8109 Cancer-Associated Fibroblasts Correlate with Aggressive Thyroid Cancer Behavior: Insights from Four Large Patient Cohorts

Abstract Disclosure: M.A. Loberg: None. X. George: None. P.J. Courtney: None. H.C. Eric: None. A. Golding: None. B. David: None. M. Alshalalfa: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R.T. Kloos: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc.. V. Weiss: None. Thyroid tumor molecular analysis often utilizes fine-needle aspirate (FNA) samples to predict malignancy with high sensitivity. An outstanding question is if molecular sequencing can provide prognostic information to predict disease aggression, potentially informing management. Recently, the composition of the tumor microenvironment, in particular the presence of tumor-promoting fibroblasts, has been associated with aggressive thyroid cancer. However, fibroblast gene expression has not previously been analyzed in thyroid tumor FNA samples. In this work, we detect cancer-associated fibroblast (CAF) gene signatures across 4 distinct bulk RNA sequencing cohorts and confirm detection in FNA samples. Associations between CAF gene signatures and tumor characteristics were explored in: Afirma Genomic Sequencing Classifier (GSC) cohort from FNA (n=47,695), a Memorial Healthcare System (MHS) retrospective FNA cohort with pathology outcome data (n=318), TCGA papillary thyroid cancers (n=496), and a Vanderbilt University Medical Center-University of Washington (VUMC-UW) resection cohort (n=312). Published breast CAF gene sets were used to generate normal fibroblast and CAF subtype scores. Novel thyroid cancer specific CAF gene sets were generated from thyroid cancer single-cell RNA sequencing data. Scores for each gene set were calculated as the average Z-score. Across all cohorts, multiple CAF subsets were enriched in samples with BRAFV600E and papillary histology. The strongest enrichment was in an SFRP2+ CAF subset identified in thyroid cancer single-cell sequencing data. In Afirma GSC FNA samples, SFRP2+ CAFs were enriched in GSC-suspicious and Bethesda V/VI relative to GSC-benign nodules (Wilcoxon p value < 2e-[1]6 for all). In TCGA, SFRP2+ CAFs were associated with extrathyroidal extension, advanced disease stage, and aggressive histology. In the MHS cohort of 318 malignant FNA samples, SFRP2+ CAFs were significantly higher in patients with vascular invasion or lymph node metastasis (LNM) (OR:2.75 [95% CI 1.63-4.75], p=4e-5). In the VUMC-UW cohort, SFRP2+ CAFs were associated with shorter progression-free survival (PFS) (p=0.0033). In summary we created a novel thyroid cancer-specific CAF gene signature that is elevated in BRAFV600E+ and aggressive thyroid cancers across multiple large patient cohorts. We also demonstrated the ability to detect these CAF signatures in thyroid FNAs using the Afirma GSC molecular testing platform, with enrichment in suspicious and malignant samples. Amongst the CAF scores tested, thyroid-specific CAF subsets had the highest prognostic potential, and SFRP2+ CAFs, specifically, were associated with shorter PFS, tumor invasion and LNM. Together, these results highlight the potential of interrogating the thyroid tumor stroma in FNA using RNA-based assays to inform prognosis and possibly management. Presentation: 6/3/2024