Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction

Tracey B. Lewis, John E. Robison, Roy Bastien, Brett Milash, Ken Boucher, Wolfram E. Samlowski, Sancy Leachman, R. Dirk Noyes, Carl T. Wittwer, Layrent Perreard, Philip S. Bernard

Research output: Contribution to journalArticle

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Abstract

BACKGROUND. The early detection and characterization of metastatic melanoma are important for prognosis and management of the disease. Molecular methods are more sensitive in detecting occult lymph node metastases compared with standard histopathology and are reported to have utility in clinical diagnostics. METHODS. Using real-time quantitative reverse transcriptase- polymerase chain reaction ([q]RT-PCR), the authors examined 36 samples (30 melanomas, 4 benign nevi, and 2 reactive lymph nodes) for the expression of 20 melanoma-related genes that function in cell growth and differentiation (epidermal growth factor receptor [EGFR], WNT5A, BRAF, FOS, JUN, MATP, and TMP1), cell proliferation (KI-67, TOP2A, BUB1, BIRC5, and STK6), melanoma progression (CD63, MAGEA3, and GALGT], and melanin synthesis (TYR, MLANA, SILV, PAX3, and MITF). In addition, samples were tested for mutations in BRAF (exons 11 and 15) and NRAS (exons 2 and 3). RESULTS. Hierarchical clustering analysis of the expression data was able to distinguish between the melanoma and nonmelanoma samples and further stratified the melanoma samples into two groups differentiated by high expression of the genes involved in β-catenin activation (EGFR and WNT5A) and the MAPK/ERK pathway (BRAF, FOS, and JUN). Eighteen of the 28 patients (64%) were found to have mutations in either exon 15 of BRAF (V599 substitution) or codon 61 of NRAS. The mutations were mutually exclusive and did not appear to be associated with the different expression subtypes. CONCLUSIONS. The results of the current study demonstrate that real-time qRT-PCR can be analyzed using hierarchical clustering to identify expression patterns that differentiate between melanomas and other tissue types. Using a supervised analysis of the data, the authors found that the best discriminators for molecularly distinguishing between melanoma, benign nevi, and lymph nodes were MLANA, CD63, and BUB1. These markers could have diagnostic utility for the detection of melanoma micrometastasis in sentinel lymph nodes.

Original languageEnglish (US)
Pages (from-to)1678-1686
Number of pages9
JournalCancer
Volume104
Issue number8
DOIs
StatePublished - Oct 15 2005
Externally publishedYes

Fingerprint

Reverse Transcriptase Polymerase Chain Reaction
Melanoma
Exons
Lymph Nodes
Epidermal Growth Factor Receptor
Mutation
Cluster Analysis
Nevi and Melanomas
Catenins
Neoplasm Micrometastasis
MAP Kinase Signaling System
Nevus
Melanins
Disease Management
Codon
Real-Time Polymerase Chain Reaction
Cell Differentiation
Cell Proliferation
Neoplasm Metastasis
Gene Expression

Keywords

  • Melanoma
  • Micrometastasis
  • Molecular staging
  • mRNA expression profiling

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Lewis, T. B., Robison, J. E., Bastien, R., Milash, B., Boucher, K., Samlowski, W. E., ... Bernard, P. S. (2005). Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction. Cancer, 104(8), 1678-1686. https://doi.org/10.1002/cncr.21372

Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction. / Lewis, Tracey B.; Robison, John E.; Bastien, Roy; Milash, Brett; Boucher, Ken; Samlowski, Wolfram E.; Leachman, Sancy; Noyes, R. Dirk; Wittwer, Carl T.; Perreard, Layrent; Bernard, Philip S.

In: Cancer, Vol. 104, No. 8, 15.10.2005, p. 1678-1686.

Research output: Contribution to journalArticle

Lewis, TB, Robison, JE, Bastien, R, Milash, B, Boucher, K, Samlowski, WE, Leachman, S, Noyes, RD, Wittwer, CT, Perreard, L & Bernard, PS 2005, 'Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction', Cancer, vol. 104, no. 8, pp. 1678-1686. https://doi.org/10.1002/cncr.21372
Lewis TB, Robison JE, Bastien R, Milash B, Boucher K, Samlowski WE et al. Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction. Cancer. 2005 Oct 15;104(8):1678-1686. https://doi.org/10.1002/cncr.21372
Lewis, Tracey B. ; Robison, John E. ; Bastien, Roy ; Milash, Brett ; Boucher, Ken ; Samlowski, Wolfram E. ; Leachman, Sancy ; Noyes, R. Dirk ; Wittwer, Carl T. ; Perreard, Layrent ; Bernard, Philip S. / Molecular classification of melanoma using real-time quantitative reverse transcriptase-polymerase chain reaction. In: Cancer. 2005 ; Vol. 104, No. 8. pp. 1678-1686.
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abstract = "BACKGROUND. The early detection and characterization of metastatic melanoma are important for prognosis and management of the disease. Molecular methods are more sensitive in detecting occult lymph node metastases compared with standard histopathology and are reported to have utility in clinical diagnostics. METHODS. Using real-time quantitative reverse transcriptase- polymerase chain reaction ([q]RT-PCR), the authors examined 36 samples (30 melanomas, 4 benign nevi, and 2 reactive lymph nodes) for the expression of 20 melanoma-related genes that function in cell growth and differentiation (epidermal growth factor receptor [EGFR], WNT5A, BRAF, FOS, JUN, MATP, and TMP1), cell proliferation (KI-67, TOP2A, BUB1, BIRC5, and STK6), melanoma progression (CD63, MAGEA3, and GALGT], and melanin synthesis (TYR, MLANA, SILV, PAX3, and MITF). In addition, samples were tested for mutations in BRAF (exons 11 and 15) and NRAS (exons 2 and 3). RESULTS. Hierarchical clustering analysis of the expression data was able to distinguish between the melanoma and nonmelanoma samples and further stratified the melanoma samples into two groups differentiated by high expression of the genes involved in β-catenin activation (EGFR and WNT5A) and the MAPK/ERK pathway (BRAF, FOS, and JUN). Eighteen of the 28 patients (64{\%}) were found to have mutations in either exon 15 of BRAF (V599 substitution) or codon 61 of NRAS. The mutations were mutually exclusive and did not appear to be associated with the different expression subtypes. CONCLUSIONS. The results of the current study demonstrate that real-time qRT-PCR can be analyzed using hierarchical clustering to identify expression patterns that differentiate between melanomas and other tissue types. Using a supervised analysis of the data, the authors found that the best discriminators for molecularly distinguishing between melanoma, benign nevi, and lymph nodes were MLANA, CD63, and BUB1. These markers could have diagnostic utility for the detection of melanoma micrometastasis in sentinel lymph nodes.",
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AU - Lewis, Tracey B.

