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Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies
Risk-stratification of cutaneous melanoma is important. Patients want to know what to expect after diagnosis, and physicians need to decide on a treatment plan. Historically, melanoma that had spread beyond the skin and regional lymph nodes was largely incurable, and the only approach to preventing...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162102/ https://www.ncbi.nlm.nih.gov/pubmed/35654998 http://dx.doi.org/10.1038/s41379-022-01101-y |
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author | Sadurní, Mariana B. Meves, Alexander |
author_facet | Sadurní, Mariana B. Meves, Alexander |
author_sort | Sadurní, Mariana B. |
collection | PubMed |
description | Risk-stratification of cutaneous melanoma is important. Patients want to know what to expect after diagnosis, and physicians need to decide on a treatment plan. Historically, melanoma that had spread beyond the skin and regional lymph nodes was largely incurable, and the only approach to preventing a bad outcome was surgery. Through the seminal work of Alexander Breslow and Donald Morton, a system was devised to carefully escalate surgery based on primary tumor thickness and sentinel lymph node status. Today, we know that prophylactic lymph node dissections do not improve survival, but we continue to appreciate the prognostic implications of a positive sentinel node and the benefits of removing nodal metastases, which facilitates locoregional disease control. However, the question arises whether we can better select patients for sentinel lymph node biopsies (SLNB) as, currently, 85% of these procedures are negative and non-therapeutic. Here, we argue that gene expression profiling (GEP) of the diagnostic biopsy is a valuable step toward better patient selection when combined with reliable clinicopathologic (CP) information such as patient age and Breslow thickness. Recently, a CP-GEP-based classifier of nodal metastasis risk, the Merlin Assay, has become commercially available. While CP-GEP is still being validated in prospective studies, preliminary data suggest that it is an independent predictor of nodal metastasis, outperforming clinicopathological variables. The hunt is on for Breslow thickness 2.0. |
format | Online Article Text |
id | pubmed-9162102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-91621022022-06-02 Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies Sadurní, Mariana B. Meves, Alexander Mod Pathol Review Article Risk-stratification of cutaneous melanoma is important. Patients want to know what to expect after diagnosis, and physicians need to decide on a treatment plan. Historically, melanoma that had spread beyond the skin and regional lymph nodes was largely incurable, and the only approach to preventing a bad outcome was surgery. Through the seminal work of Alexander Breslow and Donald Morton, a system was devised to carefully escalate surgery based on primary tumor thickness and sentinel lymph node status. Today, we know that prophylactic lymph node dissections do not improve survival, but we continue to appreciate the prognostic implications of a positive sentinel node and the benefits of removing nodal metastases, which facilitates locoregional disease control. However, the question arises whether we can better select patients for sentinel lymph node biopsies (SLNB) as, currently, 85% of these procedures are negative and non-therapeutic. Here, we argue that gene expression profiling (GEP) of the diagnostic biopsy is a valuable step toward better patient selection when combined with reliable clinicopathologic (CP) information such as patient age and Breslow thickness. Recently, a CP-GEP-based classifier of nodal metastasis risk, the Merlin Assay, has become commercially available. While CP-GEP is still being validated in prospective studies, preliminary data suggest that it is an independent predictor of nodal metastasis, outperforming clinicopathological variables. The hunt is on for Breslow thickness 2.0. Nature Publishing Group US 2022-06-02 2022 /pmc/articles/PMC9162102/ /pubmed/35654998 http://dx.doi.org/10.1038/s41379-022-01101-y Text en © The Author(s), under exclusive licence to United States & Canadian Academy of Pathology 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Sadurní, Mariana B. Meves, Alexander Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title | Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title_full | Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title_fullStr | Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title_full_unstemmed | Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title_short | Breslow thickness 2.0: Why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
title_sort | breslow thickness 2.0: why gene expression profiling is a step toward better patient selection for sentinel lymph node biopsies |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162102/ https://www.ncbi.nlm.nih.gov/pubmed/35654998 http://dx.doi.org/10.1038/s41379-022-01101-y |
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