An Optimized NGS Workflow Defines Genetically Based Prognostic Categories for Patients with Uveal Melanoma

An Optimized NGS Workflow Defines Genetically Based Prognostic Categories for Patients with Uveal Melanoma

Background: Despite advances in uveal melanoma (UM) diagnosis and treatment, about 50% of patients develop distant metastases, thereby displaying poor overall survival. Molecular profiling has identified several genetic alterations that can stratify patients with UM into different risk categories. H...

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Main Authors: Michele Massimino, Elena Tirrò, Stefania Stella, Cristina Tomarchio, Sebastiano Di Bella, Silvia Rita Vitale, Chiara Conti, Marialuisa Puglisi, Rosa Maria Di Crescenzo, Silvia Varricchio, Francesco Merolla, Giuseppe Broggi, Federica Martorana, Alice Turdo, Miriam Gaggianesi, Livia Manzella, Andrea Russo, Giorgio Stassi, Rosario Caltabiano, Stefania Staibano, Paolo Vigneri
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Biomolecules
Subjects:
molecular profiling
TCGA
uveal melanoma
NGS
Online Access:https://www.mdpi.com/2218-273X/15/1/146
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Summary:Background: Despite advances in uveal melanoma (UM) diagnosis and treatment, about 50% of patients develop distant metastases, thereby displaying poor overall survival. Molecular profiling has identified several genetic alterations that can stratify patients with UM into different risk categories. However, these genetic alterations are currently dispersed over multiple studies and several methodologies, emphasizing the need for a defined workflow that will allow standardized and reproducible molecular analyses. Methods: Following the findings published by “The Cancer Genome Atlas–UM” (TCGA-UM) study, we developed an NGS-based gene panel (called the UMpanel) that classifies mutation sets in four categories: initiating alterations (<i>CYSLTR2</i>, <i>GNA11</i>, <i>GNAQ</i> and <i>PLCB4</i>), prognostic alterations (<i>BAP1</i>, <i>EIF1AX</i>, <i>SF3B1</i> and <i>SRSF2</i>), emergent biomarkers (<i>CDKN2A</i>, <i>CENPE</i>, <i>FOXO1</i>, <i>HIF1A</i>, <i>RPL5</i> and <i>TP53</i>) and chromosomal abnormalities (imbalances in chromosomes 1, 3 and 8). Results: Employing commercial gene panels, reference mutated DNAs and Sanger sequencing, we performed a comparative analysis and found that our methodological approach successfully predicted survival with great specificity and sensitivity compared to the TCGA-UM cohort that was used as a validation group. Conclusions: Our results demonstrate that a reproducible NGS-based workflow translates into a reliable tool for the clinical stratification of patients with UM.
ISSN:2218-273X

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