Sharon N. Edmiston

Number of Nevi and Early-Life Ambient UV Exposure Are Associated with BRAF-Mutant Melanoma

Malignant melanomas often contain BRAF or NRAS mutations, but the relationship of these mutations to ambient UV exposure in combination with phenotypic characteristics is unknown. In a population-based case series from North Carolina, 214 first primary invasive melanoma patients in the year 2000 were interviewed regarding their risk factors. Ambient solar UV exposures were estimated using residential histories and a satellite-based model. Cases were grouped on the basis of BRAF and NRAS somatic mutations, determined using single-strand conformation polymorphism analysis and radiolabeled DNA sequencing, and the risk profiles of these groups were compared. Mutually exclusive BRAF-mutant and NRAS-mutant cases occurred at frequencies of 43.0% and 13.6% with mean ages at diagnosis of 47.3 and 62.1 years, respectively. Tumors from patients with >14 back nevi were more likely to harbor either a BRAF mutation [age-adjusted odds ratio (OR), 3.2; 95% confidence interval (95% CI), 1.4-7.0] or an NRAS mutation (age-adjusted OR, 1.7; 95% CI, 0.6-4.8) compared with patients with 0 to 4 back nevi. However, BRAF-mutant and NRAS-mutant tumors were distinctive in that BRAF-mutant tumors were characteristic of patients with high early-life ambient UV exposure (adjusted OR, 2.6; 95% CI, 1.2-5.3). When ambient UV irradiance was analyzed by decadal age, high exposure at ages 0 to 20 years was associated with BRAF-mutant cases, whereas high exposure at ages 50 and 60 years was characteristic of NRAS-mutant cases. Our results suggest that although nevus propensity is important for the occurrence of both BRAF and NRAS-mutant melanomas, ambient UV irradiance influences risk differently based on the age of exposure. The association of BRAF mutations with early-life UV exposure provides evidence in support of childhood sun protection for melanoma prevention. (Cancer Epidemiol Biomarkers Prev 2007;16(5):991–7)

FAK overexpression and p53 mutations are highly correlated in human breast cancer

Focal adhesion kinase (FAK) is overexpressed in a number of tumors, including breast cancer. Another marker of breast cancer tumorigenesis is the tumor suppressor gene p53 that is frequently mutated in breast cancer. In the present study, our aim was to find a correlation between FAK overexpression, p53 expression and mutation status in a population‐based series of invasive breast cancer tumors from the Carolina Breast Cancer Study. Immunohistochemical analyses of 622 breast cancer tumors revealed that expression of FAK and p53 were highly correlated (p = 0.0002) and FAK positive tumors were 1.8 times more likely to be p53 positive compared to FAK negative tumors [odds ratio (OR) = 1.8; 95% Confidence Interval (CI) 1.2–2.8, adjusted for age, race and stage at diagnosis]. Tumors positive for p53 expression showed higher intensity of FAK staining (p < 0.0001) and higher percent of FAK positive staining (p < 0.0005). From the same study, we evaluated 596 breast tumors for mutations in the p53 gene, using single strand conformational polymorphism and sequencing. Statistical analyses were performed to determine the correlation between p53 mutation status and FAK expression in these tumors. We found that FAK expression and p53 mutation were positively correlated (p < 0.0001) and FAK positive tumors were 2.5 times more likely to be p53 mutation positive compared to FAK negative tumors [adjusted OR = 2.5, 95% CI 1.6–3.9]. This is the first analysis demonstrating a high correlation between FAK expression and p53 mutations in a population‐based series of breast tumors.

DNA‐methylation profiling distinguishes malignant melanomas from benign nevi

DNA methylation, an epigenetic alteration typically occurring early in cancer development, could aid in the molecular diagnosis of melanoma. We determined technical feasibility for high‐throughput DNA‐methylation array‐based profiling using formalin‐fixed paraffin‐embedded tissues for selection of candidate DNA‐methylation differences between melanomas and nevi. Promoter methylation was evaluated in 27 common benign nevi and 22 primary invasive melanomas using a 1505 CpG site microarray. Unsupervised hierarchical clustering distinguished melanomas from nevi; 26 CpG sites in 22 genes were identified with significantly different methylation levels between melanomas and nevi after adjustment for age, sex, and multiple comparisons and with β‐value differences of ≥0.2. Prediction analysis for microarrays identified 12 CpG loci that were highly predictive of melanoma, with area under the receiver operating characteristic curves of >0.95. Of our panel of 22 genes, 14 were statistically significant in an independent sample set of 29 nevi (including dysplastic nevi) and 25 primary invasive melanomas after adjustment for age, sex, and multiple comparisons. This first report of a DNA‐methylation signature discriminating melanomas from nevi indicates that DNA methylation appears promising as an additional tool for enhancing melanoma diagnosis.

