{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T04:18:13Z","timestamp":1782274693122,"version":"3.54.5"},"reference-count":93,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T00:00:00Z","timestamp":1737590400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","award":["DRCNPG-May21_100001"],"award-info":[{"award-number":["DRCNPG-May21_100001"]}],"id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","award":["P500PM_217647 \/ 1"],"award-info":[{"award-number":["P500PM_217647 \/ 1"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Institute of Cancer Research; Data Science Initiative"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>The applications of artificial intelligence (AI) and deep learning (DL) are leading to significant advances in cancer research, particularly in analysing histopathology images for prognostic and treatment-predictive insights. However, effective translation of these computational methods requires computational researchers to have at least a basic understanding of histopathology. In this work, we aim to bridge that gap by introducing essential histopathology concepts to support AI developers in their research. We cover the defining features of key cell types, including epithelial, stromal, and immune cells. The concepts of malignancy, precursor lesions, and the tumour microenvironment (TME) are discussed and illustrated. To enhance understanding, we also introduce foundational histopathology techniques, such as conventional staining with hematoxylin and eosin (HE), antibody staining by immunohistochemistry, and including the new multiplexed antibody staining methods. By providing this essential knowledge to the computational community, we aim to accelerate the development of AI algorithms for cancer research.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012708","type":"journal-article","created":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T18:25:31Z","timestamp":1737656731000},"page":"e1012708","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["The tumour histopathology \u201cglossary\u201d for AI developers"],"prefix":"10.1371","volume":"21","author":[{"given":"Soham","family":"Mandal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ann-Marie","family":"Baker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trevor A.","family":"Graham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3966-3579","authenticated-orcid":true,"given":"Konstantin","family":"Br\u00e4utigam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,1,23]]},"reference":[{"key":"pcbi.1012708.ref001","article-title":"The AI revolution in cancer","author":"M. 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Hanahan","year":"2022","journal-title":"Cancer Discov"},{"issue":"2","key":"pcbi.1012708.ref029","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1053\/j.gastro.2019.08.059","article-title":"Pathways of Colorectal Carcinogenesis.","volume":"158","author":"LH Nguyen","year":"2020","journal-title":"Gastroenterology"},{"issue":"5991","key":"pcbi.1012708.ref030","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1126\/science.1189992","article-title":"Identification of a Cell of Origin for Human Prostate Cancer","volume":"329","author":"AS Goldstein","year":"2010","journal-title":"Science"},{"issue":"5","key":"pcbi.1012708.ref031","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1186\/bcr1286","article-title":"Myoepithelial cells: good fences make good neighbors","volume":"7","author":"MC Adriance","year":"2005","journal-title":"Breast Cancer Res"},{"issue":"1","key":"pcbi.1012708.ref032","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1111\/j.1751-2980.2011.00550.x","article-title":"The gastric precancerous cascade.","volume":"13","author":"P Correa","year":"2012","journal-title":"J Dig Dis"},{"key":"pcbi.1012708.ref033","first-page":"1178","volume-title":"Encyclopedia of Cancer","author":"Springer","year":"2011"},{"issue":"10","key":"pcbi.1012708.ref034","doi-asserted-by":"crossref","first-page":"djw121","DOI":"10.1093\/jnci\/djw121","article-title":"De Novo vs Nevus-Associated Melanomas: Differences in Associations With Prognostic Indicators and Survival. 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Pathol."},{"issue":"2","key":"pcbi.1012708.ref041","doi-asserted-by":"crossref","first-page":"S41","DOI":"10.1038\/modpathol.3800516","article-title":"Unusual variants of malignant melanoma.","volume":"19","author":"CM Magro","year":"2006","journal-title":"Mod Pathol."},{"issue":"3","key":"pcbi.1012708.ref042","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1038\/s41416-022-02119-4","article-title":"Tumour-infiltrating lymphocytes: from prognosis to treatment selection","volume":"128","author":"K Brummel","year":"2023","journal-title":"Br J Cancer"},{"issue":"10","key":"pcbi.1012708.ref043","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1038\/s41571-019-0222-4","article-title":"Tumour-associated neutrophils in patients with cancer","volume":"16","author":"ME Shaul","year":"2019","journal-title":"Nat Rev Clin 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Kim","year":"2016","journal-title":"J Pathol Transl Med"},{"issue":"3","key":"pcbi.1012708.ref048","first-page":"779","article-title":"US-guided Core-Needle Biopsy of the Breast: How Many Specimens Are Necessary?","volume":"226","author":"JE Fishman","year":"2003","journal-title":"RadiologyMar"},{"issue":"1","key":"pcbi.1012708.ref049","first-page":"970813","article-title":"Needle Gauge and Cytological Yield in CT-Guided Lung Biopsy.","volume":"2011","author":"W Moore","year":"2011","journal-title":"Int Sch Res Not"},{"issue":"2","key":"pcbi.1012708.ref050","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1309\/AJCPMY8UI7WSFSYY","article-title":"Adequacy of Core Needle Biopsy Specimens and Fine-Needle Aspirates for Molecular Testing of Lung Adenocarcinomas","volume":"143","author":"F Schneider","year":"2015","journal-title":"Am J Clin 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A method for normalizing histology slides for quantitative analysis. In: 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro [Internet]. 