Endocrine Pathology最新文献

Poorly differentiated thyroid carcinoma (PDTC) is a rare thyroid cancer with aggressive clinical course and peculiar clinical/pathological characteristics but lacking effective therapeutic options, when surgery is not curative. We aimed at the molecular characterization of PDTC with a specific focus on the identification of potential therapeutic targets. A series of PDTC cases was selected from a multi-institutional network. Fifty-nine samples underwent wide targeted DNA and RNA next-generation sequencing (NGS) testing and immunohistochemical analysis for mismatch repair (MMR) proteins. Gene fusion analysis was enriched by 25 additional samples. Prevalence of MMR protein loss was 11.9%. The most prevalent mutations were in NRAS (25%) and TP53 (25%), mutually exclusive. TERT promoter (TERTp) mutations were detected in 19.6% of cases (10/51). NRAS-mutated cases were enriched for mutations in genes belonging to the same pathway. TP53-mutated samples lacked TERTp co-mutations, but were associated with mutations in PTEN and in genes related to MMR system and/or loss of MMR proteins. TERTp mutations were the most prevalent alterations (28%, 7/25) in a third group that lacked NRAS or TP53 mutations. Four cases harbored gene fusions, including two cases harboring the TBL1XR1::PIK3CA fusion that has never been reported in thyroid cancer, so far. In conclusion, PDTC may be genomically segregated in subgroups with specific molecular characteristics. Overall, targetable gene fusions have a prevalence of 9% (4/42). Moreover, 47% of cases are potential candidates for individualized target therapies since they harbor mutations in genes coding for potentially targetable molecules and/or have defects in the MMR system.

The pivotal role of Ki67 in grading pancreatic neuroendocrine tumors (PanNETs) is well recognized and firmly established in current WHO guidelines. Intratumoral heterogeneity is a well-known phenomenon, and it has also been documented for Ki67; however, the data on the magnitude of the impact of this heterogeneity on the final grade in primary NETs is relatively limited. In this study, Ki67 labeling index (KI) was calculated by using the manual count of camera-captured image method in 91 PanNETs both in hot-spots (KI(h)) as well as 6 different random-areas (KI(r)), each counted in a minimum of 2000 cells. The process was repeated for 29 samples from metastatic foci. Mean KI of the hot-spots was more than twofold higher than that of the random (5 vs 2.1%), with a low kappa agreement (0.2770). This changed the final grade in almost half of the cases (42/91; p < 0.001). Random counting missed all 4 G3 NETs as well as 6/7 of the Grade 2b cases (those with Ki67 10-≤ 20%). On the other hand, in only 4 cases, the difference in KI was > 10%. Similar heterogeneity was also observed in the 29 metastatic tumors analyzed with the final grade differing in 55% based on KI(h) versus KI(r). KI(h) had a stronger correlation with signs of aggressiveness including metastasis and tumor size and also trended with perineural invasion in tumors > 5 cm. The intratumoral heterogeneity in Ki67 in pancreatic NETs lead to a change in final grade in 46% of cases by hot-spot versus random count. This underscores the importance of both making a reliable Ki67 count and providing a numerical index in addition to the final grade, and interpretation of the results case-by-case basis for management purposes, rather than the rigid grade-based approach. This study also supports the usage of hot-spot rather than random count as the grade parameter. Reporting Ki67 in cytology and small biopsy specimens should be supplemented by a comment highlighting that the final grade may change when the entire tumor is evaluated but that the difference in the nominal count will seldom be higher than 10%.