No Association Between the MDM2 −309 T/G Promoter Polymorphism and Breast Cancer in African-Americans or Whites

MDM2, a protein that binds and inactivates the tumor suppressor p53, is overexpressed in a variety of human cancers ([1][1]). Bond et al. ([2][2]) recently identified a single nucleotide polymorphism in the MDM2 gene, −309 T/G within the MDM2 promoter (database for single nucleotide polymorphism

The estrogen receptor-α A908G (K303R) mutation occurs at a low frequency in invasive breast tumors: results from a population-based study

IntroductionEvidence suggests that alterations in estrogen signaling pathways, including estrogen receptor-α (ER-α), occur during breast cancer development. A point mutation in ER-α (nucleotide A908G), producing an amino acid change from lysine to arginine at codon 303 (K303R) results in receptor hypersensitivity to estrogen. This mutation was initially reported in one-third of hyperplastic benign breast lesions, although several recent studies failed to detect it in benign or malignant breast tissues.MethodsWe screened 653 microdissected, newly diagnosed invasive breast tumors from patients in the Carolina Breast Cancer Study, a population-based case-control study of breast cancer in African American and white women in North Carolina, for the presence of the ER-α A908G mutation by using single-strand conformational polymorphism (SSCP) analysis and 33P-cycle sequencing.ResultsWe detected the ER-α A908G mutation in 37 of 653 (5.7%) breast tumors. The absence of this mutation in germline DNA confirmed it to be somatic. Three tumors exhibited only the mutant G base at nucleotide 908 on sequencing, indicating that the wild-type ER-α allele had been lost. The ER-α A908G mutation was found more frequently in higher-grade breast tumors (odds ratio (OR) 2.83; 95% confidence interval (CI) 1.09 to 7.34, grade II compared with grade I), and in mixed lobular/ductal tumors (OR 2.10; 95% CI 0.86 to 5.12) compared with ductal carcinomas, although the latter finding was not statistically significant.ConclusionThis population-based study, the largest so far to screen for the ER-α A908G mutation in breast cancer, confirms the presence of the mutant in invasive breast tumors. The mutation was associated with higher tumor grade and mixed lobular/ductal breast tumor histology.

DNA methylation profiling in the Carolina Breast Cancer Study defines cancer subclasses differing in clinicopathologic characteristics and survival

IntroductionBreast cancer is a heterogeneous disease, with several intrinsic subtypes differing by hormone receptor (HR) status, molecular profiles, and prognosis. However, the role of DNA methylation in breast cancer development and progression and its relationship with the intrinsic tumor subtypes are not fully understood.MethodsA microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 breast tumors from the Carolina Breast Cancer Study, a population-based study of invasive breast cancer.ResultsConsensus clustering using methylation (β) values for the 167 most variant CpG loci defined four clusters differing most distinctly in HR status, intrinsic subtype (luminal versus basal-like), and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified 266 differentially methylated CpG loci with considerable overlap. Genes relatively hypermethylated in HR+, luminal A, or p53 wild-type breast cancers included FABP3, FGF2, FZD9, GAS7, HDAC9, HOXA11, MME, PAX6, POMC, PTGS2, RASSF1, RBP1, and SCGB3A1, whereas those more highly methylated in HR-, basal-like, or p53 mutant tumors included BCR, C4B, DAB2IP, MEST, RARA, SEPT5, TFF1, THY1, and SERPINA5. Clustering also defined a hypermethylated luminal-enriched tumor cluster 3 that gene ontology analysis revealed to be enriched for homeobox and other developmental genes (ASCL2, DLK1, EYA4, GAS7, HOXA5, HOXA9, HOXB13, IHH, IPF1, ISL1, PAX6, TBX1, SOX1, and SOX17). Although basal-enriched cluster 2 showed worse short-term survival, the luminal-enriched cluster 3 showed worse long-term survival but was not independently prognostic in multivariate Cox proportional hazard analysis, likely due to the mostly early stage cases in this dataset.ConclusionsThis study demonstrates that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status and may show heterogeneity within tumor subclass. Among HR+ breast tumors, a subset exhibiting a gene signature characterized by hypermethylation of developmental genes and poorer clinicopathologic features may have prognostic value and requires further study. Genes differentially methylated between clinically important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to establishing and maintaining tumor phenotypes and clinical outcomes.

