Histology-based molecular profiling improves mutation detection for advanced thyroid cancer

Markus Eszlinger1,2, Moosa Khalil3, Aaron Hill Gillmor4

  • 1Departments of Oncology, Pathology and Laboratory Medicine, Biochemistry and Molecular Biology, and Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Insights

Histologic heterogeneity in advanced thyroid cancer correlates with molecular differences. Comprehensive molecular profiling guided by histology can identify actionable mutations for targeted tyrosine kinase inhibitor (TKI) therapy.

Area of Science:

  • Oncology
  • Genomics
  • Precision Medicine

Background:

  • Advanced thyroid carcinomas often exhibit significant intratumoral heterogeneity.
  • Radioiodine-resistant (RAIR) thyroid cancers present therapeutic challenges due to this heterogeneity.
  • Understanding molecular drivers is crucial for effective treatment strategies.

Purpose of the Study:

  • To comprehensively characterize advanced, metastatic RAIR thyroid carcinomas at the molecular level.
  • To investigate the relationship between histologic and molecular heterogeneity.
  • To identify actionable mutations for guiding tyrosine kinase inhibitor (TKI) treatment.

Main Methods:

  • Whole exome sequencing (WES) of 29 macrodissected tissue samples from heterogeneous and homogeneous areas, and metastases.
  • Analysis of potential driver mutations, copy number alterations, and microsatellite instability.
  • Reconstruction of molecular phylogeny to assess evolutionary history and heterogeneity.

Main Results:

  • Identified known driver mutations (BRAF, NRAS, TERT, etc.) and novel actionable drivers (AKT1, ATM, MLH3, etc.).
  • Demonstrated a strong association between histologic heterogeneity and molecular profiling results.
  • Revealed mutant-allele tumor heterogeneity within samples.

Conclusions:

  • Histologic heterogeneity significantly impacts molecular profiling in advanced thyroid cancer.
  • Comprehensive molecular analysis guided by meticulous histologic evaluation is essential for patient stratification.
  • This approach can optimize the use of targeted therapies like TKIs for improved precision medicine outcomes.

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