Oliveira MMGL, Lemos CS, Brazão MLS, Rodrigues ALA, do Nascimento EDC, Cardoso EMP, Arantes MFF, de Melo FF. Immune landscape of melanoma: Tumor microenvironment, resistance mechanisms, and predictive biomarkers. World J Clin Oncol 2026; 17(1): 114913 [DOI: 10.5306/wjco.v17.i1.114913]
Corresponding Author of This Article
Fabrício F de Melo, PhD, Professor, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, No. 58 Rua Hormindo Barros, Quadra 17, Lote 58, Vitória da Conquista 45029-094, Bahia, Brazil. freiremeloufba@gmail.com
Research Domain of This Article
Oncology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Oncol. Jan 24, 2026; 17(1): 114913 Published online Jan 24, 2026. doi: 10.5306/wjco.v17.i1.114913
Immune landscape of melanoma: Tumor microenvironment, resistance mechanisms, and predictive biomarkers
Marina M G L Oliveira, Carol S Lemos, Mariangela L S Brazão, Alice L A Rodrigues, Evelin da C do Nascimento, Emylli M P Cardoso, Maria F F Arantes, Fabrício F de Melo
Marina M G L Oliveira, Carol S Lemos, Mariangela L S Brazão, Alice L A Rodrigues, Evelin da C do Nascimento, Emylli M P Cardoso, Maria F F Arantes, Fabrício F de Melo, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
Author contributions: Oliveira MMGL, Lemos CS, Brazão MLS, Rodrigues ALA, do Nascimento EDC, Cardoso EMP, and Arantes MFF researched the content and wrote the original draft; Oliveira MMGL developed the tables and figure, systematized the text, developed the abstract, introduction, conclusion, and handled the guidelines for the preparation and submission of the review; de Melo FF reviewed the articles during the writing process, providing suggestions, and directing the research, thoroughly reviewed the entire article; all the cited authors contributed significantly to the production of the article and approved the final version to publish.
Supported by CNPq Research Productivity Fellow, No. 309110/2025-4.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fabrício F de Melo, PhD, Professor, Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, No. 58 Rua Hormindo Barros, Quadra 17, Lote 58, Vitória da Conquista 45029-094, Bahia, Brazil. freiremeloufba@gmail.com
Received: October 1, 2025 Revised: October 24, 2025 Accepted: November 27, 2025 Published online: January 24, 2026 Processing time: 111 Days and 10.9 Hours
Abstract
Melanoma, a highly immunogenic malignancy, has become a paradigm for immune-based therapies. Despite remarkable responses to immune checkpoint inhibitors, many patients exhibit primary or acquired resistance. These outcomes are largely driven by the composition and dynamics of the tumor microenvironment, which shape immune activation, suppression, and therapeutic responsiveness, contributing to immune escape. Moreover, checkpoint molecule expression, altered antigen presentation, and immunosuppressive cytokine profiles further hinder effective immune surveillance. Advances in biomarker discovery have provided valuable insights into predicting therapy response and guiding individualized treatment. This review discusses the interplay between melanoma and its immune microenvironment, explores mechanisms of immune resistance, and highlights emerging predictive biomarkers with potential to refine clinical decision-making and improve outcomes.
Core Tip: Melanoma represents a model disease for immuno-oncology, highlighting both the efficacy and limitations of immune-based therapies. Its highly immunogenic nature, coupled with the complexity of the tumor microenvironment, drives variable treatment responses and resistance to immune checkpoint blockade and targeted therapies. By integrating insights into tumor-immune interactions, resistance pathways, and predictive biomarkers, novel therapeutic strategies, particularly rational combinations of immunotherapy, targeted agents, and next-generation immunomodulators, are paving the way toward more durable and personalized clinical outcomes.
