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Development and validation of a plasma-based melanoma biomarker suitable for clinical use

BACKGROUND: In Australia, more money is spent on skin cancer than any other malignancy. Despite this, the mortality rate of melanoma, the deadliest form, has steadily increased over the past 50 years. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible f...

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Autores principales: Van Laar, Ryan, Lincoln, Mitchel, Van Laar, Barton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886119/
https://www.ncbi.nlm.nih.gov/pubmed/29360813
http://dx.doi.org/10.1038/bjc.2017.477
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author Van Laar, Ryan
Lincoln, Mitchel
Van Laar, Barton
author_facet Van Laar, Ryan
Lincoln, Mitchel
Van Laar, Barton
author_sort Van Laar, Ryan
collection PubMed
description BACKGROUND: In Australia, more money is spent on skin cancer than any other malignancy. Despite this, the mortality rate of melanoma, the deadliest form, has steadily increased over the past 50 years. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress. METHODS: Whole-microRNAome profiling was performed on plasma samples from 32 patients with histologically confirmed melanoma and 16 normal controls. A classification algorithm was trained on these data and independently validated on multiple previously published microRNA data sets, representing (i) melanoma patient- and normal-blood, (ii) melanoma and nevi biopsy tissue, and (iii) cell lines and purified exosomes. RESULTS: 38 circulating microRNAs had biologically and statistically significant differences between melanoma and normal plasma samples (MEL38). A support vector machine algorithm, trained on these markers, showed strong independent classification accuracy (AUC 0.79–0.94). A majority of MEL38 genes have been previously associated with melanoma and are known regulators of angiogenesis, metastasis, tumour suppression, and treatment resistance. CONCLUSIONS: MEL38 exhibits disease state specificity and robustness to platform and specimen-type variation. It has potential to become an objective diagnostic biomarker and improve the precision and accuracy of melanoma detection and monitoring.
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spelling pubmed-58861192019-03-20 Development and validation of a plasma-based melanoma biomarker suitable for clinical use Van Laar, Ryan Lincoln, Mitchel Van Laar, Barton Br J Cancer Molecular Diagnostics BACKGROUND: In Australia, more money is spent on skin cancer than any other malignancy. Despite this, the mortality rate of melanoma, the deadliest form, has steadily increased over the past 50 years. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress. METHODS: Whole-microRNAome profiling was performed on plasma samples from 32 patients with histologically confirmed melanoma and 16 normal controls. A classification algorithm was trained on these data and independently validated on multiple previously published microRNA data sets, representing (i) melanoma patient- and normal-blood, (ii) melanoma and nevi biopsy tissue, and (iii) cell lines and purified exosomes. RESULTS: 38 circulating microRNAs had biologically and statistically significant differences between melanoma and normal plasma samples (MEL38). A support vector machine algorithm, trained on these markers, showed strong independent classification accuracy (AUC 0.79–0.94). A majority of MEL38 genes have been previously associated with melanoma and are known regulators of angiogenesis, metastasis, tumour suppression, and treatment resistance. CONCLUSIONS: MEL38 exhibits disease state specificity and robustness to platform and specimen-type variation. It has potential to become an objective diagnostic biomarker and improve the precision and accuracy of melanoma detection and monitoring. Nature Publishing Group 2018-03-20 2018-01-23 /pmc/articles/PMC5886119/ /pubmed/29360813 http://dx.doi.org/10.1038/bjc.2017.477 Text en Copyright © 2018 Cancer Research UK http://creativecommons.org/licenses/by-nc-sa/4.0/ From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/
spellingShingle Molecular Diagnostics
Van Laar, Ryan
Lincoln, Mitchel
Van Laar, Barton
Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title_full Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title_fullStr Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title_full_unstemmed Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title_short Development and validation of a plasma-based melanoma biomarker suitable for clinical use
title_sort development and validation of a plasma-based melanoma biomarker suitable for clinical use
topic Molecular Diagnostics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886119/
https://www.ncbi.nlm.nih.gov/pubmed/29360813
http://dx.doi.org/10.1038/bjc.2017.477
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