Official Publication of the Instituto Israelita de Ensino e Pesquisa Albert Einstein ORIGINAL ARTICLE einstein (São Paulo) ❚ Authors Bárbara dos Santos Dias, Larissa Figueiredo Alves Diniz, Lucca D’Arco Corrêa, Rafael Pereira de Souza, Leticia Torres Ferreira, Denise da Cunha Pasqualin, Rafael de Cicco, Eloiza Helena Tajara da Silva, Patricia Severino ❚ Correspondence E-mail: patricia.severino@einstein.br ❚ DOI DOI: 10.31744/einstein_journal/2025AO1372 ❚ In Brief We evaluated the performance of TargetScan, miRDB, and miRWalk for predicting miRNA-mRNA interactions in HNSCC. Based on clinical tumor and cancer-free tissue data, miRWalk emerged as the most comprehensive tool. Validation using NanoString technology and MiRTarBase confirmed key predictions, highlighting the important roles of the PI3K-Akt and Wnt pathways. This study underscores the importance of integrating bioinformatics and experimental data to better understand HNSCC. ❚ How to cite this article: Dias BS, Diniz LF, Corrêa LD, Souza RP, Ferreira LT, Pasqualin DC, et al. Comparative analysis of miRNA-mRNA interaction prediction tools based on experimental head and neck cancer data. einstein (São Paulo). 2025;23:eAO1372. Comparative analysis of miRNA-mRNA interaction prediction tools based on experimental head and neck cancer data ❚ Highlights ■ miRWalk had the highest predicted interactions and validated miRNA networks in HNSCC. ■ Around 3.3% of interactions overlapped across tools, emphasizing the need for multitool approaches. ■ Dysregulated genes and miRNAs were tied to cancer- driving PI3K-Akt and Wnt pathways. ■ The validated approach highlights the importance of integrating computational and molecular data.