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Article

Validation of the Combined Biomarker for Prediction of Response to Checkpoint Inhibitor in Patients with Advanced Cancer

by 1,†,‡, 2,‡, 3,‡, 1 and 3,*
1
Samsung Medical Center, Department of Medicine, Division of Hematology-Oncology, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
2
Samsung Medical Center, The Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University School of Medicine, Seoul 06351, Korea
3
Samsung Medical Center, Department of Pathology and Translational Genomics, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
*
Author to whom correspondence should be addressed.
Present address: Department of Hematology-Oncology, Inha University College of Medicine and Hospital, Incheon 06351, Korea.
These authors contributed equally to this work as first authors.
Academic Editor: Constantin N. Baxevanis
Cancers 2021, 13(10), 2316; https://doi.org/10.3390/cancers13102316
Received: 8 March 2021 / Revised: 4 May 2021 / Accepted: 6 May 2021 / Published: 12 May 2021
(This article belongs to the Collection Cancer Biomarkers)
IMAGiC model is the model consisting of four-gene and PD-L1 expression levels to predict immunotherapy response. The IMAGiC model’s predictive performance was validated in patients with several advanced tumor types in this study. The PFS and OS demonstrated significant differences between the dichotomous IMAGiC groups. IMAGiC group could be utilized as a binary biomarker for predicting response to immunotherapy regardless of TMB level or MSI status.
Although immune checkpoint inhibitors can induce durable responses in patients with multiple types of advanced cancer, only a limited number of patients have a known reliable biomarker. This study aimed to validate the IMmunotherapy Against GastrIc Cancer (IMAGiC) model, which was developed based on a previous study of four-gene and PD-L1 level, to predict immunotherapy response. We developed a clinical assay for formalin-fixed paraffin-embedded samples using quantitative real-time polymerase chain reaction to measure the expression level of the previously published four-gene set. The predictive performance was validated in a cohort of 89 patients with several advanced tumor types. The IMAGiC score was derived from tumor samples of 89 patients consisting of eight cancer types, and 73 out of 89 patients available for clinical response were analyzed with clinicopathological factors. The IMAGiC group (responder vs. non-responder) was determined with a specific value of the IMAGiC score as a cutoff, which was set by log-rank statistics for progression-free survival (PFS) divided the patients into 56 (76.7%) non-responders and 17 (23.3%) responders. Clinical responders (complete response/partial response) were higher in the IMAGiC responder group than in the non-responder group (70.6 vs. 21.4%). The median PFS of the IMAGiC responder group and non-responder was 20.8 months (95% CI 9.1-not reached) and 6.7 months (95% CI 4.9–11.1, p = 0.007), respectively. Among the 17 IMAGiC responders, 11 patients had tumor mutation burden-low and microsatellite-stable tumors. This study validated a predictive model based on a four-gene expression signature. Along with conventional biomarkers, our model could be useful for predicting response to immunotherapy in patients with advanced cancer. View Full-Text
Keywords: immune checkpoint inhibitors; prediction; biomarker; cancer; PD-L1 immune checkpoint inhibitors; prediction; biomarker; cancer; PD-L1
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MDPI and ACS Style

Kim, J.-C.; Heo, Y.-J.; Kang, S.-Y.; Lee, J.; Kim, K.-M. Validation of the Combined Biomarker for Prediction of Response to Checkpoint Inhibitor in Patients with Advanced Cancer. Cancers 2021, 13, 2316. https://doi.org/10.3390/cancers13102316

AMA Style

Kim J-C, Heo Y-J, Kang S-Y, Lee J, Kim K-M. Validation of the Combined Biomarker for Prediction of Response to Checkpoint Inhibitor in Patients with Advanced Cancer. Cancers. 2021; 13(10):2316. https://doi.org/10.3390/cancers13102316

Chicago/Turabian Style

Kim, Jin-Chul, You-Jeong Heo, So-Young Kang, Jeeyun Lee, and Kyoung-Mee Kim. 2021. "Validation of the Combined Biomarker for Prediction of Response to Checkpoint Inhibitor in Patients with Advanced Cancer" Cancers 13, no. 10: 2316. https://doi.org/10.3390/cancers13102316

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