Metastatic Risk Stratification of 2526 Medullary Thyroid Carcinoma Patients: A Study Based on Surveillance, Epidemiology, and End Results Database

Transcriptomic Differences in Medullary Thyroid Carcinoma According to Grade

Medullary thyroid carcinoma (MTC) is a rare cancer derived from neuroendocrine C-cells of the thyroid. In contrast to other neuroendocrine tumors, a histological grading system was lacking until recently. A novel two-tier grading system based on the presence of high proliferation or necrosis is associated with prognosis. Transcriptomic analysis was conducted on 21 MTCs, including 9 high-grade tumors, with known mutational status, using the NanoString Tumor Signaling 360 Panel. This analysis, covering 760 genes, revealed upregulation of the genes EGLN3, EXO1, UBE2T, UBE2C, FOXM1, CENPA, DLL3, CCNA2, SOX2, KIF23, and CDCA5 in high-grade MTCs. Major pathways differentially expressed between high-grade and low-grade MTCs were DNA damage repair, p53 signaling, cell cycle, apoptosis, and Myc signaling. Validation through qRT-PCR in 30 MTCs demonstrated upregulation of ASCL1, DLL3, and SOX2 in high-grade MTCs, a gene signature akin to small-cell lung carcinoma, molecular subgroup A. Subsequently, DLL3 expression was validated by immunohistochemistry. MTCs with DLL3 overexpression (defined as ≥ 50% of positive tumor cells) were associated with significantly lower disease-free survival (p = 0.041) and overall survival (p = 0.01). Moreover, MTCs with desmoplasia had a significantly increased expression of DLL3. Our data supports the idea that DLL3 should be further explored as a predictor of aggressive disease and poor outcomes in MTC.

Novel prognostic nomogram for predicting recurrence-free survival in medullary thyroid carcinoma

AIMS

Recently, there have been attempts to improve prognostication and therefore better guide treatment for patients with medullary thyroid carcinoma (MTC). In 2022, the International MTC Grading System (IMTCGS) was developed and validated using a multi-institutional cohort of 327 patients. The aim of the current study was to build upon the findings of the IMTCGS to develop and validate a prognostic nomogram to predict recurrence-free survival (RFS) in MTC.

METHODS AND RESULTS

Data from 300 patients with MTC from five centres across the USA, Europe, and Australia were used to develop a prognostic nomogram that included the following variables: age, sex, AJCC stage, tumour size, mitotic count, necrosis, Ki67 index, lymphovascular invasion, microscopic extrathyroidal extension, and margin status. A process of 10-fold cross-validation was used to optimize the model's performance. To assess discrimination and calibration, the area-under-the-curve (AUC) of a receiver operating characteristic (ROC) curve, concordance-index (C-index), and dissimilarity index (D-index) were calculated. Finally, the model was externally validated using a separate cohort of 87 MTC patients. The model demonstrated very strong performance, with an AUC of 0.94, a C-index of 0.876, and a D-index of 19.06. When applied to the external validation cohort, the model had an AUC of 0.9.

CONCLUSIONS

Using well-established clinicopathological prognostic variables, we developed and externally validated a robust multivariate prediction model for RFS in patients with resected MTC. The model demonstrates excellent predictive capability and may help guide decisions on patient management. The nomogram is freely available online at https://nomograms.shinyapps.io/MTC_ML_DFS/.

Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database

Objectives

We aimed to establish an effective machine learning (ML) model for predicting the risk of distant metastasis (DM) in medullary thyroid carcinoma (MTC).

Methods

Demographic data of MTC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database of the National Institutes of Health between 2004 and 2015 to develop six ML algorithm models. Models were evaluated based on accuracy, precision, recall rate, F1-score, and area under the receiver operating characteristic curve (AUC). The association between clinicopathological characteristics and target variables was interpreted. Analyses were performed using traditional logistic regression (LR).

Results

In total, 2049 patients were included and 138 developed DM. Multivariable LR showed that age, sex, tumor size, extrathyroidal extension, and lymph node metastasis were predictive features for DM in MTC. Among the six ML models, the random forest (RF) had the best predictability in assessing the risk of DM in MTC, with an accuracy, precision, recall rate, F1-score, and AUC higher than those of the traditional binary LR model.

Conclusion

RF was superior to traditional LR in predicting the risk of DM in MTC and can provide a valuable reference for clinicians in decision-making.

