Jian-Xian Lin1,2,3, Jun-Peng Lin1,2,3, Yong Weng4, Chen-Bin Lv5, Jian-Hua Chen6, Chuan-Yin Zhan6, Ping Li1,2,3, Jian-Wei Xie1,2,3, Jia-Bin Wang1,2,3, Jun Lu1,2,3, Qi-Yue Chen1,2,3, Long-Long Cao1,2,3, Mi Lin1,2,3, Wen-Xing Zhou4, Xiao-Jing Zhang4, Chao-Hui Zheng1,2,3, Li-Sheng Cai5, Yu-Bin Ma4, Chang-Ming Huang7,8,9. 1. Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou,, Fujian Province, China. 2. Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, Fujian Province, China. 3. Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China. 4. Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai Province, China. 5. Department of General Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, China. 6. Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, China. 7. Department of Gastric Surgery, Fujian Medical University Union Hospital, Fuzhou,, Fujian Province, China. hcmlr2002@163.com. 8. Key Laboratory of Ministry of Education of Gastrointestinal Cancer, Fujian Medical University, Fuzhou, Fujian Province, China. hcmlr2002@163.com. 9. Fujian Key Laboratory of Tumor Microbiology, Fujian Medical University, Fuzhou, China. hcmlr2002@163.com.
Abstract
BACKGROUND: The tumor immunosuppressive microenvironment can influence treatment response and outcomes. A previously validated immunosuppression scoring system (ISS) assesses multiple immune checkpoints in gastric cancer (GC) using tissue-based assays. We aimed to develop a radiological signature for non-invasive assessment of ISS and treatment outcomes. METHODS: A total of 642 patients with resectable GC from three centers were divided into four cohorts. Radiomic features were extracted from portal venous-phase CT images of GC. A radiomic signature for predicting ISS (RISS) was constructed using the least absolute shrinkage and selection operator (LASSO) regression method. Moreover, we investigated the value of the RISS in predicting survival and chemotherapy response. RESULTS: The RISS, which consisted of 10 selected features, showed good discrimination of immunosuppressive status in three independent cohorts (area under the curve = 0.840, 0.809, and 0.843, respectively). Multivariate analysis revealed that the RISS was an independent prognostic factor for both disease-free survival (DFS) and overall survival (OS) in all cohorts (all p < 0.05). Further analysis revealed that stage II and III GC patients with low RISS exhibited a favorable response to adjuvant chemotherapy (OS: hazard ratio [HR] 0.407, 95% confidence interval [CI] 0.284-0.584); DFS: HR 0.395, 95% CI 0.275-0.568). Furthermore, the RISS could predict prognosis and select stage II and III GC patients who could benefit from adjuvant chemotherapy independent of microsatellite instability status and Epstein-Barr virus status. CONCLUSION: The new, non-invasive radiomic signature could effectively predict the immunosuppressive status and prognosis of GC. Moreover, the RISS could help identify stage II and III GC patients most likely to benefit from adjuvant chemotherapy and avoid overtreatment.
BACKGROUND: The tumor immunosuppressive microenvironment can influence treatment response and outcomes. A previously validated immunosuppression scoring system (ISS) assesses multiple immune checkpoints in gastric cancer (GC) using tissue-based assays. We aimed to develop a radiological signature for non-invasive assessment of ISS and treatment outcomes. METHODS: A total of 642 patients with resectable GC from three centers were divided into four cohorts. Radiomic features were extracted from portal venous-phase CT images of GC. A radiomic signature for predicting ISS (RISS) was constructed using the least absolute shrinkage and selection operator (LASSO) regression method. Moreover, we investigated the value of the RISS in predicting survival and chemotherapy response. RESULTS: The RISS, which consisted of 10 selected features, showed good discrimination of immunosuppressive status in three independent cohorts (area under the curve = 0.840, 0.809, and 0.843, respectively). Multivariate analysis revealed that the RISS was an independent prognostic factor for both disease-free survival (DFS) and overall survival (OS) in all cohorts (all p < 0.05). Further analysis revealed that stage II and III GC patients with low RISS exhibited a favorable response to adjuvant chemotherapy (OS: hazard ratio [HR] 0.407, 95% confidence interval [CI] 0.284-0.584); DFS: HR 0.395, 95% CI 0.275-0.568). Furthermore, the RISS could predict prognosis and select stage II and III GC patients who could benefit from adjuvant chemotherapy independent of microsatellite instability status and Epstein-Barr virus status. CONCLUSION: The new, non-invasive radiomic signature could effectively predict the immunosuppressive status and prognosis of GC. Moreover, the RISS could help identify stage II and III GC patients most likely to benefit from adjuvant chemotherapy and avoid overtreatment.
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Authors: Martin Reck; Delvys Rodríguez-Abreu; Andrew G Robinson; Rina Hui; Tibor Csőszi; Andrea Fülöp; Maya Gottfried; Nir Peled; Ali Tafreshi; Sinead Cuffe; Mary O'Brien; Suman Rao; Katsuyuki Hotta; Melanie A Leiby; Gregory M Lubiniecki; Yue Shentu; Reshma Rangwala; Julie R Brahmer Journal: N Engl J Med Date: 2016-10-08 Impact factor: 91.245
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