A Case Report - Volatile Metabolomic Signature of Malignant Melanoma using Matching Skin as a Control
- *Corresponding Author:
- Dr. Tatjana Abaffy, RMSB
Molecular and Cellular Pharmacology
Miller School of Medicine, University of Miami, Miami, Fl 33136
Tel: 305 243-1508
Fax: 305 243-455
E-mail: [email protected]
Received Date: April 18, 2011; Accepted Date: June 30, 2011; Published Date: July 12, 2011
Citation: Abaffy T, Möller M, Riemer DD, Milikowski C, DeFazio RA (2011) A Case Report - Volatile Metabolomic Signature of Malignant Melanoma using Matching Skin as a Control . J Cancer Sci Ther 3: 140-144. doi: 10.4172/1948-5956.1000076
Copyright: © 2011 Abaffy T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Melanoma is the most serious form of skin cancer. The quest for melanoma diagnostic biomarkers is paramount since early detection of melanoma and surgical excision represent the only effective treatment of this capricious disease. Our recent study tested the hypothesis that melanoma forms a unique volatile signature that is different than control, healthy tissue. Here, we are reporting a case study, the analysis of the volatile metabolic signature of a malignant melanoma using matched, non-neoplastic skin tissue from the same patient as a control. This is a significant improvement in the methodology, since it is well known that diet, skin type, genetic background, age, sex and environment all contribute to individual variation in the skin volatile signature. In the present study, we have identified 32 volatile compounds; 9 volatile compounds were increased in melanoma when compared to normal skin and 23 volatile compounds were detected only in melanoma and not in normal skin. Out of these 32 compounds, 10 have been reported previously by our group, thus confirming our results and adding additional confidence in our untargeted metabolomics approach for detection of melanoma biomarkers.