Cargando…

Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma

PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure beca...

Descripción completa

Detalles Bibliográficos
Autores principales: Bellomo, Domenico, Arias-Mejias, Suzette M., Ramana, Chandru, Heim, Joel B., Quattrocchi, Enrica, Sominidi-Damodaran, Sindhuja, Bridges, Alina G., Lehman, Julia S., Hieken, Tina J., Jakub, James W., Pittelkow, Mark R., DiCaudo, David J., Pockaj, Barbara A., Sluzevich, Jason C., Cappel, Mark A., Bagaria, Sanjay P., Perniciaro, Charles, Tjien-Fooh, Félicia J., van Vliet, Martin H., Dwarkasing, Jvalini, Meves, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Clinical Oncology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220172/
https://www.ncbi.nlm.nih.gov/pubmed/32405608
http://dx.doi.org/10.1200/PO.19.00206
_version_ 1783533102748925952
author Bellomo, Domenico
Arias-Mejias, Suzette M.
Ramana, Chandru
Heim, Joel B.
Quattrocchi, Enrica
Sominidi-Damodaran, Sindhuja
Bridges, Alina G.
Lehman, Julia S.
Hieken, Tina J.
Jakub, James W.
Pittelkow, Mark R.
DiCaudo, David J.
Pockaj, Barbara A.
Sluzevich, Jason C.
Cappel, Mark A.
Bagaria, Sanjay P.
Perniciaro, Charles
Tjien-Fooh, Félicia J.
van Vliet, Martin H.
Dwarkasing, Jvalini
Meves, Alexander
author_facet Bellomo, Domenico
Arias-Mejias, Suzette M.
Ramana, Chandru
Heim, Joel B.
Quattrocchi, Enrica
Sominidi-Damodaran, Sindhuja
Bridges, Alina G.
Lehman, Julia S.
Hieken, Tina J.
Jakub, James W.
Pittelkow, Mark R.
DiCaudo, David J.
Pockaj, Barbara A.
Sluzevich, Jason C.
Cappel, Mark A.
Bagaria, Sanjay P.
Perniciaro, Charles
Tjien-Fooh, Félicia J.
van Vliet, Martin H.
Dwarkasing, Jvalini
Meves, Alexander
author_sort Bellomo, Domenico
collection PubMed
description PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. PATIENTS AND METHODS: Genes with functional roles in melanoma metastasis were discovered by analysis of next-generation sequencing data and case-control studies. We then used polymerase chain reaction to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin- and intermediate-thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross-validation scheme to predict the presence of SLN metastasis from molecular, clinical, and histologic variables. RESULTS: Expression of genes with roles in epithelial-to-mesenchymal transition (glia-derived nexin, growth differentiation factor 15, integrin-β3, interleukin 8, lysyl oxidase homolog 4, transforming growth factor-β receptor type 1, and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model that included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age (area under the receiver operating characteristic curve, 0.82; 95% CI, 0.78 to 0.86; SLN biopsy reduction rate, 42%; negative predictive value, 96%). CONCLUSION: A combined model that included clinicopathologic and gene expression variables improved the identification of patients with melanoma who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis.
format Online
Article
Text
id pubmed-7220172
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher American Society of Clinical Oncology
record_format MEDLINE/PubMed
spelling pubmed-72201722020-05-13 Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma Bellomo, Domenico Arias-Mejias, Suzette M. Ramana, Chandru Heim, Joel B. Quattrocchi, Enrica Sominidi-Damodaran, Sindhuja Bridges, Alina G. Lehman, Julia S. Hieken, Tina J. Jakub, James W. Pittelkow, Mark R. DiCaudo, David J. Pockaj, Barbara A. Sluzevich, Jason C. Cappel, Mark A. Bagaria, Sanjay P. Perniciaro, Charles Tjien-Fooh, Félicia J. van Vliet, Martin H. Dwarkasing, Jvalini Meves, Alexander JCO Precis Oncol Original Reports PURPOSE: More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here, we describe a model that combines clinicopathologic and molecular variables to identify patients with thin- and intermediate-thickness melanomas who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. PATIENTS AND METHODS: Genes with functional roles in melanoma metastasis were discovered by analysis of next-generation sequencing data and case-control studies. We then used polymerase chain reaction to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin- and intermediate-thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross-validation scheme to predict the presence of SLN metastasis from molecular, clinical, and histologic variables. RESULTS: Expression of genes with roles in epithelial-to-mesenchymal transition (glia-derived nexin, growth differentiation factor 15, integrin-β3, interleukin 8, lysyl oxidase homolog 4, transforming growth factor-β receptor type 1, and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model that included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age (area under the receiver operating characteristic curve, 0.82; 95% CI, 0.78 to 0.86; SLN biopsy reduction rate, 42%; negative predictive value, 96%). CONCLUSION: A combined model that included clinicopathologic and gene expression variables improved the identification of patients with melanoma who may forgo the SLN biopsy procedure because of their low risk of nodal metastasis. American Society of Clinical Oncology 2020-04-14 /pmc/articles/PMC7220172/ /pubmed/32405608 http://dx.doi.org/10.1200/PO.19.00206 Text en © 2020 by American Society of Clinical Oncology https://creativecommons.org/licenses/by/4.0/ Licensed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/
spellingShingle Original Reports
Bellomo, Domenico
Arias-Mejias, Suzette M.
Ramana, Chandru
Heim, Joel B.
Quattrocchi, Enrica
Sominidi-Damodaran, Sindhuja
Bridges, Alina G.
Lehman, Julia S.
Hieken, Tina J.
Jakub, James W.
Pittelkow, Mark R.
DiCaudo, David J.
Pockaj, Barbara A.
Sluzevich, Jason C.
Cappel, Mark A.
Bagaria, Sanjay P.
Perniciaro, Charles
Tjien-Fooh, Félicia J.
van Vliet, Martin H.
Dwarkasing, Jvalini
Meves, Alexander
Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title_full Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title_fullStr Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title_full_unstemmed Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title_short Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma
title_sort model combining tumor molecular and clinicopathologic risk factors predicts sentinel lymph node metastasis in primary cutaneous melanoma
topic Original Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220172/
https://www.ncbi.nlm.nih.gov/pubmed/32405608
http://dx.doi.org/10.1200/PO.19.00206
work_keys_str_mv AT bellomodomenico modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT ariasmejiassuzettem modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT ramanachandru modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT heimjoelb modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT quattrocchienrica modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT sominididamodaransindhuja modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT bridgesalinag modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT lehmanjulias modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT hiekentinaj modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT jakubjamesw modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT pittelkowmarkr modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT dicaudodavidj modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT pockajbarbaraa modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT sluzevichjasonc modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT cappelmarka modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT bagariasanjayp modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT perniciarocharles modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT tjienfoohfeliciaj modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT vanvlietmartinh modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT dwarkasingjvalini modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma
AT mevesalexander modelcombiningtumormolecularandclinicopathologicriskfactorspredictssentinellymphnodemetastasisinprimarycutaneousmelanoma