Expression of cell surface zinc transporter LIV1 in triple negative breast cancer is an indicator of poor prognosis and therapy failure.

Triple negative breast cancers (TNBC) are an aggressive molecular subtype of breast carcinoma (BC) identified by the lack of receptor expression for estrogen, progesterone, & human epidermal growth factor receptor-2. Lack of tangible drug targets warrants further research in TNBC. LIV1, is a zinc (Zn) transporter known to be overexpressed in few cancer types including BCs. Recently, in the United States of America, FDA approved the use of a new drug targeting LIV1, antibody drug conjugate SGN-LIV1A for treatment of TNBC patients. Though LIV1 also has a role in modulating immune cells by its differential transport of Zn, a correlation between the tumor cell expression of LIV1 and immune cell infiltrations were scantily reported. Further adequate baseline data on LIV1 expression in other populations have not been documented. Our objective was to screen a large Indian cohort of TNBC patient samples for LIV1, categorize the immune cell infiltration using CD4/CD8 expression and correlate the findings with therapy outcomes. Further, we also investigated for LIV1 expression in matched samples of primary & secondary tumors; pre & postchemotherapy in TNBC patients. Results showed an elevated expression of LIV1 in TNBC samples as compared to adjacent normal, the mean Q scores being 183.06 ± 6.39 and 120.78 ± 7.37 (p < 0.0001), respectively. Similarly, LIV1 levels were elevated in secondary tumors than primary & in patient samples postchemotherapy as compared to naïve. In the TNBC cohort, using automated method, cell morphology parameters were computed and analysis showed LIV1 levels were elevated in grade 3 TNBC samples presenting with altered cell morphology parameters namely cell size, cell perimeter, & nucleus size. Thus indicating LIV1 expressing TNBC samples portrayed an aggressive phenotype. Finally, TNBC patients with 3+ staining intensity showed poor survival (4.44 year) as compared to patients with 2+ LIV1 expression (5.47 year), emphasizing that LIV1 expression is a poor prognostic factor in TNBC. In conclusion, the study reports elevated expression of LIV1 in a large Indian TNBC cohort; high expression is a poor prognostic factor and correlated with aggressive disease and indicating the need for LIV1 targeted therapies.

Manual and Semi-Automated Measurement and Calculation of Osteosarcoma Treatment Effect Using Whole Slide Image and Qupath.

INTRODUCTION: In osteosarcoma, the most significant indicator of prognosis is the histologic changes related to tumor response to preoperative chemotherapy, such as necrosis. We have developed a method to measure the osteosarcoma treatment effect using whole slide image (WSI) with an open-source digital image analytical software Qupath. MATERIALS AND METHODS: In Qupath, each osteosarcoma case was treated as a project. All H&E slides from the entire representative slice of osteosarcoma were scanned into WSIs and imported into a project in Qupath. The regions of tumor and tumor necrosis were annotated, and their areas were measured in Qupath. In order to measure the osteosarcoma treatment effect, we needed to calculate the percentage of total necrosis area over total tumor area. We developed a tool that can automatically extract all values of tumor and necrosis areas from a Qupath project into an Excel file, sum these values for necrosis and whole tumor respectively, and calculate necrosis/tumor percentage. CONCLUSION: Our method that combines WSI with Qupath can provide an objective measurement to facilitate pathologist's assessment of osteosarcoma response to treatment. The proposed approach can also be used for other types of tumors that have clinical need for post-treatment response assessment.

Sigma-1 receptor agonist, (+)-pentazocine, is neuroprotective in a Brown Norway rat microbead model of glaucoma.

