The Journal of Pathology最新文献

Crohn's disease (CD) involves chronic transmural inflammation of the intestines, leading to progressive wall fibrosis with stenosis and luminal obstruction, predominantly in the terminal ileum. Fibrosis is a significant therapeutic challenge, thus improved understanding of localisation, cellular composition, and cell-cell interactions in CD fibrostenosing lesions (FSLs) may identify potential targetable pathways. Using CD FSL patient resection samples, we identify and quantify novel pathological changes in structure, collagen, and cell numbers for each ileal layer (mucosa, muscularis mucosae, submucosa, muscularis propria, serosa). In addition, fresh resection ileal samples were single-cell RNA (scRNA)-sequenced, validating the cell types and cell-cell interactions. We found significantly increased collagenous fibrosis expansion, significantly increased infiltration of lymphocytes, macrophages, endothelium, and Crohn's lymphoid aggregates (CLAs) in all layers, except for the ulcerated mucosa. Importantly, endothelial cells accumulate in clusters around CLAs, and scRNA-seq data demonstrated ligand-receptor intercellular signalling interactions between endothelium, B and T lymphocytes, macrophages, and myofibroblasts via multiple pathways that included GAS, SELL, and SELPLG, among many others. The highest levels of fibrotic collagen and CLAs with accumulated endothelium were observed in submucosa, followed by serosa, demonstrating colocalisation and correlation of endothelial-CLAs with collagen that is consistent with CLAs having a role in promoting collagenous fibrosis that requires further investigation. © 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.

Enteropathogenic bacteria are a major cause of morbidity and mortality globally. While mouse models have been indispensable in advancing our understanding of infectious enteric diseases, key differences in intestinal microbiota and immunobiology between mice and humans underscore the need for alternative mammalian models that better recapitulate human disease states. The naked mole rat (NMR), the longest-lived rodent and a model of healthy ageing, presents a unique opportunity. It possesses an exceptionally robust intestinal barrier, an abundance of goblet cells, a thicker mucin layer, and reduced gut permeability compared to mice. Additionally, the NMR gut microbiome exhibits compositional and functional features shared with human centenarians and traditional-lifestyle populations (e.g. Hadza hunter-gatherers), including an enrichment of health-associated taxa and metabolic pathways. Here, we leverage this model to show that systemic Citrobacter braakii infection is associated with colonic inflammation and epithelial injury that closely mimics human haemorrhagic colitis. Infected NMRs develop mucosal erosions, ulcerations, depletion of goblet cells, expansion of proliferative compartments, and active inflammation in the lamina propria. Without intervention, systemic inflammation associated with sepsis ensues and results in high mortality. Furthermore, we demonstrate the utility of this model for therapeutic testing by showing a strong effect of a probiotic cocktail comprising lactobacilli, bifidobacteria, streptococci, and enterococci. Treatment with this cocktail promoted mucosal healing, restored intestinal homeostasis, and exerted an anti-inflammatory effect. Taken together, we establish the NMR as a translatable model for investigating disease mechanisms in infectious colitis, including disruptions in mucosal barrier permeability, gut microbial ecology, and local and systemic immune regulation, as well as for testing functional probiotic strains as potential therapeutics. © 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.

Colorectal cancer (CRC) typically originates from benign polyps within the colorectum. However, the mechanisms driving this transformation remain poorly understood. In this study, we employed a comprehensive multi-omics approach, incorporating multiplex immunostaining and adeno-associated virus (AAV)-mediated mouse models, to systematically dissect the key drivers of malignant transformation in CRC. Our investigations revealed a dynamic and stage-specific expression pattern of thrombospondin 2 (encoded by the gene THBS2), characterized by significantly downregulated expression during the polyp stage, followed by markedly upregulated expression in malignant CRC tissues compared to healthy colon tissue. Intriguingly, THBS2 expression was primarily localized within a distinct fibroblast subpopulation, with THBS2⁺ fibroblasts exhibiting a tumor-tropic infiltration pattern. Through a series of analyses, we hypothesized that THBS2⁺ fibroblasts may play a role in coordinating CRC progression via the THBS2-CD36 and THBS2-SDC1 pathways. Furthermore, depletion of THBS2⁺ fibroblasts enhanced polyp formation but suppressed tumor formation in a thymidine kinase 1/ganciclovir/azoxymethane/dextran sulfate sodium mouse model. The comprehensive multi-omics atlas and complementary data presented here will advance our understanding of the mechanisms underlying CRC malignant transformation and may provide a potential therapeutic target. © 2026 The Pathological Society of Great Britain and Ireland.

