Endocrine Pathology最新文献

Hand2 is a core transcription factor responsible for chromaffin cell differentiation. However, its potential utility in surgical pathology has not been studied. Thus, we aimed to investigate its expression in paragangliomas, other neuroendocrine neoplasms (NENs), and additional non-neuroendocrine tumors. We calibrated Hand2 immunohistochemistry on adrenal medulla cells and analyzed H-scores in 46 paragangliomas (PGs), 9 metastatic PGs, 21 cauda equina neuroendocrine tumors (CENETs), 48 neuroendocrine carcinomas (NECs), 8 olfactory neuroblastomas (ONBs), 110 well-differentiated NETs (WDNETs), 10 adrenal cortical carcinomas, 29 adrenal cortical adenomas, 8 melanomas, 41 different carcinomas, and 10 gastrointestinal stromal tumors (GISTs). Both tissue microarrays (TMAs) and whole sections (WSs) were studied. In 171 NENs, previously published data on Phox2B and GATA3 were correlated with Hand2. Hand2 was positive in 98.1% (54/55) PGs, but only rarely in WDNETs (9.6%, 10/104), CENETs (9.5%, 2/21), NECs (4.2%, 2/48), or ONBs (12.5%, 1/8). Any Hand2 positivity was 98.1% sensitive and 91.7% specific for the diagnosis of PG. The Hand2 H-score was significantly higher in primary PGs compared to Hand2-positive WDNETs (median 166.3 vs. 7.5; p < 0.0001). Metastatic PGs were positive in 88.9% (8/9). No Hand2 positivity was observed in any adrenal cortical neoplasm or other non-neuroendocrine tumors, with exception of 8/10 GISTs. Parasympathetic PGs showed a higher Hand2 H-score compared to sympathetic PGs (median H-scores 280 vs. 104, p < 0.0001). Hand2 positivity in NENs serves as a reliable marker of primary and metastatic PG, since other NENs only rarely exhibit limited Hand2 positivity.

Cytosine modifications at the 5-carbon position play a critical role in gene expression regulation and have been implicated in cancer development. 5-Hydroxymethylcytosine (5hmC), arising from 5-methylcytosine (5-mC) oxidation, has shown promise as a potential malignancy marker due to its depletion in various human cancers. However, its significance in thyroid tumors remains underexplored, primarily due to limited data. In our study, we evaluated 5hmC expression levels by immunohistochemistry in a cohort of 318 thyroid tumors. Our analysis revealed significant correlations between 5hmC staining extension scores and nodule size, vascular invasion, and oncocytic morphology. Nuclear 5hmC staining intensity demonstrated associations with focality, capsule status, extrathyroidal extension, vascular invasion, and oncocytic morphology. Follicular/oncocytic adenomas exhibited higher 5hmC expression than uncertain malignant potential (UMP) or noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP), as well as malignant neoplasms, including papillary thyroid carcinomas (PTCs), oncocytic carcinomas (OCAs), follicular thyroid carcinomas (FTCs), and invasive encapsulated follicular variants of PTC (IEFV-PTC). TERT promoter mutation cases showed notably lower values for the 5hmC expression, while RAS (H, N, or K) mutations, particularly HRAS mutations, were associated with higher 5hmC expression. Additionally, we identified, for the first time, a significant link between 5hmC expression and oncocytic morphology. However, despite the merits of these discoveries, we acknowledge that 5hmC currently cannot segregate minimally invasive from widely invasive tumors, although 5hmC levels were lower in wi-FPTCs. Further research is needed to explore the potential clinical implications of 5hmC in thyroid tumors.

