The Journal of Pathology最新文献

Risk stratification across the three main clinical subsets of malignant peripheral nerve sheath tumor (MPNST), neurofibromatosis type I (NF1-related), sporadic, and prior radiation therapy (RT), is based mainly on clinicopathologic parameters, such as size, grade, stage, and NF1 status. Moreover, no prior study investigated the additional impact of genomic alterations in the prognosis of high-grade MPNST using clinically validated DNA targeted next-generation sequencing (NGS) panels. Our goal was to integrate clinicopathologic and genomic parameters using an elastic-net penalized Cox proportional hazards machine learning model using OncoCast for risk prediction. Herein we perform comprehensive mutational and copy number profiling using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) on 81 primary localized high-grade MPNSTs (51% NF1-related, 38% sporadic, 11% RT-associated). The most common genomic alterations included NF1 (51% germline, 59% somatic), CDKN2A/B (62%), PRC2 components (SUZ12, EED) (53%), and TP53 (25%). Variables selected by OncoCast as significantly associated with survival were used to construct a three-tier risk stratification model for progression-free survival (PFS) and disease-specific survival (DSS). For PFS, patients with chr16 deletion were classified as high-risk, those with concurrent germline and somatic NF1 alterations as low-risk, and the remainder was assigned to the intermediate-risk group. For DSS, cases with fraction genome altered (FGA) > 50% were defined as high-risk, those with PRC2 abnormalities, CDKN2A deletion, TERT promoter mutation, or chr16 deletion as intermediate-risk, and cases lacking all the aforementioned alterations as low-risk. The high-risk group showed significantly inferior survival compared to the low-risk group (both PFS and DSS p < 0.001). Subgroup analysis showed that among NF1-related MPNST, co-occurring somatic NF1 mutation or WT TP53 was associated with superior PFS. Collectively, genomic alterations detected by clinical NGS panels provide potential new biomarkers for risk stratification that can be integrated with conventional parameters to provide improved prognostication and guide therapeutic strategies. © 2026 The Pathological Society of Great Britain and Ireland.

MYO7A is a causal gene, underlying Usher syndrome type 1B (USH1B) and both autosomal recessive (DFNB2) and dominant (DFNA11) non-syndromic hearing loss. Despite the large number of reported MYO7A variants (over 2,200), variants located in an extended splice region remain difficult to interpret and are often classified as variants of uncertain significance (VUS). We investigated the clinical impact of MYO7A extended splice region variants, located within ±50 bp of exon-intron boundaries, by analyzing a nationwide Chinese cohort of 10,664 undiagnosed individuals with hearing loss. Twelve such variants (in 11 probands, two variants were in cis) were identified for functional analysis. Using minigene splicing assays coupled with in silico splicing predictions, we evaluated each variant's effect on pre-mRNA processing and applied ACMG/AMP guidelines for classification. Six of the tested variants completely disrupted normal splicing, and eight variants in total were reclassified from VUS to pathogenic or likely pathogenic based on aberrant transcript outcomes. Notably, several variants generated multiple distinct abnormal transcripts, and two-thirds of these variants fell within the myosin motor domain (others in the FERM2 domain). Splicing predictions from in silico algorithms were largely concordant with the experimental results, further supporting their utility in variant interpretation. This functional evidence enabled definitive molecular diagnoses in previously unresolved cases spanning DFNA11, DFNB2, and USH1B phenotypes. In summary, our study demonstrated that integrating experimental splicing assays with predictive tools can definitively determine the pathogenicity of extended splice region variants in MYO7A, thereby improving the diagnostic accuracy of genetic testing for both non-syndromic and syndromic hearing loss. This approach could be applied to other genes to enhance genetic diagnosis. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The naked mole-rat (NMR; Heterocephalus glaber) is a subterranean rodent native to the arid regions of the Horn of Africa. The NMR is the longest-lived rodent and is known for its distinctive physiological and social traits. This species has become a notable model organism for studying aging, cancer biology, behavioral ecology, and reproduction. Recently, NMRs have gained attention because their gastrointestinal tract features an exceptionally strong intestinal barrier, a large number of goblet cells, a thicker mucin layer, and reduced gut permeability. The NMR gut microbiome, similar to that observed in human centenarians, is highly diverse and characterized by a high microbial load. In fact, Hart et al (2026) demonstrated that spontaneous infection with Citrobacter braakii in the NMR causes clinical symptoms and histopathological changes that are very similar to those observed in human colitis. If left untreated, the disease can progress and become fatal. However, probiotic treatment can reverse the clinical and histopathological phenotypes. These findings indicate that, in addition to serving as a powerful model for aging, cancer, and reproduction, the NMR may also serve as a powerful tool for studying human diseases such as gut dysbiosis, gut barrier dysfunction, and colitis. © 2026 The Pathological Society of Great Britain and Ireland.