Understanding the lymphatic network is crucial for immunological research. Currently, a complete map of lymphatic drainage in mice is lacking. We present a detailed lymphatic system flow dynamic of two mouse strains with swollen lymph nodes (LNs), using region-specific tracer injection and high-resolution micro-CT imaging to characterize LN volume, weight, density, and spatial topology. No significant differences were observed in LN localization or numbers by strain or sex. Notably, we identified previously unreported drainage pathways and asymmetries, including distinct right and left lymphatic flows. We also discovered intranodal lympho-venous shunts in LNs, which facilitate unidirectional fluid transport and prevent interstitial fluid buildup and edema. Our findings suggest that these shunts may play a significant role in the delivery of therapeutics within LNs and highlight the need for further research into lymphatic structure-function relationships. © 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.

Bile duct tumor thrombus (BDTT), a tumor cluster occupying the luminal space in the large bile duct, is rare in intrahepatic cholangiocarcinoma (iCCA). Most studies on BDTT in iCCA to date are case reports, and the clinicopathological characteristics remain unknown. This study aimed to characterize iCCA with BDTT clinicopathologically and genetically. We analyzed 223 surgically resected iCCA cases, including 102 small duct type (SDT) and 121 large duct type (LDT) cases. BDTT was found in 19.6% (20/102) of SDT cases. Histological and immunohistochemical features of BDTT-positive SDT were comparable with those of conventional SDT (MUC1⁺MUC2^-MUC5AC^-MUC6^+/-CDX-2^-). BDTT-positive SDT showed female predominance and higher T factors compared with conventional SDT. SDT was associated with a significantly longer survival in iCCA. SDT patients with BDTT had significantly shorter survival than those without BDTT and survival rates similar to those of LDT patients; the presence of BDTT in SDT was an independent unfavorable prognostic factor (HR = 2.601, p = 0.006). Whole-exome sequencing analysis revealed recurrent altered gene expression: those more frequent in SDT compared with LDT (BAP1, IDH1/2, ZNF717, FGFR2, NRAS); those more frequent in LDT (KRAS, TP53, SMAD4, MUC6, CACNA1A, MLL2, MDM2, TGFBR1/2); and those found comparably in both SDT and LDT (MUC4, ARID1A, EPHA2, PIK3CA, MUC17, MAP3K4, MUC2, BRAF, NF1). Genetic landscapes were similar in SDT iCCA with and without BDTT; recurrent mutations in MUC2 and MUC17 and FGFR2 fusion genes were more frequent in BDTT-positive SDTs. PTPRK::RSPO3 fusion gene was found in one LDT case. Intraglandular papillary and tubular proliferation is a unique and rare histology of SDT. BDTT was frequently found in SDT with this pattern, and FGFR2 gene rearrangement was frequent. These results highlight the importance of evaluating BDTT in SDT, as it may be the main route of hilar extension in aggressive cases. © 2026 The Pathological Society of Great Britain and Ireland.

Prostate cancer (PC) is a prevalent malignancy, and outcomes range from indolent disease to terminal illness. Prostate-specific antigen-based diagnostics lack specificity and correlation with tumor aggressiveness, leading to overdiagnosis and undertreatment. Recent studies on cancer-associated fibroblasts (CAFs) have identified antigen presenting CAFs (apCAF), inflammatory CAFs (iCAF), and myofibrillar CAFs (myCAF) in pancreatic ductal adenocarcinoma, non-small-cell lung cancer, and breast cancer. However, their significance in PC is not yet understood. This study employs publicly available single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data combined with multiplex immunofluorescence (mIF) and digital pathology analyses of radical prostatectomy (RP) specimens from two cohorts (cohort 1, n = 235; cohort 2, n = 240) to identify CAF subtypes in localized PC and their association with biochemical recurrence (BCR) by uni- and multivariable [adjusted for Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score] Cox regression analyses. We identified myCAFs, iCAFs, and apCAFs in PC by analyzing scRNA-seq and ST data. We also identified the three CAF subtypes by mIF staining of RP specimens from cohorts 1 and 2. In prostate tumors, higher numbers of apCAFs and myCAFs were present close to malignant versus adjacent nonmalignant (AN) glands (p < 0.001, Wilcoxon test), whereas we saw no significant difference for iCAFs. In univariable Cox regression analyses, high levels of apCAFs and iCAFs were associated with increased risk of BCR in cohort 1 [apCAF: hazard ratio (HR): 1,78, p < 0.05, iCAF: HR: 1,76, p < 0.05] and confirmed in cohort 2 (apCAF: HR: 1.85, p < 0.05, iCAF: HR: 2.06, p < 0.05). In multivariable Cox regression analyses, both apCAF and iCAF levels remained independently associated with BCR after adjustment for CAPRA-S score. Our findings imply the potential of CAF subtypes as biomarkers for risk stratification in PC. © 2026 The Pathological Society of Great Britain and Ireland.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers due to late diagnosis and chemoresistance. Patient-derived organoids (PDOs) hold promise for predicting individualized drug responses, but their establishment is often constrained by the limited availability of tumor material and prior neoadjuvant treatment. Standard PDO generation relies on dissected tissue slices from the cut surface of the tumor, which may include both the invasive front, where it is postulated that more aggressive cancer cells reside, and potentially fewer viable neoplastic cells in the tumor center. This study investigated whether scraping the cut surface of the PDAC enhanced PDO establishment compared to standard tissue samples, to take advantage of potential harvesting of viable neoplastic cells from the invasive front. Tumor scrapings from 26 patients and matched tissue slices from 20 patients were collected. PDOs were successfully established from 10 tumor scrapings and eight matched tissue slices, including three neoadjuvant-treated cases. Organoid histological architecture was comparable to the surgical tumor specimens, with paired scraping PDOs and tissue slice PDOs showing genomic and transcriptomic concordance. Pharmacotyping demonstrated that scraping PDOs reliably captured patient-specific chemosensitivity, highlighting the potential for a viable alternative method to standard tissue-slice PDOs. As proliferative and treatment-resistant neoplastic cells often originate from tumor edges, increasing representation of the periphery and across the tumor may offer a more clinically relevant model of PDAC biology, improving therapeutic decision-making and patient outcomes. © 2026 The Pathological Society of Great Britain and Ireland.