Significant interobserver variabilities exist for Bethesda category III: atypia of undetermined significance (AUS) of The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). Thus, subcategorization of AUS including AUS "nuclear" and AUS "other" is proposed in the recent 3rd edition of TBSRTC. This study investigated the impact of the nuclear features/architectural features/nuclear score (NS) (3-tiered)/subcategories and subgroups on risk of malignancy (ROM) in thyroid fine-needle aspirations (FNA). 6940 FNAs were evaluated. 1224 (17.6%) cases diagnosed as AUS were reviewed, and 240 patients (initial FNAs of 260 nodules and 240 thyroidectomies) were included. Subcategories and subgroups were defined according to TBSRTC 2nd and 3rd editions. Histological diagnostic groups included nonneoplastic disease, benign neoplasm, low-risk neoplasm, and malignant neoplasm. Overall, ROM was 30.7%. ROM was significantly higher in FNAs with nuclear overlapping (35.5%), nuclear molding (56.9%), irregular contours (42.1%), nuclear grooves (74.1%), chromatin clearing (49.4%), and chromatin margination (57.7%), and these features were independent significant predictors for malignancy. FNAs with NS3 had significantly higher ROM (64.2%). Three-dimensional groups were significantly more frequent in malignant neoplasms (35.7%). ROM was significantly higher in AUS-nuclear subcategory (48.2%) and in AUS-nuclear and architectural subcategory (38.3%). The highest ROM was detected in AUS-nuclear1 subgroup (65.2%). ROM was significantly higher in the group including AUS-nuclear and AUS-nuclear and architectural subcategories, namely "high-risk group" than the group including other subcategories, namely "low-risk group" (42.0%vs 13.9%). In conclusion, subcategorization may not be the end point, and nuclear scoring and evaluation of architectural patterns according to strict criteria may provide data for remodeling of TBSRTC categories.

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma and has characteristic nuclear features. Genetic abnormalities of PTC affect recent molecular target therapeutic strategy towards RET-altered cases, and they affect clinical prognosis and progression. However, there has been insufficient objective analysis of the correlation between genetic abnormalities and nuclear features. Using our newly developed methods, we studied the correlation between nuclear morphology and molecular abnormalities of PTC with the aim of predicting genetic abnormalities of PTC. We studied 72 cases of PTC and performed genetic analysis to detect BRAF p.V600E mutation and RET fusions. Nuclear features of PTC, such as nuclear grooves, pseudo-nuclear inclusions, and glassy nuclei, were also automatically detected by deep learning models. After analyzing the correlation between genetic abnormalities and nuclear features of PTC, logistic regression models could be used to predict gene abnormalities. Nuclear features were accurately detected with over 0.90 of AUCs in every class. The ratio of glassy nuclei to nuclear groove and the ratio of pseudo-nuclear inclusion to glassy nuclei were significantly higher in cases that were positive for RET fusions (p = 0.027, p = 0.043, respectively) than in cases that were negative for RET fusions. RET fusions were significantly predicted by glassy nuclei/nuclear grooves, pseudo-nuclear inclusions/glassy nuclei, and age (p = 0.023). Our deep learning models could accurately detect nuclear features. Genetic abnormalities had a correlation with nuclear features of PTC. Furthermore, our artificial intelligence model could significantly predict RET fusions of classic PTC.

Digital pathology uses digitized images for cancer research. We aimed to assess morphometric parameters using digital pathology for predicting recurrence in patients with papillary thyroid carcinoma (PTC) and lateral cervical lymph node (LN) metastasis. We analyzed 316 PTC patients and assessed the longest diameter and largest area of metastatic focus in LNs using a whole slide imaging scanner. In digital pathology assessment, the longest diameters and largest areas of metastatic foci in LNs were positively correlated with traditional optically measured diameters (R = 0.928 and R² = 0.727, p < 0.001 and p < 0.001, respectively). The optimal cutoff diameter was 8.0 mm in both traditional microscopic (p = 0.009) and digital pathology (p = 0.016) evaluations, with significant differences in progression-free survival (PFS) observed at this cutoff (p = 0.006 and p = 0.002, respectively). The predictive area’s cutoff was 35.6 mm² (p = 0.005), which significantly affected PFS (p = 0.015). Using an 8.0-mm cutoff in traditional microscopic evaluation and a 35.6-mm² cutoff in digital pathology showed comparable predictive results using the proportion of variation explained (PVE) methods (2.6% vs. 2.4%). Excluding cases with predominant cystic changes in LNs, the largest metastatic areas by digital pathology had the highest PVE at 3.9%. Furthermore, high volume of LN metastasis (p = 0.001), extranodal extension (p = 0.047), and high ratio of metastatic LNs (p = 0.006) were associated with poor prognosis. Both traditional microscopic and digital pathology evaluations effectively measured the longest diameter of metastatic foci in LNs. Moreover, digital pathology offers limited advantages in predicting PFS of patients with lateral cervical LN metastasis of PTC, especially those without predominant cystic changes in LNs.