Tridimensional Visualization and Analysis of Early Human Development.

Generating a precise cellular and molecular cartography of the human embryo is essential to our understanding of the mechanisms of organogenesis in normal and pathological conditions. Here, we have combined whole-mount immunostaining, 3DISCO clearing, and light-sheet imaging to start building a 3D cellular map of the human development during the first trimester of gestation. We provide high-resolution 3D images of the developing peripheral nervous, muscular, vascular, cardiopulmonary, and urogenital systems. We found that the adult-like pattern of skin innervation is established before the end of the first trimester, showing important intra- and inter-individual variations in nerve branches. We also present evidence for a differential vascularization of the male and female genital tracts concomitant with sex determination. This work paves the way for a cellular and molecular reference atlas of human cells, which will be of paramount importance to understanding human development in health and disease. PAPERCLIP.

In situ proximity labeling identifies Lewy pathology molecular interactions in the human brain.

The intracellular misfolding and accumulation of alpha-synuclein into structures collectively called Lewy pathology (LP) is a central phenomenon for the pathogenesis of synucleinopathies, including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Understanding the molecular architecture of LP is crucial for understanding synucleinopathy disease origins and progression. Here we used a technique called biotinylation by antibody recognition (BAR) to label total (BAR-SYN1) and pathological alpha-synuclein (BAR-PSER129) in situ for subsequent mass spectrometry analysis. Results showed superior immunohistochemical detection of LP following the BAR-PSER129 protocol, particularly for fibers and punctate pathology within the striatum and cortex. Mass spectrometry analysis of BAR-PSER129-labeled LP identified 261 significantly enriched proteins in the synucleinopathy brain when compared to nonsynucleinopathy brains. In contrast, BAR-SYN1 did not differentiate between disease and nonsynucleinopathy brains. Pathway analysis of BAR-PSER129-enriched proteins revealed enrichment for 718 pathways; notably, the most significant KEGG pathway was PD, and Gene Ontology (GO) cellular compartments were the vesicle, extracellular vesicle, extracellular exosome, and extracellular organelle. Pathway clustering revealed several superpathways, including metabolism, mitochondria, lysosome, and intracellular vesicle transport. Validation of the BAR-PSER129-identified protein hemoglobin beta (HBB) by immunohistochemistry confirmed the interaction of HBB with PSER129 Lewy neurites and Lewy bodies. In summary, BAR can be used to enrich for LP from formalin-fixed human primary tissues, which allowed the determination of molecular signatures of LP. This technique has broad potential to help understand the phenomenon of LP in primary human tissue and animal models.

A Pipeline for Evaluation of Machine Learning/Artificial Intelligence Models to Quantify Programmed Death Ligand 1 Immunohistochemistry.

Immunohistochemistry (IHC) is used to guide treatment decisions in multiple cancer types. For treatment with checkpoint inhibitors, programmed death ligand 1 (PD-L1) IHC is used as a companion diagnostic. However, the scoring of PD-L1 is complicated by its expression in cancer and immune cells. Separation of cancer and noncancer regions is needed to calculate tumor proportion scores (TPS) of PD-L1, which is based on the percentage of PD-L1-positive cancer cells. Evaluation of PD-L1 expression requires highly experienced pathologists and is often challenging and time-consuming. Here, we used a multi-institutional cohort of 77 lung cancer cases stained centrally with the PD-L1 22C3 clone. We developed a 4-step pipeline for measuring TPS that includes the coregistration of hematoxylin and eosin, PD-L1, and negative control (NC) digital slides for exclusion of necrosis, segmentation of cancer regions, and quantification of PD-L1+ cells. As cancer segmentation is a challenging step for TPS generation, we trained DeepLab V3 in the Visiopharm software package to outline cancer regions in PD-L1 and NC images and evaluated the model performance by mean intersection over union (mIoU) against manual outlines. Only 14 cases were required to accomplish a mIoU of 0.82 for cancer segmentation in hematoxylin-stained NC cases. For PD-L1-stained slides, a model trained on PD-L1 tiles augmented by registered NC tiles achieved a mIoU of 0.79. In segmented cancer regions from whole slide images, the digital TPS achieved an accuracy of 75% against the manual TPS scores from the pathology report. Major reasons for algorithmic inaccuracies include the inclusion of immune cells in cancer outlines and poor nuclear segmentation of cancer cells. Our transparent and stepwise approach and performance metrics can be applied to any IHC assay to provide pathologists with important insights on when to apply and how to evaluate commercial automated IHC scoring systems.

Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer.

Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.

Immunohistochemical assessment of HER2 low breast cancer: interobserver reproducibility and correlation with digital image analysis.

PURPOSE: The recent findings from the DESTINY-Breast04 trial highlighted the clinical importance of distinguishing between HER2 immunohistochemistry (IHC) scores 0 and 1 + in metastatic breast cancer (BC). However, pathologist interpretation of HER2 IHC scoring is subjective, and standardized methodology is needed. We evaluated the consistency of HER2 IHC scoring among pathologists and the accuracy of digital image analysis (DIA) in interpreting HER2 IHC staining in cases of HER2-low BC. METHODS: Fifty whole-slide biopsies of BC with HER2 IHC staining were evaluated, comprising 25 cases originally reported as IHC score 0 and 25 as 1 +. These slides were digitally scanned. Six pathologists with breast expertise independently reviewed and scored the scanned images, and DIA was applied. Agreement among pathologists and concordance between pathologist scores and DIA results were statistically analyzed using Kendall coefficient of concordance (W) tests. RESULTS: Substantial agreement among at least five of the six pathologists was found for 18 of the score 0 cases (72%) and 15 of the score 1 + cases (60%), indicating excellent interobserver agreement (W = 0.828). DIA scores were highly concordant with pathologist scores in 96% of cases (47/49), indicating excellent concordance (W = 0.959). CONCLUSION: Although breast subspecialty pathologists were relatively consistent in evaluating BC with HER2 IHC scores of 0 and 1 +, DIA may be a reliable supplementary tool to enhance the standardization and quantification of HER2 IHC assessment, especially in challenging cases where results may be ambiguous (i.e., scores 0-1 +). These findings hold promise for improving the accuracy and consistency of HER2 testing.

A Deep Learning-Based Assay for Programmed Death Ligand 1 Immunohistochemistry Scoring in Non-Small Cell Lung Carcinoma: Does it Help Pathologists Score?

Several studies have developed various artificial intelligence (AI) models for immunohistochemical analysis of programmed death ligand 1 (PD-L1) in patients with non-small cell lung carcinoma; however, none have focused on specific ways by which AI-assisted systems could help pathologists determine the tumor proportion score (TPS). In this study, we developed an AI model to calculate the TPS of the PD-L1 22C3 assay and evaluated whether and how this AI-assisted system could help pathologists determine the TPS and analyze how AI-assisted systems could affect pathologists' assessment accuracy. We assessed the 4 methods of the AI-assisted system: (1 and 2) pathologists first assessed and then referred to automated AI scoring results (1, positive tumor cell percentage; 2, positive tumor cell percentage and visualized overlay image) for final confirmation, and (3 and 4) pathologists referred to the automated AI scoring results (3, positive tumor cell percentage; 4, positive tumor cell percentage and visualized overlay image) while determining TPS. Mixed-model analysis was used to calculate the odds ratios (ORs) with 95% CI for AI-assisted TPS methods 1 to 4 compared with pathologists' scoring. For all 584 samples of the tissue microarray, the OR for AI-assisted TPS methods 1 to 4 was 0.94 to 1.07 and not statistically significant. Of them, we found 332 discordant cases, on which the pathologists' judgments were inconsistent; the ORs for AI-assisted TPS methods 1, 2, 3, and 4 were 1.28 (1.06-1.54; P = .012), 1.29 (1.06-1.55; P = .010), 1.28 (1.06-1.54; P = .012), and 1.29 (1.06-1.55; P = .010), respectively, which were statistically significant. For discordant cases, the OR for each AI-assisted TPS method compared with the others was 0.99 to 1.01 and not statistically significant. This study emphasized the usefulness of the AI-assisted system for cases in which pathologists had difficulty determining the PD-L1 TPS.

