Journal of Clinical Pathology最新文献

{"title":"Expert diagnostic reasoning in breast pathology: insights from international masterclass question-and-answer sessions.","authors":"Emad A Rakha, Cecily Quinn, Abeer M Shaaban, Elena Provenzano, Laura C Collins, Hannah Wen, Edi Brogi, Wentao Yang, Gary M K Tse, Areeg Abbas, Jennifer Baldwin, Basel Altrabulsi, Gabor Cserni, Maria P Foschini, Stephen B Fox, Sarah E Pinder, Stuart Schnitt, Ian O Ellis, Puay Hoon Tan","doi":"10.1136/jcp-2026-210966","DOIUrl":"https://doi.org/10.1136/jcp-2026-210966","url":null,"abstract":"<p><strong>Aims: </strong>Standardised diagnostic criteria in breast pathology primarily guide classification rather than real-world decision-making in borderline or context-dependent scenarios. This study evaluated question-and-answer data from international masterclass cohorts to characterise real-world diagnostic uncertainties, quantify cognitive domain distributions and detail expert decision-making frameworks.</p><p><strong>Methods: </strong>We analysed a structured dataset of 430 attendee questions collected across five international online Breast Pathology Masterclasses (2022-2026), each attended by over 500 participants. Questions were categorised into thematic and cognitive domains by the lead investigator, followed by a collaborative co-author audit to establish classification consensus. Faculty responses were evaluated to assess reasoning patterns, consensus points and areas of diagnostic variation.</p><p><strong>Results: </strong>Diagnostic uncertainty clustered within specific recurring clinical challenges, with borderline and grey-zone lesions constituting a primary focus. Threshold-based queries regarding diagnostic boundaries formed the single largest cognitive domain (40%), rather than queries seeking basic entity definitions. Other major clinical domains included biomarker interpretation, radiology-pathology discordance management and core biopsy sampling limitations. Analysis of faculty responses identified a recurring morphology-first, context-integrated and risk-informed approach to diagnostic decision-making. While consensus on foundational diagnostic principles was high, minor variations occurred in setting specific quantitative thresholds and framing diagnostic uncertainty in pathology reports.</p><p><strong>Conclusions: </strong>These exploratory findings indicate that practical challenges in diagnostic breast pathology frequently arise from boundary determination and contextual ambiguity rather than gaps in established disease classification schemes. Although expert judgement and confidence in managing diagnostic uncertainty develop substantially through experience, educational initiatives may complement experiential learning by making threshold calibration, risk communication and context-dependent reasoning more explicit.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidental detection of <i>JAK2</i> V617F mutations in next-generation sequencing analysis of solid tumours: a guide to further workup.","authors":"Pranav Pramod Patwardhan, John M Skaugen, Somak Roy, Nidhi Aggarwal","doi":"10.1136/jcp-2026-210854","DOIUrl":"https://doi.org/10.1136/jcp-2026-210854","url":null,"abstract":"<p><strong>Objectives: </strong>Genomic alterations related to hematopoietic elements may be seen in solid tumour next-generation sequencing (NGS) panels. Here, we report the incidental finding of <i>JAK2</i> V617F mutations in NGS performed on solid tumours.</p><p><strong>Methods: </strong>Cases where <i>JAK2</i> V617F mutation was detected on solid tumour NGS performed in-house between 2016 and 2021 were analysed.</p><p><strong>Results: </strong>12 cases (0.2%) of solid tumour NGS testing that identified <i>JAK2</i> V617F were reviewed. The mean age of the patient population was 73.8 years (range: 53-87 years). The diagnosis included lung carcinoma ((n=9); adenocarcinoma (n=7), non-small cell carcinoma of the lung (n=1), metastatic adenocarcinoma, favour lung primary (n=1)), renal cell carcinoma-unclassified (1), undifferentiated malignant neoplasm (1) and metastatic poorly differentiated CK7 positive carcinoma (1).The variant allele frequency (VAF) for the <i>JAK2</i> V617F mutation ranged from 2.4 to 18.4% (mean: 8.2%) and was consistently and statistically significantly different from the VAF observed for tumour-specific genomic variants based on Wilcoxon test. On further work-up, 8/12 patients had clinical history or laboratory evidence of an underlying clonal myeloid process, 6/12 patients had evidence of a <i>JAK2</i> V617F positive myeloid neoplasm while 2/12 had evidence of pre-treatment thrombocytosis. The remaining two patients had no prior history of a myeloid neoplasm or documented abnormal blood counts.</p><p><strong>Conclusion: </strong>A work-up for potential haematological disease should be undertaken when an alteration associated with haematological neoplasms is identified in solid tumour NGS panels, particularly when the VAF is different compared to the VAF of other tumour-associated variants.