PURPOSE: Glaucoma is a worldwide leading cause of irreversible blindness. Standard treatments lower intraocular pressure (IOP). Novel treatments to prevent optic nerve (ON) degeneration are needed. Here, we investigate the hypothesis that sigma-1 receptor (S1R) agonist (+)-pentazocine (PTZ) is neuroprotective in a Brown Norway (BN) rat, microbead model of glaucoma. METHODS: BN rats (9-11 weeks, male and female) were treated by intraperitoneal injection, 3 times per week with (+)-PTZ (2 mg/kg) or vehicle (VEH) alone. Treatment started 1 week prior to intraocular injection of polystyrene microbeads to elevate IOP. IOP was measured 2-3 times per week. Five weeks post microbead injection, rats were euthanized. ONs were removed, then fixed and processed for 63x oil, light microscope imaging of toluidine blue stained ON cross sections. To facilitate comparison of ON morphology from VEH and (+)-PTZ treated rats with similar ocular hypertensive insults, rats were assigned to low (IOP ≤15.8 mmHg), moderate (15.8 < IOP <28.0 mmHg), and high (IOP ≥28.0 mmHg) groups based on average IOP in the microbead injected eye. Axon numbers, axon density, axonal and glial areas, axon loss, and axon size distributions of naïve, bead, and contralateral ONs were assessed using QuPath program for automated image analysis. RESULTS: (+)-PTZ treatment of BN rats protected ONs from damage caused by moderate IOP elevation. Treatment with (+)-PTZ significantly reduced axon loss and glial areas, and increased axon density and axonal areas compared to ONs from VEH treated rats with moderate IOP. (+)-PTZ-mediated neuroprotection was independent of IOP lowering effects. At average IOP ≥28.0 mmHg, (+)-PTZ treatment did not provide measurable neuroprotection. ONs from contralateral eyes exhibited subtle, complex changes in response to conditions in the bead eyes. CONCLUSIONS: S1R agonist (+)-PTZ shows promise as a neuroprotective treatment for glaucoma. Future studies to understand the complex molecular mechanisms by which (+)-PTZ provides this neuroprotection are needed.

Automated Analysis of PD1 and PDL1 Expression in Lymph Nodes and the Microenvironment of Transmissible Tumors in Tasmanian Devils.

The wild Tasmanian devil (Sarcophilus harrisii) population has suffered a devastating decline due to two clonal transmissible cancers. The first devil facial tumor 1 (DFT1) was observed in 1996, followed by a second genetically distinct transmissible tumor, the devil facial tumor 2 (DFT2), in 2014. DFT1/2 frequently metastasize, with lymph nodes being common metastatic sites. MHC-I downregulation by DFT1 cells is a primary means of evading allograft immunity aimed at polymorphic MHC-I proteins. DFT2 cells constitutively express MHC-I, and MHC-I is upregulated on DFT1/2 cells by interferon gamma, suggesting other immune evasion mechanisms may contribute to overcoming allograft and anti-tumor immunity. Human clinical trials have demonstrated PD1/PDL1 blockade effectively treats patients showing increased expression of PD1 in tumor draining lymph nodes, and PDL1 on peritumoral immune cells and tumor cells. The effects of DFT1/2 on systemic immunity remain largely uncharacterized. This study applied the open-access software QuPath to develop a semiautomated pipeline for whole slide analysis of stained tissue sections to quantify PD1/PDL1 expression in devil lymph nodes. The QuPath protocol provided strong correlations to manual counting. PD-1 expression was approximately 10-fold higher than PD-L1 expression in lymph nodes and was primarily expressed in germinal centers, whereas PD-L1 expression was more widely distributed throughout the lymph nodes. The density of PD1 positive cells was increased in lymph nodes containing DFT2 metastases, compared to DFT1. This suggests PD1/PDL1 exploitation may contribute to the poorly immunogenic nature of transmissible tumors in some devils and could be targeted in therapeutic or prophylactic treatments.Abbreviations: PD1: programmed cell death protein 1; PDL1: programmed death ligand 1; DFT1: devil facial tumor 1; DFT2: devil facial tumor 2; DFTD: devil facial tumor disease; MCC: Matthew's correlation coefficient; DAB: diaminobenzidine; ROI: region of interest.

Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology.