Identification of high-performing antibodies for the reliable detection of Tau proteoforms by Western blotting and immunohistochemistry.

Antibodies are essential research tools whose performance directly impacts research conclusions and reproducibility. Owing to its central role in Alzheimer's disease and other dementias, hundreds of distinct antibody clones have been developed against the microtubule-associated protein Tau and its multiple proteoforms. Despite this breadth of offer, limited understanding of their performance and poor antibody selectivity have hindered research progress. Here, we validate a large panel of Tau antibodies by Western blot (79 reagents) and immunohistochemistry (35 reagents). We address the reagents' ability to detect the target proteoform, selectivity, the impact of protein phosphorylation on antibody binding and performance in human brain samples. While most antibodies detected Tau at high levels, many failed to detect it at lower, endogenous levels. By WB, non-selective binding to other proteins affected over half of the antibodies tested, with several cross-reacting with the related MAP2 protein, whereas the "oligomeric Tau" T22 antibody reacted with monomeric Tau by WB, thus calling into question its specificity to Tau oligomers. Despite the presumption that "total" Tau antibodies are agnostic to post-translational modifications, we found that phosphorylation partially inhibits binding for many such antibodies, including the popular Tau-5 clone. We further combine high-sensitivity reagents, mass-spectrometry proteomics and cDNA sequencing to demonstrate that presumptive Tau "knockout" human cells continue to express residual protein arising through exon skipping, providing evidence of previously unappreciated gene plasticity. Finally, probing of human brain samples with a large panel of antibodies revealed the presence of C-term-truncated versions of all main Tau brain isoforms in both control and tauopathy donors. Ultimately, we identify a validated panel of Tau antibodies that can be employed in Western blotting and/or immunohistochemistry to reliably detect even low levels of Tau expression with high selectivity. This work represents an extensive resource that will enable the re-interpretation of published data, improve reproducibility in Tau research, and overall accelerate scientific progress.

Diagnosis of verruciform acanthotic vulvar intra-epithelial neoplasia (vaVIN) using CK17, SOX2 and GATA3 immunohistochemistry.

AIMS: Verruciform acanthotic vulvar intra-epithelial neoplasia (vaVIN) is an HPV-independent, p53 wild-type lesion with distinct morphology and documented risk of recurrence and cancer progression. vaVIN is rare, and prospective distinction from non-neoplastic hyperplastic lesions can be difficult. CK17, SOX2 and GATA3 immunohistochemistry has emerging value in the diagnosis of HPV-independent lesions, particularly differentiated VIN. We aimed to test the combined value of these markers in the diagnosis of vaVIN versus its non-neoplastic differentials in the vulva. METHODS AND RESULTS: CK17, SOX2 and GATA3 immunohistochemistry was evaluated on 16 vaVINs and 34 mimickers (verruciform xanthoma, lichen simplex chronicus, lichen sclerosus, psoriasis, pseudo-epitheliomatous hyperplasia). CK17 was scored as 3+ = full-thickness, 2+ = partial-thickness, 1+ = patchy, 0 = absent; SOX2 as 3+ = strong staining ≥ 10% cells, 2+ = moderate, 1 + =weak, 0 = staining in < 10% cells; and GATA3 as pattern 0 = loss in < 25% basal cells, 1 = loss in 25-75% basal cells, 2 = loss in > 75% basal cells. For analysis, results were recorded as positive (CK17 = 3+, SOX2 = 3+, GATA3 = patterns 1/2) or negative (CK17 = 2+/1+/0, SOX2 = 2+/1+/0, GATA3 = pattern 0). CK17, SOX2 and GATA3 positivity was documented in 81, 75 and 58% vaVINs, respectively, versus 32, 17 and 22% of non-neoplastic mimickers, respectively; ≥ 2 marker positivity conferred 83 sensitivity, 88 specificity and 86% accuracy in vaVIN diagnosis. Compared to vaVIN, SOX2 and GATA3 were differentially expressed in lichen sclerosus, lichen simplex chronicus and pseudo-epitheliomatous hyperplasia, whereas CK17 was differentially expressed in verruciform xanthoma and adjacent normal mucosa. CONCLUSIONS: CK17, SOX2 and GATA3 can be useful in the diagnosis of vaVIN and its distinction from hyperplastic non-neoplastic vulvar lesions. Although CK17 has higher sensitivity, SOX2 and GATA3 are more specific, and the combination of all markers shows optimal diagnostic accuracy.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Expression of CD44 is associated with aggressiveness in seminomas.

