Predictive biomarkers in advanced melanoma: integration of spatial transcriptomics and multimodal data for personalized therapies

• Grant number: 25/00393-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: October 01, 2025
• End date: September 30, 2028
• Field of knowledge: Biological Sciences - Immunology - Applied Immunology
• Principal Investigator: Lidia Maria Rebolho Batista Arantes
• Grantee: Renan de Jesus Teixeira
• Host Institution: Hospital do Câncer de Barretos. Barretos , SP, Brazil
• Associated research grant: 19/07111-9 - Immune-checkpoint inhibitors: immunophenotyping and clinical outcome to predict response at Barretos Cancer Hospital, AP.JP

Abstract

Introduction: Melanoma is a highly lethal cancer with a rising global incidence. Immunotherapy has revolutionized the management of advanced melanoma, significantly improving patient survival. However, challenges such as treatment resistance, tumor heterogeneity, and high costs still limit its overall effectiveness. The identification of response biomarkers emerges as a strategy to select patients who may benefit from immunotherapy, optimizing clinical outcomes and reducing costs. Objective: To identify biomarkers capable of predicting therapeutic response and progression-free survival in patients with advanced melanoma treated with immune checkpoint inhibitors. Methodology: This study will include patients with advanced melanoma treated with anti-PD-1 therapy at the Barretos Cancer Hospital between 2016 and 2024. Immunotherapy response will be assessed according to iRECIST criteria. Tumor samples from 16 patients will be analyzed using spatial transcriptomics with the Human Immuno-Oncology Panel (10x Genomics) to identify biomarkers associated with antitumor immune response. Biomarker validation will be performed through immunofluorescence in a cohort of 100 patients. Statistical analyses, conducted using SPSS software, will explore associations between molecular data, clinical parameters, and therapeutic outcomes. Expected Results: The study aims to identify predictive biomarkers that can guide therapeutic decisions and optimize the effectiveness of immunotherapy. Tools such as Xenium in situ technology, which enables the mapping of gene expression across specific tumor regions, and immunofluorescence, will be key to translating these findings into clinical applications.