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Atrophic changes in thyroid tumors are strong indicators of underlying DICER1 mutations: a bi-institutional genotype-phenotype correlation study.

Vincenzo CondelloJames W RobertsStenman AdamCatharina LarssonKartik ViswanathanCarl Christofer Juhlin
Published in: Virchows Archiv : an international journal of pathology (2024)
Somatic and biallelic DICER1 mutations are reported in subsets of thyroid tumors, supporting the role of this gene in thyroid tumor development. As recent studies have brought attention to macrofollicular patterns, atrophic changes, and papillary structures as being associated with DICER1 mutations, we sought to explore these observations in a bi-institutional cohort. A total of 61 thyroid lesions (54 tumors and 7 cases of thyroid follicular nodular disease; TFND), including 26 DICER1 mutated and 35 DICER1 wildtype controls were subjected to histological re-investigation and clinical follow-up. DICER1-mutated lesions showed a statistically significant association with younger age at surgery (29.2 ± 12.5 versus 51.3 ± 18.8, p = 0.0001), a predominant macrofollicular growth pattern (20/26 mutated cases versus 18/35 wildtype; p = 0.01) and atrophic changes (20/26 mutated cases versus 2/35 wildtype; p = 0.0001). Similar results were obtained when excluding TFND cases. We also present clinical and histological triaging criteria for DICER1 sequencing of thyroid lesions, which led to the identification of DICER1 variants in 16 out of 26 cases (62%) when followed. Among these, 3 out of 12 cases with available data were found to carry a constitutional DICER1 mutation. This observation suggests that the majority of DICER1 mutations are somatic-however implies that sequencing of constitutional tissues could be clinically motivated. We conclude that DICER1 mutations are amassed in younger patients with macrofollicular-patterned tumors and, most strikingly, atrophic changes. Given the rate of constitutional involvement, our findings could be of clinical value, allowing the pathologist to triage cases for genetic testing based on histological findings.
Keyphrases
  • copy number
  • emergency department
  • gene expression
  • minimally invasive
  • machine learning
  • dna methylation
  • genome wide
  • acute coronary syndrome
  • percutaneous coronary intervention