Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study

Author:

Peña-Martín Jesús1234,Belén García-Ortega María34,Palacios-Ferrer José Luis1234,Díaz Caridad5,Ángel García María1346,Boulaiz Houria1234,Valdivia Javier37,Jurado José Miguel37,Almazan-Fernandez Francisco M38,Arias Santiago Salvador39,Vicente Francisca5,del Val Coral310,Pérez del Palacio José5,Marchal Juan Antonio1234ORCID

Affiliation:

1. Biopathology and Regenerative Medicine Institute (IBIMER), Centre for Biomedical Research (CIBM)

2. Department of Human Anatomy and Embryology, Faculty of Medicine

3. Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA) , Granada , Spain

4. Excellence Research Unit “Modeling Nature” (MNat)

5. Fundación MEDINA, Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía. Parque Tecnológico Ciencias de la Salud , Granada , Spain

6. Department of Biochemistry 3 and Immunology, Faculty of Medicine

7. Department of Oncology

8. Department of Dermatology, San Cecilio University Hospital , Granada , Spain

9. Department of Dermatology, Virgen de las Nieves University Hospital , Granada , Spain

10. Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada , Granada , Spain

Abstract

Abstract Background Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge. Objectives To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management. Methods In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM. Results We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample. Conclusions These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

Funder

Ministerio de Ciencia e Innovación

Instituto de Salud Carlos III

Junta de Andalucía

Publisher

Oxford University Press (OUP)

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