The introduction of the term pituitary neuroendocrine tumor (PitNET) to replace pituitary adenoma has sparked a versatile debate among experts. The controversy surrounding this nomenclature change includes the question of whether these tumors' biological identity truly corresponds to neuroendocrine tumors. In this meta-analysis, DNA methylation data were interrogated to clarify whether the old or new nomenclature more accurately reflects the epigenome of these tumors. Publicly available DNA methylation data of 100 NETs, 100 PitNETs/adenomas, and 100 adenomas of various origins and lineages were compiled from 18 different publications. Epigenomic signatures characteristic of NETs and adenomas were defined and compared to those of PitNETs/adenomas. Promoter CpG methylation levels were investigated for hallmarks of cellular differentiation. Comparative DNA methylation analyses demonstrated that all 100 PitNETs/adenomas aligned more closely with NETs than with adenomas. Focusing on promoter-associated CpGs moreover confirmed robust epigenomic features associated with neuroendocrine differentiation in PitNETs/adenomas. These findings indicate that PitNETs/adenomas resemble NETs rather than adenomas on the epigenomic level and support PitNET as the biologically more accurate term. Of note, appropriately addressing the broad spectrum of clinical behaviors in these tumors remains a critical issue in the current pituitary tumor classification framework and nomenclature.

The histological identification of papillary thyroid carcinoma (PTC) is straightforward for experienced endocrine pathologists. The increase in radical thyroidectomies led to a raise in the rate of postoperative incidental subcentimeter PTC foci and the recent introduction of the Non-Invasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP) as a less aggressive mimicker of PTC, which significantly complicated the histology screening of thyroid histology specimens. Artificial Intelligence (AI) applied to Whole Slide Images (WSI) can speed up these processes, aiding pathologists to improve diagnostic accuracy and turnaround times. Here we present a computational pathology pipeline for the identification of Microscopic foci of papillary Thyroid Carcinoma-like nuclear features using Artificial intelligence (MiThyCA). This algorithm relies on a tandem architecture consisting of a Convolutional Neural Network (CNN) designed to identify neoplastic areas within thyroid specimens, and a Vision Transformer (TinyViT) focused on detecting PTC-like areas within the neoplastic regions identified by the first model. The study was conducted on a multi-institutional cohort of 73 WSIs from 67 patients with normal thyroid tissue (n = 22 patients, 33%), NIFTP (n = 19, 28%), PTC (n = 23, 34%), and lymph nodes (n = 3, 5%). Cases were divided into training (n = 40 patients, 41 WSIs), validation (n = 13 patients, 14 WSIs) and test (n = 14 patients, 18 WSIs) sets. Each model singly demonstrated excellent performance at the tile-level on the validation set (accuracy = 0.95 and AUC-ROC = 0.95 for CNN, accuracy = 0.86 and AUC-ROC = 0.84 for TinyViT), with their tandem combination in MiThyCA showing accuracy = 0.85 and F1 score = 0.8 on the validation set at the whole WSI-level. The average total execution time of MiThyCA on the test set WSIs was 51 ± 27 s on average on workstations not equipped with GPU, and up to 16 ± 6 s and 11 ± 4 s per WSI with Nvidia GPU and Apple's laptop chip, respectively. Worthy of note, WSIs dimension did not significantly impact the algorithm processing time. Given its speed and accessibility, MiThyCA is a promising AI-based computer-aided diagnostic tool for the detection of subcentimeter PTC foci in histology.

Introduction: Paragangliomas (PGLs) are rare malignant non-epithelial neuroendocrine neoplasms characterized by a strong genetic determinism and heterogeneous metastatic potential with no reliable histopathological predictors. In this retrospective study we investigated the role of serum succinate as a biomarker for metastatic risk and developed a novel preoperative scoring tool.

Matherials and methods: Seventy patients with PGLs evaluated between 2006 and 2023 were analysed. Clinical, biochemical, imaging, and genetic data were collected. Germline genetic variants were analysed via Sanger sequencing or NGS through a targeted panel of susceptibility genes. Serum succinate concentrations were quantified by gas chromatography-mass spectrometry.

Results: Succinate levels were significantly higher in patients with Cluster 1 genetic variants (p < 0.001), extra-adrenal PGLs (p = 0.006), and metastatic disease (p = 0.024). We developed a novel preoperative risk assessment tool, the P-SMART (Preoperative Succinate MetAstatic Risk Tool), combining serum succinate levels, tumour size, and location. P-SMART assigns: 3 points for extra-adrenal localization, 3.5 points for serum succinate ≥ 8.95 µM, and 3 points for tumour size ≥ 7.0 cm. In our cohort a P-SMART score > 4.75 predicted metastatic disease with 72.7% sensitivity and 83% specificity, outperforming the ASES score (Age, Size, Extra-adrenal, Secretory type; AUC 0.891 vs 0.752, p = 0.005).

