Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target
Background/Aims Identifying patients with intrahepatic cholangiocarcinoma (ICC) likely to benefit from immunochemotherapy, the new front-line treatment, remains challenging. We aimed to unveil a novel radiotranscriptomic signature that can facilitate treatment response prediction by multi-omics inte...
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| Format: | Article |
| Language: | English |
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Korean Association for the Study of the Liver
2025-07-01
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| Series: | Clinical and Molecular Hepatology |
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| Online Access: | http://e-cmh.org/upload/pdf/cmh-2024-0895.pdf |
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| author | Gu-Wei Ji Zheng-Gang Xu Shuo-Chen Liu Shu-Ya Cao Chen-Yu Jiao Ming Lu Biao Zhang Yue Yang Qing Xu Xiao-Feng Wu Ke Wang Yong-Xiang Xia Xiang-Cheng Li Xue-Hao Wang |
| author_facet | Gu-Wei Ji Zheng-Gang Xu Shuo-Chen Liu Shu-Ya Cao Chen-Yu Jiao Ming Lu Biao Zhang Yue Yang Qing Xu Xiao-Feng Wu Ke Wang Yong-Xiang Xia Xiang-Cheng Li Xue-Hao Wang |
| author_sort | Gu-Wei Ji |
| collection | DOAJ |
| description | Background/Aims Identifying patients with intrahepatic cholangiocarcinoma (ICC) likely to benefit from immunochemotherapy, the new front-line treatment, remains challenging. We aimed to unveil a novel radiotranscriptomic signature that can facilitate treatment response prediction by multi-omics integration and multiscale modelling. Methods We analyzed bulk, single-cell and spatial transcriptomic data comprising 457 ICC patients to identify an immune-related score (IRS), followed by decoding its spatial immune context. We mapped radiomics profiles onto spatial-specific IRS using machine learning to define a novel radiotranscriptomic signature, followed by multi-scale and multi-cohort validation covering 331 ICC patients. The signature was further explored for the potential therapeutic target from in vitro to in vivo. Results We revealed a novel 3-gene (PLAUR, CD40LG, and FGFR4) IRS whose down-regulation correlated with better survival and improved sensitivity to immunochemotherapy. We highlighted functional IRS-immune interactions within tumor epithelium, rather than stromal compartment, irrespective of geospatial locations. Machine learning pipeline identified the optimal 3-feature radiotranscriptomic signature that was well-validated by immunohistochemical assays in molecular cohort, exhibited favorable external prognostic validity with C-index over 0.64 in resection cohort, and predicted treatment response with an area under the curve of up to 0.84 in immunochemotherapy cohort. We also showed that anti-uPAR/PLAUR alone or in combination with anti-programmed cell death protein 1 therapy remarkably curbed tumor growth, using in vitro ICC cell lines and in vivo humanized ICC patient-derived xenograft mouse models. Conclusions This proof-of-concept study sheds light on the spatially-resolved radiotranscriptomic signature to improve patient selection for emerging immunochemotherapy and high-order immunotherapy combinations in ICC. |
| format | Article |
| id | doaj-art-4dbd06206a5b42efad47fc8a04e2f77e |
| institution | Kabale University |
| issn | 2287-2728 2287-285X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Korean Association for the Study of the Liver |
| record_format | Article |
| series | Clinical and Molecular Hepatology |
| spelling | doaj-art-4dbd06206a5b42efad47fc8a04e2f77e2025-08-20T03:50:06ZengKorean Association for the Study of the LiverClinical and Molecular Hepatology2287-27282287-285X2025-07-0131393595910.3350/cmh.2024.08952172Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic targetGu-Wei Ji0Zheng-Gang Xu1Shuo-Chen Liu2Shu-Ya Cao3Chen-Yu Jiao4Ming Lu5Biao Zhang6Yue Yang7Qing Xu8Xiao-Feng Wu9Ke Wang10Yong-Xiang Xia11Xiang-Cheng Li12Xue-Hao Wang13 Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Department of General Surgery, Yancheng No.1 People’s Hospital, Yancheng, China Department of General Surgery, The First People’s Hospital of Changzhou, Changzhou, China Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaBackground/Aims Identifying patients with intrahepatic cholangiocarcinoma (ICC) likely to benefit from immunochemotherapy, the new front-line treatment, remains challenging. We aimed to unveil a novel radiotranscriptomic signature that can facilitate treatment response prediction by multi-omics integration and multiscale modelling. Methods We analyzed bulk, single-cell and spatial transcriptomic data comprising 457 ICC patients to identify an immune-related score (IRS), followed by decoding its spatial immune context. We mapped radiomics profiles onto spatial-specific IRS using machine learning to define a novel radiotranscriptomic signature, followed by multi-scale and multi-cohort validation covering 331 ICC patients. The signature was further explored for the potential therapeutic target from in vitro to in vivo. Results We revealed a novel 3-gene (PLAUR, CD40LG, and FGFR4) IRS whose down-regulation correlated with better survival and improved sensitivity to immunochemotherapy. We highlighted functional IRS-immune interactions within tumor epithelium, rather than stromal compartment, irrespective of geospatial locations. Machine learning pipeline identified the optimal 3-feature radiotranscriptomic signature that was well-validated by immunohistochemical assays in molecular cohort, exhibited favorable external prognostic validity with C-index over 0.64 in resection cohort, and predicted treatment response with an area under the curve of up to 0.84 in immunochemotherapy cohort. We also showed that anti-uPAR/PLAUR alone or in combination with anti-programmed cell death protein 1 therapy remarkably curbed tumor growth, using in vitro ICC cell lines and in vivo humanized ICC patient-derived xenograft mouse models. Conclusions This proof-of-concept study sheds light on the spatially-resolved radiotranscriptomic signature to improve patient selection for emerging immunochemotherapy and high-order immunotherapy combinations in ICC.http://e-cmh.org/upload/pdf/cmh-2024-0895.pdfintrahepatic cholangiocarcinomaradiogenomicsmulti-omics profilingmachine learningprediction model |
| spellingShingle | Gu-Wei Ji Zheng-Gang Xu Shuo-Chen Liu Shu-Ya Cao Chen-Yu Jiao Ming Lu Biao Zhang Yue Yang Qing Xu Xiao-Feng Wu Ke Wang Yong-Xiang Xia Xiang-Cheng Li Xue-Hao Wang Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target Clinical and Molecular Hepatology intrahepatic cholangiocarcinoma radiogenomics multi-omics profiling machine learning prediction model |
| title | Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| title_full | Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| title_fullStr | Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| title_full_unstemmed | Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| title_short | Radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| title_sort | radiogenomics of intrahepatic cholangiocarcinoma predicts immunochemotherapy response and identifies therapeutic target |
| topic | intrahepatic cholangiocarcinoma radiogenomics multi-omics profiling machine learning prediction model |
| url | http://e-cmh.org/upload/pdf/cmh-2024-0895.pdf |
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