Malignant germ cell tumors (GCTs) are relatively rare tumors with limited therapeutic options. This study examined the homologous recombination deficiency (HRD) status and genomic characteristics in 14 patients with GCT who underwent next-generation sequencing. HRD was evaluated using the genomic instability score (GIS), which incorporates three components: loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale transition (LST). Our findings showed that 57.1% (8/14) of participants were HRD positive. Female patients presented a significantly higher prevalence of HRD positivity (87.5%, 7/8) compared with male patients (16.7%, 1/6). HRD positivity in female cases had a mean GIS of 56 (range 48-76), including one patient harboring a germline BRCA2 p.S2670L (c.8009C>T) likely pathogenic mutation. LST demonstrated the strongest correlation with the integrated GIS (R² = 0.945), followed by LOH (R² = 0.872). Distinct mutation patterns were observed based on gender. GCTs in male cases predominantly exhibited mutations in TP53 (50% in yolk sac tumors; 50% in teratomas). GCTs in male cases also demonstrated TP53 mutations in one mediastinal yolk sac tumor and one mediastinal teratoma. Male cases showed recurrent alterations in KRAS, PRKDC, and CDKN1B, alongside frequent chromosome 12p amplifications in two cases. One particularly complex mediastinal teratoma in a male patient, featuring rhabdomyosarcomatous transformation, displayed bidirectional intergenic (TWSG1, MANEA-DT)-ROS1fusions, a HRAS-intergenic (RNH1) fusion, and MET focal amplification. These findings suggest a promising therapeutic opportunity with poly (ADP-ribose) polymerase (PARP) inhibitors for female patients with HRD-positive GCTs. Additionally, the complex composition of gene variants found in male patients with GCTs, including ROS1 fusions and MET focal amplification, points toward potential targeted therapeutic strategies. This study underscores the presence of sex-specific therapeutic vulnerabilities in GCTs, which warrant further exploration in larger cohorts. © 2026 The Pathological Society of Great Britain and Ireland.

Neutrophil extracellular traps (NETs) contribute to chronic obstructive pulmonary disease (COPD) pathogenesis by amplifying airway inflammation. Gasdermin D (GSDMD)-mediated pyroptosis is a critical driver of COPD progression. This study provides insights into COPD pathogenesis and provides a theoretical basis for potential therapeutic targets. Mice were exposed to cigarette smoke (CS) for 16 weeks to establish a COPD model. In vitro, alveolar macrophages (AMs) (MH-S) and alveolar epithelial cells (MLE-12) were treated with cigarette smoke extract (CSE). Subsequently, NETs were isolated from phorbol-12-myristate-13-acetate (PMA)-stimulated neutrophils. Lung histopathology, inflammatory markers, and pyroptosis-related proteins were analyzed. Co-immunoprecipitation analysis was used to verify the binding of GSDMD and ubiquitin molecules in cells. Interventions included DNase1 to degrade NET and GSDMD knockdown. In CS-exposed mice, NETs increased the levels of proinflammatory cells and mediators, and lung structure was further disrupted. Pyroptosis of AMs was increased, while phagocytosis of AMs was inhibited. However, treatment with DNAse1 partially reversed the results caused by CS exposure and NET induction. Consistently, NETs aggravated inflammatory response and pyroptosis in the CSE-induced MH-S cell model. Furthermore, NETs significantly caused an increase in ROS, which promoted the activation of GSDMD deubiquitination and subsequent pyroptosis pathway in AMs. DNase1 treatment or GSDMD silencing attenuated pyroptosis, reduced inflammatory mediators, and improved lung function. NETs aggravated CS-induced lung inflammation and injury by activating GSDMD to promote pyroptosis in AMs. Targeting GSDMD or NETs represents a novel therapeutic strategy for COPD. © 2026 The Pathological Society of Great Britain and Ireland.