BACKGROUND: Testicular germ cell tumors (TGCTs) exhibit diverse biological and pathological features and are divided in two main types, seminomas and nonseminomatous germ cell tumors (NSGCTs). CD44 is a cell surface receptor, which is highly expressed in malignancies and is implicated in tumorigenesis affecting cell-matrix interactions and cell signaling. METHODS AND RESULTS: Here, we examined the expression of CD44 in tumor cell lines and in patients' material. We found that CD44 is over-expressed in TGCTs compared to normal tissues. Immunohistochemical staining in 71 tissue specimens demonstrated increased expression of CD44 in some patients, whereas CD44 was absent in normal tissue. In seminomas, a high percentage of tumor and stromal cells showed cytoplasmic and/or cell surface staining for CD44 as well as increased staining for CD44 in the tumor stroma was found in some cases. The increased expression of CD44 either in tumor cells or in stromal components was associated with tumor size, nodal metastasis, vascular/lymphatic invasion, and disease stage only in seminomas. The increased stromal expression of CD44 in TGCTs was positively associated with angiogenesis. CONCLUSIONS: CD44 may exhibit diverse biological functions in seminomas and NSGCTs. The expression of CD44 in tumor cells as well as in tumor stroma fosters an aggressive phenotype in seminomas and should be considered in disease treatment.

A new mode for the diagnosis of angioimmunoblastic T-cell lymphoma.

In order to explore a new mode for the diagnosis of angioimmunoblastic T-cell lymphoma (AITL), 31 cases of AITL and 28 cases of peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) were used as the study subjects. Identifying T follicular helper (TFH) cells with CD4, CD10, Bcl-6, and PD-1, identifying proliferative B cells with CD20 and EZH2, identifying proliferative follicular dendritic cells (FDCs) with CD21 and CD23, and analyzing the value of TFH/B/FDC proliferation and immunolocalization in the diagnosis of AITL. (1) Outside the inherent lymphoid follicles, simultaneous proliferation of TFH/B/FDC (a new diagnostic mode) were observed in AITL [83.87%; 26/31], with their immunolocalizations in the same site [83.87%; 26/31], while this phenomenon was not observed in 28 cases of PTCL-NOS (P<0.05). (2) The sensitivity and specificity of using this new mode to diagnose AITL were both high (83.87%, 100%), which was superior to CD2 (100%, 0%), CD3 (100%, 0%), CD4 (100%, 32.14%), CD5 (100%, 25%), CD10 (61.9%, 100%), Bcl-6 (42.86%, 100%), PD-1 (83.87%, 96.43%), and its Youden Index (0.84) was the highest. The areas under the curve (AUC) of CD10, Bcl-6, PD-1, and new mode to diagnosis AITL were 0.81, 0.71, 0.90, and 0.92, respectively, while the new mode had the highest AUC. The simultaneous proliferation of TFH/B/FDC cells outside the inherent lymphoid follicles can be used to assist in the diagnosis of AITL, and the simultaneous spatiotemporal proliferation of TFH/B/FDC cells is a specific immunomorphology of AITL.

The combined immunohistochemical expression of AMBRA1 and SQSTM1 identifies patients with poorly differentiated cutaneous squamous cell carcinoma at risk of metastasis: A proof of concept study.

BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) incidence continues to increase globally with, as of yet, an unmet need for reliable prognostic biomarkers to identify patients at increased risk of metastasis. The aim of the present study was to test the prognostic potential of the combined immunohistochemical expression of the autophagy regulatory biomarkers, AMBRA1 and SQSTM1, to identify high-risk patient subsets. METHODS: A retrospective cohort of 68 formalin-fixed paraffin-embedded primary cSCCs with known 5-year metastatic outcomes were subjected to automated immunohistochemical staining for AMBRA1 and SQSTM1. Digital images of stained slides were annotated to define four regions of interest: the normal and peritumoral epidermis, the tumor mass, and the tumor growth front. H-score analysis was used to semi-quantify AMBRA1 or SQSTM1 expression in each region of interest using Aperio ImageScope software, with receiver operator characteristics and Kaplan-Meier analysis used to assess prognostic potential. RESULTS: The combined loss of expression of AMBRA1 in the tumor growth front and SQSTM1 in the peritumoral epidermis identified patients with poorly differentiated cSCCs at risk of metastasis (*p < 0.05). CONCLUSIONS: Collectively, these proof of concept data suggest loss of the combined expression of AMBRA1 in the cSCC growth front and SQSTM1 in the peritumoral epidermis as a putative prognostic biomarker for poorly differentiated cSCC.

Establishing guidelines for sentinel lymph node ultrastaging in endometrial cancer.

BACKGROUND: Many sentinel lymph node (SLN) ultrastaging protocols for endometrial cancer exist, but there is no consensus method. OBJECTIVE: This study aims to develop guidelines for size criteria in SLN evaluation for endometrial cancer, to determine whether a single cytokeratin AE1:AE3 immunohistochemical slide provides sufficient data for diagnosis, and to compare cost efficiency between current and limited ultrastaging protocols at a large tertiary care institution. METHODS: Our current SLN ultrastaging protocol consists of cutting two adjacent paraffin block sections at two levels (L1 and L2), 50 µm apart, with two slides at each level stained with hematoxylin and eosin and cytokeratin AE1:AE3 immunohistochemistry. We retrospectively reviewed digitized L1 and L2 slides of all positive ultrastaged SLNs from patients treated for endometrial cancer between January 2013 and January 2020. SLN diagnosis was defined by measuring the largest cluster of contiguous tumor cells in a single cross section: macrometastasis (>2.0 mm), micrometastasis (>0.2 to ≤2.0 mm or >200 cells), or isolated tumor cells (≤0.2 mm or ≤200 cells). Concordance between L1 and L2 results was evaluated. Cost efficiency between current (two immunohistochemical slides per block) and proposed limited (one immunohistochemical slide per block) protocols was compared. RESULTS: Digitized slides of 147 positive SLNs from 109 patients were reviewed; 4.1% of SLNs were reclassified based on refined size criteria. Complete concordance between L1 and L2 interpretations was seen in 91.8% of SLNs. A false-negative rate of 0%-0.9% in detecting micrometastasis and macrometastasis using a limited protocol was observed. Estimated charge-level savings of a limited protocol were 50% per patient. CONCLUSION: High diagnostic accuracy in SLN interpretation may be achieved using a limited ultrastaging protocol of one immunohistochemical slide per block and linear measurement of the largest cluster of contiguous tumor cells. Implementation of the proposed limited ultrastaging protocol may result in laboratory cost savings with minimal impact on health outcomes.

Construction of mouse cochlin mutants with different GAG-binding specificities and their use for immunohistochemistry.

Glycosaminoglycan (GAG) is a polysaccharide present on the cell surface as an extracellular matrix component, and is composed of repeating disaccharide units consisting of an amino sugar and uronic acid except in the case of the keratan sulfate. Sulfated GAGs, such as heparan sulfate, heparin, and chondroitin sulfate mediate signal transduction of growth factors, and their functions vary with the type and degree of sulfated modification. We have previously identified human and mouse cochlins as proteins that bind to sulfated GAGs. Here, we prepared a recombinant cochlin fused to human IgG-Fc or Protein A at the C-terminus as a detection and purification tag and investigated the ligand specificity of cochlin. We found that cochlin can be used as a specific probe for highly sulfated heparan sulfate and chondroitin sulfate E. We then used mutant analysis to identify the mechanism by which cochlin recognizes GAGs and developed a GAG detection system using cochlin. Interestingly, a mutant lacking the vWA2 domain bound to various types of GAGs. The N-terminal amino acid residues of cochlin contributed to its binding to heparin. Pathological specimens from human myocarditis patients were stained with a cochlin-Fc mutant. The results showed that both tryptase-positive and tryptase-negative mast cells were stained with this mutant. The identification of detailed modification patterns of GAGs is an important method to elucidate the molecular mechanisms of various diseases. The method developed for evaluating the expression of highly sulfated GAGs will help understand the biological and pathological importance of sulfated GAGs in the future.

