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

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 diag...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Cancer 2005-10, Vol.104 (8), p.1678-1686
Hauptverfasser: Lewis, Tracey B., Robison, John E., Bastien, Roy, Milash, Brett, Boucher, Ken, Samlowski, Wolfram E., Leachman, Sancy A., Dirk Noyes, R., Wittwer, Carl T., Perreard, Laurent, Bernard, Philip S.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1686
container_issue 8
container_start_page 1678
container_title Cancer
container_volume 104
creator Lewis, Tracey B.
Robison, John E.
Bastien, Roy
Milash, Brett
Boucher, Ken
Samlowski, Wolfram E.
Leachman, Sancy A.
Dirk Noyes, R.
Wittwer, Carl T.
Perreard, Laurent
Bernard, Philip S.
description 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. Cancer 2005. © 2005 American Cancer Society. Real‐time quantitative reverse transcriptase‐polymerase chain reaction (RT‐PCR) and fluorescent melting curve analyses were used to profile melanomas and identify those markers important for detecting and distinguishing between different molecular subtypes of the disease. The authors believe that these results provide independent validation of several melanoma markers currently used in clinical trials. I
doi_str_mv 10.1002/cncr.21372
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_68670789</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>21131369</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3882-d0c39318921f1056787461dac5fc5fd655904ebc2af5f02b6102b3478a10cef03</originalsourceid><addsrcrecordid>eNqF0cFq3DAQBmARWpJt2kseoPjSHApONJIl2ceyJG0haaC00JuZ1Y5SFdneSHbC3vIIecY-SeXuQm4tCIlBH_8gDWMnwM-Ac3FuexvPBEgjDtgCeGNKDpV4wRac87pUlfxxxF6l9CuXRih5yI5AA2jVqAWbrodAdgoYCxswJe-8xdEPfTG4oqOA_dBhMSXf3xaRMPx-fBp9R8XdhP3ox0zvKV_cU0xUjBH7ZKPfjJgoy80Qth3FXBT2J_p-TrBz-Gv20mFI9GZ_HrPvlxfflp_Kq5uPn5cfrkor61qUa25lI6FuBDjgSpvaVBrWaJXLa62VanhFKyvQKcfFSkPeZGVqBG7JcXnMTne5mzjcTZTGtvPJUsjPomFKra614aZu_gsFgASpZ_h-B20cUork2k30HcZtC7ydp9HO02j_TiPjt_vUadXR-pnuvz-Dd3uAyWJw-f-sT8_OgM5Dg-xg5x58oO0_WrbLL8uvu-Z_AGBOphY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>21131369</pqid></control><display><type>article</type><title>Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction</title><source>MEDLINE</source><source>Wiley Free Content</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Wiley Online Library All Journals</source><source>Alma/SFX Local Collection</source><creator>Lewis, Tracey B. ; Robison, John E. ; Bastien, Roy ; Milash, Brett ; Boucher, Ken ; Samlowski, Wolfram E. ; Leachman, Sancy A. ; Dirk Noyes, R. ; Wittwer, Carl T. ; Perreard, Laurent ; Bernard, Philip S.</creator><creatorcontrib>Lewis, Tracey B. ; Robison, John E. ; Bastien, Roy ; Milash, Brett ; Boucher, Ken ; Samlowski, Wolfram E. ; Leachman, Sancy A. ; Dirk Noyes, R. ; Wittwer, Carl T. ; Perreard, Laurent ; Bernard, Philip S.</creatorcontrib><description>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. Cancer 2005. © 2005 American Cancer Society. Real‐time quantitative reverse transcriptase‐polymerase chain reaction (RT‐PCR) and fluorescent melting curve analyses were used to profile melanomas and identify those markers important for detecting and distinguishing between different molecular subtypes of the disease. The authors believe that these results provide independent validation of several melanoma markers currently used in clinical trials. In addition, they have identified other markers that could improve the accuracy of RT‐PCR assays when used for molecular staging in patients with melanoma.</description><identifier>ISSN: 0008-543X</identifier><identifier>EISSN: 1097-0142</identifier><identifier>DOI: 10.1002/cncr.21372</identifier><identifier>PMID: 16116595</identifier><identifier>CODEN: CANCAR</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Biological and medical sciences ; Biomarkers, Tumor - genetics ; Dermatology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Lymphatic Metastasis ; Medical sciences ; melanoma ; Melanoma - classification ; Melanoma - genetics ; micrometastasis ; molecular staging ; mRNA expression profiling ; Neoplasm Proteins - genetics ; Reverse Transcriptase Polymerase Chain Reaction ; RNA, Messenger - metabolism ; RNA, Neoplasm - genetics ; Skin Neoplasms - classification ; Skin Neoplasms - genetics ; Tumors ; Tumors of the skin and soft tissue. Premalignant lesions</subject><ispartof>Cancer, 2005-10, Vol.104 (8), p.1678-1686</ispartof><rights>Copyright © 2005 American