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BACKGROUND AND OBJECTIVE: Quantity and the spatial relationship of specific immune cell types can provide prognostic information in bladder cancer. The objective of the study was to characterize the spatial interplay and prognostic role of different immune cell subpopulations in bladder cancer. METHODS: A total of 2463 urothelial bladder carcinomas were immunostained with 21 antibodies using BLEACH&STAIN multiplex fluorescence immunohistochemistry in a tissue microarray format and analyzed using a framework of neuronal networks for an image analysis. Spatial immune parameters were compared with histopathological parameters and overall survival data. KEY FINDINGS AND LIMITATIONS: The identification of > 300 different immune cell subpopulations and the characterization of their spatial relationship resulted in numerous spatial interaction patterns. Thirty-nine immune parameters showed prognostic significance in univariate analyses, of which 16 were independent from pT, pN, and histological grade in muscle-invasive bladder cancer. Among all these parameters, the strongest association with prolonged overall survival was identified for intraepithelial CD8+ cytotoxic T cells (time-dependent area under receiver operating characteristic curve [AUC]: 0.70), while stromal CD8+ T cells were less relevant (AUC: 0.65). A favorable prognosis of inflamed cancers with high levels of "exhaustion markers" suggests that TIM3, PD-L1, PD-1, and CTLA-4 on immune cells do not hinder antitumoral immune response in tumors rich of tumor infiltrating immune cells. CONCLUSIONS AND CLINICAL IMPLICATIONS: The density of intraepithelial CD8+ T cells was the strongest prognostic feature in muscle-invasive bladder cancer. Given that tumor cell killing by CD8+ cytotoxic T lymphocytes through direct cell-to-cell-contacts represents the "terminal end route" of antitumor immunity, the quantity of "tumor cell adjacent CD8+ T cells" may constitute a surrogate for the efficiency of cancer recognition by the immune system that can be measured straightaway in routine pathology as the CD8 labeling index. PATIENT SUMMARY: Quantification of intraepithelial CD8+ T cells, the strongest prognosticfeature identified in muscle-invasive bladder cancer, can easily be assessed by brightfield immunohistochemistry and is therefore "ready to use" for routine pathology.
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Neoplasias de la Vejiga Urinaria , Humanos , Neoplasias de la Vejiga Urinaria/inmunología , Neoplasias de la Vejiga Urinaria/patología , Neoplasias de la Vejiga Urinaria/mortalidad , Pronóstico , Linfocitos Infiltrantes de Tumor/inmunología , Linfocitos Infiltrantes de Tumor/patología , Linfocitos T CD8-positivos/inmunología , Inmunohistoquímica , Masculino , Femenino , Análisis de Matrices Tisulares , Urotelio/inmunología , Urotelio/patología , Carcinoma de Células Transicionales/inmunología , Carcinoma de Células Transicionales/patología , Carcinoma de Células Transicionales/mortalidad , Anciano , Microambiente Tumoral/inmunología , Biomarcadores de Tumor/análisis , Persona de Mediana EdadRESUMEN
Prognostic markers in routine clinical management of breast cancer are often assessed using RNA-based multi-gene panels that depend on fluctuating tumor purity. Multiplex fluorescence immunohistochemistry (mfIHC) holds the potential for an improved risk assessment. To enable automated prognosis marker detection (i.e., progesterone receptor [PR], estrogen receptor [ER], androgen receptor [AR], GATA3, TROP2, HER2, PD-L1, Ki67, TOP2A), a framework for automated breast cancer identification was developed and validated involving thirteen different artificial intelligence analysis steps and an algorithm for cell distance analysis using 11+1-marker-BLEACH&STAIN-mfIHC staining in 1404 invasive breast cancers of no special type (NST). The framework for automated breast cancer detection discriminated normal glands from malignant glands with an accuracy of 98.4%. This approach identified that five (PR, ER, AR, GATA3, PD-L1) of nine biomarkers were associated with prolonged overall survival (p ≤ 0.0095 each) and two of these (PR, AR) were found to be independent risk factors in multivariate analysis (p ≤ 0.0151 each). The combined assessment of PR-ER-AR-GATA3-PD-L1 as a five-marker prognosis score showed strong prognostic relevance (p < 0.0001) and was an independent risk factor in multivariate analysis (p = 0.0034). Automated breast cancer detection in combination with an artificial intelligence-based analysis of mfIHC enables a rapid and reliable analysis of multiple prognostic parameters. The strict limitation of the analysis to malignant cells excludes the impact of fluctuating tumor purity on assay precision.
