학술논문

Lipid fingerprint-based histology accurately classifies nevus, primary melanoma, and metastatic melanoma samples.
Document Type
Academic Journal
Author
Huergo-Baños C; Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain.; Velasco V; Department of Pathology, Cruces University Hospital, Barakaldo, Spain.; Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain.; Garate J; Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain.; Fernández R; Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain.; Martín-Allende J; Languages and Computer Systems, School of Engineering University of the Basque Country (UPV/EHU), Bilbao, Spain.; Zabalza I; Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain.; Department of Pathology, Galdakao-Usansolo University Hospital, Galdakao, Spain.; Artola JL; Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain.; Department of Dermatology, Galdakao-Usansolo University Hospital, Galdakao, Spain.; Martí RM; Department of Dermatology, Arnau de Vilanova University Hospital, Institute of Biomedic Research (IRBLleida), University of Lleida, Lleida, Spain.; Centre of Biomedical Research on Cancer (CIBERONC), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.; Asumendi A; Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain.; Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain.; Astigarraga E; Department R+D, IMG Pharma Biotech S.L., Derio, Spain.; Barreda-Gómez G; Department R+D, IMG Pharma Biotech S.L., Derio, Spain.; Fresnedo O; Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain.; Ochoa B; Department of Physiology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain.; Boyano MD; Biocruces-Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain.; Department of Cell Biology and Histology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Spain.; Fernández JA; Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain.
Source
Publisher: Wiley-Liss Country of Publication: United States NLM ID: 0042124 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0215 (Electronic) Linking ISSN: 00207136 NLM ISO Abbreviation: Int J Cancer Subsets: MEDLINE
Subject
Language
English
Abstract
Probably, the most important factor for the survival of a melanoma patient is early detection and precise diagnosis. Although in most cases these tasks are readily carried out by pathologists and dermatologists, there are still difficult cases in which no consensus among experts is achieved. To deal with such cases, new methodologies are required. Following this motivation, we explore here the use of lipid imaging mass spectrometry as a complementary tool for the aid in the diagnosis. Thus, 53 samples (15 nevus, 24 primary melanomas, and 14 metastasis) were explored with the aid of a mass spectrometer, using negative polarity. The rich lipid fingerprint obtained from the samples allowed us to set up an artificial intelligence-based classification model that achieved 100% of specificity and precision both in training and validation data sets. A deeper analysis of the image data shows that the technique reports important information on the tumor microenvironment that may give invaluable insights in the prognosis of the lesion, with the correct interpretation.
(© 2023 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)