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

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 re...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512473/
https://www.ncbi.nlm.nih.gov/pubmed/34733630
http://dx.doi.org/10.21037/tlcr-21-734
Descripción
Sumario: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 vs. 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.