Journal of Pathology Clinical Research最新文献

{"title":"Impact of tissue staining and scanner variation on the performance of pathology foundation models: a study of sarcomas and their mimics","authors":"Binghao Chai,&nbsp;Jianan Chen,&nbsp;Paul Cool,&nbsp;Fatine Oumlil,&nbsp;Anna Tollitt,&nbsp;David F Steiner,&nbsp;Tapabrata Chakraborti,&nbsp;Adrienne M Flanagan","doi":"10.1002/2056-4538.70080","DOIUrl":"10.1002/2056-4538.70080","url":null,"abstract":"<p>Histopathological analysis is considered the gold standard for the diagnosis and prognostication of cancer. Recent advances in AI, driven by large-scale digitisation and pan-cancer foundation models, are opening new opportunities for clinical integration. However, it remains unclear how robust these foundation models are to real-world sources of variability, particularly in H&amp;E staining and scanners produced by different manufacturers. In this study, we use soft tissue tumours, a rare and morphologically diverse tumour type, as a challenging test case to systematically investigate the colour-related robustness and generalisability of seven AI models. Controlled staining and scanning experiments were utilised to assess model performance across diverse real-world data sources. Foundation models, particularly UNI-v2, Virchow and TITAN, demonstrated encouraging robustness to staining and scanning variation, particularly when a small number of stain-varied slides were included in the training loop, highlighting their potential as adaptable and data-efficient tools for real-world digital pathology workflows.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12932120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147285733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148088558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148091231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer-associated fibroblasts are associated with CD8+ T cell depletion and poor prognosis in colorectal adenocarcinoma: a multi-omics and machine learning analysis","authors":"Myungsun Shim,&nbsp;One-Zoong Kim,&nbsp;Byoung Kwan Son,&nbsp;Jung Ki Jo,&nbsp;Seung Wook Lee,&nbsp;Hong Sang Moon,&nbsp;Hyung Suk Kim,&nbsp;Mi Jung Kwon,&nbsp;Sung Hak Lee,&nbsp;Yung-Kyun Noh,&nbsp;Kyueng-Whan Min","doi":"10.1002/2056-4538.70076","DOIUrl":"10.1002/2056-4538.70076","url":null,"abstract":"<p>Fibroblastic proliferation in various tumor microenvironments influences cancer survival through complex interactions with diverse immune responses. This study investigated the impact of histologically unique activated cancer-associated fibroblasts (aCAFs) on survival outcomes and immune responses and examined their association with various pathophysiological mechanisms. We analyzed a total of 1,024 colorectal adenocarcinoma patients from two cohorts. aCAFs were evaluated based on hematoxylin and eosin-stained whole-slide images, and their associations with clinicopathological features, immune cell infiltration, and survival were assessed. We developed a machine learning-based survival prediction model incorporating aCAFs and clinicopathologic parameters. Additionally, we performed differential gene expression analysis, functional enrichment analyses, and <i>in vitro</i> drug screening of aCAF-related genes. aCAFs were associated with advanced T stage, lymphovascular invasion, perineural invasion, and decreased CD8+ and CD4+ T cell infiltration. aCAFs were also associated with worse overall and disease-free survival in both univariate and multivariate analyses. Functional enrichment analysis revealed that aCAF-related genes were implicated in immunosuppressive signaling, oxidative stress regulation, and tumor progression pathways. Survival prediction models based on machine learning and incorporating aCAFs demonstrated superior prognostic accuracy for overall survival and disease-free survival compared to models excluding aCAFs. Our analysis of aCAFs' association with immune responses through bioinformatics-based genomic analysis and machine learning provides a foundation for future research in CRC patients.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12928035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147272511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148086855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expression of Nectin-4 and Trop-2 in upper tract urothelial carcinoma: implications for biomarker-driven antibody-drug conjugate therapy","authors":"Ping Shi,&nbsp;Qingqing Wu,&nbsp;Yong Zhang,&nbsp;Tiane Chen,&nbsp;Joshua I. Warrick,&nbsp;David J. DeGraff,&nbsp;Jay D. Raman,&nbsp;Guoli Chen","doi":"10.1002/2056-4538.70077","DOIUrl":"10.1002/2056-4538.70077","url":null,"abstract":"<p>Recent advancements in antibody-drug conjugates, including FDA-approved therapies targeting Nectin-4 and Trop-2, have transformed the cancer treatment landscape, including upper tract urothelial carcinoma (UTUC). However, varied treatment effects and drug-associated adverse effects raise the question of whether patients should be selected based on a biomarker study to achieve optimal outcomes. A better understanding of the patterns and clinicopathological significance of Nectin-4 and Trop-2 expression in UTUC remains to be achieved. We generated tissue microarrays (TMAs) with 120 UTUC specimens from patients who underwent nephroureterectomy at our institution and evaluated the expression of Nectin-4 and Trop-2 in tumor and non-tumor tissue. Nectin-4 expression was significantly higher in both invasive and noninvasive high-grade UTUC compared to noninvasive low-grade tumors. In contrast, Trop-2 expression did not vary significantly between noninvasive low-grade and high-grade tumors. When analyzed by stage, Nectin-4 expression was significantly elevated in tumors of higher stages than in early-stage tumors, similar to Trop-2 expression. Although both Nectin-4 and Trop-2 were broadly expressed in tumor and adjacent non-tumor urothelium, a subset of patients demonstrated low expression in non-tumor tissue but high expression in tumor tissue. Nectin-4 expression, but not Trop-2, was significantly correlated with the Ki-67 index, indicating that they may have different roles in tumor proliferation. The differential expression of Nectin-4 and Trop-2 by tumor grade and stage highlights their potential relevance in guiding targeted therapy for UTUC. Notably, a subset of patients exhibits high expression in tumor tissue, accompanied by low expression in adjacent non-tumor urothelium, suggesting a favorable therapeutic index for antibody-drug conjugate therapy. These findings support the need for further biomarker-driven studies to optimize patient selection and treatment outcomes.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12900618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146182913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 2","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148074515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148086021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI for pathologists: a universal lymph node metastasis detection app that enhances efficiency while preserving diagnostic accuracy","authors":"Jennifer Vazzano,&nbsp;Bindu Challa,&nbsp;Vidya Arole,&nbsp;Konstantin Shilo,&nbsp;Sarah Reuss,&nbsp;Peter Kobalka,&nbsp;Swati Satturwar,&nbsp;Juan Xie,&nbsp;Dongjun Chung,&nbsp;Saba Shafi,&nbsp;David Kellough,&nbsp;Erin Palermini,&nbsp;Zaibo Li,&nbsp;Wei Chen,&nbsp;Anil Parwani,&nbsp;Shaoli Sun","doi":"10.1002/2056-4538.70073","DOIUrl":"10.1002/2056-4538.70073","url":null,"abstract":"<p>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.</p>","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12820412/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146012867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48612,"journal":{"name":"Journal of Pathology Clinical Research","volume":"12 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148081337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}