ArticleMolecular cancer research : MCR2023
BLEACH&STAIN 15-marker Multiplexed Imaging in 3,098 Human Carcinomas Reveals Six Major PD-L1-driven Immune Phenotypes with Distinct Spatial Orchestration.
Article in Molecular cancer research : MCR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 11 citations in OpenAlex.
- Protocol for extended-plex immunofluorescence staining of FFPE tissues using a sequential bleach-and-stain approach.STAR protocols · 2026Article
- A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.The Journal of pathology · 2025Article
- Advances in Breast Cancer Care: The Role of Artificial Intelligence and Digital Pathology in Precision Medicine.European journal of breast health · 2025Article
- Double-Multiplex Immunostainings for Immune Profiling of Invasive Breast Carcinoma: Emerging Novel Immune-Based Biomarkers.International journal of molecular sciences · 2025Review
- Automated Prognosis Marker Assessment in Breast Cancers Using BLEACH&STAIN Multiplexed Immunohistochemistry.Biomedicines · 2023Article
- New-generation technologies for spatial tissue analysis, indispensable tools for deciphering intratumor heterogeneity in the development of antibody-drug conjugates and radio-immunoconjugates for cancer treatment.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2023Review
- Semi-automated validation and quantification of CTLA-4 in 90 different tumor entities using multiple antibodies and artificial intelligence.Laboratory investigation; a journal of technical methods and pathology · 2022Article
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Authors and funding
27 authors at 2 institutions in 2 countries.
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Abstract
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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