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Multiplex fluorescence IHC (mfIHC) approaches were yet either limited to six markers or limited to a small tissue size that hampers translational studies on large tissue microarray cohorts. Here we have developed a BLEACH&STAIN mfIHC method that enabled the simultaneous analysis of 15 biomarkers (PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, and CD31) in 3,098 tumor samples from 44 different carcinoma entities within one week. To facilitate automated immune checkpoint quantification on tumor and immune cells and study its spatial interplay an artificial intelligence-based framework incorporating 17 different deep-learning systems was established. Unsupervised clustering showed that the three PD-L1 phenotypes (PD-L1+ tumor and immune cells, PD-L1+ immune cells, PD-L1-) were either inflamed or noninflamed. In inflamed PD-L1+patients, spatial analysis revealed that an elevated level of intratumoral M2 macrophages as well as CD11c+ dendritic cell (DC) infiltration (P < 0.001 each) was associated with a high CD3+ CD4± CD8± FOXP3± T-cell exclusion and a high PD-1 expression on T cells (P < 0.001 each). In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival (OS; AUC, 0.72, P < 0.001) compared with the commonly used percentage of PD-L1+ tumor cells (AUC, 0.54). In conclusion, our deep-learning-based BLEACH&STAIN framework facilitates rapid and comprehensive assessment of more than 60 spatially orchestrated immune cell subpopulations and its prognostic relevance. IMPLICATIONS: The development of an easy-to-use high-throughput 15+1 multiplex fluorescence approach facilitates the in-depth understanding of the immune tumor microenvironment (TME) and enables to study the prognostic relevance of more than 130 immune cell subpopulations.
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Antígeno B7-H1 , Carcinoma , Humanos , Antígeno B7-H1/genética , Colorantes , Inteligencia Artificial , Receptor de Muerte Celular Programada 1/genética , Linfocitos Infiltrantes de Tumor , Carcinoma/patología , Fenotipo , Factores de Transcripción Forkhead/genética , Microambiente Tumoral , Biomarcadores de Tumor/genéticaRESUMEN
Introduction: Trophoblast cell surface antigen 2 (TROP2; EpCAM2) is a transmembrane glycoprotein which is closely related to EpCAM (EpCAM; EpCAM1). Both proteins share partial overlapping functions in epithelial development and EpCAM expression but have not been comparatively analyzed together in bladder carcinomas. TROP2 constitutes the target for the antibody-drug conjugate Sacituzumab govitecan (SG; TrodelvyTM) which has been approved for treatment of metastatic urothelial carcinoma by the United States Food and Drug administration (FDA) irrespective of its TROP2 expression status. Methods: To evaluate the potential clinical significance of subtle differences in TROP2 and EpCAM expression in urothelial bladder cancer, both proteins were analyzed by multiplex fluorescence immunohistochemistry in combination with a deep-learning based algorithm for automated cell detection on more than 2,700 urothelial bladder carcinomas in a tissue microarray (TMA) format. Results: The staining pattern of TROP2 and EpCAM were highly similar. For both proteins, the staining intensity gradually decreased from pTa G2 low grade (TROP2: 68.8±36.1; EpCAM: 21.5±11.7) to pTa G2 high grade (64.6±38.0; 19.3±12.2) and pTa G3 (52.1±38.7; 16.0±13.0, p<0.001 each). In pT2-4 carcinomas, the average TROP2 and EpCAM staining intensity was intermediate (61.8±40.9; 18.3±12.3). For both proteins, this was significantly lower than in pTa G2 low grade (p<0.001 each) but also higher than in pTa G3 tumors (p=0.022 for TROP2, p=0.071 for EpCAM). Within pT2-4 carcinomas, the TROP2 and EpCAM staining level was unrelated to pT, grade, UICC-category, and overall or tumor-specific patient survival. The ratio TROP2/EpCAM was unrelated to malignant phenotype and patient prognosis. Conclusion: Our data show that TROP2 and EpCAM expression is common and highly interrelated in urothelial neoplasms. Despite of a progressive loss of TROP2/EpCAM during tumor cell dedifferentiation in pTa tumors, the lack of associations with clinicopathological parameters in pT2-4 cancer argues against a major cancer driving role of both proteins for the progression of urothelial neoplasms.