Conclusions: Though limited by sample size and retrospective design, our findings suggest that succinate is a minimally invasive biomarker that could enhance preoperative metastatic risk stratification, especially when integrated into a multiparametric score such as P-SMART. Larger prospective studies are needed to validate its role, but P-SMART could optimize clinical decision-making, refine patient selection for whole-body imaging, reduce unnecessary radiation exposure, and inform surveillance strategies.

Although a diagnosis of anaplastic thyroid carcinoma (ATC) can be rendered on fine needle aspiration (FNA), a core needle biopsy is often performed to provide sufficient material for immunohistochemical and molecular analysis. Rendering an ATC diagnosis on core biopsy can be challenging due to limited material. It is crucial that other diagnostic entities in the differential, such as poorly differentiated thyroid carcinoma, medullary thyroid carcinoma, lymphoma, metastases, and NUT carcinoma (among others), are considered and that immunohistochemistry (IHC) is employed judiciously to support the diagnosis. IHC for BRAF V600E should also be performed for ATC to expeditiously assess BRAF V600E mutation status because BRAF-targeted therapy is a critical treatment option for patients with BRAF V600E-mutant ATC. Molecular testing utilizing next-generation sequencing (NGS) should also be initiated at the time of an ATC diagnosis both to confirm BRAF V600E mutation status and to evaluate for other actionable alterations in BRAF-wild-type ATC (such and NTRK or RET fusions or mismatch repair deficiency) and to assess tumor mutation burden. Additionally, IHC for PD-L1 is increasingly being utilized given the results of studies demonstrating the efficacy of checkpoint inhibitors in some ATC patients with PD-L1 expression in tumor cells (especially when utilized along with BRAF inhibitors in patients with BRAF V600E-mutant ATC). In this review, the morphologic and immunophenotypic features of ATC are outlined, the differential diagnosis is reviewed, and the therapeutic implications of key biomarkers are highlighted.

Thyroid lesions associated with DICER1 syndrome include multifocal hyperplastic and benign neoplastic proliferations (follicular nodular disease) with characteristic macrofollicular and/or intrafollicular centripetal papillary growth patterns, frequently associated with atrophic and involutional changes. There are also well-differentiated thyroid carcinomas showing intermediate-type nuclei, sometimes combining high-grade areas (tumor-in-tumor pattern) and poorly differentiated carcinomas. Here, for the first time, we describe an encapsulated follicular cell thyroid tumor showing a mixed follicular and morular growth pattern, which presented in an 11-year-old girl with follicular nodular disease and a constitutional (germline) DICER1 p.(Tyr1357fs*18) pathogenic variant. The tumoral follicular component showed colloid and tumor cells with round nuclei, frequent chromatin clearing, and overlapping without grooves or pseudoinclusions (intermediate-type nuclei). There were scattered mitotic figures, but no tumor necrosis, infiltration, or vascular invasion. The morular structures lacked keratinization. The follicular areas were positive for TTF1/NKX2, PAX8, thyroglobulin, thyroperoxidase, keratin clones CKAE1/AE3 and 34bE12, CK19, and vimentin, whereas the morular component was positive for CKAE1/AE3, CK19, CD10, and CDX2. Aberrant (nuclear and cytoplasmic) immunolabeling pattern for β-catenin was limited to the morular structures. The Ki67 proliferation index was 21% in the follicular component and less than 1% in the morulae. In addition to the constitutional DICER1 p.(Tyr1357fs*18) variant, the somatic DICER1 p.(Asp1910Tyr) oncogenic variant and the somatic CTNNB1 p.(Thr41Ala) oncogenic variant were also identified in this tumor. This "DICER1-related pediatric thyroid neoplasm with follicular and morular growth" expands the spectrum of DICER1-associated thyroid lesions. Indirectly, the absence of follicular markers only in the areas with WNT/β-catenin pathway activation (morular structures) in this neoplasm could explain the absence of follicular differentiation in cribriform morular thyroid carcinoma. The additional study of one of the accompanying thyroid nodules (follicular nodular disease) confirmed the constitutional DICER1 variant, along with DICER1 p.(Asp1709Gly) and p.(Asp1810Val) variants.

