1. ¹Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill (UNC-CH), Chapel Hill, North Carolina, USA
2. ²Lineberger Comprehensive Cancer Center, UNC-CH, Chapel Hill, North Carolina, USA
3. ³Center for Environmental Health and Susceptibility, UNC-CH, Chapel Hill, North Carolina, USA
4. ⁴Department of Biostatistics, UNC-CH, Chapel Hill, North Carolina, USA
5. ⁵Department of Dermatology, UNC-CH, Chapel Hill, North Carolina, USA
6. ⁶Department of Pharmacology, UNC-CH, Chapel Hill, North Carolina, USA
7. ⁷Department of Dermatology, University of Rochester, Rochester, New York, USA
8. ⁸Department of Genetics, UNC-CH, Chapel Hill, North Carolina, USA
9. ⁹Department of Medicine, UNC-CH, Chapel Hill, North Carolina, USA

Correspondence: Dr William K. Kaufmann, CB#7295, Rm 31-325, Lineberger Comprehensive Cancer Center, UNC-CH, Chapel Hill, North Carolina 27599-7295, USA. E-mail: wkarlk@med.unc.edu

Received 22 March 2007; Revised 25 April 2007; Accepted 30 April 2007; Published online 28 June 2007.

Abstract

Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wild-type N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression.