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目的 探讨治疗前骨肉瘤活检组织中CD8~+T细胞浸润预测新辅助化疗(NACT)的反应及患者预后的价值。方法 选取2021年1月1日至2025年4月23日期间于首都医科大学北京积水潭医院收治的185例肢体骨肉瘤患者，分为训练队列(n=129)和验证队列(n=56)，收集患者治疗前活检肿瘤组织样本。采用免疫组化染色法检测肿瘤组织中CD8~+T细胞的浸润密度，并依据浸润密度中位数值将患者分为高浸润组和低浸润组。采用Logistic回归模型分析CD8~+T细胞浸润与NACT疗效的关系，随访患者的总生存期(OS)、无转移生存期(DMFS)和无瘤生存期(DFS)，采用KaplanMeier法绘制生存曲线，生存差异进行Log-rank检验。结果 训练队列骨肉瘤活检组织中CD8~+T细胞密度为0.74～1322.10个/mm2，中位数值为25.28个/mm2；验证队列为0.70～548.71个/mm2，中位数值为18.79个/mm2。训练队列和验证队列均显示CD8~+T细胞高浸润与NACT敏感性显著相关(P<0.001)；多因素Logistic回归分析结果显示，CD8~+T细胞浸润预测NACT疗效的显著因子(OR=0.03, P<0.001)；生存分析结果显示，高浸润组患者的DMFS和DFS均显著优于低浸润组。结论 治疗前骨肉瘤组织中CD8~+T细胞浸润水平与NACT疗效密切相关，高浸润患者从NACT中获益更多。CD8~+T细胞浸润水平可作为预测NACT疗效的潜在生物标志物。
Abstract：Objective To explore the value of CD8~+T cell infiltration in osteosarcoma biopsy tissues before treatment in predicting the response to neoadjuvant chemotherapy(NACT) and the prognosis of patients. Methods A total of 185 patients with limb osteosarcoma admitted to Beijing Jishuitan Hospital, Capital Medical University from January 1, 2021 to April 23, 2025 were selected and divided into a training cohort(n=129) and a validation cohort(n=56). Biopsy tumor tissue samples of the patients before treatment were collected. The infiltration density of CD8+ T cells in tumor tissues was detected by immunohistochemical staining, and the patients were divided into the high infiltration group and the low infiltration group based on the median value of the infiltration density. The relationship between CD8+ T cell infiltration and the therapeutic effect of NACT was analyzed by the Logistic regression model. The overall survival time(OS), metastasis-free survival time(DMFS), and tumor-free survival time(DFS) of the patients were followed up. The survival curve was plotted using the Kaplan-Meier method, and the survival difference was tested by Log-rank. Results The density of CD8+ T cells in osteosarcoma biopsy tissues of the training cohort ranged from 0.74 to 1 322.10 cells/mm2, with a median value of 25.28 cells/mm2. The verification cohort ranged from 0.70 to 548.71 pieces/mm2, with a median of 18.79 pieces/mm2. Both the training cohort and the validation cohort showed that high infiltration of CD8+ T cells was significantly correlated with NACT sensitivity(P<0.001). The results of multivariate Logistic regression analysis showed that CD8+ T cell infiltration was a significant factor in predicting the efflcacy of NACT(OR=0.03, P<0.001). The DMFS and DFS of patients in the high infiltration group were significantly better than those in the low infiltration group. Conclusion The infiltration level of CD8+ T cells in osteosarcoma tissues before treatment is closely related to the therapeutic effect of NACT. Patients with high infiltration benefit more from NACT. The infiltration level of CD8+ T cells can serve as a potential biomarker for predicting the efflcacy of NACT.
[1]Beird HC, Bielack SS, Flanagan AM, et al. Osteosarcoma[J]. Nat Rev Dis Primers, 2022, 8(1):77.
[2]Gross SW. The Classic:sarcoma of the long bones:based upon a study of one hundred and sixty-five cases. 1879[J]. Clin Orthop Relat Res, 2005, 438:9-14.
[3]Meltzer PS, Helman LJ. New horizons in the treatment of osteosarcoma[J].N Engl J Med, 2021, 385(22):2066-2076.
[4]Bielack SS, Kempf-Bielack B, Delling G, et al. Prognostic factors in high-grade osteosarcoma of the extremities or trunk:an analysis of1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols[J]. J Clin Oncol, 2023, 41(27):4323-4337.
[5]Maki RG, Schwartz GK. Flashback foreword:Prognostic factors in osteosarcoma[J]. J Clin Oncol, 2023, 41(27):4321-4322.
[6]Bramer JA, van Linge JH, Grimer RJ, et al. Prognostic factors in localized extremity osteosarcoma:a systematic review[J]. Eur J Surg Oncol, 2009, 35(10):1030-1036.
[7]Winkler K, Beron G, Delling G, et al. Neoadjuvant chemotherapy of osteosarcoma:results of a randomized cooperative trial(COSS-82)with salvage chemotherapy based on histological tumor response[J]. J Clin Oncol, 1988, 6(2):329-337.
[8]Lozano-Calderón SA, Albergo JI, Groot OQ, et al. Complete tumor necrosis after neoadjuvant chemotherapy defines good responders in patients with Ewing sarcoma[J]. Cancer, 2023, 129(1):60-70.
[9]Zhang C, Zhang G, Sun N, et al. An individualized immune signature of pretreatment biopsies predicts pathological complete response to neoadjuvant chemoradiotherapy and outcomes in patients with esophageal squamous cell carcinoma[J]. Signal Transduct Target Ther,2020, 5(1):182.
[10]Ma L, Wang L, Khatib SA, et al. Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma[J]. J Hepatol, 2021, 75(6):1397-1408.
[11]Chan YT, Zhang C, Wu J, et al. Biomarkers for diagnosis and therapeutic options in hepatocellular carcinoma[J]. Mol Cancer, 2024,23(1):189.
[12]Dejardin D, Kraxner A, Blank A, et al. A composite decision rule of CD8+T-cell density in tumor biopsies predicts efflcacy in early-stage immunotherapy trials[J]. Clin Cancer Res, 2024, 30(4):877-882.
[13]Zhao S, Liu Y, Ding L, et al. Gastric cancer immune microenvironment score predicts neoadjuvant chemotherapy efflcacy and prognosis[J]. J Pathol Clin Res, 2024, 10(3):e12378.
[14]Yang Z, Tian H, Chen X, et al. Single-cell sequencing reveals immune features of treatment response to neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma[J]. Nat Commun, 2024,15(1):9097.
[15]Ren S, Lan T, Wu F, et al. Intratumoral CD103(+)CD8(+)T cells predict response to neoadjuvant chemoimmunotherapy in advanced head and neck squamous cell carcinoma[J]. Cancer Commun(Lond), 2023,43(10):1143-1163.
[16]Bouhamama A, Leporq B, Khaled W, et al. Prediction of histologic neoadjuvant chemotherapy response in osteosarcoma using pretherapeutic MRI radiomics[J]. Radiol Imaging Cancer, 2022, 4(5):e210107.
[17]Zhong J, Zhang C, Hu Y, et al. Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram[J]. Eur Radiol, 2022, 32(9):6196-6206.
[18]Tang Y, Yang C, Guo Z, et al. P16 protein expression as a useful predictive biomarker for neoadjuvant chemotherapy response in patients with high-grade osteosarcoma:a systematic meta-analysis under guideline of PRISMA[J]. Medicine(Baltimore), 2017, 96(19):e6714.
[19]Liang X, Guo W, Ren T, et al. Macrophages reduce the sensitivity of osteosarcoma to neoadjuvant chemotherapy drugs by secreting Interleukin-1 beta[J]. Cancer Lett, 2020, 480:4-14.
[20]Van den Ende NS, Nguyen AH, Jager A, et al. Triple-negative breast cancer and predictive markers of response to neoadjuvant chemotherapy:a systematic review[J]. Int J Mol Sci, 2023, 24(3):2960.
[21]Wei LJ, Fu J, Yang HX, et al. Evaluation of pathological response to neoadjuvant chemotherapy in locally advanced cervical cancer[J]. J Transl Med, 2024, 22(1):655.
[22]Di Roio A, Hubert M, Besson L, et al. MDR1-expressing CD4(+)T cells with Th1.17 features resist to neoadjuvant chemotherapy and are associated with breast cancer clinical response[J]. J Immunother Cancer, 2023, 11(11):e008169.
基本信息:
中图分类号:R738.1
引用信息:
[1]郭昊宇,彭秀晴,骆玥君,等.肿瘤活检CD8~+T细胞早期预测骨肉瘤新辅助化疗疗效和预后的价值[J].临床肿瘤学杂志,2025,30(12):1157-1164.
基金信息:
国家自然科学基金资助项目(52473310); 北京市创伤骨科研究所自主选题项目(BJRITO-RDP-2025); 北京市医院管理中心临床医学发展专项经费资助(ZLRK202507)