Medullary Thyroid Carcinomas Classified According to the International Medullary Carcinoma Grading System and a Surveillance, Epidemiology, and End Results-Based Metastatic Risk Score: A Correlation With Genetic Profile and Angioinvasion

Due to the lack of a standardized tool for risk-based stratification, the International Medullary Carcinoma Grading System (IMTCGS) has been proposed for medullary thyroid carcinomas (MTCs) based on necrosis, mitosis, and Ki67. Similarly, a risk stratification study using the Surveillance, Epidemiology, and End Results (SEER) database highlighted significant differences in MTCs in terms of clinical-pathological variables. We aimed to validate both the IMTCGS and SEER-based risk table on 66 MTC cases, with special attention to angioinvasion and the genetic profile. We found a significant association between the IMTCGS and survival because patients classified as high-grade had a lower event-free survival probability. Angioinvasion was also found to be significantly correlated with metastasis and death. Applying the SEER-based risk table, patients classified either as intermediate- or high-risk had a lower survival rate than low-risk patients. In addition, high-grade IMTCGS cases had a higher average SEER-based risk score than low-grade cases. Moreover, when we explored angioinvasion in correlation with the SEER-based risk table, patients with angioinvasion had a higher average SEER-based score than patients without angioinvasion. Deep sequencing analysis found that 10 out of 20 genes frequently mutated in MTCs belonged to a specific functional class, namely chromatin organization, and function, which may be responsible for the MTC heterogeneity. In addition, the genetic signature identified 3 main clusters; cases belonging to cluster II displayed a significantly higher number of mutations and higher tumor mutational burden, suggesting increased genetic instability, but cluster I was associated with the highest number of negative events. In conclusion, we confirmed the prognostic performance of the IMTCGS and SEER-based risk score, showing that patients classified as high-grade had a lower event-free survival probability. We also underline that angioinvasion has a significant prognostic role, which has not been incorporated in previous risk scores.

The 2022 WHO classification of thyroid tumors: novel concepts in nomenclature and grading

The fifth edition of the Classification of Endocrine and Neuroendocrine Tumors has been released by the World Health Organization. This timely publication integrates several changes to the nomenclature of non-neoplastic and neoplastic thyroid diseases, as well as novel concepts that are essential for patient management. The heterogeneous group of non-neoplastic and benign neoplastic lesions are now collectively termed as 'thyroid follicular nodular disease' to better reflect the clonal and non-clonal proliferations that clinically present as multinodular goiter. Thyroid neoplasms originating from follicular cells are distinctly divided into benign, low-risk and malignant neoplasms. The new classification scheme stresses that papillary thyroid carcinoma (PTC) should be subtyped based on histomorphologic features irrespective of tumor size to avoid treating all sub-centimeter/small lesions as low-risk disease. Formerly known as the cribriform-morular variant of PTC is redefined as cribriform-morular thyroid carcinoma since this tumor is now considered a distinct malignant thyroid neoplasm of uncertain histogenesis. The 'differentiated high-grade thyroid carcinoma' is a new diagnostic category including PTCs, follicular thyroid carcinomas and oncocytic carcinomas with high-grade features associated with poorer prognosis similar to the traditionally defined poorly differentiated thyroid carcinoma as per Turin criteria. In addition, squamous cell carcinoma of the thyroid is now considered a morphologic pattern/subtype of anaplastic thyroid carcinoma. In this review, we will highlight the key changes in the newly devised fifth edition of the WHO classification scheme of thyroid tumors with reflections on its applicability in patient management and future directions in this field.

Investigating the role of core needle biopsy in evaluating tumor-stroma ratio (TSR) of invasive breast cancer: a retrospective study

PURPOSE

Tumor-stroma ratio (TSR) of invasive breast carcinoma has gained attention in recent years due to its prognostic significance. Previous studies showed TSR is a potential biomarker for indicating the tumor response to neoadjuvant chemotherapy. However, it is not clear how well TSR evaluation in biopsy specimens might reflect the TSR in resection specimens. We conducted a study to investigate whether biopsy evaluation of TSR can be an alternative method.

METHOD

We collected cases with invasive breast carcinoma of no special type (IBC-NST) from University of Yamanashi hospital between 2011 and 2017 whose biopsy and resection specimens both had a pathologically diagnosis of IBC-NST (n = 146). We conceptualized a method for evaluating TSR in biopsy specimens within a preliminary cohort (n = 50). Within the studied cohort (n = 96), biopsy-based TSR (b-TSR) and resection-based TSR (r-TSR) were scored by two pathologists. We then evaluated our method's validity and performance by measuring interobserver variability between the two pathologists, Spearman's correlation between b-TSR and r-TSR, and the receiver operating characteristics (ROC) analysis for defining stroma-rich and stroma-poor tumors.

RESULTS

Intra-class coefficient between the two pathologists was 0.59. The correlation coefficients between b-TSR and r-TSR in the two pathologists were 0.45 and 0.37. The ROC areas under the curve were 0.7 and 0.67. By considering an r-TSR of < 50% as stroma-rich, the sensitivity and specificity of detecting stroma-rich tumors were 64.1% and 66.7%, respectively, when b-TSR was < 40%.

CONCLUSION

Our current b-TSR evaluation method can provide information about r-TSR and facilitate pre-treatment therapy follow-up.