PDL1 high expression without TP53, KEAP1 and EPHA5 mutations could better predict survival for patients with NSCLC receiving atezolizumab.


Journal

Lung cancer (Amsterdam, Netherlands)
ISSN: 1872-8332
Titre abrégé: Lung Cancer
Pays: Ireland
ID NLM: 8800805

Informations de publication

Date de publication:
01 2021
Historique:
received: 23 09 2020
revised: 21 10 2020
accepted: 10 11 2020
pubmed: 29 11 2020
medline: 28 5 2021
entrez: 28 11 2020
Statut: ppublish

Résumé

Non-small cell lung cancer (NSCLC) patients with high expression of PDL1 are more likely to benefit from atezolizumab. There are no relevant research focusing on the relationship between the PDL1 expression and clinical variables and gene mutation types among NSCLC patients. NSCLC patients with confirmed PDL1 expression and gene mutation information from OAK study were included in our study. Logistic regression proportional model was applied to analyze the risk factors on PDL1 high expression. The biomarker evaluable population (BEP) was screened to analyze the gene mutation informaion among these patients. High frequency gene mutations were screened based on different PDL1 expressions. Moreover, the log rank test was applied to analyze the overall survival (OS) difference based on different gene mutation types. A total of 838 patients with NSCLC were included in our study. White patients are more likely to have PDL1 ≥ 1% (P = 0.004). ERBB4, EP300, PREX2, SLIT2, EPHB1 and IGF2R mutations were high frequency mutations in patients with high PDL1 expression, and the patients with EGFR, SMARCA4, EPHA5, FAT1, STK11, TET2 mutations were more likely to be seen in negative PDL1 expression group. Worse survival could be found in patients with KEAP1 (P < 0.001), TP53 (P = 0.004) and EPHA5 (P = 0.013) mutations who received atezolizumab compared with those who had none of these gene mutations. Importantly, for PDL1 high patients without KEAP1, EPHA5, TP53 mutations receiving atezolizumab, they all showed relatively longer median survival with 22.47, 22.18 and 23.33 months, respectively (all, P < 0.01). Different high frequency gene mutations could be found between the patients with high and negative PDL1. PDL1 expression combined with specific gene mutation may better predict the survival for patients receiving atezolizumab.

Sections du résumé

BACKGROUND
Non-small cell lung cancer (NSCLC) patients with high expression of PDL1 are more likely to benefit from atezolizumab. There are no relevant research focusing on the relationship between the PDL1 expression and clinical variables and gene mutation types among NSCLC patients.
METHODS
NSCLC patients with confirmed PDL1 expression and gene mutation information from OAK study were included in our study. Logistic regression proportional model was applied to analyze the risk factors on PDL1 high expression. The biomarker evaluable population (BEP) was screened to analyze the gene mutation informaion among these patients. High frequency gene mutations were screened based on different PDL1 expressions. Moreover, the log rank test was applied to analyze the overall survival (OS) difference based on different gene mutation types.
RESULTS
A total of 838 patients with NSCLC were included in our study. White patients are more likely to have PDL1 ≥ 1% (P = 0.004). ERBB4, EP300, PREX2, SLIT2, EPHB1 and IGF2R mutations were high frequency mutations in patients with high PDL1 expression, and the patients with EGFR, SMARCA4, EPHA5, FAT1, STK11, TET2 mutations were more likely to be seen in negative PDL1 expression group. Worse survival could be found in patients with KEAP1 (P < 0.001), TP53 (P = 0.004) and EPHA5 (P = 0.013) mutations who received atezolizumab compared with those who had none of these gene mutations. Importantly, for PDL1 high patients without KEAP1, EPHA5, TP53 mutations receiving atezolizumab, they all showed relatively longer median survival with 22.47, 22.18 and 23.33 months, respectively (all, P < 0.01).
CONCLUSIONS
Different high frequency gene mutations could be found between the patients with high and negative PDL1. PDL1 expression combined with specific gene mutation may better predict the survival for patients receiving atezolizumab.

Identifiants

pubmed: 33246647
pii: S0169-5002(20)30681-4
doi: 10.1016/j.lungcan.2020.11.006
pii:
doi:

Substances chimiques

Antibodies, Monoclonal, Humanized 0
B7-H1 Antigen 0
CD274 protein, human 0
KEAP1 protein, human 0
Kelch-Like ECH-Associated Protein 1 0
NF-E2-Related Factor 2 0
Nuclear Proteins 0
TP53 protein, human 0
Transcription Factors 0
Tumor Suppressor Protein p53 0
atezolizumab 52CMI0WC3Y
EPHA5 protein, human EC 2.7.10.1
Receptor, EphA5 EC 2.7.10.1
SMARCA4 protein, human EC 3.6.1.-
DNA Helicases EC 3.6.4.-

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

76-83

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

Haiyong Wang (H)

Department of Internal Medicine-Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.

Qinge Shan (Q)

Department of Internal Medicine-Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.

Jun Guo (J)

Department of Internal Medicine-Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.

Xiao Han (X)

Department of Internal Medicine-Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.

Chenglong Zhao (C)

Department of Pathology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.

Huijuan Li (H)

Department of Clinical Drug Research, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China. Electronic address: ywb234@126.com.

Zhehai Wang (Z)

Department of Internal Medicine-Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China. Electronic address: badgood007@126.com.

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