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非小细胞肺癌中硫氧还蛋白还原酶及其他外周血生物标志物变化与基于PD-1抑制剂的联合免疫治疗反应之间的关联:一项回顾性研究

Association between changes in thioredoxin reductase and other peripheral blood biomarkers with response to PD-1 inhibitor-based combination immunotherapy in non-small cell lung cancer: a retrospective study.

作者信息

Wen Shaodi, Du Xiaoyue, Chen Yuzhong, Xia Jingwei, Wang Ruotong, Zhu Miaolin, Peng Weiwei, Spitaleri Gianluca, Hofman Paul, Bironzo Paolo, Wang Xin, Shen Bo

机构信息

Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China.

Division of Thoracic Oncology, European Institute of Oncology, IRCCS, Milan, Italy.

出版信息

Transl Lung Cancer Res. 2022 May;11(5):757-775. doi: 10.21037/tlcr-22-300.

Abstract

BACKGROUND

Immunotherapy deeply changed the treatment paradigm of advanced non-small cell lung cancer (NSCLC) in the past years. However, the objective response rate (ORR) after immunotherapy is about 20-30% of NSCLC patients. Therefore, identification of predictive biomarkers is crucial for selecting patients with NSCLC who would most benefit from programmed cell death receptor protein 1 (PD-1) inhibitor-based immunotherapy.

METHODS

We retrospectively collected medical records and thioredoxin reductase (TrxR) data from 90 patients with a NSCLC who received PD-1 inhibitor-based combination therapy. Serum biomarkers were also measured at 6- and 12-week post-treatment and compared with their baseline values. Associations between changes in serum biomarkers, clinical characteristics and treatment efficacy were evaluated using univariate tests. The patients who were still alive were followed up remotely by phone or email to assess survival. The association between serum biomarkers and TrxR with overall survival (OS) and progression-free survival (PFS) were assessed by univariate and multivariate Cox proportional hazard regression. Nomogram prediction models were constructed using factors associated with PFS and OS, respectively.

RESULTS

The median follow-up time among the 90 patients was 19.7 (range, 13.6 to 25.8) months. Median PFS and OS were 13.6 [95% confidence interval (CI): 13.5 to 13.7] and 19.7 (95% CI: 13.6 to 25.8) months, respectively. Patients with decreased carcinoembryonic antigen (CEA), albumin (Alb), and TrxR values at 6- and 12-week post-treatment compared to baseline had statistically significantly improved disease remission rates (P<0.05). Patients with decreased white blood cell (WBC), neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR) at week 6, and decreased Alb, CEA, and lymphocyte-to-monocyte ratio (LMR) at week 12 had statistically significantly increased ORRs (P<0.05). According to the univariate and multivariate Cox regression analyses, we included adenocarcinoma, Eastern Cooperative Oncology Group performance status (ECOG PS), and CEA change at week 6 post-treatment as predictors for PFS, and adenocarcinoma, change in absolute lymphocyte count (ALC), and TrxR at week 6 as predictors for OS in the nomogram models. Each nomogram was also validated internally using a bootstrap method with 1,000 resamples.

CONCLUSIONS

Change in TrxR at 6 weeks post-treatment in combination with other clinical and hematological biomarkers could be used as a predictor for treatment outcome and prognosis in NSCLC patients after PD-1 inhibitor-based combination immunotherapy.

摘要

背景

在过去几年中,免疫疗法深刻改变了晚期非小细胞肺癌(NSCLC)的治疗模式。然而,免疫治疗后客观缓解率(ORR)约为NSCLC患者的20%-30%。因此,识别预测性生物标志物对于选择最能从基于程序性细胞死亡受体蛋白1(PD-1)抑制剂的免疫治疗中获益的NSCLC患者至关重要。

方法

我们回顾性收集了90例接受基于PD-1抑制剂联合治疗的NSCLC患者的病历和硫氧还蛋白还原酶(TrxR)数据。在治疗后6周和12周还检测了血清生物标志物,并将其与基线值进行比较。使用单变量检验评估血清生物标志物变化、临床特征与治疗疗效之间的关联。对仍存活的患者通过电话或电子邮件进行远程随访以评估生存情况。通过单变量和多变量Cox比例风险回归评估血清生物标志物和TrxR与总生存期(OS)和无进展生存期(PFS)之间的关联。分别使用与PFS和OS相关的因素构建列线图预测模型。

结果

90例患者的中位随访时间为19.7(范围13.6至25.8)个月。中位PFS和OS分别为13.6 [95%置信区间(CI):13.5至13.7]个月和19.7(95%CI:13.6至25.8)个月。与基线相比,治疗后6周和12周癌胚抗原(CEA)、白蛋白(Alb)和TrxR值降低的患者疾病缓解率有统计学显著改善(P<0.05)。治疗后6周白细胞(WBC)、中性粒细胞与淋巴细胞比值(NLR)、衍生NLR(dNLR)降低,以及治疗后12周Alb、CEA和淋巴细胞与单核细胞比值(LMR)降低的患者ORR有统计学显著升高(P<0.05)。根据单变量和多变量Cox回归分析,我们在列线图模型中纳入腺癌、东部肿瘤协作组体能状态(ECOG PS)和治疗后6周CEA变化作为PFS的预测因素,以及腺癌、绝对淋巴细胞计数(ALC)变化和治疗后6周TrxR作为OS的预测因素。每个列线图还使用1000次重采样的自举法进行了内部验证。

结论

治疗后6周TrxR的变化与其他临床和血液学生物标志物相结合,可作为NSCLC患者接受基于PD-1抑制剂联合免疫治疗后治疗结果和预后的预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50b2/9186172/9c9cd7d0ab74/tlcr-11-05-757-f1.jpg

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