{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T06:52:28Z","timestamp":1791183148802,"version":"4.1.0"},"reference-count":25,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T00:00:00Z","timestamp":1791072000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T00:00:00Z","timestamp":1791072000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2023A04J2212"],"award-info":[{"award-number":["2023A04J2212"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014219","name":"National Science Fund for Distinguished Young Scholars","doi-asserted-by":"publisher","award":["GWJJMB202510022036"],"award-info":[{"award-number":["GWJJMB202510022036"]}],"id":[{"id":"10.13039\/501100014219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Health Care Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The T cell\u2010inflamed gene expression profile (GEP) provides a biomarker for immunotherapy response across various cancers. However, specific biomarkers for immunotherapy response in hepatocellular carcinoma (HCC) are lacking. In this study, we established a computed tomography (CT)\u2010based radiomics model to predict the T cell\u2010inflamed GEP and immunotherapy response in HCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This retrospective, multicenter study included 270 patients with HCC, who were divided into training (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009227) and test sets (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200943). All included patients had available contrast\u2010enhanced CT and RNA sequencing data. The T cell\u2010inflamed GEP consisted of 18 genes derived from RNA sequencing data, and patients were classified into GEP\u2010high and GEP\u2010low groups. A support vector machine was used to establish the radiomics model. The immunotherapy dataset comprised patients who underwent contrast\u2010enhanced CT and received anti\u2010programmed cell death protein 1\/programmed cell death ligand 1\u00a0immunotherapy at three hospitals (209 lesions). This immunotherapy dataset was used to evaluate the association between the predicted GEP status and immunotherapy response. Additionally, overall survival was compared between patients with and without predicted GEP\u2010high lesions in the immunotherapy dataset.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The areas under the receiver operating characteristic curve of the radiomics model for predicting GEP in the training and test sets were 0.824 (95% confidence interval [CI] = 0.757\u20130.892) and 0.827 (95% CI: 0.674\u20130.980), respectively. In the immunotherapy dataset, the response rate of liver lesions at 6 months was significantly higher in the GEP\u2010high group than in the GEP\u2010low group (48.1%\n                      <jats:italic>vs<\/jats:italic>\n                      . 9.3%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). The areas under the receiver operating characteristic curve of the radiomics model for predicting immunotherapy response at 6 months was 0.750 (95% CI: 0.614\u20130.886). Median overall survival among patients with GEP\u2010high lesions was 17.5 months, which notably exceeded the value of 8.3 months for patients without GEP\u2010high lesions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study provides the first CT\u2010based radiomics model for predicting the T cell\u2010inflamed GEP in HCC. This model highlights the potential of the T cell\u2010inflamed GEP as a noninvasive biomarker to help guide immunotherapy selection.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/hcs2.70106","type":"journal-article","created":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T06:25:37Z","timestamp":1791181537000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Computed Tomography Radiomics Approach for Assessing the T Cell\u2010Inflamed Gene Expression Profile in Hepatocellular Carcinoma and Its Association With Immunotherapy Response"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7643-1054","authenticated-orcid":false,"given":"Mimi","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Radiology, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiyu","family":"Sun","sequence":"additional","affiliation":[{"name":"Center of Gastrointestinal Surgery, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dasheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Medical AI Lab, School of Biomedical Engineering Shenzhen University Medical School, Shenzhen University Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujian","family":"Zou","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Dongguan Hospital Southern Medical University Dongguan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Radiology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer Sun Yat\u2010sen University Cancer Center Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"Clinical Trials Unit, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanjing","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Precision Medicine, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenpeng","family":"Peng","sequence":"additional","affiliation":[{"name":"Department of Radiology, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou 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Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"},{"name":"Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou 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