Journal of Pathology Clinical Research最新文献

Increasing workload combined with the shortage of pathologists is the leading cause of diagnostic errors and delays. Nonetheless, in clinical practice, pathologists often spend hours on tedious tasks such as counting mitoses and searching for lymph node micro-metastasis, which may yield unreliable results. The advent of digital pathology and the development of artificial intelligence (AI) applications (app) for image analysis have opened new possibilities for improving the efficiency and accuracy of pathologists. However, the perceived black box nature of AI has led to skepticism among many pathologists about its diagnostic capabilities, resulting in a lack of trust in AI. In addition, it is a common belief that AI applications should be limited to the areas they were trained in, which has significantly limited their generalizability. Given the homogeneous cell population of lymph nodes and overlapping of tumor morphology across different organs, we hypothesized that a lymph node metastasis detection application trained on a few organs could potentially recognize metastasis from multiple organs. We used the commercially available Visiopharm app (AI tool), initially trained on lymph node metastases from breast and colon cancer, to detect metastasis of 12 distinct types of cancer from 15 organ systems based on the analysis of 172 slides (all with corresponding immunohistochemical staining confirmation). Furthermore, by using the annotation map generated by the app as a guide, pathologists were also able to reduce the time spent searching for metastasis substantially (from 54.7 to 42.1 s per slide on average) without compromising diagnostic accuracy. With pathologists serving as the trusted gatekeepers and the development of more sophisticated image analysis applications, the use of AI can help to address the shortage of pathologists, enhance their performance and eventually improve patient care.

Basal cell carcinoma (BCC) is the most frequent malignancy in fair-skinned populations. Although curable in most cases, approximately 4% of patients develop locally advanced or metastatic disease (advBCC) requiring systemic therapy. Hedgehog pathway inhibitors (HHIs; vismodegib/sonidegib) constitute standard first-line treatment, yet individual responses vary and no histopathological biomarker predicting therapeutic outcome exists. We conducted a retrospective, multicenter analysis of 70 BCCs encompassing clinically common and advanced stages. Routine hematoxylin and eosin and Alcian blue (AB; pH 2.5) staining was evaluated using a 17-parameter, numerically encoded histopathology matrix spanning tumor morphology, stromal composition, and immune contexture. Data were mapped by unsupervised hierarchical clustering. Distinct AB staining patterns were observed: superficial and nodular BCCs typically exhibited an AB-positive peritumoral border, whereas infiltrative and sclerosing subtypes displayed a diffuse AB-positive desmoplastic stroma. The latter also correlated with advanced EADO clinical stages (correlation coefficients 0.46–0.48; p < 0.001). In a subset of 30 advBCCs obtained before or during HHI therapy, AB-positive stroma was the only parameter independently associated with shorter progression-free survival (multivariable hazard ratio = 23.8; 95% CI 4.02–141.3; p < 0.001). Established clinical or histological features failed to associate with outcome. Our findings identify diffuse AB-positive stroma as a readily detectable feature of histologically aggressive BCC and as a candidate biomarker associated with progression under HHI treatment. Because AB staining is routine, inexpensive, and easily standardized, this phenotype represents an immediately implementable readout for prospective validation and a potential link between extracellular-matrix remodeling and therapy resistance in BCC.

