Genomic and transcriptomic analyses of thyroid cancers identify DICER1 somatic mutations in adult follicular-patterned RAS-like tumors

Abstract

Background: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC). Several genomic and transcriptomic studies explored the molecular landscape of follicular cell-derived TCs, and BRAFV600E, RAS mutations, and gene fusions are well-established drivers. DICER1 mutations were described in specific sets of TC patients but represent a rare event in adult TC patients.

Methods: Here, we report the molecular characterization of 30 retrospective follicular cell-derived thyroid tumors, comprising PTCs (90%) and poorly differentiated TCs (10%), collected at our Institute. We performed DNA whole-exome sequencing using patient-matched control for somatic mutation calling, and targeted RNA-seq for gene fusion detection. Transcriptional profiles established in the same cohort by microarray were investigated using three signaling-related gene signatures derived from The Cancer Genome Atlas (TCGA).

Results: The occurrence of BRAFV600E (44%), RAS mutations (13%), and gene fusions (13%) was confirmed in our cohort. In addition, in two patients lacking known drivers, mutations of the DICER1 gene (p.D1709N and p.D1810V) were identified. DICER1 mutations occur in two adult patients with follicular-pattern lesions, and in one of them a second concurrent DICER1 mutation (p.R459*) is also observed. Additional putative drivers include ROS1 gene (p.P2130A mutation), identified in a patient with a rare solid-trabecular subtype of PTC. Transcriptomics indicates that DICER1 tumors are RAS-like, whereas the ROS1-mutated tumor displays a borderline RAS-/BRAF-like subtype. We also provide an overview of DICER1 and ROS1 mutations in thyroid lesions by investigating the COSMIC database.

Conclusion: Even though small, our series recapitulates the genetic background of PTC. Furthermore, we identified DICER1 mutations, one of which is previously unreported in thyroid lesions. For these less common alterations and for patients with unknown drivers, we provide signaling information applying TCGA-derived classification.

Keywords: DICER1; mutations; thyroid cancer; transcriptomics; whole exome sequencing.

Figure 1

Summary of the thyroid cancer caselist processing and features. (A) Flowchart of thyroid tissue selection and processing to obtain the set of 30 thyroid cancer (TC) patients who undergone genomic and transcriptomic molecular profiling. Part of this Figure has been created using Biorender under institutional account. (B) Pie chart of the histological subtype distribution in the 30 TC patients. Abbreviations: NT, non-neoplastic thyroid; FFPE, formalin-fixed paraffin-embedded tissue; H&E, hematoxylin and eosin; WES, whole-exome sequencing; PTC, papillary thyroid carcinoma; PDTC, poorly differentiated thyroid carcinoma.

Figure 2

Genomic and transcriptomic characterization of the 30 thyroid cancer patients. (A) The mutational load (bar chart, top panel), histology features (middle panel), and driver/putative driver mutations (lower panel) are shown for each patient. Mutational load represents the number of somatic non-synonymous mutations (missense, nonsense, and splice-site mutations with amino acid changing). (B) Gene fusion detected by targeted RNA-seq. (C) Selected genes mutated in our cohort, including mitochondrial function-related genes (middle panel) and commonly mutated genes (lower panel). (D) Signaling subtypes defined by gene expression score based on TCGA gene signatures related to BRAF-RAS signaling (BRAF-/RAS-like score, BRS), thyroid differentiation (TD score), and activation status of the MAPK pathway (MAPK output score). Patient identifiers and color-code legends are shown at the bottom. (E) Pie chart showing the distribution of driver/putative driver alterations in the 30 TC patients. (F) Boxplot with scatter plot showing signaling subtypes in the 30 TC patients stratified for alteration. Two non-neoplastic thyroids (NTs) are included as controls. Tumors with unknown driver and gene fusion data not available (NA) are shown as a separate group.

Figure 3

DICER1 mutations in thyroid lesions derived from COSMIC. Heatmap of DICER1 mutations in 53 patients across 20 studies. The tissue histology is shown, when available, according to the color-code legend on the right; the study identifier (see Table 2 ) is at the bottom. Each column represents a patient; four patients with multiple tissues tested are displayed as adjacent lanes, highlighted by bolt lines on study identifier. DICER1 mutations (row) are listed based on (A) most frequently mutated codons, the percentage across samples (n = 61) reported; (B) patient-specific mutations; (C) second-hit somatic mutations. Green squares on the mutation list highlight the two mutations identified also in the present study. (D) Pie chart of histological subtypes distribution; all the specimens (n = 58) were considered. Abbreviation: A, adenoma; NG, nodular goiter, FA, follicular adenoma; TC, thyroid carcinoma; PTC, papillary TC; FV, follicular variant/subtype; FTC, follicular TC; HCC, hurtle cell carcinoma; solid, solid subtype; PDTC, poorly differentiated TC; ATC, anaplastic TC. A/NG/FA were computed as a single class of benign lesions. PTC and TC non-specified classes include samples with a non-specified histological subtype.