Cancer Society</rights><rights>2005 INIST-CNRS</rights><rights>Copyright 2005 American Cancer Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3882-d0c39318921f1056787461dac5fc5fd655904ebc2af5f02b6102b3478a10cef03</citedby><cites>FETCH-LOGICAL-c3882-d0c39318921f1056787461dac5fc5fd655904ebc2af5f02b6102b3478a10cef03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcncr.21372$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcncr.21372$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,1432,27923,27924,45573,45574,46408,46832</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=17160001$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16116595$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lewis, Tracey B.</creatorcontrib><creatorcontrib>Robison, John E.</creatorcontrib><creatorcontrib>Bastien, Roy</creatorcontrib><creatorcontrib>Milash, Brett</creatorcontrib><creatorcontrib>Boucher, Ken</creatorcontrib><creatorcontrib>Samlowski, Wolfram E.</creatorcontrib><creatorcontrib>Leachman, Sancy A.</creatorcontrib><creatorcontrib>Dirk Noyes, R.</creatorcontrib><creatorcontrib>Wittwer, Carl T.</creatorcontrib><creatorcontrib>Perreard, Laurent</creatorcontrib><creatorcontrib>Bernard, Philip S.</creatorcontrib><title>Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction</title><title>Cancer</title><addtitle>Cancer</addtitle><description>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. Cancer 2005. © 2005 American Cancer Society. Real‐time quantitative reverse transcriptase‐polymerase chain reaction (RT‐PCR) and fluorescent melting curve analyses were used to profile melanomas and identify those markers important for detecting and distinguishing between different molecular subtypes of the disease. The authors believe that these results provide independent validation of several melanoma markers currently used in clinical trials. In addition, they have identified other markers that could improve the accuracy of RT‐PCR assays when used for molecular staging in patients with melanoma.</description><subject>Biological and medical sciences</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Dermatology</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Humans</subject><subject>Lymphatic Metastasis</subject><subject>Medical sciences</subject><subject>melanoma</subject><subject>Melanoma - classification</subject><subject>Melanoma - genetics</subject><subject>micrometastasis</subject><subject>molecular staging</subject><subject>mRNA expression profiling</subject><subject>Neoplasm Proteins - genetics</subject><subject>Reverse Transcriptase Polymerase Chain Reaction</subject><subject>RNA, Messenger - metabolism</subject><subject>RNA, Neoplasm - genetics</subject><subject>Skin Neoplasms - classification</subject><subject>Skin Neoplasms - genetics</subject><subject>Tumors</subject><subject>Tumors of the skin and soft tissue. Premalignant lesions</subject><issn>0008-543X</issn><issn>1097-0142</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqF0cFq3DAQBmARWpJt2kseoPjSHApONJIl2ceyJG0haaC00JuZ1Y5SFdneSHbC3vIIecY-SeXuQm4tCIlBH_8gDWMnwM-Ac3FuexvPBEgjDtgCeGNKDpV4wRac87pUlfxxxF6l9CuXRih5yI5AA2jVqAWbrodAdgoYCxswJe-8xdEPfTG4oqOA_dBhMSXf3xaRMPx-fBp9R8XdhP3ox0zvKV_cU0xUjBH7ZKPfjJgoy80Qth3FXBT2J_p-TrBz-Gv20mFI9GZ_HrPvlxfflp_Kq5uPn5cfrkor61qUa25lI6FuBDjgSpvaVBrWaJXLa62VanhFKyvQKcfFSkPeZGVqBG7JcXnMTne5mzjcTZTGtvPJUsjPomFKra614aZu_gsFgASpZ_h-B20cUork2k30HcZtC7ydp9HO02j_TiPjt_vUadXR-pnuvz-Dd3uAyWJw-f-sT8_OgM5Dg-xg5x58oO0_WrbLL8uvu-Z_AGBOphY</recordid><startdate>20051015</startdate><enddate>20051015</enddate><creator>Lewis, Tracey B.</creator><creator>Robison, John E.</creator><creator>Bastien, Roy</creator><creator>Milash, Brett</creator><creator>Boucher, Ken</creator><creator>Samlowski, Wolfram E.</creator><creator>Leachman, Sancy A.</creator><creator>Dirk Noyes, R.</creator><creator>Wittwer, Carl T.</creator><creator>Perreard, Laurent</creator><creator>Bernard, Philip S.