The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with 'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://onlinelibrary.wiley.com/journal/10969896). © 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Upregulation of HLA class II in pancreatic beta cells from organ donors with type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to characterise and quantify the expression of HLA class II (HLA-II) in human pancreatic tissue sections and to analyse its induction in human islets. METHODS: We immunostained human pancreatic tissue sections from non-diabetic (n = 5), autoantibody positive (Aab+; n = 5), and type 1 diabetic (n = 5) donors, obtained from the Network of Pancreatic Organ Donors (nPOD), with HLA-II, CD68 and insulin. Each tissue section was acquired with a widefield slide scanner and then analysed with QuPath software. In total, we analysed 7415 islets that contained 338,480 cells. Widefield microscopy was further complemented by high resolution imaging of 301 randomly selected islets, acquired using a Zeiss laser scanning confocal (LSM880) to confirm our findings. Selected beta cells were acquired in enhanced resolution using LSM880 with an Airyscan detector. Further, we cultured healthy isolated human islets and reaggregated human islet microtissues with varying concentrations of proinflammatory cytokines (IFN-γ, TNF-α and IL-1ß). After proinflammatory cytokine culture, islet function was measured by glucose-stimulated insulin secretion, and HLA-I and HLA-II expression was subsequently evaluated with immunostaining or RNA sequencing. RESULTS: Insulin-containing islets (ICIs) of donors with type 1 diabetes had a higher percentage of HLA-II positive area (24.31%) compared with type 1 diabetic insulin-deficient islets (IDIs, 0.67%), non-diabetic (3.80%), and Aab+ (2.31%) donors. In ICIs of type 1 diabetic donors, 45.89% of the total insulin signal co-localised with HLA-II, and 27.65% of the islet beta cells expressed both HLA-II and insulin, while in non-diabetic and Aab+ donors 0.96% and 0.59% of the islet beta cells, respectively, expressed both markers. In the beta cells of donors with type 1 diabetes, HLA-II was mostly present in the cell cytoplasm, co-localising with insulin. In the experiments with human isolated islets and reaggregated human islets, we observed changes in insulin secretion upon stimulation with proinflammatory cytokines, as well as higher expression of HLA-II and HLA-I when compared with controls cultured with media, and an upregulation of HLA-I and HLA-II RNA transcripts. CONCLUSIONS/INTERPRETATION: After a long-standing controversy, we provide definitive evidence that HLA-II can be expressed by pancreatic beta cells from patients with type 1 diabetes. Furthermore, this upregulation can be induced in vitro in healthy isolated human islets or reaggregated human islets by treatment with proinflammatory cytokines. Our findings support a role for HLA-II in type 1 diabetes pathogenesis since HLA-II expressing beta cells can potentially become a direct target of autoreactive CD4+ lymphocytes.

Development of a semi-automated method for tumour budding assessment in colorectal cancer and comparison with manual methods.

AIMS: Tumour budding (TB) is an established prognostic feature in multiple cancers but is not routinely assessed in pathology practice. Efforts to standardise and automate assessment have shifted from haematoxylin and eosin (H&E)-stained images towards cytokeratin immunohistochemistry. The aim of this study was to compare manual H&E and cytokeratin assessment methods with a semi-automated approach built within QuPath open-source software. METHODS AND RESULTS: TB was assessed in cores from the advancing tumour edge in a cohort of stage II/III colon cancers (n = 186). The total numbers of buds detected with each method were as follows: manual H&E, n = 503; manual cytokeratin, n = 2290; and semi-automated, n = 5138. More than four times the number of buds were identified manually with cytokeratin assessment than with H&E assessment. One thousand seven hundred and thirty-four individual buds were identified with both manual and semi-automated assessments applied to cytokeratin images, representing 75.7% of the buds identified manually (n = 2290) and 33.7% of the buds detected with the semi-automated method (n = 5138). Higher semi-automated TB scores were due to any discrete area of cytokeratin immunopositivity within an accepted area range being identified as a bud, regardless of shape or crispness of definition, and to the inclusion of tumour cell clusters within glandular lumina ('luminal pseudobuds'). Although absolute numbers differed, semi-automated and manual bud counts were strongly correlated across cores (ρ = 0.81, P < 0.0001). All methods of TB assessment demonstrated poorer survival associated with higher TB scores. CONCLUSIONS: We present a new QuPath-based approach to TB assessment, which compares favourably with established methods and offers a freely available, rapid and transparent tool that is also applicable to whole slide images.