The heterogeneity of breast cancer at molecular and histological levels poses significant challenges for precise diagnosis and treatment. Current molecular subtyping, crucial for guiding personalized therapy, relies on immunohistochemistry, which is often limited by intratumoral heterogeneity and potential sampling bias. While deep learning shows promise in digital pathology, existing models face computational and technical hurdles in capturing multiscale morphological features and long-range dependencies from high-resolution images, particularly in the context of tissue microarrays (TMAs). To address this, we developed and validated the pathomics breast cancer hierarchical image pyramid transformer (PBC-HIPT), a novel deep learning framework designed for automated molecular subtyping from standard H&E-stained images. The PBC-HIPT model utilizes a multilevel transformer-based architecture to hierarchically aggregate histopathological features from the cellular to the tissue scale, enabling a comprehensive analysis. We trained and validated the model on a multi-institutional cohort comprising 252 TMA cases and 46 independent whole-slide images (WSIs), assessing its performance via five-fold cross-validation on three-, four-, and five-class molecular subtyping tasks, as well as key biomarker [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), Ki-67] prediction, comparing it against several established multiple instance learning methods. PBC-HIPT demonstrated superior performance, achieving a mean accuracy of 84.3% and a mean area under the curve (AUC) of 0.91 in the clinically critical three-class subtyping task (luminal, HER2-enriched, triple-negative breast cancer), significantly outperforming baseline models. The framework excelled in biomarker prediction, attaining accuracies of 91.8% (AUC: 0.97) for ER status and 92.0% (AUC: 0.96) for PR status. It also achieved an accuracy of 73.8% (AUC: 0.81) for Ki-67 proliferation status and 84.6% (AUC: 0.85) for binary HER2 status classification. While the model showed robust intramodality generalization on TMAs (ER AUC > 0.96), its performance dropped in WSI cross-modality validation. In conclusion, the PBC-HIPT model provides a robust, automated solution for accurate molecular subtyping and biomarker assessment from H&E-stained TMAs. © 2026 The Pathological Society of Great Britain and Ireland.

Artificial intelligence (AI) and deep learning (DL) are transforming cancer research and clinical care, with histopathology playing a central role in this transformation. In colorectal cancer (CRC), the second leading cause of cancer mortality world-wide, multimodal and vision-language models (VLMs) hold particular promise for enhancing the standardisation of histopathology reporting, the understanding of disease biology, and the discovery of novel prognostic indicators. Despite the availability of guidelines and reporting templates for essential prognostic indicators, variability remains in how key features such as TNM staging or tumour deposits are assessed and reported in routine clinical practice. AI-based tools have the potential to support refined extraction of established and extended features directly from whole-slide images. In parallel, recent studies have shown that DL models applied to pathology slides and associated AI-based biomarkers can outperform traditional histopathological prognostic indicators and uncover novel parameters, including tumour-adipocyte interactions, tumour-stroma ratio, and immune cell patterns at the invasive margin. Here, we review recent advances in both domains: AI-assisted standardisation of CRC pathology reporting and AI-driven identification of novel prognostic biomarkers. We highlight the need to refine and standardise CRC reporting practices and propose that a harmonised approach combining established pathology features with AI-derived prognostic indicators could refine risk assessment and improve outcomes for CRC patients. © 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.