{"entity": "journal", "iuid": "86f1e3f4186b4f11aaf257c70bc5d616", "timestamp": "2026-08-20T21:18:47.644Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/journal/J%20Pathol%20Clin%20Res.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/journal/J%20Pathol%20Clin%20Res"}}, "title": "J Pathol Clin Res", "issn": "2056-4538", "issn-l": null, "publications_count": 2, "publications": [{"entity": "publication", "iuid": "c429155a65c2485e889f0c8355749a7e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/c429155a65c2485e889f0c8355749a7e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/c429155a65c2485e889f0c8355749a7e"}}, "title": "Validation of fibroblast activation protein and \u03b1-smooth muscle actin as prognostic biomarkers in prostate cancer through AI-assisted image analysis of dual-marker IHC.", "authors": [{"family": "S\u00e4il\u00e4", "given": "Jenni", "initials": "J", "orcid": "0000-0001-7510-3483", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/7ea2623a64b249339bcfaf11810b7249.json"}}, {"family": "Lehto", "given": "Timo-Pekka", "initials": "TP"}, {"family": "Rannikko", "given": "Antti", "initials": "A"}, {"family": "Kallioniemi", "given": "Olli", "initials": "O"}, {"family": "Mirtti", "given": "Tuomas", "initials": "T"}, {"family": "Pellinen", "given": "Teijo", "initials": "T", "orcid": "0000-0001-9652-7373", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8e73595c0cc64a68a59cd95772784859.json"}}], "type": "journal article", "published": "2026-01-00", "journal": {"title": "J Pathol Clin Res", "issn": "2056-4538", "volume": "12", "issue": "1", "pages": "e70068", "issn-l": null}, "abstract": "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 \u03b1-smooth muscle actin (\u03b1SMA) 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 \u03b1SMA, 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 \u03b1SMA 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 \u03b1SMA 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 \u03b1SMA 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.", "doi": "10.1002/2056-4538.70068", "pmid": "41410015", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC12712236"}], "notes": [], "created": "2026-08-20T06:27:10.832Z", "modified": "2026-08-20T06:27:10.944Z"}, {"entity": "publication", "iuid": "c63e2dfc19124c239f8ea1edc6858e36", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/c63e2dfc19124c239f8ea1edc6858e36.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/c63e2dfc19124c239f8ea1edc6858e36"}}, "title": "Combined epithelial marker analysis of tumour budding in stage II colorectal cancer.", "authors": [{"family": "Slik", "given": "Khadija", "initials": "K"}, {"family": "Blom", "given": "Sami", "initials": "S"}, {"family": "Turkki", "given": "Riku", "initials": "R"}, {"family": "V\u00e4lim\u00e4ki", "given": "Katja", "initials": "K"}, {"family": "Kurki", "given": "Samu", "initials": "S"}, {"family": "Mustonen", "given": "Harri", "initials": "H"}, {"family": "Haglund", "given": "Caj", "initials": "C"}, {"family": "Carp\u00e9n", "given": "Olli", "initials": "O"}, {"family": "Kallioniemi", "given": "Olli", "initials": "O"}, {"family": "Korkeila", "given": "Eija", "initials": "E"}, {"family": "Sundstr\u00f6m", "given": "Jari", "initials": "J"}, {"family": "Pellinen", "given": "Teijo", "initials": "T", "orcid": "0000-0001-9652-7373", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8e73595c0cc64a68a59cd95772784859.json"}}], "type": "journal article", "published": "2019-01-00", "journal": {"title": "J Pathol Clin Res", "issn": "2056-4538", "volume": "5", "issue": "1", "pages": "63-78", "issn-l": null}, "abstract": "Tumour budding predicts survival of stage II colorectal cancer (CRC) and has been suggested to be associated with epithelial-to-mesenchymal transition (EMT). However, the underlying molecular changes of tumour budding remain poorly understood. Here, we performed multiplex immunohistochemistry (mIHC) to phenotypically profile tumours using known EMT-associated markers: E-cadherin (adherence junctions), integrin \u03b24 (ITGB4; basement membrane), ZO-1 (tight junctions), and pan-cytokeratin. A subpopulation of patients showed high ITGB4 expression in tumour buds, and this coincided with a switch of ITGB4 localisation from the basal membrane of intact epithelium to the cytoplasm of budding cells. Digital image analysis demonstrated that tumour budding with high ITGB4 expression in tissue microarray (TMA) cores correlated with tumour budding assessed from haematoxylin and eosin (H&E) whole sections and independently predicted poor disease-specific survival in two independent stage II CRC cohorts (hazard ratio [HR] = 4.50 (95% confidence interval [CI] = 1.50-13.5), n = 232; HR = 3.52 (95% CI = 1.30-9.53), n = 72). Furthermore, digitally obtained ITGB4-high bud count in random TMA cores was better associated with survival outcome than visual tumour bud count in corresponding H&E-stained samples. In summary, the mIHC-based phenotypic profiling of human tumour tissue shows strong potential for the molecular characterisation of tumour biology and for the discovery of novel prognostic biomarkers.", "doi": "10.1002/cjp2.119", "pmid": "30358171", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC6317060"}], "notes": [], "created": "2026-08-20T06:31:18.111Z", "modified": "2026-08-20T06:31:18.173Z"}], "created": "2026-08-20T06:27:10.911Z", "modified": "2026-08-20T06:27:10.911Z"}