AU - Robison, John E.

AU - Bastien, Roy

AU - Milash, Brett

AU - Boucher, Ken

AU - Samlowski, Wolfram E.

AU - Leachman, Sancy

AU - Noyes, R. Dirk

AU - Wittwer, Carl T.

AU - Perreard, Layrent

AU - Bernard, Philip S.

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N2 - BACKGROUND. The early detection and characterization of metastatic melanoma are important for prognosis and management of the disease. Molecular methods are more sensitive in detecting occult lymph node metastases compared with standard histopathology and are reported to have utility in clinical diagnostics. METHODS. Using real-time quantitative reverse transcriptase- polymerase chain reaction ([q]RT-PCR), the authors examined 36 samples (30 melanomas, 4 benign nevi, and 2 reactive lymph nodes) for the expression of 20 melanoma-related genes that function in cell growth and differentiation (epidermal growth factor receptor [EGFR], WNT5A, BRAF, FOS, JUN, MATP, and TMP1), cell proliferation (KI-67, TOP2A, BUB1, BIRC5, and STK6), melanoma progression (CD63, MAGEA3, and GALGT], and melanin synthesis (TYR, MLANA, SILV, PAX3, and MITF). In addition, samples were tested for mutations in BRAF (exons 11 and 15) and NRAS (exons 2 and 3). RESULTS. Hierarchical clustering analysis of the expression data was able to distinguish between the melanoma and nonmelanoma samples and further stratified the melanoma samples into two groups differentiated by high expression of the genes involved in β-catenin activation (EGFR and WNT5A) and the MAPK/ERK pathway (BRAF, FOS, and JUN). Eighteen of the 28 patients (64%) were found to have mutations in either exon 15 of BRAF (V599 substitution) or codon 61 of NRAS. The mutations were mutually exclusive and did not appear to be associated with the different expression subtypes. CONCLUSIONS. The results of the current study demonstrate that real-time qRT-PCR can be analyzed using hierarchical clustering to identify expression patterns that differentiate between melanomas and other tissue types. Using a supervised analysis of the data, the authors found that the best discriminators for molecularly distinguishing between melanoma, benign nevi, and lymph nodes were MLANA, CD63, and BUB1. These markers could have diagnostic utility for the detection of melanoma micrometastasis in sentinel lymph nodes.

AB - BACKGROUND. The early detection and characterization of metastatic melanoma are important for prognosis and management of the disease. Molecular methods are more sensitive in detecting occult lymph node metastases compared with standard histopathology and are reported to have utility in clinical diagnostics. METHODS. Using real-time quantitative reverse transcriptase- polymerase chain reaction ([q]RT-PCR), the authors examined 36 samples (30 melanomas, 4 benign nevi, and 2 reactive lymph nodes) for the expression of 20 melanoma-related genes that function in cell growth and differentiation (epidermal growth factor receptor [EGFR], WNT5A, BRAF, FOS, JUN, MATP, and TMP1), cell proliferation (KI-67, TOP2A, BUB1, BIRC5, and STK6), melanoma progression (CD63, MAGEA3, and GALGT], and melanin synthesis (TYR, MLANA, SILV, PAX3, and MITF). In addition, samples were tested for mutations in BRAF (exons 11 and 15) and NRAS (exons 2 and 3). RESULTS. Hierarchical clustering analysis of the expression data was able to distinguish between the melanoma and nonmelanoma samples and further stratified the melanoma samples into two groups differentiated by high expression of the genes involved in β-catenin activation (EGFR and WNT5A) and the MAPK/ERK pathway (BRAF, FOS, and JUN). Eighteen of the 28 patients (64%) were found to have mutations in either exon 15 of BRAF (V599 substitution) or codon 61 of NRAS. The mutations were mutually exclusive and did not appear to be associated with the different expression subtypes. CONCLUSIONS. The results of the current study demonstrate that real-time qRT-PCR can be analyzed using hierarchical clustering to identify expression patterns that differentiate between melanomas and other tissue types. Using a supervised analysis of the data, the authors found that the best discriminators for molecularly distinguishing between melanoma, benign nevi, and lymph nodes were MLANA, CD63, and BUB1. These markers could have diagnostic utility for the detection of melanoma micrometastasis in sentinel lymph nodes.

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