The aim of this study was to evaluate the predictive value of homologous recombination deficiency scores for therapeutic efficacy in prostate cancer across various disease stages under different regimens. We collected tissue samples from 167 prostate cancer patients and performed genomic sequencing to assess homologous recombination deficiency scores. Among them, 67 patients with localized disease received radical prostatectomy, and 100 patients with metastatic disease received androgen receptor target inhibitor treatment. We examined the predictive value of homologous recombination deficiency scores in forecasting the therapeutic efficacy of standard-of-care treatment of prostate cancer under different disease stages. Among patients who underwent radical prostatectomy, those with higher homologous recombination deficiency scores experienced notably shorter biochemical progression-free survival and overall survival than those with lower scores (median biochemical progression-free survival: 50.6 versus 148.4 months, p = 0.037; median overall survival: 149.0 months versus not reached, p = 0.0018). In patients receiving androgen receptor pathway inhibitor treatment, men with higher homologous recombination deficiency scores exhibited reduced prostate-specific antigen progression-free survival, radiographic progression-free survival, and overall survival compared to the lower score group at the metastatic castration-resistant stage (median prostate-specific antigen progression-free survival: 8.17 versus 24.17 months, p = 0.032; median radiographic progression-free survival: 11.8 versus 24.8 months, p = 0.015; median overall survival: 36.5 months versus not reached, p = 0.056) and a deteriorating trend in the metastatic hormone-sensitive stage. Molecular characterization showed that higher homologous recombination deficiency scores were associated with higher alteration rates in genes such as BRCA2, CDK12, MYC, and PTEN. This study reveals that higher homologous recombination deficiency scores are associated with unfavorable treatment efficacy of radical prostatectomy in localized prostate cancer and of androgen receptor target inhibitor treatment in metastatic prostate cancer.

Expression of the β-adrenergic receptors' family has been associated with survival outcomes in multiple different cancer types, showing their potential to act as prognostic factors. No previous work has evaluated these receptors in relation to survival in oesophageal adenocarcinoma. We sought to analyse the expression of β₁ and β₂ adrenergic receptors in oesophageal adenocarcinoma and their association with survival outcomes. The expression of β₁ and β₂ adrenergic receptors was evaluated in a cohort of oesophageal adenocarcinoma patients treated with neo-adjuvant chemotherapy prior to surgical resection at the Northern Ireland Cancer Centre between 2004 and 2012. Immunohistochemical staining for was assessed using a Tissue Microarray with triplicate tumour cores. Cox proportional hazards regression was used to investigate the association of β₁ and β₂ adrenergic receptor expression with survival outcomes, including adjustment for clinical factors. In total, 115 and 122 patients were assessed for β₁ and β₂ adrenergic receptor expression, respectively. In adjusted analysis, high β₂ adrenergic receptor expression was associated with improved recurrence-free [hazard ratio [HR] 0.57, 95% CI 0.33–0.97] and overall survival (HR 0.53, 95% CI 0.30–0.94) with restriction to gastro-oesophageal junction tumours showing a stronger association with improved overall survival (HR 0.27, 95% CI 0.13–0.59). No significant association was observed for β₁ adrenergic receptor expression and any survival outcome. In summary, we found that higher expression of the β₂ adrenergic receptor was associated with a significant improvement in survival in oesophageal adenocarcinoma patients, and gastro-oesophageal junction tumours in particular, treated with neoadjuvant chemotherapy followed by surgical resection.

The Immunoscore (IS) quantifies the immune contexture of colorectal cancer (CRC) by measuring CD3⁺ and CD8⁺ T-cell densities in the tumour centre and invasive margin, providing superior prognostic performance compared with TNM staging and mismatch-repair (MMR) status alone. Large international cohort studies have validated its ability to predict benefit from adjuvant chemotherapy in stage III colon cancer. More recently, Immunoscore-IC – a refined version that incorporates PD-L1⁺ cell density and spatial interactions – has emerged as the first biomarker capable of identifying the subset of patients with proficient-MMR (pMMR/MSS) metastatic CRC who derive significant benefit from immune checkpoint inhibitors. Despite these advances, technical requirements, biological limitations, and reliance on retrospective data continue to hinder widespread clinical adoption. Addressing some of these challenges could enhance its utility and facilitate broader integration into routine pathology practice. In this commentary, we place landmark IS publications within the evolving research landscape, including papers published in The Journal of Pathology Clinical Research; integrate findings from recent international validation cohorts and adjuvant trials; and highlight the growing evidence supporting IS as a robust prognostic tool with clear predictive implications for both chemotherapy and immunotherapy in CRC.

