Literature DB >> 28385373

Computed Tomography Features of Lung Adenocarcinomas With Programmed Death Ligand 1 Expression.

Gouji Toyokawa1, Kazuki Takada2, Tatsuro Okamoto3, Mototsugu Shimokawa4, Yuka Kozuma3, Taichi Matsubara3, Naoki Haratake3, Shinkichi Takamori3, Takaki Akamine3, Masakazu Katsura3, Fumihiro Shoji3, Yoshinao Oda5, Yoshihiko Maehara3.   

Abstract

INTRODUCTION: The development of immune checkpoint inhibitors against programmed death 1 has paved the way for a new era of treatment of lung cancer. Programmed death-ligand 1 (PD-L1) is expected to predict the response of immune checkpoint inhibitors in lung cancer. Predicting PD-L1 expression using a noninvasive method before immunotherapy would, therefore, help identify patients for whom immunotherapy can be successful. PATIENTS AND METHODS: A total of 394 patients with resected lung adenocarcinoma who had undergone preoperative thin-section computed tomography (CT) were analyzed for PD-L1 expression by immunohistochemistry and evaluated to determine the association between PD-L1 expression and CT characteristics, including convergence, surrounding ground glass opacity (GGO), air bronchogram, notching, pleural indentation, spiculation, and cavitation.
RESULTS: Of the 394 patients, 78 (19.8%) were positive and 316 (80.2%) were negative for PD-L1 expression. Univariate analysis demonstrated that PD-L1+ adenocarcinoma was significantly associated with the presence of convergence (P < .01), notching (P < .01), spiculation (P < .01), and cavitation (P < .01) and the absence of surrounding GGO (P < .01) compared with PD-L1- cases. On multivariate analysis, the presence of convergence (P < .01) and cavitation (P < .01) and the absence of surrounding GGO (P = .02) and air bronchogram (P = .03) were significantly associated with PD-L1 expression.
CONCLUSION: PD-L1+ adenocarcinoma cases showed convergence and cavitation more frequently than did PD-L1- cases. In contrast, surrounding GGO and air bronchogram were observed less frequently in PD-L1+ cases than in PD-L1- cases. These results will prove helpful in identifying PD-L1-expressing adenocarcinoma by CT before immunotherapy.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CT; Lung adenocarcinoma; PD-L1

Mesh:

Substances:

Year:  2017        PMID: 28385373     DOI: 10.1016/j.cllc.2017.03.008

Source DB:  PubMed          Journal:  Clin Lung Cancer        ISSN: 1525-7304            Impact factor:   4.785


  9 in total

1.  Radiological Features of Programmed Cell Death-Ligand 2-positive Lung Adenocarcinoma: A Single-institution Retrospective Study.

Authors:  Kazuki Takada; Gouji Toyokawa; Koichi Azuma; Shinkichi Takamori; Tomoko Jogo; Fumihiko Hirai; Tetsuzo Tagawa; Akihiko Kawahara; Jun Akiba; Isamu Okamoto; Yoichi Nakanishi; Yoshinao Oda; Tomoaki Hoshino; Yoshihiko Maehara
Journal:  In Vivo       Date:  2018 Nov-Dec       Impact factor: 2.155

2.  Association between 18F-FDG metabolic activity and programmed death ligand-1 (PD-L1) expression using 22C3 immunohistochemistry assays in non-small cell lung cancer (NSCLC) resection specimens.

Authors:  Long Zhao; Jinjun Liu; Huoqiang Wang; Jingyun Shi
Journal:  Br J Radiol       Date:  2021-01-25       Impact factor: 3.039

3.  The growth of non-solid neoplastic lung nodules is associated with low PD L1 expression, irrespective of sampling technique.

Authors:  Chandra Bortolotto; Claudio Maglia; Antonio Ciuffreda; Manuela Coretti; Roberta Catania; Filippo Antonacci; Sergio Carnevale; Ivana Sarotto; Roberto Dore; Andrea Riccardo Filippi; Gabriele Chiara; Daniele Regge; Lorenzo Preda; Patrizia Morbini; Giulia Maria Stella
Journal:  J Transl Med       Date:  2020-02-03       Impact factor: 5.531

4.  Molecular Alterations in Lung Adenocarcinoma With Ground-Glass Nodules: A Systematic Review and Meta-Analysis.

Authors:  Zihan Wei; Ziyang Wang; Yuntao Nie; Kai Zhang; Haifeng Shen; Xin Wang; Manqi Wu; Fan Yang; Kezhong Chen
Journal:  Front Oncol       Date:  2021-09-13       Impact factor: 6.244

5.  Correlation between PD-L1 expression and radiomic features in early-stage lung adenocarcinomas manifesting as ground-glass nodules.

Authors:  Wenjia Shi; Zhen Yang; Minghui Zhu; Chenxi Zou; Jie Li; Zhixin Liang; Miaoyu Wang; Hang Yu; Bo Yang; Yulin Wang; Chunsun Li; Zirui Wang; Wei Zhao; Liang'an Chen
Journal:  Front Oncol       Date:  2022-09-13       Impact factor: 5.738

6.  Comparison of PD-L1 Expression Status between Pure-Solid Versus Part-Solid Lung Adenocarcinomas.

Authors:  Kenichi Suda; Masaki Shimoji; Shigeki Shimizu; Katsuaki Sato; Masato Chiba; Kenji Tomizawa; Toshiki Takemoto; Junichi Soh; Tetsuya Mitsudomi
Journal:  Biomolecules       Date:  2019-09-07

7.  Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas.

Authors:  Jiyoung Yoon; Young Joo Suh; Kyunghwa Han; Hyoun Cho; Hye-Jeong Lee; Jin Hur; Byoung Wook Choi
Journal:  Thorac Cancer       Date:  2020-02-11       Impact factor: 3.500

8.  A CT-derived deep neural network predicts for programmed death ligand-1 expression status in advanced lung adenocarcinomas.

Authors:  Ying Zhu; Yang-Li Liu; Yu Feng; Xiao-Yu Yang; Jing Zhang; Dan-Dan Chang; Xi Wu; Xi Tian; Ke-Jing Tang; Can-Mao Xie; Yu-Biao Guo; Shi-Ting Feng; Zun-Fu Ke
Journal:  Ann Transl Med       Date:  2020-08

Review 9.  Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges.

Authors:  Francisco Silva; Tania Pereira; Inês Neves; Joana Morgado; Cláudia Freitas; Mafalda Malafaia; Joana Sousa; João Fonseca; Eduardo Negrão; Beatriz Flor de Lima; Miguel Correia da Silva; António J Madureira; Isabel Ramos; José Luis Costa; Venceslau Hespanhol; António Cunha; Hélder P Oliveira
Journal:  J Pers Med       Date:  2022-03-16
  9 in total

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