Multi-omics profiling of papillary thyroid microcarcinoma reveals different somatic mutations and a unique transcriptomic signature

Predicting papillary thyroid microcarcinoma in American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 3 nodules: radiomics analysis based on intratumoral and peritumoral ultrasound images

Background

A subset of patients undergoing thyroid surgery for presumed benign thyroid disease presented with papillary thyroid microcarcinoma (PTMC). A non-invasive and precise method for early recognition of PTMC are urgently needed. The aim of this study was to construct and validate a nomogram that combines intratumoral and peritumoral radiomics features as well as clinical features for predicting PTMC in the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 3 nodules using ultrasonography.

Methods

A retrospective review was conducted on a cohort of 221 patients who presented with ACR TI-RADS 3 nodules. These patients were subsequently pathologically diagnosed with either PTMC or benign thyroid nodules. These patients were randomly divided into a training and test cohort with an 8:2 ratio for developing the clinical model, intratumor-region model, peritumor-region model and the combined-region model respectively. The radiomics features were extracted from ultrasound (US) images of each patient. We employed K-nearest neighbor (KNN) model as the base model for building the radiomics signature and clinical signature. Finally, a radiomics-clinical nomogram that combined intratumoral and peritumoral radiomics features as well as clinical features was developed. The prediction performance of each model was assessed by the area under the curve (AUC), sensitivity, specificity and calibration curve.

Results

A total of 23 radiomics features were selected to develop radiomics models. The combined-region radiomics model showed favorable prediction efficiency in both the training dataset (AUC: 0.955) and the test dataset (AUC: 0.923). A radiomics-clinical nomogram was constructed and achieved excellent calibration and discrimination, which yielded an AUC value of 0.950, a sensitivity of 0.950 and a specificity of 0.920.

Conclusions

This study proposed the nomogram that contributes to the accurate and intuitive identification of PTMC in ACR TI-RADS 3 nodules.

Feasibility of whole-exome sequencing in fine-needle aspiration specimens of papillary thyroid microcarcinoma for the identification of novel gene mutations

Genetic profiling is important for assisting the management of papillary thyroid microcarcinoma (PTMC). Although whole-exome sequencing (WES) of surgically resected PTMC tissue has been performed and revealed potential prognostic biomarkers, its application in PTMC fine-needle aspiration (FNA) specimens has not been explored. This study aimed to evaluate the feasibility of WES using FNA specimens of PTMC. Five PTMC patients were enrolled with clinical characteristics gathered. Fine aspiration cytology needle (23 gauges) was used to collect FNA biopsy with ultrasound guidance. WES analysis of FNA specimens from five PTMC patients and matched blood samples was performed. The WES of FNA samples yielded an average sequencing depth of 281× and average coverage of 99.5%. We identified 534 somatic single-nucleotide variants and 13 indels in total, and per sample, we found a mean of 24 exonic mutations, which affected a total of 120 genes. In the PTMC FNA samples, the most frequently mutated genes were BRAF and ANKRD18B, and the four driver genes were BRAF, AFF3, SRCAP, and EGFR. We also identified several germline cancer predisposing gene mutations. The results suggest that WES of FNA specimens is feasible for PTMC and can identify novel genetic mutations.