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Intramucosal Inoculation of Squamous Cell Carcinoma Cells in Mice for Tumor Immune Profiling and Treatment Response Assessment
Published on: April 22, 2019
Lymphocyte Infiltration Score and Spatial Characteristics Refined the Prognosis and Denosumab Treatment
Hai-Lin Wu1, Chao Xia2, Fu-Sheng Liu1
1Department of Spine Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.
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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