Lung cancer is the leading cause of global cancer-related morbidity and mortality, with tobacco smoking as its strongest risk factor. Nuclear factor erythroid 2-related factor 2 (NRF2) is a redox-regulated transcription factor frequently dysregulated in non-small cell lung cancer (NSCLC), leading to aggressive disease and resistance to therapy. In this study, we analyzed circulating cell-free tumor DNA from a real-world cohort to characterize clinicopathological features and identify risk factors associated with oncogenic NRF2 activation in inoperable NSCLC. Key findings were further validated using retrospective datasets. Our results demonstrate that NRF2 pathway-mutated NSCLC represents a smoking-associated, high-risk molecular subtype frequently accompanied by detrimental SMARCA4 mutations. Importantly, these co-occurring mutations cumulatively worsen clinical outcomes independently of other risk factors. We show that NRF2-mutated tumors generally exhibit lower leukocyte infiltration, while high tumor mutation burden independently correlates with increased cytotoxic T lymphocyte density, regardless of NRF2 status. Furthermore, our data indicate that NRF2 activation can be reliably identified through immunohistochemical detection of protein expression of markers AKR1B10 and AKR1C1, both of which correlate with inferior outcomes. As mutations in NRF2-regulating tumor suppressors KEAP1 and CUL3 are not confined to specific hotspot regions, our findings advocate for a multimodal profiling approach combining somatic mutation assessment with protein or transcriptomic evaluation of NRF2 targets. This comprehensive strategy effectively identifies oncogenic NRF2 hyperactivity, enhancing diagnostic accuracy and clinical decision-making in NSCLC management. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The integration of artificial intelligence into pathology is transforming the assessment of histological and immunohistochemical (IHC) slides, offering opportunities to reduce variability and streamline diagnostics. In practical terms, most available tools and research models emulate the diagnostic capabilities of pathologists by detecting, grading, and classifying tumours and other diseases. More recent applications have moved beyond mimicry, aiming to predict established biomarkers, such as microsatellite instability or IHC-based markers, and to tackle even more ambitious tasks, such as directly predicting patient prognosis from H&E whole slide images. Remarkably, novel computational tools are now being designed as companion diagnostic assays, linking the automated evaluation of specific IHC biomarkers to the prediction of response to specific drugs, potentially marking a new chapter in the evolution of digital and computational pathology. The TROPION-PanTumor01 trial recently demonstrated the superiority of a supervised machine learning model (termed the quantitative continuous score [QCS] by the vendor) in assessing TROP2 IHC compared with human scoring, promising better stratification of patients with non-small cell lung cancer for treatment with datopotamab deruxtecan. The same approach has shown promise in refining HER2 (human epidermal growth factor receptor 2) and PD-L1 (programmed death-ligand 1) evaluations, revealing patient subgroups that may benefit from targeted therapies. Moreover, other similar approaches are progressively reaching the market, posing significant opportunities and challenges for clinicians involved in the care of patients with cancer. This Perspective is promoted by the European Society of Digital and Integrative Pathology (ESDIP, founded in 2016, and having long-standing experience in computational pathology, esdipath.org) and the European Interdisciplinary Society of Artificial Intelligence for Cancer Research (ESAC, a recently established initiative, founded in 2024, esac-network.eu), both bringing together clinicians, engineers and other professionals dedicated to the development and clinical translation of computational approaches aimed at improving patient care. It aims to provide an informed overview of novel computational pathology companion diagnostic tools, with a particular focus on the background that practicing pathologists and oncologists need to have with these tools, when transitioning from research to clinical practice, irrespective of their prior familiarity with computational approaches. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Late-onset Fuchs endothelial corneal dystrophy (FECD) is the most common primary disease of the corneal endothelium and the leading indication for corneal transplantation in Western countries. It is characterized by progressive accumulation, over two to three decades, of extracellular matrix (ECM) components in Descemet's membrane (DM), leading to the formation of abnormal excrescences, known as guttae, and additional DM layers. Clinical forms and evolutionary profiles vary widely among patients. FECD is strongly associated with intronic CTG trinucleotide repeats (TNRs) in the transcription factor 4 (TCF4) gene. We analysed 500 DMs removed during keratoplasty for FECD across 25 European centres to identify different anatomopathological forms of the disease. Following flat mounting and dehydration, the samples were digitized using transmitted light microscopy and independently assessed by three independent readers. A total of ten parameters - six related to guttae and four on other forms of ECM - were scored. Principal component analysis and an unsupervised clustering method separated three clusters from these parameters. In addition, manual classification was performed by grouping samples with major common features. The number of TNRs in TCF4 was analysed by short tandem repeat (STR)- and triplet repeat primed-polymerase chain reaction (TP-PCR) for 109 patients. We found that (1) five FECD phenotypes exist; (2) guttae and other ECM structures were radially arranged in 95% of samples; (3) 33% of samples exhibited peripheral radial striae that corresponded to a hypertrophied form of similar structures present in healthy corneas; and (4) patients with fewer than 50 TNRs had only two out of five phenotypes and had a significantly higher number of peripheral radial striae (94% versus 49%, p < 0.001). Taken together, these new findings demonstrate the existence of different FECD phenotypes; reveal that lesions affect both the centre and the periphery of the endothelium; and suggest that radial deposits may be produced by pathological cells migrating from the periphery towards the centre. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Over recent years, several deep learning (DL) models have been presented to predict colorectal cancer (CRC) patient survival directly from haematoxylin and eosin (H&E)-stained routine whole-slide images (WSIs). Unlike traditional studies that rely on manually defined histopathological features, weakly supervised DL allows training directly on clinical endpoints without prior specification of the model's focus. This offers a unique opportunity to study the tissue morphology underlying these predictions, improving our understanding of disease biology. Here, we present a comprehensive analysis of the clinicopathological features, tumour morphology and biology, as well as gene expression-based predicted drug response of over 4,000 CRC patients derived from four different international cohorts with available H&E-inferred DL-based risk scores (low- versus high-risk as well as absolute risk scores). The results from our study suggest that conventional clinicopathological risk factors, such as grade of differentiation, presence of lymph node metastasis, tumour budding, and percentage of tumour necrosis, are positively associated with DL-based risk scores. Moreover, CRCs with direct tumour-adipocyte interactions are enriched in the DL-based high-risk group. Through detailed morphologic review, we provide comprehensive evidence that direct tumour-adipocyte interaction, a high degree of tumour budding, and poorly differentiated morphology are linked to high DL-based risk scores. Transcriptomic and genetic subgroups show only limited association with H&E-derived DL-based risk scores. Moreover, we present data suggesting that DL-based low- versus high-risk CRCs may be characterised by differential drug sensitivity. Our study highlights that DL-based risk scores derived from H&E WSIs not only align with established clinicopathological features but also highlight morphological features, such as tumour-adipocyte interaction, that are not routinely captured by established clinicopathological scoring systems. Moreover, DL-based risk groups may be associated with a differential treatment response, underlining their potential to guide patient stratification in routine clinical practice. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Angioimmunoblastic T-cell lymphoma (AITL) exemplifies a neoplasm characterized by prominent inflammatory infiltration and robust immune responses in the tumor microenvironment (TME). The pathophysiology of refractory/recurrent (RR) AITL remains poorly understood due to profound intratumoral heterogeneity and complex TME features, contributing to limited therapeutic efficacy. Using Xenium-based spatial transcriptomics on 10 clinical samples, we compared RR AITL with treatment-responsive [non-refractory/recurrent event in 3 years (NR)] cases to map the TME architecture. We identified a novel cluster of NEIL3+ (Nei Like DNA Glycosylase 3) T-follicular helper (Tfh) cells, which exhibited stem-like characteristics at the transcriptional level, featuring self-renewal and multilineage differentiation capacity, and were highly enriched in RR tumors. Furthermore, we found major differences in immune cell organization between NR and RR microenvironments: RR cases were dominated by B cells primed for adaptive immunity and myeloid cells driving angiogenesis, whereas NR cases exhibited a chemokine-mediated regulatory landscape. These findings provide comprehensive characterization of the TME ecosystem in AITL and reveal potential therapeutic targets for high-risk RR AITL patients. © 2026 The Pathological Society of Great Britain and Ireland.