Background: Hydatidiform moles (HMs), entities of
gestational trophoblastic diseases, are either complete
moles (CHM) or partial moles (PHM). The interaction
between programmed cell death-1 (PD-1) and its ligand
(PD-L1) is one of the most important immune
checkpoints which can be used by the trophoblasts.
Objectives: This study aims to investigate the
expression of PD-L1 by immunohistochemistry (IHC) in
HMs as well as in normal trophoblastic tissues
"products of conception (POC) and placentas" using a
model of Tissue MicroArray (TMA).
Methods: TMAs were constructed using the archival
material of 240 HMs (130 PHM and 110 CHM) and 240
control normal trophoblastic tissues; POC and
unremarkable placentas. Sections were IHC stained
using antibodies against PD-L1 (clone SP142). The
staining was assessed semi-quantitively (intensity and
percentage of the positive cells) in different cellular
components (trophoblasts and villous stromal cells).
Results: PD-L1 was highly expressed in
syncytiotrophoblasts of PHM compared to CHM with
(core of 4, p-value 0.003). The cytotrophoblasts show less
expression of PD-L1compared to syncytiotrophoblasts of
same cases (score of 3, p-value 0.002). Control cases
show less expression of PD-L1 in both
syncytiotrophoblasts and cytotrophoblasts. HMs with
progression showed high expression of PD-L1 compared
to the regressed cases. All the different cellular
components were visible in the TMAs using two spots
(3mm) from each case in more than 90% of the cases.
Conclusions: Increased expression of PD-L1 in the
syncytitrophoblasts, especially in the progressed cases,
indicates its vital role in the biological behavior of these
lesions. Our data shed light on the usefulness of immune
checkpoint inhibitors in treating gestational trophoblastic
diseases. Construction of TMA with two cores, each of
3mm diameter, can overcome tissue heterogeneity of
complex lesions.

Background
Oral epithelial dysplasia (OED) grade is routinely used to help risk stratify oral potentially malignant disorders in the clinic and inform management strategies. The SAVER trial (Sodium valporate for the epigenetic reprogramming of high-risk oral epithelial dysplasia) used three epithelial dysplasia grading schemes: the World Health Organisation (WHO) recommended system, a binary classification (low vs. high) and a previously described clinical trial-specific system comprising nine categories (0=normal: 1-7=increasing grades of epithelial dysplasia: 8=squamous cell carcinoma). The latter contributed to the primary end point assessment of the SAVER trial.
Purpose
We audited the SAVER trial dysplasia grading data to investigate the reproducibility of scoring systems between the study pathologists.
Methods
Pathology services for the SAVER study were supported by Cellular Pathology at Newcastle Hospitals. Following consent to take part in the SAVER trial, 5mm punch biopsies (baseline and primary end point biopsies) were examined and diagnosed independently by two pathologists using the SAVER trial designated grading systems. Disagreements between pathologists were resolved by slide review and consensus diagnosis. Inter-pathologist agreement was assessed using quadratic weighted kappa statistics.
Results
218 biopsies were received during recruitment to the SAVER study from December 2019-April 2025. The majority of the biopsies (n=200) were graded by the lead pathologist for the SAVER study, five head and neck pathologists provided independent grading and participated in the slide review in cases of disagreement. Based on the assessment of quadratic weighted kappa scores, the pathologists showed ‘almost perfect agreement’ across the different grading systems (Kappa scores: WHO 0.921: binary 0.885: trial-specific 0.928).
Conclusions
Assessment of OED grade in the SAVER trial showed ‘almost perfect agreement’ between head and neck pathologists at Newcastle Hospitals. These data suggest consistent dysplasia grading during recruitment to the study.
This study was supported by a Pathological Society Undergraduate Elective Bursary.

Background

T-cell lymphoma (TCL) arises from a clonal expansion of T lymphocytes. TCL is often difficult to distinguish histologically from benign T-cell infiltrates. Patients often require multiple biopsies, meaning diagnosis can be delayed by months or even years. Current PCR‑based T‑cell receptor (TCR) clonality studies have long turnaround times and cannot assess tissue architecture, morphology, or immunophenotype.

Purpose

We previously validated a pair of highly specific antibodies against mutually exclusively expressed T-cell receptor beta constant regions, TCRbeta1 and TCRbeta2. These are amenable to immunohistochemical staining of formalin-fixed, paraffin-embedded (FFPE) tissue sections, providing a novel strategy to determine T-cell monotypia as a surrogate for T-cell clonality, like kappa and lambda for B cells. Here we develop automated cell counting for accurate quantification of the TCRbeta2:TCRbeta1 ratio.

Methods

For 8 benign and 13 TCL-containing samples, three non-overlapping fields of TCRbeta1 or TCRbeta2-immunostained serial sections were photographed and used for quantitative analysis. Automated cell counting was performed in QuPath, an image analysis software, using a pre-trained StarDist model, under human supervision.

