Cheng Yang , Yan Lai , Juan Wang , Qin Chen , Qilin Pan , Canhua Xu , Pingfan Mo , Guangxiu Guo , Rongchun Chen , Ning Liu , Yaohong Wu
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引用次数: 0
Abstract
Osteosarcoma, predominantly affecting children and adolescents, is a highly aggressive bone cancer with a 5-year survival rate of 65% to 70%. The spatial dynamics between tumor-associated macrophage (TAM) and other cellular subtypes, including T cells, osteoblasts, and osteoclasts, are critical for understanding the complexities of the osteosarcoma tumor microenvironment (TME) and can provide insights into potential immunotherapeutic strategies. Our study employs a pioneering approach that combines deep learning-based digital image analysis with multiplex fluorescence immunohistochemistry to accurately implement cell detection, segmentation, and fluorescence intensity measurements for the in-depth study of the TME. We introduce a novel algorithm for TAM/osteoclast differentiation, crucial for the accurate characterization of cellular composition. Our findings reveal distinct heterogeneity in cell composition and spatial orchestration between PD-1 (−/+) and PD-L1 (−/+) patients, highlighting the role of T-cell functionality in this context. Furthermore, our analysis demonstrates the efficacy of nivolumab in suppressing tumor growth and enhancing lymphocyte infiltration without altering the M1/M2-TAM ratio. This study provides critical insights into the spatial orchestration of cellular subtypes within the PD-1/PD-L1 defined osteosarcoma TME. By leveraging advanced multiplex fluorescence immunohistochemistry and artificial intelligence, we underscore the critical role of TAMs and T-cell interactions, proposing new therapeutic avenues focusing on TAM repolarization and targeted immunotherapies, thus underscoring the study’s potential impact on improving osteosarcoma treatment.
期刊介绍:
Laboratory Investigation is an international journal owned by the United States and Canadian Academy of Pathology. Laboratory Investigation offers prompt publication of high-quality original research in all biomedical disciplines relating to the understanding of human disease and the application of new methods to the diagnosis of disease. Both human and experimental studies are welcome.