Whole-slide laser microdissection for tumour enrichment.

The practical application of genome-scale technologies to precision oncology research requires flexible tissue processing strategies that can be used to differentially select both tumour and normal cell populations from formalin-fixed, paraffin-embedded tissues. As tumour sequencing scales towards clinical implementation, practical difficulties in scheduling and obtaining fresh tissue biopsies at scale, including blood samples as surrogates for matched 'normal' DNA, have focused attention on the use of formalin-preserved clinical samples collected routinely for diagnostic purposes. In practice, such samples often contain both tumour and normal cells which, if correctly partitioned, could be used to profile both tumour and normal genomes, thus identifying somatic alterations. Here we report a semi-automated method for laser microdissecting entire slide-mounted tissue sections to enrich for cells of interest with sufficient yield for whole genome and transcriptome sequencing. Using this method, we demonstrated enrichment of tumour material from mixed tumour-normal samples by up to 67%. Leveraging new methods that allow for the extraction of high-quality nucleic acids from small amounts of formalin-fixed tissues, we further showed that the method was successful in yielding sequence data of sufficient quality for use in BC Cancer's Personalized OncoGenomics (POG) program. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Automated Tumor Count for Mitosis-Karyorrhexis Index Determination in Neuroblastoma Using Whole Slide Image and Qupath, an Image Analytic Software.

INTRODUCTION: Mitosis-karyorrhexis index (MKI) is important for risk stratification workup of neuroblastic tumors. MKI is calculated by estimating the denominator (5000 tumor cells). We hypothesized that whole slide image (WSI) with appropriate digital image analytical software could provide an objective aid to pathologist's MKI workup. MATERIALS & METHODS: With IRB approval, sixteen cases of neuroblastic tumors as convenient cases were used. H&E slides were scanned at 40X using an Aperio Scanscope AT2 scanner and stored in SVS format. Digital photos were also taken and stored in TIFF format. Qupath, an open source image analytical software, was used to annotate, define region of interest (ROI) and automatically count the cells within ROI. RESULTS: With selected parameters, Qupath was able to provide cell count using both WSI (.svs) and digital images (.TIFF). Comparison of automated count and eyeball manual count generated precision above .96, recall above .96, F1 scores above .98, with false positive rate ranging from .6 to 3.7%, and false negative rate from .6 to 3.8%. Compared to original pathological report, automated tumor cell count led to lower MKI in 3 of 16 cases (18.8%) and change of "unfavorable histology" to "favorable" in one case (1/16, 6.3%). CONCLUSION: Combination of WSI (or digital images) with Qupath is able to provide an automated, objective and consistent way for cell count to facilitate pathologist's MKI determination in neuroblastic tumors' workup and research.

Loss of NPM2 expression is a potential immunohistochemical marker for malignant peritoneal mesothelioma: a single-center study of 92 cases.

BACKGROUND: Malignant peritoneal mesothelioma (MPM) is a rare malignant tumor with a high mortality rate and extremely poor prognosis. In-depth pathological analysis is essential to assess tumor biological behaviors and explore potential therapeutic targets of MPM. Nucleoplasmin 2 (NPM2) is a molecular chaperone that binds histones and may play a key role in the development and progression of tumors. This study aimed to analyze the correlation between the expression level of NPM2 and the main clinicopathological characteristics and prognosis of MPM. METHODS: Ninety-two postoperative specimens from MPM patients following cytoreductive surgery were collected. Postoperative specimens were stained with immunohistochemistry. The expression level of NPM2 was quantitatively analyzed by QuPath-0.3.2 software. Univariate and multivariate analyses were conducted to investigate the correlation between NPM2 expression and other conventional clinicopathological characteristics. RESULTS: Among the 92 MPM patients, there were 47 males (48.9%) and 45 females (51.1%), with a median age of 56 (range: 24-73). There were 70 (76.0%) cases with loss of NPM2 protein expression, 11 (12.0%) cases with low expression, and 11 (12.0%) cases with high expression. Univariate analysis showed that NPM2 protein expression level (negative vs. low expression vs. high expression) was negatively correlated with the following three clinicopathological factors: completeness of cytoreduction (CC) score, vascular tumor emboli, and serious adverse events (SAEs) (all P < 0.05). Multivariate analysis showed that NPM2 protein expression level (negative vs. low expression vs. high expression) was independently negatively correlated with the following two clinicopathological factors: CC score [odds ratio (OR) = 0.317, 95% CI: 0.317-0.959, P = 0.042] and vascular tumor emboli (OR = 0.092, 95% CI = 0.011-0.770, P = 0.028). Survival analysis showed that loss of NPM2 protein expression (negative vs. positive) was associated with poor prognosis of MPM. CONCLUSIONS: Loss of NPM2 expression is a potential immunohistochemical marker for MPM.

