Molecular Prioritization of Gene Therapy Targets in Skin Cancer Using the MEREC–VIKOR Multi-Criteria Decision-Making Approach

Abstract

Despite advances in oncogenomics, the development of gene therapies for melanoma continues to experience a considerable rate of failure during clinical translation. This limitation largely stems from reliance on unidimensional selection criteria, such as mutation frequency, while overlooking critical technical and safety-related challenges. The present study aims to establish a systematic Multi-Criteria Decision-Making (MCDM) framework for the optimal prioritization of therapeutic targets by balancing biological potential with operational feasibility. In this study, 20 candidate genes—including oncogenic drivers, tumor suppressors, and immune-related factors—were evaluated against 10 key criteria, including functional significance, compatibility with gene-delivery vectors, druggability, and immunological risk profile. By integrating the Method based on the Removal Effects of Criteria (MEREC) method for objective weighting and bias reduction with the Multicriteria Optimization and Compromise Solution (VIKOR) method for ranking, a comprehensive framework was developed to identify and prioritize promising therapeutic targets. The findings revealed that the genes NRAS, STAT3, and TP53 achieved the highest rankings and emerged as the most promising therapeutic candidates. The consistency of these priorities with previously reported evidence supports the scientific validity of the proposed framework. However, the principal innovation of this study lies in its ability to systematically identify candidates that maintain therapeutic efficacy while imposing the lowest technical and safety burdens for gene delivery. Notably, the proposed approach strategically assigned lower priority to targets with high clinical relevance but substantial technological and translational challenges, such as PD-L1, thereby demonstrating its discriminatory power under real-world clinical constraints. By moving beyond conventional target-selection paradigms, this framework provides a strategic tool for precision medicine, enabling research resources to be directed toward targets with the greatest likelihood of successful clinical translation rather than toward high-risk exploratory approaches. Ultimately, this study offers a reproducible roadmap for translational oncogenomics and establishes a foundation for future in vivo investigations aimed at advancing the next generation of safe and effective gene therapies for melanoma.