Adult T-cell leukemia/lymphoma (ATLL) is a distinct type of peripheral T-cell lymphoma (PTCL) driven by human T-lymphotropic virus type I (HTLV-1)–infected T cells, but diagnosis can be confounded by histological overlap with non-ATLL PTCL. While molecular testing is the diagnostic gold standard in endemic areas, HTLV-1/2 serology is often used as a surrogate in nonendemic settings, yet its accuracy and limitations remain unclear. We retrospectively analyzed 881 PTCL cases over 25 years at two tertiary referral hospitals in Taiwan, where HTLV-1 is nonendemic. Serology was available in 48.2% of cases. Molecular confirmation was performed using HBZ in situ hybridization and tax quantitative polymerase chain reaction. Among the 44 seropositive PTCL patients with tissue available, 37 were diagnosed and molecularly confirmed as ATLL. Of the seven initially diagnosed as non-ATLL PTCL, three were reclassified as ATLL, while four showed no molecular evidence, including three likely false seropositives with borderline signal-to-cutoff (S/CO) values in serology assay and T follicular helper cell phenotype. In seropositive PTCL, clinicopathologic interpretation without molecular testing yielded 100% positive predictive value, 93% sensitivity, and 93% accuracy, compared with 91% positive predictive value by serology alone. In addition, retrospective molecular screening in 59 PTCL without prior serologic data revealed one case of ATLL that had initially been overlooked. In conclusion, our findings support routine HTLV-1/2 serologic testing in all newly diagnosed PTCLs. However, interpretation should be guided by clinicopathological correlation and serology index values. Borderline index results warrant molecular confirmation.

Prostate cancer (PCa) lacks reliable and accurate tissue-based biomarkers to support prognostic stratification and clinical treatment decisions. Current diagnostic assessment, including Gleason grading, has limitations such as interobserver variability and insufficient granularity for disease aggressiveness. Fibroblast activation protein (FAP) and α-smooth muscle actin (αSMA) have emerged as putative stromal biomarkers, but their prognostic value in localised PCa has not been validated at scale. In this study, we developed a novel artificial intelligence (AI)-augmented image analysis pipeline tailored for dual-marker immunohistochemistry of FAP and αSMA, enabling automated, tissue compartment-specific quantification of biomarker expression. This deep learning model was trained and validated using digitised high-resolution whole-slide images of tissue microarrays from three prostatectomy cohorts, comprising 4,097 cores from 835 patients with comprehensive clinical follow-up data. The AI pipeline demonstrated high accuracy in detecting epithelial, stromal, and immune compartments, as well as in quantifying FAP and αSMA signals. We validated stromal FAP as a robust prognostic marker consistently associated with adverse clinical outcomes, including earlier biochemical recurrence, metastasis, and cancer-specific death. Epithelial FAP and stromal αSMA showed additional prognostic associations in selected analyses, particularly in MRI-visible tumours. Our findings reinforce the biological and clinical relevance of stromal FAP in the prostate tumour microenvironment. By enabling standardised and scalable biomarker quantification, our newly developed AI-assisted workflow advances the clinical utility of FAP and αSMA and demonstrates the power of integrating digital pathology with biomarker quantification. This study represents a critical step toward implementing stromal biomarkers in routine PCa diagnostics and underscores the potential of AI-enhanced histopathology in advancing precision oncology.

