Haotian Liao1,2, Zhen Zhang3, Jie Chen3, Mingheng Liao1,2, Lin Xu1,2, Zhenru Wu4, Kefei Yuan1,2, Bin Song5, Yong Zeng6,7. 1. Department of Liver Surgery, Liver Transplantation Division, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. 2. Laboratory of Liver Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. 3. Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. 4. Laboratory of Pathology, Department of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. 5. Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. songb_radiology@163.com. 6. Department of Liver Surgery, Liver Transplantation Division, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. zengyong@medmail.com.cn. 7. Laboratory of Liver Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China. zengyong@medmail.com.cn.
Abstract
BACKGROUND: To help identify potential hepatocellular carcinoma (HCC) candidates for immunotherapies, we aimed to develop and validate a radiomics-based biomarker (Rad score) to predict the infiltration of tumor-infiltrating CD8+ T cells in HCC patients, and to evaluate the correlation of Rad score with tumor immune characteristics. METHODS: Overall, 142 HCC patients (n = 100 and n = 42 in the training and validation sets, respectively) were subjected to radiomic feature extraction. Imaging features and immunochemistry data of patients in the training set were subjected to elastic-net regularized regression analysis to predict the level of CD8+ T cell infiltration. RESULTS: A Rad score for CD8+ T-cell infiltration, which contained seven variables, was developed and was validated in the validation set (area under the curve [AUC]: training set 0.751, 95% confidence interval [CI] 0.656-0.846; validation set 0.705, 95% CI 0.547-0.863). The decision curve indicated the clinical usefulness of the Rad score. A higher Rad score correlated with superior overall and disease-free survival outcomes (p = 0.012 and 0.0088, respectively). Using the pathological slides, we found that the Rad score positively correlated with the percentage of tumor-infiltrating lymphocytes (TILs; Spearman rho = 0.51, p < 0.0001). Moreover, the Rad score could also discriminate inflamed tumors from immune-desert and immune-excluded tumors (Kruskal-Wallis, p < 0.0001), and higher Rad scores could be found in patients with positive programmed cell death ligand 1 expression in tumor/immune cells, as well as those with positive programmed cell death protein 1 expression. CONCLUSION: The newly developed Rad score was a powerful predictor of CD8+ T-cell infiltration, which could be useful in identifying potential HCC patients who can benefit from immunotherapies when validated in large-scale prospective cohorts.
BACKGROUND: To help identify potential hepatocellular carcinoma (HCC) candidates for immunotherapies, we aimed to develop and validate a radiomics-based biomarker (Rad score) to predict the infiltration of tumor-infiltrating CD8+ T cells in HCCpatients, and to evaluate the correlation of Rad score with tumor immune characteristics. METHODS: Overall, 142 HCCpatients (n = 100 and n = 42 in the training and validation sets, respectively) were subjected to radiomic feature extraction. Imaging features and immunochemistry data of patients in the training set were subjected to elastic-net regularized regression analysis to predict the level of CD8+ T cell infiltration. RESULTS: A Rad score for CD8+ T-cell infiltration, which contained seven variables, was developed and was validated in the validation set (area under the curve [AUC]: training set 0.751, 95% confidence interval [CI] 0.656-0.846; validation set 0.705, 95% CI 0.547-0.863). The decision curve indicated the clinical usefulness of the Rad score. A higher Rad score correlated with superior overall and disease-free survival outcomes (p = 0.012 and 0.0088, respectively). Using the pathological slides, we found that the Rad score positively correlated with the percentage of tumor-infiltrating lymphocytes (TILs; Spearman rho = 0.51, p < 0.0001). Moreover, the Rad score could also discriminate inflamed tumors from immune-desert and immune-excluded tumors (Kruskal-Wallis, p < 0.0001), and higher Rad scores could be found in patients with positive programmed cell death ligand 1 expression in tumor/immune cells, as well as those with positive programmed cell death protein 1 expression. CONCLUSION: The newly developed Rad score was a powerful predictor of CD8+ T-cell infiltration, which could be useful in identifying potential HCCpatients who can benefit from immunotherapies when validated in large-scale prospective cohorts.
Authors: Emily Harding-Theobald; Jeremy Louissaint; Bharat Maraj; Edward Cuaresma; Whitney Townsend; Mishal Mendiratta-Lala; Amit G Singal; Grace L Su; Anna S Lok; Neehar D Parikh Journal: Aliment Pharmacol Ther Date: 2021-08-12 Impact factor: 9.524