Computerised scoring protocol for identification and quantification of different immune cell populations in breast tumour regions by the use of QuPath software.

AIMS: As important prognostic and predictive information can be obtained from the composition, functionality and spatial arrangement of different immune cell subtypes, this study aims at characterizing the immune infiltrate in breast tumours. METHODS AND RESULTS: Tumour-infiltrating lymphocytes (TILs) in 62 patients with luminal B-like breast cancer were characterised by immunohistochemical staining with standard markers, and were subsequently classified and quantified by the use of QuPath software. In different delineated tumour regions, the proportion and density of CD3+ , CD4+ , CD5+ , CD8+ , CD20+ and FOXP3+ cells were assessed. The results of the software analysis were compared with those of manual counting for CD8 and CD20 staining. The QuPath scoring protocol slightly overestimated positive, negative and total lymphocyte counts and density, while minimally underestimating the proportion of positively stained lymphocytes. However, for density and proportion, no real differences from manual counting were observed. For all markers, the density of positively stained immune cells was higher in the invasive front than in the tumour centre, pointing to an accumulation of immune cells near the tumour boundaries. When we looked at the proportion of immunohistochemically positive immune cells, we observed enrichment of CD5 (P = 0.025) and CD20 (P < 0.001) at the periphery, and FOXP3 enrichment in the centre (P < 0.001). CONCLUSION: The QuPath scoring protocol can adequately identify positively stained immune cells in breast tumours, and allows the evaluation of differences in immune cell proportion and density within different tumour regions. The entire tumour section can be quantitatively assessed quite rapidly, which is a major advantage over manual counting.

Comparison of different anti-Ki67 antibody clones and hot-spot sizes for assessing proliferative index and grading in pancreatic neuroendocrine tumours using manual and image analysis.

AIMS: Ki67 proliferative index (PI) is essential for grading gastroenteric and pancreatic neuroendocrine tumours (GEP NETs). Analytical and preanalytical variables can affect Ki67 PI. In contrast to counting methodology, until now little attention has focused on the question of clone equivalence and the effect of hot-spot size on Ki67 PI in GEP NETs. Using manual counting and image analysis, this study compared the Ki67 PI achieved using MM1, K2 and 30-9 to MIB1, a clone which has been validated for, and is referenced in, guidelines relating to assessment of Ki67 PI in GEP NETs. METHODS AND RESULTS: Forty-two pancreatic NETs were each immunohistochemically stained for the anti-Ki67 clones MIB1, MM1, K2 and 30-9. Ki67 PI was calculated manually and by image analysis, the latter using three different hot-spot sizes. In manual comparisons using single hot-spot high-power fields, non-MIB1 clones overestimated Ki67 PI compared to MIB1, resulting in grading discordances. Image analysis shows good agreement with manual Ki67 PI but a tendency to overestimate absolute Ki67 PI. Increasing the size of tumour hot-spot from 500 to 2000 cells resulted in a decrease in Ki67 PI. CONCLUSION: Different anti-Ki67 clones do not produce equivalent PIs in GEP NETs, and clone selection may therefore affect patient care. Increasing the hot-spot size decreases the Ki67 PI. Greater standardisation in terms of antibody clone selection and hot-spot size is required for grading GEP NETs. Image analysis is an effective tool for assisting Ki67 assessment and allows easier standardisation of the size of the tumour hot-spot.

