Validation of an Ultraviolet Light Response Gene Signature for Predicting Prognosis in Patients with Uveal Melanoma

Author:

Orozco Carlos A.1234ORCID,Mejía-García Alejandro5,Ramírez Marcela12,González Johanna13,Castro-Vega Luis6,Kreider Richard B.7ORCID,Serrano Silvia8,Combita Alba Lucia910,Bonilla Diego A.1112ORCID

Affiliation:

1. Health and Sport Sciences Research Group, School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá 111221, Colombia

2. Professional Program in Surgical Instrumentation, School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá 111221, Colombia

3. Professional Program in Optometry, School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá 111221, Colombia

4. Technical Program in Radiology and Diagnostic Imaging, School of Health and Sport Sciences, Fundación Universitaria del Área Andina, Bogotá 111221, Colombia

5. Grupo de Investigación Genética Molecular (GENMOL), Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia, Medellín 050010, Colombia

6. Genetics and Development of Brain Tumors Team, Paris Brain Institute (ICM), Hôpital Pitié-Salpêtrière, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, 75013 Paris, France

7. Exercise & Sport Nutrition Lab, Human Clinical Research Facility, Texas A&M University, College Station, TX 77843, USA

8. Grupo de Investigación en Biología del Cáncer, Instituto Nacional de Cancerología de Colombia, Bogotá 111511, Colombia

9. Grupo de Investigación Traslacional en Oncología, Instituto Nacional de Cancerología de Colombia, Bogotá 111511, Colombia

10. School of Medicine, Microbiology Department, Universidad Nacional de Colombia, Bogotá 111321, Colombia

11. Research Division, Dynamical Business & Science Society—DBSS International SAS, Bogotá 110311, Colombia

12. Research Group in Physical Activity, Sports and Health Sciences (GICAFS), Universidad de Córdoba, Montería 230002, Colombia

Abstract

Uveal melanoma (UVM) is a highly aggressive ocular cancer with limited therapeutic options and poor prognosis particularly for patients with liver metastasis. As such, the identification of new prognostic biomarkers is critical for developing effective treatment strategies. In this study, we aimed to investigate the potential of an ultraviolet light response gene signature to predict the prognosis of UVM patients. Our approach involved the development of a prognostic model based on genes associated with the cellular response to UV light. By employing this model, we generated risk scores to stratify patients into high- and low-risk groups. Furthermore, we conducted differential expression analysis between these two groups and explored the estimation of immune infiltration. To validate our findings, we applied our methodology to an independent UVM cohort. Through our study, we introduced a novel survival prediction tool and shed light on the underlying cellular processes within UVM tumors, emphasizing the involvement of immune subsets in tumor progression.

Funder

Exercise and Sport Nutrition Laboratory at Texas A&M

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry

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