Review of immunohistochemistry techniques: Applications, current status, and future perspectives.

The Hematoxylin and Eosin stain is a cornerstone in histopathology that facilitates the microscopic examination of tissue samples for identifying infections and tumors. However, challenges arise from the similar appearances of diseases and cells, prompting the emergence of Immunohistochemistry (IHC) as an important technique. This review summarizes the principles, procedures, and applications and future perspectives of IHC, a prevalent immunostaining method allowing the detection of specific proteins in tissue sections. The multistep IHC process involves fixation, embedding, sectioning, antigen retrieval, blocking, detection, counterstaining, mounting, and visualization, with interpretation relying on factors such as microanatomic distribution and staining intensity. Common errors in IHC such as non-specific staining, tissue artifacts, inadequately inactivation of endogenous peroxidase activity and cross-reactivity, can substantially affect the accuracy and reliability of results, thereby impacting the interpretation of biological findings. Serving diagnostic, prognostic, predictive, and therapeutic roles in various conditions, including tumors, infectious diseases, neurodegenerative disorders, and muscle diseases, IHC remains pivotal despite its intricate nature. The adoption of digital pathology emerges as a progressive enhancement, addressing limitations and ensuring more accurate analyses in histopathology.

Primary peritoneal low-grade serous carcinoma detected in cervical smear: Pitfalls mitigated by clinicocytopathologic clues and cellblock immunocytochemistry.

Pap smears play a role in detecting extrauterine serous tumours in asymptomatic women. Certain cytopathologic and histopathologic findings combined with relevant clinical and radiologic findings indicate the possibility of primary peritoneal serous tumours. Cellblock immunohistochemistry is a valuable confirmatory diagnostic tool.

Artificial intelligence algorithm accurately assesses oestrogen receptor immunohistochemistry in metastatic breast cancer cytology specimens: A pilot study.

OBJECTIVE: The Visiopharm artificial intelligence (AI) algorithm for oestrogen receptor (ER) immunohistochemistry (IHC) in whole slide images (WSIs) has been successfully validated in surgical pathology. This study aimed to assess its efficacy in cytology specimens. METHODS: The study cohort comprised 105 consecutive cytology specimens with metastatic breast carcinoma. ER IHC WSIs were seamlessly integrated into the Visiopharm platform from the Image Management System (IMS) during our routine digital workflow, and an AI algorithm was employed for analysis. ER AI scores were compared with pathologists' manual consensus scores. Optimization steps were implemented and evaluated to reduce discordance. RESULTS: The overall concordance between pathologists' scores and AI scores was excellent (99/105, 94.3%). Six cases exhibited discordant results, including two false-negative (FN) cases due to abundant histiocytes incorrectly counted as negatively stained tumour cells by AI, two FN cases owing to weak staining, and two false-positive (FP) cases where pigmented macrophages were erroneously counted as positively stained tumour cells by AI. The Pearson correlation coefficient of ER-positive percentages between pathologists' and AI scores was 0.8483. Optimization steps, such as lowering the cut-off threshold and additional training using higher input magnification, significantly improved accuracy. CONCLUSIONS: The automated ER AI algorithm demonstrated excellent concordance with pathologists' assessments and accurately differentiated ER-positive from ER-negative metastatic breast carcinoma cytology cases. However, precision in identifying tumour cells in cytology specimens requires further enhancement.

Characteristic morphology and immunohistochemical patterns of clear cell papillary renal cell tumours may be observed in renal cell carcinomas, a critical pitfall in renal biopsy cytopathology.

