TY - JOUR
T1 - Classification of node-positive melanomas into prognostic subgroups using keratin, immune, and melanogenesis expression patterns
AU - Netanely, Dvir
AU - Leibou, Stav
AU - Parikh, Roma
AU - Stern, Neta
AU - Vaknine, Hananya
AU - Brenner, Ronen
AU - Amar, Sarah
AU - Factor, Rivi Haiat
AU - Perluk, Tomer
AU - Frand, Jacob
AU - Nizri, Eran
AU - Hershkovitz, Dov
AU - Zemser-Werner, Valentina
AU - Levy, Carmit
AU - Shamir, Ron
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/3/10
Y1 - 2021/3/10
N2 - Cutaneous melanoma tumors are heterogeneous and show diverse responses to treatment. Identification of robust molecular biomarkers for classifying melanoma tumors into clinically distinct and homogenous subtypes is crucial for improving the diagnosis and treatment of the disease. In this study, we present a classification of melanoma tumors into four subtypes with different survival profiles based on three distinct gene expression signatures: keratin, immune, and melanogenesis. The melanogenesis expression pattern includes several genes that are characteristic of the melanosome organelle and correlates with worse survival, suggesting the involvement of melanosomes in melanoma aggression. We experimentally validated the secretion of melanosomes into surrounding tissues by melanoma tumors, which potentially affects the lethality of metastasis. We propose a simple molecular decision tree classifier for predicting a tumor’s subtype based on representative genes from the three identified signatures. Key predictor genes were experimentally validated on melanoma samples taken from patients with varying survival outcomes. Our three-pattern approach for classifying melanoma tumors can contribute to advancing the understanding of melanoma variability and promote accurate diagnosis, prognostication, and treatment.
AB - Cutaneous melanoma tumors are heterogeneous and show diverse responses to treatment. Identification of robust molecular biomarkers for classifying melanoma tumors into clinically distinct and homogenous subtypes is crucial for improving the diagnosis and treatment of the disease. In this study, we present a classification of melanoma tumors into four subtypes with different survival profiles based on three distinct gene expression signatures: keratin, immune, and melanogenesis. The melanogenesis expression pattern includes several genes that are characteristic of the melanosome organelle and correlates with worse survival, suggesting the involvement of melanosomes in melanoma aggression. We experimentally validated the secretion of melanosomes into surrounding tissues by melanoma tumors, which potentially affects the lethality of metastasis. We propose a simple molecular decision tree classifier for predicting a tumor’s subtype based on representative genes from the three identified signatures. Key predictor genes were experimentally validated on melanoma samples taken from patients with varying survival outcomes. Our three-pattern approach for classifying melanoma tumors can contribute to advancing the understanding of melanoma variability and promote accurate diagnosis, prognostication, and treatment.
UR - http://www.scopus.com/inward/record.url?scp=85100732321&partnerID=8YFLogxK
U2 - 10.1038/s41388-021-01665-0
DO - 10.1038/s41388-021-01665-0
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C2 - 33564068
AN - SCOPUS:85100732321
SN - 0950-9232
VL - 40
SP - 1792
EP - 1805
JO - Oncogene
JF - Oncogene
IS - 10
ER -