Computational portraits of the tumoral microenvironment in human breast cancer.
Breast cancer is the most diagnosed cancer in humans. In recent years, myxoid and proportionated stroma have been described as clinically significant in many cancer subtypes. Here computational portraits of tumor-associated stromata were created from a machine learning (ML) classifier using QuPath t...
| Publicado en: | Virchows Archiv: European Journal of Pathology Vol. 481; no. 3; pp. 367 - 386 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159197693&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159197693 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09456317 O1Z jtl: Virchows Archiv: European Journal of Pathology issn: 09456317 maglogo: N pubinfo: dt: Sep2022 vid: 481 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159197693 157932167 159197693 NLM35821350 10.1007/s00428-022-03376-7 NLM35821350 159197693 ppf: 367 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Computational portraits of the tumoral microenvironment in human breast cancer. aug: au: Wu, Dongling Hacking, Sean M. Chavarria, Hector Abdelwahed, Mohammed Nasim, Mansoor affil: Department of Pathology and Laboratory Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Greenvale, NY, USA sug: subj: Breast Neoplasms Pathology Receptors, Cell Surface Female Cell Physiology Proteins Tyrosine Scales Female ab: Breast cancer is the most diagnosed cancer in humans. In recent years, myxoid and proportionated stroma have been described as clinically significant in many cancer subtypes. Here computational portraits of tumor-associated stromata were created from a machine learning (ML) classifier using QuPath to evaluate proportionated stromal area (PSA), myxoid stromal ratio (MSR), and immune stroma proportion (ISP) from whole slide images (WSI). The ML classifier was validated in independent training (n = 40) and validation (n = 109) cohorts finding MSR, PSA, and ISP to be associated with tumor stage, lymph node status, Nottingham grade, stromal differentiation (SD), tumor size, estrogen receptor (ER), progesterone receptor (PR), and receptor tyrosine-protein kinase erbB-2 (HER-2). Overall, MSR correlated better with the clinicopathologic profile than PSA and ISP. High MSR was found to be associated with high tumor stage, low ISP, and high Nottingham histologic score. As a computational biomarker, high MSR was more likely to be associated with luminal B like, Her-2 enriched, and triple-negative biomarker status when compared to luminal A like. The supervised ML superpixel approach demonstrated here can be performed by a trained pathologist to provide a faster and more uniformed approach to the analysis to the tumoral microenvironment (TME). The TME may be relevant for clinical decision-making, determining chemotherapeutic efficacy, and guiding a more overall precision-based breast cancer care. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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