The Journal of Pathology最新文献

Dupuytren's disease is a fibroproliferative disorder of the palmer fascia (PF) characterised by flexion contractures in the hand. Dupuytren's disease can be treated surgically, but disease recurrence rates are high, potentially due to continual production of matrisomal proteins. Here, metabolic labelling and proteomics identified differences in the new synthesis and composition of matrisomal proteins between Dupuytren's tissue and normal PF. Dupuytren's tissue actively synthesised type I collagen, fibronectin (FN1), matrix metalloproteinases-2 and -3 (MMP2, MMP3) and tissue inhibitor of metalloproteinases 2 (TIMP2). Both tissues actively synthesised insulin-like growth factor binding protein 7 (IGFBP7). Label-free analysis implicated the transforming growth factor-β (TGFβ) pathway in the matrisomal profile of Dupuytren's tissue. The effect of TGFβ isoforms on COL1 mRNA expression was first tested in cultured young and aged equine tenocytes. COL1A1 mRNA responded to treatment with all TGFβ isoforms and was more highly expressed in cells from aged samples. In aged human cells, COL1A1 and COL1A2 mRNA was higher in cells derived from Dupuytren's tissue than normal PF and in response to TGFβ1, but no changes in COL1A1 or COL1A2 CpG methylation were detected. TGFβ1 treatment only resulted in increased type I collagen protein accumulation in the media of Dupuytren's nodule cells. In three-dimensional cultures, COL1A1 mRNA was lower in normal PF than in Dupuytren's cells, but TGFβ1 treatment only increased type I collagen accumulation in the media of normal PF cultures, and TGFβ1 inhibition did not alter new collagen protein synthesis. TGFβ1 inhibition in Dupuytren's tissue explants did not alter the proportion of homotrimeric type I collagen, nor was this changed in skin or tendon of the tight-skin (TSK) mouse, a naturally occurring model of indirect TGFβ1 activation. Therefore, the role of TGFβ in Dupuytren's disease may be predominantly related to myofibroblast phenoconversion and contractility rather than directly altering collagen protein synthesis. © 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.

Every year the editorial team of the Journal of Pathology awards the Jeremy Jass Prize for Research Excellence to the paper published in the prior calendar year that they perceive to be of the highest scientific calibre. Selection is always difficult because the standard of papers published in the Journal is so high.

The paper selected for the Jass Prize for the calendar year 2024 is:

Natálie Klubíčková*,†, Josephine K. Dermawan†, Elaheh Mosaieby, Petr Martínek, Tomáš Vaněček, Veronika Hájková, Nikola Ptáková, Petr Grossmann, Petr Šteiner, Marián Švajdler, Zdeněk Kinkor, Květoslava Michalová, Peter Szepe, Lukáš Plank, Stanislava Hederová, Alexandra Kolenová, Neofit Juriev Spasov, Kemal Kosemehmetoglu, Leo Pažanin, Zuzana Špůrková, Martin Baník, Luděk Baumruk, Anders Meyer, Antonina Kalmykova, Olena Koshyk, Michal Michal, and Michael Michal. Comprehensive clinicopathological, molecular, and methylation analysis of mesenchymal tumors with NTRK and other kinase gene aberrations. J Pathol 2024; 263: 61–73. DOI: 10.1002/path.6260

* Corresponding author. † These authors contributed equally to this study.

We offer our congratulations to the authors, some of whom are shown in Figure 1. The paper is available with Open Access at https://onlinelibrary.wiley.com/doi/full/10.1002/path.6260.