The decline of FANCM immunohistochemical expression in prostate cancer stroma correlates with the grade group.

Prostate adenocarcinoma (PCa) stromal markers have recently gained attention as complementary diagnostic tools. The DNA reparation complex protein FANCM has been shown to express in the normal prostate stroma and FANCM gene alterations to be associated with PCa susceptibility; this has led to the hypothesis that an insufficient level of FANCM expression may provide additional information for the evaluation of PCa. The study cohort comprised 60 radical prostatectomy specimens. The controls involved 11 autopsies (CTRL) and non-cancerous tissue (NCT) areas from the prostatectomy specimen. The samples were stained with the FANCM antibody. The quantification of the stromal staining index (SSI) was made using ImageJ and QuPath. Overall, 655 regions of interest (ROI) were analyzed. FANCM expression appeared equally intense and stroma specific in both CTRL and NCT, indicating the absence of underlying baseline alterations. Within the age span of the cohort 47-89 years, no significant effect of the age of the patients on the FANCM expression was seen. FANCM demonstrated Gleason grade (G) dependent decline in PCa, being statistically significant in controls versus G1 and G2 versus G3. In other adjacent International Society of Urological Pathology (ISUP) groups, it remained insignificant, still being meaningful between high and low-grade cancers.

[Assessment of PD-L1 expression using the neural network analysis algorithm in non-small cell lung carcinoma biopsy specimens]. / Otsenka v bioptatakh nemelkokletochnykh kartsinom legkogo ekspressii PD-L1 s primeneniem algoritma neirosetevogo analiza.

Neural network analysis of digital copies of histological micropreparations is one of the methods used to standardize quantitative continuous data. PD-L1 (22C3) biomarker expression in metastatic non-small cell lung carcinomas without mutations in the EGFR, ALK, and ROS1 genes serves as an indication for the use of pembrolizumab for the first-line therapy. OBJECTIVE: To quantify PD-L1 biomarker expression in non-small cell lung carcinomas using the neural network analysis of digital copies of histological micropreparations. MATERIAL AND METHODS: Immunohistochemical study of PD-L1 (22C3) expression was performed on 96 non-small cell lung carcinoma biopsy specimens. The digital copies of histological micropreparations were processed by the QuPath software neural network analysis module. RESULTS: The neural network analysis module segmented tumor, stroma, and artifacts in the micropreparations, showing a sufficient level of agreement with a visual assessment. Digital image analysis quantified stained tumor cells in the high PD-L1 expression group and showed 96% agreement rate versus visual assessment. However, the group of tumors without PD-L1 expression versus visual assessment showed a low (58%) agreement rate. CONCLUSION: The neural network analysis algorithm is applicable to the study of digital copies of histological micropreparations containing tumor, stroma, and artifacts. The algorithm allows for quantitative immunohistochemical assessment of PD-L1 expression in tumor cells. The algorithm can quantify the immunohistochemically detected expression of PD-L1 in tumor cells.

Validation of the systematic scoring of immunohistochemically stained tumour tissue microarrays using QuPath digital image analysis.

AIMS: Output from biomarker studies involving immunohistochemistry applied to tissue microarrays (TMA) is limited by the lack of an efficient and reproducible scoring methodology. In this study, we examine the functionality and reproducibility of biomarker scoring using the new, open-source, digital image analysis software, QuPath. METHODS AND RESULTS: Three different reviewers, with varying experience of digital pathology and image analysis, applied an agreed QuPath scoring methodology to CD3 and p53 immunohistochemically stained TMAs from a colon cancer cohort (n = 661). Manual assessment was conducted by one reviewer for CD3. Survival analyses were conducted and intra- and interobserver reproducibility assessed. Median raw scores differed significantly between reviewers, but this had little impact on subsequent analyses. Lower CD3 scores were detected in cases who died from colorectal cancer compared to control cases, and this finding was significant for all three reviewers (P-value range = 0.002-0.02). Higher median p53 scores were generated among cases who died from colorectal cancer compared with controls (P-value range = 0.04-0.12). The ability to dichomotise cases into high versus low expression of CD3 and p53 showed excellent agreement between all three reviewers (kappa score range = 0.82-0.93). All three reviewers produced dichotomised expression scores that resulted in very similar hazard ratios for colorectal cancer-specific survival for each biomarker. Results from manual and QuPath methods of CD3 scoring were comparable, but QuPath scoring revealed stronger prognostic stratification. CONCLUSIONS: Scoring of immunohistochemically stained tumour TMAs using QuPath is functional and reproducible, even among users of limited experience of digital pathology images, and more accurate than manual scoring.