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical translation of gut microbiome biomarkers and host immune dysregulation in colorectal neoplasia: a systematic review with Clinical and Molecular Pathology Prioritisation.","authors":"Gregorio Rangel, Pawana Panomket, Marutpong Panya, Chanwit Maneenin, Patitta Sinthuchao, Siriporn Seawsakul, Naowarat Maneenin, Chananya Jirapornkul, Surasak Wanram","doi":"10.1136/jcp-2026-210946","DOIUrl":"https://doi.org/10.1136/jcp-2026-210946","url":null,"abstract":"<p><strong>Aims: </strong>Gut microbiome signatures are promising non-invasive biomarkers for colorectal neoplasia, but clinical translation is limited by heterogeneity in populations, platforms, validation and comparator tests. We evaluated microbiome-based biomarkers and microbiome-host immune associations, emphasising applicability.</p><p><strong>Methods: </strong>We systematically reviewed human studies published from 1 January 2020 to 15 July 2026 evaluating gut microbiome-associated biomarkers in colorectal adenoma or colorectal cancer. Diagnostic studies were summarised by biomarker, target lesion, comparator, validation and performance, with Quality Assessment of Diagnostic Accuracy Studies-2 appraisal. A predefined seven-domain framework provided secondary translational prioritisation. Mechanistic and prognostic microbiome-immune studies were synthesised separately.</p><p><strong>Results: </strong>Recurrent signals included <i>Fusobacterium nucleatum</i>, multispecies panels, microbial gene and single-nucleotide-variant classifiers, multikingdom signatures and metabolite profiles. Some integrated models combining microbial biomarkers with faecal immunochemical testing, methylated DNA, clinical variables or metabolomics showed improved performance measures, but benefits were inconsistent. External validation was limited. Microbiome-immune studies linked microbial profiles with immune-related expression, immune-cell infiltration and treatment-response phenotypes without establishing improved screening accuracy.</p><p><strong>Conclusions: </strong>Microbiome biomarkers show promise for colorectal neoplasia detection, but evidence does not establish universal multimodal superiority. Routine translation requires prospective validation, analytical standardisation, reproducibility, cost-effectiveness and demonstrated incremental utility.</p><p><strong>Prospero registration number: </strong>CRD420261457983.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MILGDF: a multi-task, instance-level supervised model for oral squamous cell carcinoma integrating local-global attention and dynamic decision fusion.","authors":"Chen-Xi Li, Yan Chen, Liang-Hui Xu, Cheng Chen, Chen Chen, Xiao-Yi Lv, Zhong-Cheng Gong","doi":"10.1136/jcp-2026-210630","DOIUrl":"10.1136/jcp-2026-210630","url":null,"abstract":"<p><strong>Aims: </strong>This research was designed to establish an innovative diagnostic strategy employing whole-slide imaging (WSI) technology to address the diagnostic difficulties arising from the intricate histological architecture and morphological diversity observed in oral squamous cell carcinoma (OSCC). The developed methodology enables precise early identification and histomorphology-driven prognostic stratification of malignant lesions, thereby improving clinical management and patient prognosis.</p><p><strong>Methods: </strong>We propose a multi-task learning framework that combines local-global attention mechanisms with adaptive decision fusion (MILGDF). This model utilises instance-level category-specific attention to enhance feature extraction efficacy while overcoming the limitations inherent in traditional bag-level attention methods. An adaptive weighting system was incorporated to dynamically adjust the contribution of local and global features, ensuring optimal performance in dual tasks of OSCC diagnosis and prognostic stratification.</p><p><strong>Results: </strong>Rigorous validation on the HIDOC and TCGA-OSCC datasets revealed the predictive performance of our model. The MILGDF framework attained an area under the curve of 0.952 (accuracy: 0.909) on HIDOC and 0.745 (accuracy: 0.725) on TCGA-OSCC. Statistical comparison using DeLong's test and paired t-tests demonstrated significantly superior performance (p<0.05) over existing comparative models in both diagnostic classification and prognostic stratification.</p><p><strong>Conclusions: </strong>Our findings demonstrate that the MILGDF model represents an improvement in whole-slide image-based OSCC analysis, delivering enhanced diagnostic accuracy and prognostic reliability relative to current approaches. The framework's consistent performance highlights its computational benchmark value and preliminary translational potential for early OSCC detection and auxiliary treatment planning, serving as a valuable asset for prognostic evaluation and therapeutic strategy formulation.