Carcinosarcomas (CSs) are aggressive biphasic tumors characterized by epithelial and mesenchymal components, whose histogenesis and differentiation dynamics remain poorly understood. We present single-nucleus RNA sequencing (snRNA-seq) analysis of six CSs (five endometrial and one ovarian) and two normal endometrial samples, profiling over 96,298 cells. By integrating transcriptomic data with inferred copy number variations (CNVs), immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), and in situ hybridization (ISH) validation, we resolved the complex cellular architecture of these tumors, identified lineage-specific programs, and revealed unexpected differentiation trajectories. snRNA-seq was used to further refine the histopathological classification of three cases by uncovering heterologous differentiation not previously recognized: one rhabdomyogenic, one osteogenic, and, notably, one exhibiting a novel tenogenic program, defined by the expression of SCX, MKX, and TNMD. All CSs displayed a prominent mesenchymal compartment comprising both undifferentiated fibroblast-like cells and distinct lineage committed populations, including rhabdomyoblasts (Rhab), tenoblasts (Teno), osteoblasts (Osteo), and chondroblasts (Chond). In some tumors, multiple mesenchymal identities co-existed, and in others, differentiation gradients (e.g. immature versus mature rhabdomyoblasts) were observed. These patterns underscore the cellular plasticity and multilineage potential of the sarcomatous component. Furthermore, the expression of specialized interface markers (COL22A1, NCAM1, ACAN, CHRNG, MUSK) suggests that some tumors use structured developmental programs reminiscent of the muscle–tendon junction, enthesis, or neuromuscular junction. CNV analysis revealed tumor-specific genomic alterations with clonal and subclonal patterns linked to differentiation state, which were validated by FISH. Altogether, this study demonstrates that CSs are not static biphasic tumors but rather complex ecosystems with extensive developmental plasticity. Our findings redefine their classification and support the use of single-nucleus approaches to uncover hidden differentiation trajectories in highly heterogeneous cancers, including the discovery of a previously unreported tenogenic lineage. Our results challenge the diagnosis of homologous CS when only morphological criteria are applied. © 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.

BK polyomavirus (BKPyV) is a viral infection experienced by kidney transplant recipients that can lead to the development of BKPyV-associated nephropathy (BKPyVAN), graft dysfunction, and loss. There are no BKPyV-specific treatments available to prevent this significant cause of transplant failure. This bioinformatic study aims to characterise the cellular networks and pathways involved in BKPyVAN to identify novel therapeutic targets. Four publicly available bulk transcriptomic datasets containing BKPyVAN post-transplant biopsy tissue were identified in the National Centre for Biotechnology Information Gene Expression Omnibus (NCBI GEO). Differentially expressed genes (DEGs) (adjusted p < 0.05, fold change ≥ 1.5) were identified and dataset comparisons made between BKPyVAN versus stable grafts and acute rejection versus stable grafts. Canonical pathways were investigated using QIAGEN Ingenuity Pathway Analyses and protein interaction networks using STRING v12.0. There were 226 genes identified as differentially expressed in BKPyVAN compared with stable graft function that were conserved across all four datasets. This gene signature was associated with three cellular networks and 201 significantly enriched pathways. The cellular networks identified included 67 immune-related proteins; eight proteins associated with the absent in melanoma 2 (AIM2) inflammasome; and four HLA class II proteins. The most notable pathways significantly increased in BKPyVAN included HLA class II antigen presentation (p < 0.001), inflammasome (p < 0.001), and interleukin 6 signalling (p < 0.01). There were seven DEGs that were observed as common to all BKPyVAN versus acute rejection comparisons. The TUBB3 gene was the only gene that was consistently upregulated in all datasets. Several pathways and potential treatment targets were identified using a bulk RNA mining strategy, including HLA class II antigen presentation, AIM2 inflammasome, and IL-6 signalling in BKPyVAN pathology. Such tools provide an important first step in identifying novel mediators of disease pathogenesis and likely hold the key for the discovery of potential treatment targets for BKPyVAN in the future. © 2026 The Pathological Society of Great Britain and Ireland.

Tumor budding and poorly differentiated clusters are key prognostic indicators in colorectal cancer, yet the molecular mechanisms underlying their formation remain incompletely characterized. Using the GeoMx Digital Spatial Profiler, we analyzed gene expression profiles across tubular components, transitional zones, and tumor budding and poorly differentiated cluster regions in 12 colorectal cancer cases. While histopathological assessment revealed no definitive evidence of complete epithelial-mesenchymal transition in tumor budding or poorly differentiated clusters, transcriptional analysis demonstrated significant upregulation of epithelial-mesenchymal transition-related genes (ZEB1, ZEB2, SNAI2) alongside maintained epithelial marker expression, indicating a partial epithelial-mesenchymal transition phenotype. Tumor budding and poorly differentiated cluster regions showed reduced proliferative activity with significant downregulation of MYC and its target genes involved in protein synthesis and cell cycle progression. Conversely, RUNX2 and its targets were significantly upregulated in tumor budding and poorly differentiated cluster regions, particularly genes mediating cell adhesion, migration, and extracellular matrix interactions. KRT80 showed striking upregulation in tumor budding and poorly differentiated cluster regions, correlating with RUNX2 expression. This reciprocal pattern of MYC downregulation and RUNX2 upregulation appears to contribute to maintaining the hybrid epithelial-mesenchymal state characteristic of tumor budding and poorly differentiated cluster regions. Our findings reveal that the formation of these regions involves transcriptional changes preceding morphological alterations, with RUNX2 potentially driving this invasive phenotype while preserving epithelial features. These insights may enhance our understanding of the mechanisms driving colorectal cancer progression and identify potential therapeutic targets for aggressive disease. © 2026 The Pathological Society of Great Britain and Ireland.