Improved Preservation of Mouse Intestinal Tissue Using a Formalin/Acetic Acid Fixative and Quantitative Histological Analysis Using QuPath.

The architecture and morphology of the intestinal tissue from mice or other small animals are difficult to preserve for histological and molecular analysis due to the fragile nature of this tissue. The intestinal mucosa consists of villi and crypts lined with epithelial cells. In between the epithelial folds extends the lamina propria, a loose connective tissue that contains blood and lymph vessels, fibroblasts, and immune cells. Underneath the mucosa are two layers of contractile smooth muscle and nerves. The tissue experiences significant changes during fixation, which can impair the reliability of histologic analysis. Poor-quality histologic sections are not suitable for quantitative image-based tissue analysis. This article offers a new fixative composed of neutral buffered formalin (NBF) and acetic acid, called FA. This fixative significantly improved the histology of mouse intestinal tissue compared to traditional NBF and enabled precise, reproducible histologic molecular analyses using QuPath software. Algorithmic training of QuPath allows for automated segmentation of intestinal compartments, which can be further interrogated for cellular composition and disease-related changes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Improved preservation of mouse intestinal tissue using a formalin/acetic acid fixative Support Protocol: Quantitative tissue analysis using QuPath.

An algorithm for standardization of tumor Infiltrating lymphocyte evaluation in head and neck cancers.

PURPOSE: The prognostic and predictive significance of pathologist-read tumor infiltrating lymphocytes (TILs) in head and neck cancers have been demonstrated through multiple studies over the years. TILs have not been broadly adopted clinically, perhaps due to substantial inter-observer variability. In this study, we developed a machine-based algorithm for TIL evaluation in head and neck cancers and validated its prognostic value in independent cohorts. EXPERIMENTAL DESIGN: A network classifier called NN3-17 was trained to identify and calculate tumor cells, lymphocytes, fibroblasts and "other" cells on hematoxylin-eosin stained sections using the QuPath software. These measurements were used to construct three predefined TIL variables. A retrospective collection of 154 head and neck squamous cell cancer cases was used as the discovery set to identify optimal association of TIL variables and survival. Two independent cohorts of 234 cases were used for validation. RESULTS: We found that electronic TIL variables were associated with favorable prognosis in both the HPV-positive and -negative cases. After adjusting for clinicopathologic factors, Cox regression analysis demonstrated that electronic total TILs% (p = 0.025) in the HPV-positive and electronic stromal TILs% (p < 0.001) in the HPV-negative population were independent markers of disease specific outcomes (disease free survival). CONCLUSIONS: Neural network TIL variables demonstrated independent prognostic value in validation cohorts of HPV-positive and HPV-negative head and neck cancers. These objective variables can be calculated by an open-source software and could be considered for testing in a prospective setting to assess potential clinical implications.

Quantitative Evaluation by Digital Pathology of Immunohistochemical Expression of CK7, CK19, and EpCAM in Advanced Stages of NASH.

