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  • 21
    Online Resource
    Online Resource
    IOP Publishing ; 1972
    In:  Nuclear Fusion Vol. 12, No. 3 ( 1972-05-01), p. 297-300
    In: Nuclear Fusion, IOP Publishing, Vol. 12, No. 3 ( 1972-05-01), p. 297-300
    Type of Medium: Online Resource
    ISSN: 0029-5515 , 1741-4326
    Language: Unknown
    Publisher: IOP Publishing
    Publication Date: 1972
    detail.hit.zdb_id: 2037980-8
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  • 22
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 1987
    In:  Experimental Brain Research Vol. 67, No. 1 ( 1987-6), p. 70-76
    In: Experimental Brain Research, Springer Science and Business Media LLC, Vol. 67, No. 1 ( 1987-6), p. 70-76
    Type of Medium: Online Resource
    ISSN: 0014-4819 , 1432-1106
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 1987
    detail.hit.zdb_id: 1459099-2
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  • 23
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2021
    In:  American Journal of Clinical Pathology Vol. 156, No. Supplement_1 ( 2021-10-28), p. S137-S138
    In: American Journal of Clinical Pathology, Oxford University Press (OUP), Vol. 156, No. Supplement_1 ( 2021-10-28), p. S137-S138
    Abstract: Introduction: CTLA-4 is an inhibitory immune checkpoint receptor and a negative regulator of anti-tumor T-cell function. This study aimed at a comparative analysis of CTLA-4+ entities. cells between different tumor Methods/Case Report Methods: To quantify CTLA-4+ cells, 4,582 tumor samples from 90 different tumor entities as well as 608 samples of 76 different normal tissue types were analyzed by immunohistochemistry in a tissue microarray format. Two different antibody clones (MSVA-152R and CAL49) were validated and quantified using a deep learning framework for automated exclusion of unspecific immunostaining. Results (if a Case Study enter NA) Results: Comparing both CTLA-4 antibodies revealed a clone dependent unspecific staining pattern in adrenal cortical adenoma (63%) for MSVA-152R and in pheochromocytoma (67%) as well as hepatocellular carcinoma (36%) for CAL49. After automated exclusion of non-specific staining reaction (3.6%), a strong correlation was observed for the densities of CTLA-4+ lymphocytes obtained by both antibodies (r=0.87; p & lt;0.0001). The mean density of CTLA-4+cells was 674±1482 cells/ mm2 and ranged from 71±175 cells/mm2 in leiomyoma to 5916±3826 cells/mm2 in Hodgkin’s lymphoma. Within epithelial tumors, the density of CTLA-4+ lymphocytes were higher in squamous cell (421±467 cells/ mm2) and urothelial carcinomas (419±347 cells/ mm2) than in adenocarcinomas (269±375 cells/ mm2) and renal cell neoplasms (256±269 cells/ mm2). A high CTLA-4+ cell density was linked to low pT category (p & lt;0.0001), absent lymph node metastases (p=0.0354), and PD-L1 expression in tumor cells or inflammatory cells (p & lt;0.0001 each). A high CTLA-4/CD3-ratio was linked to absent lymph node metastases (p=0.0295) and to PD-L1 positivity on immune cells (p & lt;0.0026). Conclusion Marked differences exist in the number of CTLA-4+ lymphocytes between tumors. Analyzing two independent antibodies by a deep learning framework can facilitate automated quantification of immunohistochemically analyzed target proteins such as CTLA-4.
    Type of Medium: Online Resource
    ISSN: 0002-9173 , 1943-7722
    RVK:
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2039921-2
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