Lin Sun1, Luwen Mu2, Jing Zhou3, Wenjie Tang1, Linqi Zhang1, Sidong Xie1, Jingbiao Chen1, Jin Wang4. 1. Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, People's Republic of China. 2. Department of Interventional Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, People's Republic of China. 3. Department of Pathology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, People's Republic of China. 4. Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, 510630, People's Republic of China. wangjin3@mail.sysu.edu.cn.
Abstract
BACKGROUND: Tumor-infiltrating CD8 cells and expression of programmed cell death ligand 1 (PD-L1) are immune checkpoint markers in patients with hepatocellular carcinoma (HCC). We aimed to determine the ability of preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings to predict CD8 cell density and PD-L1 expression in HCC. METHODS: A total of 120 patients with HCC who underwent 3.0-T gadoxetic acid-enhanced MRI before curative resection from January 2016 to June 2020 were enrolled and divided into a training set (n = 84) and a testing set (n = 36). Thirty-four patients with advanced stage HCC who received anti-PD-1 inhibitor between January 2017 and April 2020 and underwent pretreated gadoxetic acid-enhanced MRI scans were enrolled in an independent validation set. PD-L1 expression and CD8 cell infiltration were assessed with immunohistochemical staining, respectively. Two radiologists blinded to pathology results evaluated the pretreated MR features in consensus. Logistic regression and the receiver operating characteristic curve (ROC) analyses were used to determine the value of image features to predict high CD8 cell density, PD-L1 positivity and the combination of high CD8 cell density and PD-L1 positivity in HCC in the training set and validated the findings in the testing set. The associations of MRI predictors with the objective response to immunotherapy were assessed in the independent validation. RESULTS: In the training set, the independent MRI predictors were irregular tumor margin (ITM, P = 0.008) and peritumoral low signal intensity (PLSI) on hepatobiliary phase (HBP) images (P < 0.001) for PD-L1 positivity, absence of an enhancing capsule (AEC, P = 0.001) and PLSI on HBP images (P = 0.025) for high CD8 cell density, and PLSI on HBP images (P = 0.001) and ITM (P = 0.023) for the both. The area under the curves (AUCs) of the predictive models for evaluating PD-L1 positivity, high CD8 cell density and the combination of high CD8 cell density and PD-L1 positivity were 0.810 and 0.809, 0.740 and 0.728, and 0.809 and 0.874 in the training and testing set, respectively. The objective response was demonstrated to be associated with the combination of PLSI on HBP images and ITM (PHI, P = 0.004), and the combination of PLSI on HBP images and AEC (PHA, P = 0.012) in the independent validation set. CONCLUSIONS: Pretreated MRI features have the potential to identify patients with HCC in an immune-activated state and predict outcomes of immunotherapy. Trial registration The study was retrospectively registered on March 5, 2020 with registration no. [2020] 02-012-01.
BACKGROUND: Tumor-infiltrating CD8 cells and expression of programmed cell death ligand 1 (PD-L1) are immune checkpoint markers in patients with hepatocellular carcinoma (HCC). We aimed to determine the ability of preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) findings to predict CD8 cell density and PD-L1 expression in HCC. METHODS: A total of 120 patients with HCC who underwent 3.0-T gadoxetic acid-enhanced MRI before curative resection from January 2016 to June 2020 were enrolled and divided into a training set (n = 84) and a testing set (n = 36). Thirty-four patients with advanced stage HCC who received anti-PD-1 inhibitor between January 2017 and April 2020 and underwent pretreated gadoxetic acid-enhanced MRI scans were enrolled in an independent validation set. PD-L1 expression and CD8 cell infiltration were assessed with immunohistochemical staining, respectively. Two radiologists blinded to pathology results evaluated the pretreated MR features in consensus. Logistic regression and the receiver operating characteristic curve (ROC) analyses were used to determine the value of image features to predict high CD8 cell density, PD-L1 positivity and the combination of high CD8 cell density and PD-L1 positivity in HCC in the training set and validated the findings in the testing set. The associations of MRI predictors with the objective response to immunotherapy were assessed in the independent validation. RESULTS: In the training set, the independent MRI predictors were irregular tumor margin (ITM, P = 0.008) and peritumoral low signal intensity (PLSI) on hepatobiliary phase (HBP) images (P < 0.001) for PD-L1 positivity, absence of an enhancing capsule (AEC, P = 0.001) and PLSI on HBP images (P = 0.025) for high CD8 cell density, and PLSI on HBP images (P = 0.001) and ITM (P = 0.023) for the both. The area under the curves (AUCs) of the predictive models for evaluating PD-L1 positivity, high CD8 cell density and the combination of high CD8 cell density and PD-L1 positivity were 0.810 and 0.809, 0.740 and 0.728, and 0.809 and 0.874 in the training and testing set, respectively. The objective response was demonstrated to be associated with the combination of PLSI on HBP images and ITM (PHI, P = 0.004), and the combination of PLSI on HBP images and AEC (PHA, P = 0.012) in the independent validation set. CONCLUSIONS: Pretreated MRI features have the potential to identify patients with HCC in an immune-activated state and predict outcomes of immunotherapy. Trial registration The study was retrospectively registered on March 5, 2020 with registration no. [2020] 02-012-01.
Authors: Andrew X Zhu; Richard S Finn; Julien Edeline; Stephane Cattan; Sadahisa Ogasawara; Daniel Palmer; Chris Verslype; Vittorina Zagonel; Laetitia Fartoux; Arndt Vogel; Debashis Sarker; Gontran Verset; Stephen L Chan; Jennifer Knox; Bruno Daniele; Andrea L Webber; Scot W Ebbinghaus; Junshui Ma; Abby B Siegel; Ann-Lii Cheng; Masatoshi Kudo Journal: Lancet Oncol Date: 2018-06-03 Impact factor: 41.316
Authors: Roger Sun; Elaine Johanna Limkin; Maria Vakalopoulou; Laurent Dercle; Stéphane Champiat; Shan Rong Han; Loïc Verlingue; David Brandao; Andrea Lancia; Samy Ammari; Antoine Hollebecque; Jean-Yves Scoazec; Aurélien Marabelle; Christophe Massard; Jean-Charles Soria; Charlotte Robert; Nikos Paragios; Eric Deutsch; Charles Ferté Journal: Lancet Oncol Date: 2018-08-14 Impact factor: 41.316