(1) Background: Nonalcoholic Steatohepatitis/Nonalcoholic Fatty Liver Disease (NASH/NAFLD) is the most recurrent chronic liver disease. NASH could present with a cholestatic (C) or hepatic (H) pattern of damage. Recently, we observed that increased Epithelial Cell Adhesion Molecule (EpCAM) expression was the main immunohistochemical feature to distinguish C from H pattern in NASH. (2) Methods: In the present study, we used digital pathology to compare the quantitative results of digital image analysis by QuPath software (Q-results), with the semi-quantitative results of observer assessment (S-results) for cytokeratin 7 and 19, (CK7, CK19) as well as EpCAM expression. Patients were classified into H or C group on the basis of the ratio between alanine transaminase (ALT) and alkaline phosphatase (ALP) values, using the "R-ratio formula". (3) Results: Q- and S-results showed a significant correlation for all markers (p < 0.05). Q-EpCAM expression was significantly higher in the C group than in the H group (p < 0.05). Importantly ALP, an indicator of hepatobiliary disorder, was the only biochemical parameter significantly correlated with Q-EpCAM. Instead, Q-CK7, but not Q-CK19, correlated only with γGlutamyl-Transferase (γGT). Of note, Stage 4 fibrosis correlated with Q-EpCAM, Q-CK19, and ALP but not with γGT or ALT. Conclusions: Image analysis confirms the relation between cholestatic-like pattern, associated with a worse prognosis, with increased ALP values, EpCAM positive biliary metaplasia, and advanced fibrosis. These preliminary data could be useful for the implementation of AI algorithms for the assessment of cholestatic NASH.

Identification and Quantification of Radiotherapy-related Protein Expression in Cancer Tissues Using the Qupath Software and Prediction of Treatment Response.

BACKGROUND/AIM: Automated measurement of immunostained samples can enable more convenient and objective prediction of treatment outcome from radiotherapy. We aimed to validate the performance of the QuPath image analysis software in immune cell markers detection by comparing QuPath cell counting results with those of physician manual cell counting. PATIENTS AND METHODS: CD8- and FoxP3-stained cervical, CD8-stained oropharyngeal, and Ku70-stained prostate cancer tumor sections were analyzed in 104 cervical, 92 oropharyngeal, and 58 prostate cancer patients undergoing radiotherapy at our Institution. RESULTS: QuPath and manual counts were highly correlated. When divided into two groups using ROC curves, the agreement between QuPath and manual counts was 89.4% for CD8 and 88.5% for FoxP3 in cervical cancer, 87.0% for CD8 in oropharyngeal cancer and 80.7% for Ku70 in prostate cancer. In cervical cancer, the high CD8 group based on QuPath counts had a better prognosis and the low CD8 group had a significantly worse prognosis [p=0.0003; 5-year overall survival (OS), 65.9% vs. 34.7%]. QuPath counts were more predictive than manual counts. Similar results were observed for FoxP3 in cervical cancer (p=0.002; 5-year OS, 62.1% vs. 33.6%) and CD8 in oropharyngeal cancer (p=0.013; 5-year OS, 80.2% vs. 47.2%). In prostate cancer, high Ku70 group had worse and low group significantly better outcome [p=0.007; 10-year progression-free survival (PFS), 56.0% vs. 93.8%]. CONCLUSION: QuPath showed a strong correlation with manual counting, confirming its utility and accuracy and potential applicability in clinical practice.

Correlation between the number of interstitial neurons of the white matter and number of neurons within cortical layers: Histological analyses in postnatal macaque.

We have examined the number and distribution of NeuN-immunoreactive cortical white matter interstitial cells (WMICs) and compared them to the neurons in layers 1-6 across the overlying cortex in coronal sections from postnatal macaques. The data have been gathered from over 300 selected regions at gyral crowns, at sulci, and at linear regions of the cortex where we also determined cortical layer thicknesses: standard thicknesses and tangential thicknesses. Cortical thicknesses and cell numbers showed variability according to gyral, linear, or sulcal regions. In spite of these variations, our standardized cell numbers in layers 1 to 6b and interstitial cells underlying layer 6b-white matter boundary have shown a consistent correlation between the number of WMICs and the number of layer 5 and 6a cortical neurons on all cortical regions studied: for each WMIC, there are on the order of five cortical neurons in layer 5 and approximately three cortical neurons in layer 6a, irrespective of the origins of the selected cortical area or whether they are from gyral, linear, or sulcal regions. We propose that the number of interstitial neurons in the postnatal macaque cortex is correlated to the density of neurons within layers 5 and 6a and, from a clinical perspective, the change in density or distribution of interstitial neurons in schizophrenia or epilepsy may in fact be linked to the number of layers 5 and 6a neurons.