Zhen-Kui Pan1, Feng Ye1, Xuan Wu1, Han-Xiang An1, Jing-Xun Wu1. 1. 1 Department of Oncology, Qingdao Municipal Hospital, Qingdao 266011, China ; 2 Department of Medical Oncology, The First Affiliated Hospital of Xiamen University, Xiamen 361003, China ; 3 Department of Medical Oncology, Peking University Shenzhen Hospital, Shenzhen 518036, China.
Abstract
OBJECTIVE: Programmed cell death 1 (PD-1) and one of its ligands, PD-L1, are key immune checkpoint proteins. Evidences showed PD-L1 is an emerging biomarker for immunotherapy by anti-PD-1 and anti-PD-L1 antibody in non-small cell lung cancer (NSCLC). To investigate the association of PD-L1 protein expression with clinicopathological features and its impact on survival outcome, we conducted a meta-analysis. METHODS: A comprehensive literature search of electronic databases (up to July 10, 2014) was performed. Correlation between PD-L1 expression and clinicopathological features and overall survival (OS) was analyzed by synthesizing the qualified data. Publication biases were examined. RESULTS: A total of 1,550 NSCLC patients from 9 studies were included. The pooled odds ratios (ORs) indicated high PD-L1 expression was associated with poor tumor differentiation [OR =0.53, 95% confidence interval (CI): 0.39-0.72, P<0.0001]. Whereas, none of other clinicopathological characteristics [gender, smoking status, histological type, invasive depth of tumor, status of lymph node metastasis and tumor node metastasis (TNM) stage] were correlated with PD-L1 expression in current analysis. The combined hazard ratio (HR) for OS showed high expression of PD-L1 impaired the OS in NSCLC (HRpositive/negative =1.47, 95% CI: 1.19-1.83, P=0.0004). CONCLUSIONS: Our meta-analysis indicated PD-L1 protein expression in NSCLC was not associated with common clinicopathological characteristics, except tumor differentiation. It was a poor prognostic biomarker for NSCLC. Further research should be performed to investigate the precise clinicopathological and prognostic significance of PD-L1 in NSCLC under uniform testing standard.
OBJECTIVE: Programmed cell death 1 (PD-1) and one of its ligands, PD-L1, are key immune checkpoint proteins. Evidences showed PD-L1 is an emerging biomarker for immunotherapy by anti-PD-1 and anti-PD-L1 antibody in non-small cell lung cancer (NSCLC). To investigate the association of PD-L1 protein expression with clinicopathological features and its impact on survival outcome, we conducted a meta-analysis. METHODS: A comprehensive literature search of electronic databases (up to July 10, 2014) was performed. Correlation between PD-L1 expression and clinicopathological features and overall survival (OS) was analyzed by synthesizing the qualified data. Publication biases were examined. RESULTS: A total of 1,550 NSCLCpatients from 9 studies were included. The pooled odds ratios (ORs) indicated high PD-L1 expression was associated with poor tumor differentiation [OR =0.53, 95% confidence interval (CI): 0.39-0.72, P<0.0001]. Whereas, none of other clinicopathological characteristics [gender, smoking status, histological type, invasive depth of tumor, status of lymph node metastasis and tumor node metastasis (TNM) stage] were correlated with PD-L1 expression in current analysis. The combined hazard ratio (HR) for OS showed high expression of PD-L1 impaired the OS in NSCLC (HRpositive/negative =1.47, 95% CI: 1.19-1.83, P=0.0004). CONCLUSIONS: Our meta-analysis indicated PD-L1 protein expression in NSCLC was not associated with common clinicopathological characteristics, except tumor differentiation. It was a poor prognostic biomarker for NSCLC. Further research should be performed to investigate the precise clinicopathological and prognostic significance of PD-L1 in NSCLC under uniform testing standard.
Entities:
Keywords:
Meta-analysis; non-small cell lung cancer (NSCLC); prognosis; programmed cell death ligand 1 (PD-L1)
Authors: Suzanne L Topalian; F Stephen Hodi; Julie R Brahmer; Scott N Gettinger; David C Smith; David F McDermott; John D Powderly; Richard D Carvajal; Jeffrey A Sosman; Michael B Atkins; Philip D Leming; David R Spigel; Scott J Antonia; Leora Horn; Charles G Drake; Drew M Pardoll; Lieping Chen; William H Sharfman; Robert A Anders; Janis M Taube; Tracee L McMiller; Haiying Xu; Alan J Korman; Maria Jure-Kunkel; Shruti Agrawal; Daniel McDonald; Georgia D Kollia; Ashok Gupta; Jon M Wigginton; Mario Sznol Journal: N Engl J Med Date: 2012-06-02 Impact factor: 91.245
Authors: Christian Blank; Juergen Kuball; Simon Voelkl; Heinz Wiendl; Bernd Becker; Bernhard Walter; Otto Majdic; Thomas F Gajewski; Mathias Theobald; Reinhard Andreesen; Andreas Mackensen Journal: Int J Cancer Date: 2006-07-15 Impact factor: 7.396
Authors: K Azuma; K Ota; A Kawahara; S Hattori; E Iwama; T Harada; K Matsumoto; K Takayama; S Takamori; M Kage; T Hoshino; Y Nakanishi; I Okamoto Journal: Ann Oncol Date: 2014-07-09 Impact factor: 32.976
Authors: Marissa Mayor; Neng Yang; Daniel Sterman; David R Jones; Prasad S Adusumilli Journal: Eur J Cardiothorac Surg Date: 2015-10-29 Impact factor: 4.191
Authors: Emily B Ehlerding; Hye Jin Lee; Todd E Barnhart; Dawei Jiang; Lei Kang; Douglas G McNeel; Jonathan W Engle; Weibo Cai Journal: Bioconjug Chem Date: 2019-04-19 Impact factor: 4.774
Authors: Adil I Daud; Kimberly Loo; Mariela L Pauli; Robert Sanchez-Rodriguez; Priscila Munoz Sandoval; Keyon Taravati; Katy Tsai; Adi Nosrati; Lorenzo Nardo; Michael D Alvarado; Alain P Algazi; Miguel H Pampaloni; Iryna V Lobach; Jimmy Hwang; Robert H Pierce; Iris K Gratz; Matthew F Krummel; Michael D Rosenblum Journal: J Clin Invest Date: 2016-08-15 Impact factor: 14.808
Authors: Matthew W Rosenbaum; Benjamin J Gigliotti; Sara I Pai; Sareh Parangi; Heather Wachtel; Mari Mino-Kenudson; Viswanath Gunda; William C Faquin Journal: Endocr Pathol Date: 2018-03 Impact factor: 3.943