p=0.035), and CD8A (rs3810831, HR=2.4, CI 95%: 0.91-6.2, p=0.048). A multivariate model including stage, subtype, and one of the SNPs (rs3810831 from CD8A), was shown to improve the AUC when compared to a model including only stage and subtype (0.77 vs. 0.79). Conclusions: We identified several immune-related loci associated with melanoma RFS and OS. The strongest association, rs2796817, maps in TGFB2, which among other functions suppresses IL-2 dependent T-cell growth. In addition to other associations found in the study these findings provide evidence for the involvement of immuno-modulatory genes in melanoma prognosis and suggest further investigations of immune related genes in disease progression. This is currently underway in the second stage validation an!

Background: Epigenetic regulatory pathways are intensely studied for their involvement in breast tumorigenesis, however little is currently known about the genetic variation in epigenome components contributing to the risk and/or prognosis of breast cancer. In this study we have tested how the novel germline genetic signatures identified in epigenetic regulatory genes (ERGs) may potentially contribute to clinical prediction of breast cancer risk. Methods: We have genotyped 711 SNPs tagging 87 ERGs in 1985 breast cancer cases and 1609 controls, using Sequenom i-Plex. The samples were of white European origin with the fraction of Ashkenazi Jewish (AJ) ancestry (n=1642). The association of SNPs with breast cancer risk was assessed using logistic regression, adjusted by age, AJ status and estrogen-receptor (ER) status. The predictive ability of SNP signatures was tested by ROC curves using logistic regression fitting the SNP/clinical covariate models, and the area under the curve (AUC) was used to assess their utility in the classification of breast cancer risk. Results: We have identified the signature of 20 SNPs tagging 13 ERGs, significantly associated with breast cancer risk. The strongest association has been observed for RUNX1 (rs7280097, OR=0.83, CI 95%: 0.71-0.94, p=0.006) and PRDM16 (rs12135987, OR=1.22, CI 95%: 1.06-1.42, p=0.007). The inclusion of predictor variables (age, AJ status, ER status) and 20 associated SNPs in logistic regression ROC curve analysis yielded in best fitting model involving 10 SNPs tagging 8 ERGs with AUC of 0.723, compared to 0.660 with predictor variables alone (p=0.003). Conclusions: We have identified a signature of 20 SNPs in epigenetic regulatory genes (20-SNP-ERG) significantly associated with breast cancer risk. In addition, the incorporation of 10 SNPs from 20-SNP-ERG into risk prediction model increases the ability to classify breast cancer risk in addition to other clinical and demographic covariates. The results suggest the promising clinical potential!