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在预测肺癌患者新辅助免疫治疗的病理反应方面,吸烟特征优于程序性死亡配体1表达。

Smoking signature is superior to programmed death-ligand 1 expression in predicting pathological response to neoadjuvant immunotherapy in lung cancer patients.

作者信息

Yang Haitang, Ma Wenyan, Sun Beibei, Fan Liwen, Xu Ke, Hall Sean R R, Al-Hurani Mohammad Faisal, Schmid Ralph A, Peng Ren-Wang, Hida Toyoaki, Wang Zhexin, Yao Feng

机构信息

Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Clinical Research Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

出版信息

Transl Lung Cancer Res. 2021 Sep;10(9):3807-3822. doi: 10.21037/tlcr-21-734.

Abstract

BACKGROUND

There is a paucity of biomarkers that can predict the degree of pathological response [e.g., pathological complete response (pCR) or major response (pMR)] to immunotherapy. Neoadjuvant immunotherapy provides an ideal setting for exploring responsive biomarkers because the pathological responses can be directly and accurately evaluated.

METHODS

We retrospectively collected the clinicopathological characteristics and treatment outcomes of non-small cell lung cancer (NSCLC) patients who received neoadjuvant immunotherapy or chemo-immunotherapy followed by surgery between 2018 and 2020 at a large academic thoracic cancer center. Clinicopathological factors associated with pathological response were analyzed.

RESULTS

A total of 39 patients (35 males and 4 females) were included. The most common histological subtype was lung squamous cell carcinoma (LUSC) (n=28, 71.8%), followed by lung adenocarcinoma (LUAD) (n=11, 28.2%). After neoadjuvant treatment, computed tomography (CT) scan-based evaluation showed poor agreement with the postoperatively pathological examination (weighted kappa =0.0225; P=0.795), suggesting the poor performance of CT scans in evaluating the response to immunotherapy. Importantly, we found that the smoking signature displayed a better performance than programmed death-ligand 1 (PD-L1) expression in predicting the pathological response (area under the curve: 0.690 0.456; P=0.0259), which might have resulted from increased tumor mutational burden (TMB) and/or microsatellite instability (MSI) relating to smoking exposure.

CONCLUSIONS

These findings suggest that CT scan-based evaluation is not able to accurately reflect the pathological response to immunotherapy and that smoking signature is a superior marker to PD-L1 expression in predicting the benefit of immunotherapy in NSCLC patients.

摘要

背景

能够预测免疫治疗病理反应程度[如病理完全缓解(pCR)或主要反应(pMR)]的生物标志物匮乏。新辅助免疫治疗为探索反应性生物标志物提供了理想的环境,因为可以直接且准确地评估病理反应。

方法

我们回顾性收集了2018年至2020年期间在一家大型学术性胸癌中心接受新辅助免疫治疗或化疗免疫治疗后进行手术的非小细胞肺癌(NSCLC)患者的临床病理特征和治疗结果。分析了与病理反应相关的临床病理因素。

结果

共纳入39例患者(35例男性和4例女性)。最常见的组织学亚型是肺鳞状细胞癌(LUSC)(n = 28,71.8%),其次是肺腺癌(LUAD)(n = 11,28.2%)。新辅助治疗后,基于计算机断层扫描(CT)的评估与术后病理检查的一致性较差(加权kappa = 0.0225;P = 0.795),表明CT扫描在评估免疫治疗反应方面表现不佳。重要的是,我们发现吸烟特征在预测病理反应方面比程序性死亡配体1(PD-L1)表达表现更好(曲线下面积:0.690对0.456;P = 0.0259),这可能是由于与吸烟暴露相关的肿瘤突变负担(TMB)增加和/或微卫星不稳定性(MSI)所致。

结论

这些发现表明,基于CT扫描的评估不能准确反映免疫治疗的病理反应,并且吸烟特征在预测NSCLC患者免疫治疗获益方面是优于PD-L1表达的标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26d0/8512473/11775a8fc09e/tlcr-10-09-3807-f1.jpg

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