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>Wiley-Liss</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TM</scope><scope>7X8</scope></search><sort><creationdate>20051015</creationdate><title>Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction</title><author>Lewis, Tracey B. ; Robison, John E. ; Bastien, Roy ; Milash, Brett ; Boucher, Ken ; Samlowski, Wolfram E. ; Leachman, Sancy A. ; Dirk Noyes, R. ; Wittwer, Carl T. ; Perreard, Laurent ; Bernard, Philip S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3882-d0c39318921f1056787461dac5fc5fd655904ebc2af5f02b6102b3478a10cef03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Biological and medical sciences</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Dermatology</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Humans</topic><topic>Lymphatic Metastasis</topic><topic>Medical sciences</topic><topic>melanoma</topic><topic>Melanoma - classification</topic><topic>Melanoma - genetics</topic><topic>micrometastasis</topic><topic>molecular staging</topic><topic>mRNA expression profiling</topic><topic>Neoplasm Proteins - genetics</topic><topic>Reverse Transcriptase Polymerase Chain Reaction</topic><topic>RNA, Messenger - metabolism</topic><topic>RNA, Neoplasm - genetics</topic><topic>Skin Neoplasms - classification</topic><topic>Skin Neoplasms - genetics</topic><topic>Tumors</topic><topic>Tumors of the skin and soft tissue. Premalignant lesions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lewis, Tracey B.</creatorcontrib><creatorcontrib>Robison, John E.</creatorcontrib><creatorcontrib>Bastien, Roy</creatorcontrib><creatorcontrib>Milash, Brett</creatorcontrib><creatorcontrib>Boucher, Ken</creatorcontrib><creatorcontrib>Samlowski, Wolfram E.</creatorcontrib><creatorcontrib>Leachman, Sancy A.</creatorcontrib><creatorcontrib>Dirk Noyes, R.</creatorcontrib><creatorcontrib>Wittwer, Carl T.</creatorcontrib><creatorcontrib>Perreard, Laurent</creatorcontrib><creatorcontrib>Bernard, Philip S.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Nucleic Acids Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lewis, Tracey B.</au><au>Robison, John E.</au><au>Bastien, Roy</au><au>Milash, Brett</au><au>Boucher, Ken</au><au>Samlowski, Wolfram E.</au><au>Leachman, Sancy A.</au><au>Dirk Noyes, R.</au><au>Wittwer, Carl T.</au><au>Perreard, Laurent</au><au>Bernard, Philip S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction</atitle><jtitle>Cancer</jtitle><addtitle>Cancer</addtitle><date>2005-10-15</date><risdate>2005</risdate><volume>104</volume><issue>8</issue><spage>1678</spage><epage>1686</epage><pages>1678-1686</pages><issn>0008-543X</issn><eissn>1097-0142</eissn><coden>CANCAR</coden><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. Cancer 2005. © 2005 American Cancer Society. Real‐time quantitative reverse transcriptase‐polymerase chain reaction (RT‐PCR) and fluorescent melting curve analyses were used to profile melanomas and identify those markers important for detecting and distinguishing between different molecular subtypes of the disease. The authors believe that these results provide independent validation of several melanoma markers currently used in clinical trials. In addition, they have identified other markers that could improve the accuracy of RT‐PCR assays when used for molecular staging in patients with melanoma.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>16116595</pmid><doi>10.1002/cncr.21372</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0008-543X
ispartof Cancer, 2005-10, Vol.104 (8), p.1678-1686
issn 0008-543X
1097-0142
language eng
recordid cdi_proquest_miscellaneous_68670789
source MEDLINE; Wiley Free Content; EZB-FREE-00999 freely available EZB journals; Wiley Online Library All Journals; Alma/SFX Local Collection
subjects Biological and medical sciences
Biomarkers, Tumor - genetics
Dermatology
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Lymphatic Metastasis
Medical sciences
melanoma
Melanoma - classification
Melanoma - genetics
micrometastasis
molecular staging
mRNA expression profiling
Neoplasm Proteins - genetics
Reverse Transcriptase Polymerase Chain Reaction
RNA, Messenger - metabolism
RNA, Neoplasm - genetics
Skin Neoplasms - classification
Skin Neoplasms - genetics
Tumors
Tumors of the skin and soft tissue. Premalignant lesions
title Molecular classification of melanoma using real‐time quantitative reverse transcriptase‐polymerase chain reaction
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T15%3A09%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Molecular%20classification%20of%20melanoma%20using%20real%E2%80%90time%20quantitative%20reverse%20transcriptase%E2%80%90polymerase%20chain%20reaction&rft.jtitle=Cancer&rft.au=Lewis,%20Tracey%20B.&rft.date=2005-10-15&rft.volume=104&rft.issue=8&rft.spage=1678&rft.epage=1686&rft.pages=1678-1686&rft.issn=0008-543X&rft.eissn=1097-0142&rft.coden=CANCAR&rft_id=info:doi/10.1002/cncr.21372&rft_dat=%3Cproquest_cross%3E21131369%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=21131369&rft_id=info:pmid/16116595&rfr_iscdi=true