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"688-695"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148317463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeted transcriptome profiling of oral cavity squamous cell carcinoma and histologic grade-associated gene expression patterns.","authors":"Brittany Ruschkowski, Bryan Lo, Jason K Wasserman","doi":"10.1136/jcp-2025-210614","DOIUrl":"10.1136/jcp-2025-210614","url":null,"abstract":"<p><strong>Aims: </strong>To characterise gene expression differences between oral cavity squamous cell carcinoma (OSCC) and non-neoplastic oral mucosa using targeted transcriptome profiling and to evaluate gene expression patterns associated with tumour differentiation.</p><p><strong>Methods: </strong>Formalin-fixed, paraffin-embedded tissue from 16 resected OSCCs (3 well differentiated, 9 moderately differentiated and 4 poorly differentiated) and 7 non-neoplastic oral mucosa samples was analysed. RNA was isolated from microdissected tissue and profiled using a targeted next-generation sequencing assay. Differential gene expression and pathway enrichment analyses were performed, including comparisons across histologic grades.</p><p><strong>Results: </strong>OSCC demonstrated broad transcriptomic differences compared with non-neoplastic oral mucosa, with enrichment of pathways related to extracellular matrix remodelling, cell adhesion, immune regulation, oncogenic signalling and cellular metabolism. Grade-stratified analyses identified additional differences involving epithelial differentiation, immune response, lipid metabolism and oxidative phosphorylation pathways.</p><p><strong>Conclusions: </strong>OSCC exhibits broad transcriptomic dysregulation involving extracellular matrix remodelling, cell adhesion, immune signalling, oncogenic signalling and cellular metabolism. Grade-stratified findings demonstrate molecular differences associated with tumour differentiation but require validation in larger independent cohorts. These findings may inform future studies of biomarkers and biologically relevant pathways in OSCC.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"678-687"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148712632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of polymerase chain reaction-indexed next-generation sequencing assay on the Illumina iSeq 100 platform for MPL exon 10 mutation detection: a robust alternative to Sanger sequencing.","authors":"Dilys Lau, Janice Yen Qi Loo, Sau-Yoke Ng, Dan Thu Van, Wei Cheng David Kuek, Chean Nee Chai, Joanna Kia Min Tan, Chun Kiat Lee, Benedict Junrong Yan, Tim Hon Man Chan","doi":"10.1136/jcp-2025-210226","DOIUrl":"10.1136/jcp-2025-210226","url":null,"abstract":"","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"717-719"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum versus lithium-heparin plasma for lipid testing: matrix-related bias and calculated LDL-C classification.","authors":"Nejd Kouched, Lobna Jmal, Khedija Zaouche, Amel Dhieb, Raida Guidara, Aouatef Jmal","doi":"10.1136/jcp-2026-210814","DOIUrl":"10.1136/jcp-2026-210814","url":null,"abstract":"<p><strong>Aims: </strong>To assess whether serum and lithium-heparin plasma can be used interchangeably for routine lipid testing and whether matrix-related bias affects calculated low-density lipoprotein (LDL)-cholesterol (LDL-C) classification near clinical decision thresholds.</p><p><strong>Methods: </strong>This prospective paired-sample method-comparison study included 104 fasting adult ambulatory patients referred for routine lipid testing. Serum and lithium-heparin plasma were collected during the same venipuncture and analysed on a Cobas 6000 c501 analyser. LDL-C was calculated using the Friedewald equation when triglycerides (TGs) were <4.5 mmol/L (n=103). Agreement was assessed using paired testing, Passing-Bablok regression, Bland-Altman analysis, intraclass correlation coefficients (ICCs), Cohen kappa and McNemar testing at selected decision thresholds. Interchangeability was interpreted using analytical bias, measurement uncertainty, limits of agreement and threshold discordance.</p><p><strong>Results: </strong>Lithium-heparin plasma yielded lower total cholesterol and calculated LDL-C than serum, with mean biases (plasma - serum) of -0.15 mmol/L (-3.06%) and -0.14 mmol/L (-4.77%), respectively. TGs and HDL-cholesterol did not differ significantly. Serum-plasma correlations and ICCs were high. LDL-C classification was discordant in 3/103, 2/103 and 7/103 paired samples at thresholds of 1.4, 1.8 and 2.6 mmol/L, respectively; all discordances classified plasma below and serum above the threshold.</p><p><strong>Conclusions: </strong>Under these local analytical and pre-analytical conditions, the mean bias was modest but directional and sufficient to alter calculated LDL-C classification in a minority of samples near decision thresholds. Laboratories using lithium-heparin plasma for lipid testing should verify matrix agreement locally, document the specimen matrix and avoid alternating serum and plasma during longitudinal monitoring unless equivalence has been demonstrated.