Despite significant progress in oncology research, pancreatic cancer remains inherently difficult to treat, and the mechanisms underlying therapeutic resistance remain unresolved. Decorin (DCN), a member of the family of small leucine-rich proteoglycans, has emerged as a versatile actor in various malignant diseases. The aim of this study was to further explore the potential clinical significance of DCN in pancreatic cancer, both regarding its dynamics in serum during chemotherapy and its compartmental and cellular distribution in tumour tissue. To this end, repeated on-treatment levels of soluble DCN were measured using proximity extension assay in 124 patients enrolled in a prospective, observational clinical study, inviting patients diagnosed with pancreatic or other pancreatobiliary-type periampullary adenocarcinoma eligible for adjuvant (n = 30) or first-line palliative (n = 94) chemotherapy. Multiplexed immunofluorescence was applied to map DCN and the associated immune landscape in resected tumours. The results showed increasing levels of DCN in serum after initiation of chemotherapy in palliative, but not in adjuvant, patients. A higher rate of change of serum DCN was an independent adverse prognostic factor in both treatment settings. There was no significant association between systemic levels and local DCN expression. Varying expression of DCN was denoted in both tumour cells, immune cells and stroma, but the prognostic significance was mainly assigned to its expression in B cells. In particular, a higher percentage of DCN positive B cells, overall and in interaction with tumour cells, were independent predictors of shorter survival. In summary, this study is the first to demonstrate the potential clinical utility of on-treatment monitoring of systemic DCN in patients with pancreatic cancer. The findings also provide interesting leads for further research into how DCN may interact with the immune microenvironment to promote tumour development and the emergence of chemoresistance.

Although adenoid ameloblastoma (AA) has recently been included in the WHO classification as a separate tumour type, its clinical, histological, immunohistochemical, and molecular similarities to dentinogenic ghost cell tumour (DGCT) raise questions about the current classification system. The aim of this study was to investigate the epigenetic similarity between AA and DGCT. A total of 35 odontogenic tumours consisting of 6 types, including 3 AAs and 4 DGCTs, were collected for this study. DNA methylation analysis was performed using the Infinium MethylationEPIC v2.0 BeadChip. Unsupervised clustering analysis was performed using t-distributed stochastic neighbour embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). No differentially methylated regions were identified between AA and DGCT. Both t-SNE and UMAP plots demonstrated that AAs clustered together with DGCTs, clearly separated from the other types of odontogenic tumour. Within the AA and DGCT methylation class, no subclasses were identified by the presence of the so-called AA-like histology, characterised by cribriform architecture and duct-like structures. These findings suggest a clear epigenetic similarity between AA and DGCT, further supporting the notion that the two tumours represent a spectrum of the same entity and may be better classified on a molecular basis as ‘WNT pathway-altered odontogenic tumours’.

This study characterizes a novel disease pattern of membranous nephropathy (MN) that exhibits overlapping clinicopathological features with minimal change disease (MCD), termed ‘MCD-like MN’. Patients with histologically confirmed MN showing sparse and segmental subepithelial electron-dense deposits (EDD) but clinically resembling MCD were enrolled, alongside age- and gender-matched classic MCD and MN controls. Clinicopathological parameters were compared across groups. MN-associated antigens and MCD-related podocyte antigens were analyzed in renal tissues and serum. Among 107 archival MCD cases re-evaluated, 16 were reclassified as MCD-like MN based on EDD presence. Pathologically, these cases demonstrated IgG deposition in podocytes (62.5%), significantly higher than classic MCD (6.2%), but lacked complement activation and showed milder interstitial fibrosis compared to MN. Clinically, MCD-like MN patients presented a shorter disease duration and higher complete remission rates compared to MN (p < 0.01), resembling classical MCD. Additionally, they had lower serum creatinine levels than MCD patients (p < 0.01), which were more similar to MN levels. Furthermore, MN-associated antigens were detected in MCD-like MN cases and some of the serum antibodies' levels were increased, suggesting shared pathogenesis with MN, albeit with distinct immune features. Besides, spectrometry counts of podocyte antigens were not increased, and serum anti-podocyte antibodies were either absent or not elevated compared to MCD patients, ruling out antibody-mediated podocytopathy. Collectively, MCD-like MN represents a distinct MN subtype with atypical MCD-like clinicopathological features, likely driven by a unique immune mechanism divergent from both classic MN and MCD.