Molecular intelligence and immune reconnaissance in thyroid cancer: a new paradigm for diagnosis, risk stratification, and therapeutic precision

Concepción-Zavaleta M.J.; Fuentes-Mendoza J.M.; Cruz-Quintá A.; Cadena-Guerrero A.V.; Barrón X.; Concepción-Urteaga L.; D. Armas C.; Paz-Ibarra J.; Quiroz-Aldave J.E. · Expert Review of Anticancer Therapy (2026) · DOI: 10.1080/14737140.2025.2604618

Resumen

Introduction: Thyroid cancer management is shifting from morphology-based assessment to precision oncology driven by integrated molecular profiling and computational analytics. This review examines how these advances address overdiagnosis, indeterminate cytology, and radioiodine-refractory disease. Areas covered: We synthesize recent evidence on multi-analyte next-generation sequencing panels, the prognostic impact of co-occurring mutations, characterization of the tumor immune microenvironment, and therapeutic innovations (targeted agents and immunomodulatory strategies). We also summarize applications of artificial intelligence in ultrasound, cytology, and text mining. Literature was identified through structured searches of PubMed/MEDLINE, Scopus, and Web of Science for English-language studies published between January 2020 and June 2024, prioritizing original research, clinical trials, meta-analyses, and high-quality reviews. Expert opinion: The field is converging toward an integrated framework that combines genomic architecture, immune contexture, and AI-derived features to refine surgical decisions, guide radioactive iodine use, and select systemic therapy. Near-term priorities include standardizing multi-omic pipelines, validating AI across diverse populations, and expanding access to testing, while emerging tools such as liquid biopsy and patient-derived organoids are poised to enable adaptive, patient-specific management.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional de Trujillo; Universidad Científica del Sur