Altered-function p53 missense mutations identified in breast cancers can have subtle effects on transactivation

Mutations of the sequence-specific master regulator p53 that alter transactivation function from promoter response elements (RE) could result in changes in the strength of gene activation or spectra of genes regulated. Such mutations in this tumor suppressor might lead to dramatic phenotypic changes and diversification of cell responses to stress. We have determined “functional fingerprints” of sporadic breast cancer–related p53 mutants, many of which are also associated with familial cancer proneness such as the Li-Fraumeni syndrome and germline BRCA1/2 mutant-associated cancers. The ability of p53, wild-type and mutants, to transactivate from 11 human target REs has been assessed at variable expression levels using a cellular, isogenomic yeast model system that allows for the rapid analysis of p53 function using a qualitative and a quantitative reporter. Among 50 missense mutants, 29 were classified as loss of function. The remaining 21 retained transactivation toward at least one RE. At high levels of galactose-induced p53 expression, 12 of 21 mutants that retain transactivation seemed similar to wild-type. When the level of galactose was reduced, transactivation defects could be revealed, suggesting that some breast cancer–related mutants can have subtle changes in transcription. These findings have been compared with clinical data from an ongoing neoadjuvant chemotherapy treatment trial for locally advanced breast tumors. The functional and nonfunctional missense mutations may distinguish tumors in terms of demographics, appearance, and relapse, implying that heterogeneity in the functionality of specific p53 mutations could affect clinical behavior and outcome. Mol Cancer Res; 8(5); 701–16. ©2010 AACR.

Relationship between Germline MC1R Variants and BRAF-Mutant Melanoma in a North Carolina Population-Based Study

A few previous studies have examined the relationship between germline melanocortin-1 receptor (MC1R) status and somatic BRAF mutations in melanoma. Two publications reported strong associations in three independent populations (two from Italy and one from San Francisco) (Fargnoli et al., 2008; Landi et al., 2006), while a more recent publication found no association in an Australian population-based study (Hacker et al., 2009). We report our finding of no significant association between MC1R status and BRAF-mutant melanomas in a population-based study of malignant melanoma in North Carolina.

Body Mass Index Is Associated with Gene Methylation in Estrogen Receptor–Positive Breast Tumors

Background: Although obesity is associated with breast cancer incidence and prognosis, the underlying mechanisms are poorly understood. Identification of obesity-associated epigenetic changes in breast tissue may advance mechanistic understanding of breast cancer initiation and progression. The goal of this study, therefore, was to investigate associations between obesity and gene methylation in breast tumors. Methods: Using the Illumina GoldenGate Cancer I Panel, we estimated the association between body mass index (BMI) and gene methylation in 345 breast tumor samples from phase I of the Carolina Breast Cancer Study, a population-based case–control study. Multivariable linear regression was used to identify sites that were differentially methylated by BMI. Stratification by tumor estrogen receptor (ER) status was also conducted. Results: In the majority of the 935 probes analyzed (87%), the average beta value increased with obesity (BMI ≥ 30). Obesity was significantly associated with differential methylation (FDR q < 0.05) in just two gene loci in breast tumor tissue overall and in 21 loci among ER-positive tumors. Obesity was associated with methylation of genes that function in immune response, cell growth, and DNA repair. Conclusions: Obesity is associated with altered methylation overall, and with hypermethylation among ER-positive tumors in particular, suggesting that obesity may influence the methylation of genes with known relevance to cancer. Some of these differences in methylation by obese status may influence levels of gene expression within breast cells. Impact: If our results are validated, obesity-associated methylation sites could serve as targets for prevention and treatment research. Cancer Epidemiol Biomarkers Prev; 24(3); 580–6. ©2015 AACR.

Racial Variation in Breast Tumor Promoter Methylation in the Carolina Breast Cancer Study

Background: African American (AA) women are diagnosed with more advanced breast cancers and have worse survival than white women, but a comprehensive understanding of the basis for this disparity remains unclear. Analysis of DNA methylation, an epigenetic mechanism that can regulate gene expression, could help to explain racial differences in breast tumor clinical biology and outcomes. Methods: DNA methylation was evaluated at 1,287 CpGs in the promoters of cancer-related genes in 517 breast tumors of AA (n = 216) or non-AA (n = 301) cases in the Carolina Breast Cancer Study (CBCS). Results: Multivariable linear regression analysis of all tumors, controlling for age, menopausal status, stage, intrinsic subtype, and multiple comparisons [false discovery rate (FDR)], identified seven CpG probes that showed significant (adjusted P < 0.05) differential methylation between AAs and non-AAs. Stratified analyses detected an additional four CpG probes differing by race within hormone receptor–negative (HR−) tumors. Genes differentially methylated by race included DSC2, KCNK4, GSTM1, AXL, DNAJC15, HBII-52, TUSC3, and TES; the methylation state of several of these genes may be associated with worse survival in AAs. TCGA breast tumor data confirmed the differential methylation by race and negative correlations with expression for most of these genes. Several loci also showed racial differences in methylation in peripheral blood leukocytes (PBL) from CBCS cases, indicating that these variations were not necessarily tumor-specific. Conclusions: Racial differences in the methylation of cancer-related genes are detectable in both tumors and PBLs from breast cancer cases. Impact: Epigenetic variation could contribute to differences in breast tumor development and outcomes between AAs and non-AAs. Cancer Epidemiol Biomarkers Prev; 24(6); 921–30. ©2015 AACR.