Molecular intelligence and immune reconnaissance in thyroid cancer: a new paradigm for diagnosis, risk stratification, and therapeutic precision.
Authors
Affiliations (7)
Affiliations (7)
- School of Medicine, Universidad Científica Del Sur Lima, Peru.
- Research Center in Health Sciences and Biomedicine, Universidad Autónoma de San Luis Potosí San Luis, Mexico.
- School of Medicine, Universidad Autónoma de San Luis Potosí San Luis Potosí, Mexico.
- School of Medicine, Universidad Nacional de Trujillo Trujillo, Peru.
- Macon & Joan Brock Virginia Health Sciences, EVMS at Old Dominion University, Norfolk, Virginia, USA.
- School of Medicine, Universidad Nacional Mayor de San Marcos Lima, Peru.
- Division of Medicine, Hospital de Apoyo Chepén Chepén, Perú.
Abstract
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. 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. 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.