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"713-716"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13638271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148630453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adapt or Become Irrelevant: the Pathologist as the new Diagnostic Architect.","authors":"Mariano De Socarraz, Jochen K Lennerz","doi":"10.1136/jcp-2026-210826","DOIUrl":"10.1136/jcp-2026-210826","url":null,"abstract":"<p><strong>Aims: </strong>Pathology is undergoing a paradigm shift as diagnostics become increasingly multimodal and computational. Yet legacy structures, incentives and workflows have not yet evolved. This misalignment created systemic vulnerabilities that threaten diagnostic precision and the profession's future. Here, we establish a framework for the cognitive integration of rapidly evolving diagnostic innovations in pathology.</p><p><strong>Methods: </strong>To characterise critical inflection points and opportunities for conceptual transformation we mapped seven diagnostic scenarios: programmed death ligand 1 testing, next-generation sequencing reimbursement constraints, artificial intelligence-based triaging, integrated diagnostics, germline (pharmacogenomics) testing, trial design and emerging assurance frameworks outside traditional pathology. Our synthesis draws from peer-reviewed literature, policy analysis, institutional data, and qualitative insights to highlight where pathologists can elevate their role as integrator of clinical, morphological and molecular knowledge.</p><p><strong>Results: </strong>Across the seven scenarios, common patterns emerged: unintentional consequences of well-intended initiatives, commoditisation, unsustainable economic models, underleveraged efficiency gains, misaligned infrastructure, missed clinical opportunity, regulatory rigidity and erosion of diagnostic accountability. These patterns signal not only operational gaps but a cognitive crisis. A failure by pathologists to position themselves as more than an interpretative service. Pathologists must assume the role of diagnostic architects, synthesising multimodal data into structured, clinically actionable insights and engaging more directly with physicians, those organising clinical trials and patients as partners in precision medicine.</p><p><strong>Conclusions: </strong>The emerging competencies of diagnostic synthesis, systems thinking, digital fluency, and strategic presence in value-based care offer a mindset guide for both personal growth and anchoring the discipline's next transformational step to improve patient care.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"659-668"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148793768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence in Digital Pathology for Prostate Cancer Detection: FDA Clearance and Real-World Implementation.","authors":"Quinn Rainer, Yue Sun, Monika Vyas, Pavel Kopach, Dibson Gondim, Vidarshi Muthukumarana, Harshwardhan Thaker, Vikram Deshpande","doi":"10.1136/jcp-2026-210643","DOIUrl":"10.1136/jcp-2026-210643","url":null,"abstract":"<p><p>Artificial intelligence (AI) has emerged as a promising adjunct in surgical pathology, particularly in the diagnosis of prostate cancer, where variability in interpretation or missed cancer foci can significantly affect patient management. This review provides a concise, practice-oriented overview of the two Food and Drug Administration (FDA)-cleared AI tools for prostate biopsy interpretation: Paige Prostate Detect and Ibex Prostate Detect (formerly Galen Second Read). We examine their regulatory indications, diagnostic performance and integration requirements within digital pathology workflows. Emphasis is placed on real-world implementation considerations, including variation in technical inputs and the level at which data are analysed. We highlight less obvious risks, such as domain shift and the potential for inequitable performance in under-represented patient populations. Trade-offs between sensitivity and specificity, particularly in the context of AI-assisted pathologist assessments, are discussed using data from clinical validation studies. We also consider the variable impact of AI tools depending on the user's expertise, noting enhanced diagnostic consistency for general pathologists. By highlighting both the opportunities and limitations of integrating AI into routine practice, we aim to provide pathologists with a pragmatic understanding of how these systems may influence diagnostic workflows and to emphasise that FDA clearance must be complemented by local validation as well as ongoing performance monitoring to ensure safe and equitable deployment.</p>","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"669-677"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148470949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reporting of both positive and negative concordance is necessary to recognise and investigate bias in digital algorithms.","authors":"Megan L Troxell, Cansu Karakas, Maggie M Lam, Alex M Dussaq, Gregory Bean, Kimberly H Allison","doi":"10.1136/jcp-2026-210804","DOIUrl":"10.1136/jcp-2026-210804","url":null,"abstract":"","PeriodicalId":15391,"journal":{"name":"Journal of Clinical Pathology","volume":" ","pages":"720"},"PeriodicalIF":2.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147987672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}