Although anaplastic thyroid carcinomas (ATCs) typically arise from papillary thyroid carcinomas (PTCs), follicular thyroid carcinomas (FTCs) can also progress to ATCs; however, histologically confirmed FTC-derived ATCs are relatively uncommon and remain poorly characterized. To clarify this phenomenon, we analyzed eight FTC-derived ATCs and compared them with 11 PTC-derived ATCs. Whole-exome sequencing (WES) was conducted on the differentiated thyroid carcinoma (DTC) and ATC components within the same tumors to examine mutational profiles; three additional cases underwent FoundationOne® testing. The demographic features were similar between FTC- and PTC-derived ATCs. Histologically, spindle-cell morphology was more common in FTC-derived ATCs (3/8), whereas PTC-derived ATCs exhibited squamoid (5/11) and giant cell features (5/11), including osteoclast-like cells. WES was successfully performed on both the ATC and FTC components in seven of the eight FTC-derived ATCs. Common alterations included TERT promoter (5/7), NRAS (4/7), and HRAS (2/7) mutations in both components. TP53 mutations were observed only in the ATC component (5/7). EIF1AX mutations co-occurred with TERT and HRAS mutations in two cases. PTEN mutations were found in two FTCs with solid/trabecular patterns but were absent in the corresponding ATC components. One tumor harbored a DGCR8 p.E518K mutation that was retained during progression. By contrast, PTC-derived ATCs consistently showed concurrent BRAF and TERT promoter mutations (11/11). Immunohistochemistry for BRAF V600E, RAS Q61R, p53, PTEN, and MTAP showed high concordance with the corresponding mutation status. These findings revealed significant histological and genetic differences between FTC- and PTC-derived ATCs, providing new insights into the molecular basis of FTC dedifferentiation into ATC.

Mixed neuroendocrine-nonneuroendocrine neoplasms (MiNEN) are usually highly aggressive tumors characterized by marked histological heterogeneity, most commonly represented by mixed adenocarcinoma and poorly differentiated neuroendocrine carcinoma (NEC). However, beyond morphological observations, the biological basis and implications of this heterogeneity remain incompletely understood. In this study, we combined component-specific next-generation sequencing and spatial transcriptomics to investigate three mixed adenocarcinoma-NEC cases from different anatomical sites (ileocecal, ovarian, gastric), tracing tumor progression from precursor lesions to invasive NEC. Genomic analyses revealed a shared trunk of driver mutations across all tumor compartments, confirming their clonal origin, while also uncovering additional compartment-specific alterations. Spatial transcriptomics, together with gene set enrichment analysis (GSEA), revealed distinct transcriptional profiles aligned with histologically annotated compartments (e.g., adenocarcinoma, NEC, precursor). In NECs, GSEA consistently showed downregulation of immune-related pathways and upregulation of proliferation-associated pathways compared to non-neuroendocrine tumor areas. Moreover, distinct transcriptomic subclusters were identified within morphologically homogeneous NEC regions in two of the three cases. These subclusters exhibited significant differences in immune regulation, proliferation signaling, and cell-cycle control, and were associated with divergent predicted chemotherapy-response signatures, suggesting clinically relevant implications for treatment sensitivity and resistance. In summary, our findings indicate that despite a shared clonal origin, MiNEN develop distinct genetic and transcriptomic features across tumor compartments. The inconsistent presence of transcriptomic subclusters within morphologically similar regions underscores the complexity of intratumoral heterogeneity in these aggressive neoplasms. By connecting morphological and molecular layers of tumor architecture, spatial profiling may aid in translating biological complexity into more targeted clinical strategies.