Netherton syndrome (NS) is a rare, severe, and often life-threatening disease for which current therapeutic approaches are limited and show variable effectiveness. NS is characterized by excessive epidermal desquamation that results in a highly defective epidermal barrier, constitutive skin inflammation, allergies, and hair abnormalities. NS develops due to loss-of-function mutations in the SPINK5 gene, which encodes the LEKTI inhibitor that regulates KLK proteases (KLK5, KLK6, KLK7, KLK13, and KLK14). These findings indicate that dysregulation of proteolytic networks underlies the extensive skin shedding and inflammation characteristic of NS. Spink5^-/- mice recapitulate the major features of the human disease but exhibit neonatal lethality. Several double- and triple-knockout models have been generated to rescue the lethal NS phenotype, and have proved instrumental in studies aiming to elucidate the biological pathways involved in NS, and to identify and validate potential targets for drug development. These studies have established that inhibition of excessive KLK protease activity in LEKTI-deficient epidermis can reverse the cutaneous manifestations of NS. In particular, ablation of KLK5 results in a marked therapeutic response, although KLK7 or TNFα must also be inhibited to rescue the most severe (lethal) form of NS. Murine models have also been essential in proving or disproving putative pathways and/or therapeutic targets proposed from in vitro studies or patient case studies. Collectively, these models have provided a deeper understanding of the epidermal proteolytic cascades involved in NS pathology and in normal skin renewal. Moreover, these models offer a platform in which disease-specific candidate therapeutics can be tested and preclinically validated. © 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.

A machine learning-based pathomics model was investigated for its value and biological significance in predicting overall survival (OS) after surgery in pancreatic cancer patients. Data from 173 patients with pancreatic ductal adenocarcinoma (PDAC) who underwent surgery and continued follow-up in two centers were retrospectively analyzed. Pathomics parameters of both the tumor and peritumor were measured in all patients, and the optimal pathomics score (Pathscore) was calculated using five machine learning methods. The best Pathscore was then combined with multiple clinical parameters to analyze its incremental value and to construct a comprehensive nomogram. TCGA data, multiplex immunofluorescence, spatial analysis, and single-cell sequencing were used to explore the biological mechanisms of pathomics. In predicting OS, pathomics parameters from the tumor and peritumoral regions provided complementary prognostic information. The LASSO-based combined model achieved the best predictive accuracy. Multivariate Cox regression analysis identified T-stage, N-stage, CA19-9, and Pathscore as independent predictors of OS in patients with PDAC. The integrated nomogram demonstrated superior and more stable predictive performance. Analysis of the TCGA dataset suggested that the pathomics model was associated with the immune status of pancreatic cancer, a finding supported by trends in the validation cohort. Spatial analysis and single-cell analysis further revealed a strong association between the Pathscore and immune cell infiltration, in particular CD8+ T cells. Machine learning-based pathomics models can help to predict the immune status and OS of patients with PDAC. The integration of pathomics with clinical parameters provides a robust basis for immune evaluation, prognostic prediction, and therapeutic decision-making in PDAC. © 2026 The Pathological Society of Great Britain and Ireland.

Neoadjuvant immunochemotherapy (NAIC) is a standard treatment for triple-negative breast cancer (TNBC), but there is no reliable biomarker to identify potential responders and optimize patient care. In this study, we developed a model named Immunotherapy Prediction based on Pathological Images (IPPI) by machine learning. The IPPI model performed well in the discovery cohort and two validation cohorts, which included a total of 209 patients, and its predictive power was significantly improved compared to clinical factors and the combined positive score for programmed death-ligand 1. TNBC patients predicted to achieve a pathological complete response had a better prognosis than those predicted to have residual disease. Moreover, we elucidated the relationship between histopathological features and biological characteristics, thereby improving the interpretability of the IPPI model. This study proposes a novel and efficient model to facilitate the prediction of NAIC response in TNBC patients, highlights key histopathological features associated with treatment response, and presents new evidence for precision immuno-oncology through the integration of machine learning and digital pathology. © 2026 The Pathological Society of Great Britain and Ireland.