BACKGROUND: Clear cell papillary renal cell tumour (CCPRCT) was renamed from previous clear cell papillary renal cell carcinoma (CCPRCC) in the latest WHO Classification of Tumours. It is essential to differentiate RCC from CCPRCT in renal mass biopsies (RMB). DESIGN: RMB cases with subsequent resections were reviewed. The pathology reports and pertinent clinical information were recorded. RESULTS: Fifteen cases displaying either CCPRCT morphology (20% diffuse, 67% focal) or immunohistochemical patterns (cup-like CA9: 20% diffuse, 47% focal; CK7: 33% diffuse, 40% focal) were identified. One case was positive for TFE3. TSC mutation was identified in one case. Both cases exhibited both CCPRCT morphology and immunohistochemical patterns for CA9 and CK7, with focal high-grade nuclei. RMB diagnoses were as follows: 6 (40%) as CCRCC, 2 (13%) as CCPRCT, 2 (13%) as CCRCC versus CCPRCT, 2 (13%) as CCRCC versus PRCC, 1 (7%) as RCC with TSC mutation versus CCPRCT, 1 (7%) as TFE3-rearranged RCC versus PRCC, and 1 (7%) as cyst with low-grade atypia. 71% of patients underwent nephrectomy, 21% received systemic treatment for stage 4 RCCs, and 7% with ablation for small renal mass (1.6 cm) with low-grade CCRCC. CONCLUSIONS: Our study highlights that morphologic and immunochemical features of CCPRCT may be present in RCCs, including RCC-TFE3 expression and TSC-associated RCC, a critical pitfall to misdiagnose aggressive RCC as indolent CCPRCT and result in undertreatment. Careful examination of morphology and immunostains for CA9, CK7, and TFE3, as well as molecular tests, is crucial for distinguishing aggressive RCC from indolent CCPRCT.

An immunohistochemical study of lymphatic elements in the human brain.

Almost 150 papers about brain lymphatics have been published in the last 150 years. Recently, the information in these papers has been synthesized into a picture of central nervous system (CNS) "glymphatics," but the fine structure of lymphatic elements in the human brain based on imaging specific markers of lymphatic endothelium has not been described. We used LYVE1 and PDPN antibodies to visualize lymphatic marker-positive cells (LMPCs) in postmortem human brain samples, meninges, cavernous sinus (cavum trigeminale), and cranial nerves and bolstered our findings with a VEGFR3 antibody. LMPCs were present in the perivascular space, the walls of small and large arteries and veins, the media of large vessels along smooth muscle cell membranes, and the vascular adventitia. Lymphatic marker staining was detected in the pia mater, in the arachnoid, in venous sinuses, and among the layers of the dura mater. There were many LMPCs in the perineurium and endoneurium of cranial nerves. Soluble waste may move from the brain parenchyma via perivascular and paravascular routes to the closest subarachnoid space and then travel along the dura mater and/or cranial nerves. Particulate waste products travel along the laminae of the dura mater toward the jugular fossa, lamina cribrosa, and perineurium of the cranial nerves to enter the cervical lymphatics. CD3-positive T cells appear to be in close proximity to LMPCs in perivascular/perineural spaces throughout the brain. Both immunostaining and qPCR confirmed the presence of adhesion molecules in the CNS known to be involved in T cell migration.

A Comprehensive Study of Meningioma Biomineralization: Morphological, Crystallographic, and Immunohistochemical Aspects.

Biomineralization of brain tissues occurs both in normal and pathological conditions. Dura mater biomineralization is widespread and occurs in 1-72% of cases, depending on the patient's age and research method. The amount of biomineral deposits under the conditions of tumor growth in the meninges only increases, reaching 100% in the case of psammomatous meningiomas. Since calcifications are often found in the meninges, the problem of differential diagnosis with calcified meningiomas arises. A total of 30 samples of meningiomas with signs of biomineralization-dense structure, characteristic crunch, psammoma bodies (group I) and 30 samples of meningiomas without any signs of biomineralization were examined as controls (group II). To detect pathological biomineralization, the meningioma tissue was studied using the methods of macroscopic description, histology, histochemistry, and immunohistochemistry, scanning electron microscopy with microanalysis, and transmission electron microscopy. A significantly higher level of caspase3 and features of the expression of osteoblastic markers (a lower level of OPG expression and a higher level of the presence of RANKL in group I, the absence of fluctuations in the expression of SPARC) may indicate a dystrophic type of development of biomineral deposits in meningiomas.