Lymphocyte Infiltration Score and Spatial Characteristics Refined the Prognosis and Denosumab Treatment Responsiveness Indicators for Giant Cell Tumor of Bone

德诺苏马布 医学 肿瘤科 内科学 骨巨细胞瘤 CD8型 免疫系统 病理 巨细胞 免疫学 骨质疏松症
作者
Hailin Wu,Chao Xia,Fusheng Liu,Bo‐Yv Zheng,Hua‐Qing Niu,Guo‐Qiang Zhu,Ming‐Xiang Zou,Bo‐Wen Zheng
出处
期刊:JCO precision oncology [American Society of Clinical Oncology]
卷期号: (8) 被引量:2
标识
DOI:10.1200/po.24.00135
摘要

PURPOSE The prognostic value of lymphocyte infiltration score (LIS) and its nearest neighbor distance to tumor cells (NNDTC) in giant cell tumor of bone (GCTB) is currently not well established. This study aims to characterize LIS and NNDTC and examine their correlation with denosumab treatment responsiveness, clinicopathologic features, and patient prognosis. METHODS Using multiplexed quantitative immunofluorescence, LIS was evaluated in 253 tumor specimens, whereas NNDTC was computed using HALO software. Subsequently, we analyzed the association of these parameters with patient outcomes (progression-free survival [PFS] and overall survival [OS]), clinicopathologic features, and denosumab treatment responsiveness. RESULTS Low LIS was indicative of both poor PFS and OS (both P < .001). In addition, LIS was significantly associated with sex ( P = .046), Enneking staging ( P < .001), Ki-67 expression ( P = .007), and denosumab treatment responsiveness ( P = .005). Lower CD8 + (tumor interior [TI]) NNDTC, and CD3 + (TI) NNDTC were associated with worse PFS ( P = .003 and .038, respectively), whereas lower CD8 + (TI) NNDTC was associated with worse OS ( P = .001), but CD8 + (tumor infiltrating margin) NNDTC had the opposite effect ( P = .002). Moreover, NNDTC showed a correlation with several clinicopathologic features. Importantly, LIS outperformed Enneking and Campanacci staging systems in predicting the clinical outcomes of GCTB. CONCLUSION These findings suggest that LIS is a reliable predictive tool for clinically relevant outcomes and response to denosumab therapy in patients with GCTB. These parameters may prove to be useful in guiding prognostic risk stratification and therapeutic optimization for patients.
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