Results

Automated quantification using QuPath and StarDist produced accurate cell counts, permitting TCRbeta2:TCRbeta1 ratio calculation. The TCRbeta2:TCRbeta1 cell ratio in benign tonsils and lymph nodes was between 0.49:1 and 1.25:1, consistent with previously published quantitative real-time PCR (Q-PCR) and in situ hybridisation (ISH) data. Most TCL cases had obvious TCRbeta1/2 restriction, rendering counting superfluous. However, automated counting of positively immunostained cells was very helpful in determining the likely clonal status of lymphomas with a significant tumour-infiltrating benign T-cell population.

Conclusions

We further validate our robust, inexpensive, and highly specific TCRbeta1/2 immunohistochemistry for assessing T cell monotypia in FFPE tissue, as a surrogate for T-cell clonality. We show that this method is amenable to automated cell counting permitting accurate calculation of the TCRbeta2:TCRbeta1 ratio, and broadening the potential clinical applications of this test.

Background
Membranous nephropathy (MN) is a common cause of nephrotic syndrome. The phospholipase A2 receptor (PLA2R) is the target antigen in 55-60% of cases, and anti-PLA2R testing is now integral to clinical practice in the United Kingdom (UK). However, many patients, including up to 83% with secondary MN, are PLA2R-negative.

Recently identified glomerular antigens, including thrombospondin type-1 domain-containing 7A 47 (THSD7A), neural epidermal growth factor-like 1 (NELL1), and exostosin 1/2 (EXT1/2) have been implicated in PLA2R-negative MN, with links to malignancy (NELL1) and lupus nephritis (EXT1/2). There are currently no protocols for their detection in UK practice.

We aimed to optimise immunohistochemistry (IHC) for THSD7A, NELL1 and EXT2 in native renal biopsies, and apply these to a UK retrospective cohort.

Methods
IHC protocols were optimised and applied to 86 retrospective renal biopsies collected between 2018 and 2025 at a UK tertiary centre. These comprised 41 cases of non-lupus PLA2R-negative MN and 45 cases of Class V lupus nephritis. Sections underwent antigen retrieval and staining with commercially available monoclonal antibodies. Positivity was defined as granular capillary wall staining. Samples without glomeruli were excluded.

Results
In PLA2R-negative MN, THSD7A was positive in 2/33 samples (6.1%), NELL1 in 10/30 (33%), and EXT2 in 1/32 (3.1%). In the lupus nephritis cohort, EXT2 was positive in 10/40 cases (25%), NELL1 in 2/36 (5.6%), and THSD7A in none.

Conclusion
This is among the first UK cohorts to systematically apply IHC for THSD7A, NELL1, and EXT2 in PLA2R-negative MN. Preliminary positivity rates align with international data. We are now analysing further retrospective cases and patient data to confirm clinical associations; investigating a prospective cohort to assess impact on clinical decision-making; and developing serological assays to support integration into UK diagnostic pathways.

Background
Immune cells in the tumour microenvironment are associated with prognosis in colorectal cancer. High numbers of tumour infiltrating lymphocytes are known to be a sign of a strong antitumour response, predicting favourable survival outcomes. Similar findings have been demonstrated for tumour associated eosinophils but are less clear for neutrophils.

Purpose
To investigate whether granulocyte density at the invasive margin, detected with a deep learning (DL) algorithm, is prognostic in colorectal cancer.

Methods
Whole slide images (WSIs) of H&E-stained slides were obtained from 144 potentially curative colorectal cancer resections. The tumour invasive margin was annotated using HeteroGenius-MIM image analysis software (HeteroGenius Ltd., Leeds, UK) and a DL model applied to detect eosinophils and neutrophils. Densities were calculated and categorised as high or low using optimised cut-points. Cox regression models and Kaplan Meier curves were used to assess the impact of granulocyte density on cancer specific survival.

Results
In total, 127 cases were assessable. 59% of cases were categorised as eosinophil high and 54% as neutrophil high. Higher numbers of eosinophils at the invasive margin were associated with a reduced risk of cancer specific death compared to lower densities (HR: 0.502, 95% CI 0.248–1.018; p=0.056). Likewise, higher numbers of neutrophils at the invasive margin were associated with a reduction in the risk of cancer specific death (HR: 0.523, 95% CI 0.256–2.069; p=0.076). A stepwise trend was noted for both eosinophils and neutrophils when analysed by quartiles suggesting a linear relationship.

Conclusions
Higher densities of eosinophils and neutrophils within the invasive margin of colorectal cancers appear to be associated with better outcomes. The prognostic impact of these cell types will be explored in different tumour regions, and within trials of neoadjuvant therapy. Ongoing quality control and refinement of the DL algorithm is simultaneously being performed.

Funded by the Pathological Society