Yi Zhang1,2, Minhua Yu1,2, Ying Jing1,2, Jiejun Cheng3, Caiyan Zhang4, Lin Cheng1,2, Haijiao Lu1,2, Mei-Chun Cai4, Jie Wu5, Wenjing Wang1,2, Weihua Lou1,2, Lihua Qiu1,2, Li Tan6, Huaiwu Lu7, Xia Yin8,9, Guanglei Zhuang10,11, Wen Di12,13. 1. State Key Laboratory of Oncogenes and Related Genes, Department of Obstetrics and Gynecology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 2. Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 3. Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 4. State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 5. Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China. 6. Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China. 7. Department of Gynecologic Oncology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. 8. State Key Laboratory of Oncogenes and Related Genes, Department of Obstetrics and Gynecology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. yinxia2@aliyun.com. 9. Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. yinxia2@aliyun.com. 10. State Key Laboratory of Oncogenes and Related Genes, Department of Obstetrics and Gynecology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. zhuanglab@163.com. 11. Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. zhuanglab@163.com. 12. State Key Laboratory of Oncogenes and Related Genes, Department of Obstetrics and Gynecology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. diwen163@163.com. 13. Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. diwen163@163.com.
Abstract
BACKGROUND: We aimed to comprehensively evaluate the immunologic landscape at baseline and upon chemotherapy in cervical cancer. The information should aid ongoing clinical investigations of checkpoint blockade immunotherapies in this disease setting. METHODS: A series of 109 cervical carcinoma patients was retrospectively assayed before and after neoadjuvant chemotherapy. Tumour-infiltrating immune markers (CD3, CD4, CD8, CD20, CD56, CD68, PD-1, PD-L1) were assessed by immunohistochemistry. RNA sequencing analysis was performed on matched pre- and post-treatment fresh-frozen tissues. RESULTS: At diagnosis, diverse immune cell types including CD20+ B cells, CD3+ T cells, CD56+ natural killer (NK) cells, and CD68+ macrophages were detected in different proportions of cervical carcinoma. Unsupervised hierarchical clustering evidently showed that CD4+ and CD8+ T cell abundance correlated with PD-L1 expression. Based on the immune infiltration patterns, the patients could be stratified into four groups with prognostic relevance, namely, 'immuno-active', 'immuno-medial', 'immuno-NK', and 'immuno-deficient'. Neoadjuvant chemotherapy was associated with increased CD4, CD8, CD20, and CD56 signals, most prominently in good responders. Transcriptomic data corroborated the improved anticancer immunity and identified immunosuppressive CD200 upregulation following chemotherapeutic intervention. CONCLUSIONS: A subset of cervical cancer harbours active immune microenvironment, and chemotherapy treatment may further exert locoregional immunostimulation. Immune checkpoint inhibitors as combination or maintenance therapies warrant future exploration in clinic.
BACKGROUND: We aimed to comprehensively evaluate the immunologic landscape at baseline and upon chemotherapy in cervical cancer. The information should aid ongoing clinical investigations of checkpoint blockade immunotherapies in this disease setting. METHODS: A series of 109 cervical carcinomapatients was retrospectively assayed before and after neoadjuvant chemotherapy. Tumour-infiltrating immune markers (CD3, CD4, CD8, CD20, CD56, CD68, PD-1, PD-L1) were assessed by immunohistochemistry. RNA sequencing analysis was performed on matched pre- and post-treatment fresh-frozen tissues. RESULTS: At diagnosis, diverse immune cell types including CD20+ B cells, CD3+ T cells, CD56+ natural killer (NK) cells, and CD68+ macrophages were detected in different proportions of cervical carcinoma. Unsupervised hierarchical clustering evidently showed that CD4+ and CD8+ T cell abundance correlated with PD-L1 expression. Based on the immune infiltration patterns, the patients could be stratified into four groups with prognostic relevance, namely, 'immuno-active', 'immuno-medial', 'immuno-NK', and 'immuno-deficient'. Neoadjuvant chemotherapy was associated with increased CD4, CD8, CD20, and CD56 signals, most prominently in good responders. Transcriptomic data corroborated the improved anticancer immunity and identified immunosuppressive CD200 upregulation following chemotherapeutic intervention. CONCLUSIONS: A subset of cervical cancer harbours active immune microenvironment, and chemotherapy treatment may further exert locoregional immunostimulation. Immune checkpoint inhibitors as combination or maintenance therapies warrant future exploration in clinic.
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