Melanoma, which is increasing in incidence, has the capacity to metastasize early and its course is rarely impacted by medical intervention. Because of the pronounced difference in survival between localized and metastatic disease, it is imperative to diagnose melanoma in its earliest form;however, early diagnosis is confounded by the overlap of the clinical and histopathological appearances of melanomas with highly prevalent benign nevi (moles). Molecular pathology has proven useful as an adjunct to diagnosis rendered by histopathologists for enhancing early cancer detection. Tumor DNA-methylation holds promise as a tool for molecular pathology because aberrant promoter methylation, which often results in the abnormal silencing of tumor suppressor genes, has been shown to occur widely in human melanomas. High-throughput methylation arrays, a new technology which can simultaneously evaluate promoter methylation in many cancer-related genes, has potential for discovery of candidate DNA-methylation sites useful for melanoma diagnosis. However, these arrays have been developed for use on unfixed tissues, and their validity and reproducibility has not been determined on formalin-fixed paraffin-embedded (FFPE) tissue, which is typically the only diagnostic tissue available for primary melanomas and nevi. The central hypothesis of our proposal is that DNA methylation patterns exist that can discriminate melanomas from benign moles with high sensitivity, specificity, and reproducibility;and high-throughput DNA-methylation assays are a feasible method for discovery of these patterns in diagnostic FFPE tissues. A goal for this R21 is to assess whether formalin-fixed tissues are a suitable source of DNA for high-throughput methylation array profiling by assessing the reproducibility of results between matched formalin-fixed and frozen melanoma specimens and between formalin-fixed duplicates. Importantly, as a second aim, a 'dose response curve'will be determined to assess the proportion of melanocytic tumor to surrounding non-melanocytic tissue necessary for tumor DNAmethylation detection using high-throughput arrays, and these results will establish the proportion tumor below which selective procurement using laser capture microdissection will be done prospectively. Furthermore, this application proposes to identify a 'proof-of-principle'methylation-signature algorithm which will differentiate melanomas from benign moles. This study will be a first step toward the development of diagnostic methylation assays that could be used to standardize melanoma diagnosis, thereby decreasing under- and over-treatment of melanocytic lesions.
Melanoma has a predilection to metastasize when only a few millimeters in depth; however, early detection and diagnosis are difficult due to the overlap in clinical and histologic appearances of melanomas with highly prevalent benign moles. DNA methylation has emerged as a sensitive technique for assessment of occult cancer in biological samples, and high-throughput methylation arrays, a new technology which can simultaneously evaluate promoter methylation in many cancer-related genes, holds the promise of discovery of candidate DNA-methylations useful for melanoma diagnosis. The goal for this R21 is to develop the application of high-throughput DNA-methylation arrays for use on formalyn-fixed tissues embedded in paraffin blocks, which is typically the only diagnostic tissue available for primary melanomas and nevi, and work towards developing a practical clinical assay for molecular diagnosis of melanoma at the earliest possible stage, while avoiding false-positives and minimizing the overall cost of diagnosis.
|Carson, Craig C; Moschos, Stergios J; Edmiston, Sharon N et al. (2015) IL2 Inducible T-cell Kinase, a Novel Therapeutic Target in Melanoma. Clin Cancer Res 21:2167-76|
|Thomas, Nancy E; Slater, Nathaniel A; Edmiston, Sharon N et al. (2014) DNA methylation profiles in primary cutaneous melanomas are associated with clinically significant pathologic features. Pigment Cell Melanoma Res 27:1097-105|
|Kuan, Pei Fen; Chiang, Derek Y (2012) Integrating prior knowledge in multiple testing under dependence with applications to detecting differential DNA methylation. Biometrics 68:774-83|
|Conway, Kathleen; Edmiston, Sharon N; Khondker, Zakaria S et al. (2011) DNA-methylation profiling distinguishes malignant melanomas from benign nevi. Pigment Cell Melanoma Res 24:352-60|
|Kuan, Pei Fen; Wang, Sijian; Zhou, Xin et al. (2010) A statistical framework for Illumina DNA methylation arrays. Bioinformatics 26:2849-55|