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.

GATA-binding protein 3 (GATA3) has been identified as a sensitive marker for breast carcinoma but its sensitivity in primary genital extramammary Paget diseases (EMPDs) has not been well studied. Here we investigated immunohistochemical expression of GATA3 in 72 primary genital EMPDs (35 from female, 37 from male; 45 with intraepithelial disease only, 26 with both intraepithelial disease and invasive adenocarcinoma including 14 also metastasis, 1 with metastatic adenocarcinoma only for study). We also compared GATA3 to gross cystic disease fluid protein 15 (GCDFP15) for their sensitivity. Positive GATA3 staining was seen in all 71 (100%) intraepithelial diseases, 25/26 (96%; female 10/10, male 15/16) invasive adenocarcinomas and 14/15 (93%; female 3/3, male 11/12) metastatic adenocarcinomas, respectively. Positive GCDFP15 staining was seen in 46/71 (65%; female 28/34 or 82%, male 18/37 or 49%) intraepithelial diseases, 20/26 (77%; female 9/10, male 11/16) invasive adenocarcinomas, and 12/15 (80%; female 2/3, male 10/12) metastatic adenocarcinomas, respectively (GATA3 versus GCDFP15: p < 0.01 for both intraepithelial disease and invasive adenocarcinoma, p = 0.28 for metastatic adenocarcinoma). In positive-stained cases, GATA3 stained more tumor cells than GCDFP15 (79% versus 25% for intraepithelial disease, 71% vs 34% for invasive adenocarcinoma, 73% vs 50% for metastatic adenocarcinoma, p < 0.01 for all 3 components). Our findings indicate that GATA3 is a very sensitive marker for primary genital EMPDs and is more sensitive than GCDFP15.

Accurate detection of HER2 expression through immunohistochemistry (IHC) is of great clinical significance in the treatment of breast cancer. However, manual interpretation of HER2 is challenging, due to the interobserver variability among pathologists. We sought to explore a deep learning method to predict HER2 expression level and gene status based on a Whole Slide Image (WSI) of the HER2 IHC section. When applied to 228 invasive breast carcinoma of no special type (IBC-NST) DAB-stained slides, our GrayMap+ convolutional neural network (CNN) model accurately classified HER2 IHC level with mean accuracy 0.952 ± 0.029 and predicted HER2 FISH status with mean accuracy 0.921 ± 0.029. Our result also demonstrated strong consistency in HER2 expression score between our system and experienced pathologists (intraclass correlation coefficient (ICC) = 0.903, Cohen’s κ = 0.875). The discordant cases were found to be largely caused by high intra-tumor staining heterogeneity in the HER2 IHC group and low copy number in the HER2 FISH group.

Background: Aquaporin2 (AQP2) is water channel protein that is widely distributed among mammalian tissues and plays a major role in water homeostasis. However, little is known about the expression and significance of AQP2 in human adrenal tumors. Thus, we performed an immunohistochemical investigation of AQP2 in normal and neoplastic adrenal tissues. Methods: AQP2 protein expression was investigated in 190 adrenal tumor patients using immunohistochemistry. Correlation between protein expression and clinicopathological features was statistically analyzed. Results: We demonstrated immunopositivity for AQP2 in all adrenal medulla-originating tumors, including 96 pheochromocytomas (PCC), 7 metastatic pheochromocytomas (MPCC), and 10 neuroblastic tumors (NT) and 13 extra-adrenal paragangliomas (EAPGL). Whereas, APQ2 was absent from the 52 adrenal cortical adenomas and 2 adrenal cortical carcinomas examined. The 10 metastatic carcinomas examined in adrenal tissue were also negative for AQP2. In 82 (85%) of the 96 samples from patients with PCC, we studied the relationship between clinicopathologic factors and AQP2 expression and our findings suggested that the tumors that exhibited diffuse expression pattern of AQP2 were larger in diameter than those exhibiting focal (P=0.007) or mediate expression pattern (P=0.001). Conclusions: AQP2 protein is significantly expressed in normal adrenal medullary tissues and medullary tumors (including PCC, MPCC and NT) as well as EAPGL. AQP2 expression may indicate the origin of normal adrenal tissues, and its expression in cancer tissue may reflect the maintenance of water metabolism via AQP2 during tumorigenesis. AQP2 may serve as a valuable marker for the differential diagnosis of adrenal tumors.

Aquaporin 3 (AQP3) is the membrane channel of water and involved in fluid homeostasis. The aim of this study was to reveal the expression and significance of AQP3 in cutaneous lesions. We analyzed AQP3 mRNA levels using RT-PCR in 311 cutaneous lesions and confirmed AQP3 expression in these lesions by immunohistochemistry. AQP3 mRNA was detected in normal epidermis, seborrheic keratosis, solar keratosis, Bowen’s disease, squamous cell carcinoma, eccrine poroma, apocrine carcinoma, and sebaceoma; however, AQP3 mRNA was absent in basal cell carcinoma, nevocellular nevus, or malignant melanoma. By immunohistochemistry, diffuse AQP3 expression was seen in all keratotic lesions including seborrheic keratosis, verruca vulgaris, molluscum contagiosum, solar keratosis, Bowen’s disease, and squamous cell carcinoma. Diffuse AQP3 expression was also present in all extramammary Paget’s disease. No AQP3 staining was obtained in basal cell carcinoma. Positive AQP3 staining was seen in sweat gland tumors including hidradenoma, eccrine poroma, and apocrine carcinoma. Among sebaceous tumors, AQP3 expressed diffusely in all sebaceous hyperplasia and sebaceous adenoma, but not in sebaceous carcinomas. Only focal AQP3 staining was seen in nevocellular nevus and no AQP3 staining in melanoma. Our findings indicate the function of AQP3 maintained in most skin tumors. AQP3 may be used for differential diagnosis in skin tumors.

Background: Adenoid cystic carcinoma (ACC) is a rare type of triple-negative breast cancer that has an indolent clinical behavior. Given the substantial overlapping morphological, immunohistochemical, and molecular features with other basal-like triple-negative breast cancer (BL-TNBC), accurate diagnosis of ACC is crucial for effective clinical treatment. The integrative analysis of the proteome and clinicopathological characteristics may help to distinguish these two neoplasms and provide a deep understanding on biological behaviors and potential target therapy of ACC.Methods: We applied mass spectrometry-based quantitative proteomics to analyze the protein expression in paired tumor and adjacent normal breast tissue of five ACC and five BL-TNBC. Bioinformatic analyses and the clinicopathological characteristics, including histological features, immunohistochemistry, and FISH results, were also collected to get comprehensive information.Results: A total of 307 differentially expressed proteins (DEPs) were identified between ACC and BL-TNBC. Clustering analysis of DEPs clearly separated ACC from BL-TNBC. GSEA found downregulation of the immune response of ACC compared with BL-TNBC, which is consistent with the negative PD-L1 expression of ACC. Vesicle-mediated transport was also inhibited, while ECM organization was enriched in ACC. The top upregulated proteins in DEPs were ITGB4, VCAN, and DPT. Moreover, in comparison with normal breast tissue, ACC showed elevated ribosome biogenesis and RNA splicing activity.Conclusion: This study provides evidence that ACC presents a substantially different proteomic profile compared with BL-TNBC and promotes our understanding on the molecular mechanisms and biological processes of ACC, which might be useful for differential diagnosis and anticancer strategy.