Biomarkers for Predicting Malignant Transformation of Premalignant Lesions of the Larynx: A Systematic Review - Rodrigo, Juan P.; de Lima-Souza; Reydson Alcides; López, Fernando; Stenman, Göran; Agaymy, Abbas; Quer, Miquel; Paleri, Vinidh; Leivo, Ilmo; Nadal, Alfons; Zidar, Nina; Mariano, Fernanda V.; et al. (MDPI AG, 2026)
Background/Objectives: Premalignant laryngeal lesions carry a variable risk of malignant transformation to squamous cell carcinoma. Identifying reliable biomarkers that predict malignant transformation could improve patient management and surveillance strategies. The objective of this work is to perform a systematic review of the literature on biomarkers that predict malignant transformation of premalignant laryngeal lesions.
Methods: We conducted a systematic review following PRISMA 2020 guidelines. The PubMed, Scopus and Embase databases, and Google Scholar were searched for studies published between January 2011 and November 2025. Studies investigating biomarkers that predict malignant transformation of histopathologically confirmed premalignant laryngeal lesions were included. Risk of bias was assessed using the ROBINS-I tool.
Results: From 166 initially identified records, 11 studies met the inclusion criteria, including 730 patients. These studies investigated diverse biomarker categories such as protein markers (cortactin, FAK, NANOG, SOX2, CSPG4), immune markers (tumor-infiltrating lymphocytes, immune gene signatures), microRNAs (miR-183-5p, miR-155-5p, miR-106b-3p), and genetic markers (chromosomal instability, PIK3CA amplification and mutations, FGFR3 mutations). Five studies provided adequate follow-up data on transformation outcomes. Most studies showed a moderate to serious risk of bias primarily due to limited confounder control and incomplete reporting.
Conclusions: While several promising biomarker candidates have been identified, the evidence base remains limited due to small sample sizes, heterogeneous methodologies, and inadequate follow-up data. Cortactin/FAK protein expression and immune signatures are the most promising but require validation in larger, well-designed prospective cohorts.