Advances in medical sciences and evidence-based medicine have led to momentous changes in classification and management of thyroid neoplasms. Much progress has been made toward avoiding overdiagnosis and overtreatment of thyroid cancers. The new 2017 World Health Organization (WHO) classification of thyroid neoplasms updated the diagnostic criteria and molecular and genetic characteristics reflecting the biology and behavior of the tumors, and newly introduced the category of borderline malignancy or uncertain malignant potential. Some neoplasms were subclassified, renamed, or redefined as a specific entity. This review introduces changes in the fourth edition WHO classification of thyroid tumors and updates the contemporary diagnosis and classification of thyroid tumors. We also discuss several challenges with the proposal of new diagnostic entities, since they have unique histopathologic and molecular features and clinical relevance.

Immune checkpoint blockade targeting PD-1/PD-L1 has shown efficacy in several types of cancers. However, the correlation between PD-L1/PD-1 expression and the specific clinicopathological features in papillary thyroid carcinoma (PTC) has not been investigated. We examined the immunohistochemical expression of PD-L1, PD-1, and BRAF V600E on whole-tissue sections from 126 cases of primary PTC more than 1 cm in size. The correlation between the PD-L1/PD-1 expression and the clinicopathological features was evaluated. PD-L1 was positively expressed in 53.2% PTCs, and its expression was positively correlated with rich tumor-infiltrating lymphocytes (TILs), background chronic lymphocytic thyroiditis (CLT), female gender, absence of psammoma bodies, and PD-1 expression. Among these parameters, rich TILs, female gender, and absence of psammoma bodies were independent factors affecting PD-L1 expression on the multivariate logistic regression analysis. PD-1 expression was detected in the TILs and was positively correlated with rich TILs, background CLT, and absence of stromal calcification. Lack of stromal calcification was an independent factor affecting PD-1 expression. Neither PD-L1 nor PD-1 expression showed significant correlation with BRAF V600E expression. Our results show that the distinctive pathological features of PTCs, including TILs, background CLT, female gender, psammoma bodies, and stromal calcification, are useful parameters for predicting PD-L1 or PD-1 expression.

Background: Insulin gene enhancer protein 1, (ISL1), a LIM‐homeodomain transcription factor, is involved in multiple tumors and is associated with insulin secretion and metabolic phenotypes. However, the role of ISL1 in stimulating glycolysis to promote tumorigenesis in gastric cancer (GC) is unclear. In this study, we aimed to characterize the expression pattern of ISL1 in GC patients and explore its molecular biological mechanism in glycolysis and tumorigenesis. Methods: We analyzed the expression and clinical significance of ISL1 in GC using immunohistochemistry and real‐time polymerase chain reaction (PCR). Flow cytometry and IncuCyte assays were used to measure cell proliferation after ISL1 knockdown. RNA‐sequencing was performed to identify differentially expressed genes, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA) to reveal key signaling pathways likely regulated by ISL1 in GC. Alteration of the glycolytic ability of GC cells with ISL1 knockdown was validated by measuring the extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) and by detecting glucose consumption and lactate production. The expression of glucose transporter 4 (GLUT4) and ISL1 was assessed by Western blotting, immunohistochemistry, and immunofluorescent microscopy. The luciferase reporter activity and chromatin immunoprecipitation assays were performed to determine the transcriptional regulation of ISL1 on GLUT4. Results: High levels of ISL1 and GLUT4 expression was associated with short survival of GC patients. ISL1 knockdown inhibited cell proliferation both in vitro and in vivo . KEGG analysis and GSEA for RNA‐sequencing data indicated impairment of the glycolysis pathway in GC cells with ISL1 knockdown, which was validated by reduced glucose uptake and lactate production, decreased ECAR, and increased OCR. Mechanistic investigation indicated that ISL1 transcriptionally regulated GLUT4 through binding to its promoter. Conclusion: ISL1 facilitates glycolysis and tumorigenesis in GC via the transcriptional regulation of GLUT4.

Controversy exists regarding whether patients with low‐risk papillary thyroid microcarcinoma (PTMC) should undergo surgery or active surveillance; the inaccuracy of the preoperative clinical lymph node status assessment is one of the primary factors contributing to the controversy. It is imperative to accurately predict the lymph node status of PTMC before surgery. We selected 208 preoperative fine‐needle aspiration (FNA) liquid‐based preparations of PTMC as our research objects; all of these instances underwent lymph node dissection and, aside from lymph node status, were consistent with low‐risk PTMC. We separated them into two groups according to whether the postoperative pathology showed central lymph node metastases. The deep learning model was expected to predict, based on the preoperative thyroid FNA liquid‐based preparation, whether PTMC was accompanied by central lymph node metastases. Our deep learning model attained a sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and accuracy of 78.9% (15/19), 73.9% (17/23), 71.4% (15/21), 81.0% (17/21), and 76.2% (32/42), respectively. The area under the receiver operating characteristic curve (value was 0.8503. The predictive performance of the deep learning model was superior to that of the traditional clinical evaluation, and further analysis revealed the cell morphologies that played key roles in model prediction. Our study suggests that the deep learning model based on preoperative thyroid FNA liquid‐based preparation is a reliable strategy for predicting central lymph node metastases in thyroid micropapillary carcinoma, and its performance surpasses that of traditional clinical examination.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, and novel methods for early/rapid diagnosis of HCC are needed. Terahertz (THz) spectroscopy is considered to have the potential to distinguish between normal liver tissue and HCC tissue; however, there are few reports on it. We conduct this observational study to explore the feasibility of THz imaging for the diagnosis of HCC. To evaluate the feasibility of THz for discriminating between HCC and normal liver tissues using fresh tissue specimens obtained from HCC patients who had undergone surgery. Normal liver tissue and HCC tissue were cryosectioned into 50 μm-thick slices and placed on cover glass. Two adjacent tissue sections were separated subjected to histopathological examination by hematoxylin and eosin staining or THz transmission examination, and THz images were compared with pathologically mapped images. We determined the typical tumor and normal liver tissue regions by pathological examination; the corresponding areas of adjacent sections were examined by THz transmission. The transmission rate of HCC tissue was 0.15-0.25, and the transmission rate of typical HCC tissue was about 0.2. THz transmittance in normal liver tissue is slightly higher than 0.4, but there were many influencing factors, including the degree of liver cirrhosis, fat components, ice crystals in frozen sections, and apoptosis. In conclusion, this study shows that THz imaging can detect HCC tissue. Further research will yield more detailed data of the THz transmission rates of HCC tissue with different degrees of differentiation.