2009. p. 1107\u20131110. Available from: https:\/\/ieeexplore.ieee.org\/abstract\/document\/5193250","DOI":"10.1109\/ISBI.2009.5193250"},{"issue":"8","key":"pcbi.1012708.ref074","doi-asserted-by":"crossref","first-page":"1962","DOI":"10.1109\/TMI.2016.2529665","article-title":"Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images","volume":"35","author":"A Vahadane","year":"2016","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"pcbi.1012708.ref075","doi-asserted-by":"crossref","first-page":"e12366","DOI":"10.1002\/2056-4538.12366","article-title":"Closing the loop\u2013the role of pathologists in digital and computational pathology research","volume":"10","author":"TT Rau","year":"2024","journal-title":"J Pathol Clin Res"},{"issue":"2","key":"pcbi.1012708.ref076","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1111\/his.14356","article-title":"The human-in-the-loop: an evaluation of pathologists\u2019 interaction with artificial intelligence in clinical practice","volume":"79","author":"ACS Bod\u00e9n","year":"2021","journal-title":"Histopathology"},{"key":"pcbi.1012708.ref077","first-page":"265","volume-title":"Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2018.","author":"U Schmidt","year":"2018"},{"issue":"10","key":"pcbi.1012708.ref078","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1038\/s41568-020-0283-9","article-title":"A new dawn for eosinophils in the tumour microenvironment","volume":"20","author":"S Grisaru-Tal","year":"2020","journal-title":"Nat Rev Cancer"},{"issue":"6","key":"pcbi.1012708.ref079","doi-asserted-by":"crossref","first-page":"1634","DOI":"10.1053\/j.gastro.2004.03.025","article-title":"Diagnosis and management of dysplasia in patients with inflammatory bowel diseases","volume":"126","author":"SH Itzkowitz","year":"2004","journal-title":"Gastroenterology"},{"issue":"12","key":"pcbi.1012708.ref080","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1038\/modpathol.2017.92","article-title":"Sessile serrated adenomas with dysplasia: morphological patterns and correlations with MLH1 immunohistochemistry.","volume":"30","author":"C Liu","year":"2017","journal-title":"Mod Pathol."},{"issue":"1","key":"pcbi.1012708.ref081","doi-asserted-by":"crossref","first-page":"19","DOI":"10.4103\/jomfp.JOMFP_13_19","article-title":"Oral epithelial dysplasia: Classifications and clinical relevance in risk assessment of oral potentially malignant disorders.","volume":"23","author":"K Ranganathan","year":"2019","journal-title":"J Oral Maxillofac Pathol."},{"key":"pcbi.1012708.ref082","first-page":"94","volume-title":"In: Navab NMedical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015.","author":"A Paul","year":"2015"},{"issue":"1","key":"pcbi.1012708.ref083","doi-asserted-by":"crossref","first-page":"10","DOI":"10.4103\/2153-3539.112695","article-title":"Automated mitosis detection in histopathology using morphological and multi-channel statistics features","volume":"4","author":"H. Irshad","year":"2013","journal-title":"J Pathol Inform"},{"issue":"1","key":"pcbi.1012708.ref084","first-page":"1","article-title":"A fully automated and explainable algorithm for predicting malignant transformation in oral epithelial dysplasia.","volume":"8","author":"AJ Shephard","year":"2024","journal-title":"Npj Precis Oncol."},{"issue":"18","key":"pcbi.1012708.ref085","article-title":"QuantifyPolarity, a new tool-kit for measuring planar polarized protein distributions and cell properties in developing tissues","volume":"148","author":"SE Tan","year":"2021","journal-title":"Development"},{"issue":"8","key":"pcbi.1012708.ref086","doi-asserted-by":"crossref","first-page":"2456","DOI":"10.1083\/jcb.201903066","article-title":"Beyond proteases: Basement membrane mechanics and cancer invasion","volume":"218","author":"J Chang","year":"2019","journal-title":"J Cell Biol"},{"issue":"6","key":"pcbi.1012708.ref087","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1093\/jjco\/hyab040","article-title":"Histopathological atlas of desmoplastic reaction characterization in colorectal cancer","volume":"51","author":"H Ueno","year":"2021","journal-title":"Jpn J Clin Oncol"},{"issue":"5","key":"pcbi.1012708.ref088","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.1111\/cas.15647","article-title":"Clinicopathological features and prognostic impact of dirty necrosis in metastatic lung cancers from the colon and rectum","volume":"114","author":"Y Konishi","year":"2023","journal-title":"Cancer Sci"},{"issue":"1","key":"pcbi.1012708.ref089","doi-asserted-by":"crossref","first-page":"16852","DOI":"10.1038\/s41598-017-16516-w","article-title":"Glandular Morphometrics for Objective Grading of Colorectal Adenocarcinoma Histology Images.","volume":"7","author":"R Awan","year":"2017","journal-title":"Sci Rep."},{"key":"pcbi.1012708.ref090","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1007\/978-3-030-20351-1_66","volume-title":"Information Processing in Medical Imaging.","author":"J Li","year":"2019"},{"issue":"2","key":"pcbi.1012708.ref091","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1038\/s43018-023-00694-w","article-title":"The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma","volume":"5","author":"X Pan","year":"2024","journal-title":"Nat Cancer"},{"issue":"4","key":"pcbi.1012708.ref092","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.tice.2015.04.009","article-title":"Automated identification of keratinization and keratin pearl area from in situ oral histological images","volume":"47","author":"DK Das","year":"2015","journal-title":"Tissue Cell"},{"key":"pcbi.1012708.ref093","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.patrec.2021.01.002","article-title":"Computer vision techniques for Upper Aero-Digestive Tract tumor grading classification\u2013Addressing pathological challenges","volume":"144","author":"P Mathialagan","year":"2021","journal-title":"Pattern Recogn Lett"}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012708","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T18:25:59Z","timestamp":1737656759000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012708"}},"subtitle":[],"editor":[{"given":"B. 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