Intratumor heterogeneity of ERBB2 amplification/HER2 overexpression is frequently observed in ERBB2-amplified high-grade endometrial carcinoma (HG-EC) and contributes to anti-HER2 therapy resistance. To elucidate the molecular pathogenesis and evolutionary trajectory of HER2-heterogeneous HG-ECs, we performed next-generation sequencing of spatially distinct HER2-negative (HER2-) and HER2-positive (HER2+) tumor areas from nine tumors (whole exome, n = 7; targeted panel, n = 2). HER2- and HER2+ components shared a high proportion of somatic mutations, particularly clonal mutations, including known EC driver genetic alterations. The 17q12 amplicon, containing the ERBB2 gene, was the only significant recurrent copy number alteration that differed between HER2- and HER2+ components. By unsupervised hierarchical clustering of genome-wide copy number alterations, samples clustered together at the patient level rather than by HER2 status. Intra- and intertumor heterogeneity in ERBB2 amplification/HER2 expression was also observed in metastatic lesions, which likely originated from different tumor subpopulations within the primary tumor. Exploratory spatial transcriptomics analyses revealed gene expression differences associated with HER2 status, including a shift from 'mesenchymal-like' toward epithelial differentiation in HER2+ components for a subset of cases, a finding that warrants further investigation. Our results suggest that HER2 heterogeneity in HG-EC reflects late acquisition of ERBB2 amplification during tumor evolution. ERBB2 does not appear to drive tumor initiation in HER2-heterogeneous HG-EC but likely serves a context-dependent role in the progression of established tumors. © 2026 The Pathological Society of Great Britain and Ireland.

Fumarate hydratase-deficient uterine leiomyomas (FHd-ULMs) represent a molecularly distinct subgroup of smooth muscle tumours associated with hereditary leiomyomatosis and renal cell cancer (HLRCC) syndrome. This study determined the detection rate of germline pathogenic FH variants in FHd-ULMs using paired tumour-normal sequencing and assessed the utility of integrated morphological, immunohistochemical (FH/2SC), genomic, and clinical features for selecting cases suspected of HLRCC. Histopathological assessment of the 252 FHd-ULMs revealed consistent morphological features, whereas molecular profiling identified three biologically distinct categories. Germline FH-mutated (hereditary) cases constituted 35.7% (74/207) of this FHd-ULM cohort, four of which showed concomitant somatic copy-number alterations. This contrasted with the somatic-mutated subgroup, which comprised 50.7% (105/207), including 18.4% (38/207) with isolated somatic copy-number losses. The remaining 13.6% (28/207), though lacking detectable FH mutations, were classified with somatic-mutated cases as sporadic FHd-ULMs based on shared clinicopathological features. Molecular analysis identified shared variant distributions across exons 2-10, with exons 5 and 7 in the fumarate lyase domain emerging as the predominant mutational hotspots. Notably, truncating mutations showed significantly higher prevalence in hereditary cases versus somatic variants (p < 0.01). Clinically, hereditary FHd-ULMs presented at younger ages (< 45 years) and manifested more aggressive phenotypes, including elevated rates of infertility (54.1% versus 26.4%), multifocal tumour development (86.5% versus 53.4%), increased surgical interventions (44.6% versus 11.5%), and familial leiomyoma clustering (51.4% versus 24.2%). Our results identify germline FH mutations, which confer significant HLRCC risk, in 35.7% of FHd-ULMs, while somatic alterations account for the majority of cases. To ensure efficient resource allocation, we propose a stratified diagnostic approach: initial universal FH/2SC immunohistochemical screening for ULMs displaying ≥ 3 FH-deficient morphological features, followed by confirmatory genetic testing in high-risk individuals, defined by either aberrant FH/2SC immunoreactivity or, in immunohistochemically normal cases, age < 45 years together with a personal/family history of multiple symptomatic leiomyomas or HLRCC-associated neoplasms. © 2026 The Pathological Society of Great Britain and Ireland.