Ping Tao1, Liang Hong2, Wenqing Tang3, Qun Lu1, Yanrong Zhao1, Si Zhang4, Lijie Ma2,5, Ruyi Xue3. 1. Department of Laboratory Medicine, Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 2. Department of General Surgery, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China. 3. Department of Gastroenterology and Hepatology, Shanghai Institute of Liver Diseases, Zhongshan Hospital, Fudan University, Shanghai, China. 4. Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai, China. 5. Department of General Surgery, Zhongshan Hospital (South), Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Abstract
BACKGROUND: Therapies targeting immune molecules have rapidly been adopted and advanced the treatment of hepatocellular carcinoma (HCC). Nonetheless, no studies have reported a systematic analysis between immunological profiles and clinical significance in HCC. METHODS: We comprehensively investigated immune patterns and systematically correlated 22 types of both adaptive and innate immune cells with genomic characteristics and clinical outcomes based on 370 HCC patients from The Cancer Genome Atlas (TCGA) database through a metagene approach (known as CIBERSORT). Based on the Quantitative Pathology Imaging and Analysis System coupled with integrated high-dimensional bioinformatics analysis, we further independently validated six immune subsets (CD4+ T cells, CD8+ T cells, CD20+ B cells, CD14+ monocytes, CD56+ NK cells, and CD68+ macrophages), and shortlisted three (CD4+ T cells, CD8+ T cells, and CD56+ NK cells) of which to investigate their association with clinical outcomes in two independent Zhongshan cohorts of HCC patients (n = 258 and n = 178). Patient prognosis was further evaluated by Kaplan-Meier analysis and univariate and multivariate regression analysis. RESULTS: By using the CIBERSORT method, the immunome landscape of HCC was constructed based on integrated transcriptomics analysis and multiplexed sequential immunohistochemistry. Further, the patients were categorized into four immune subgroups featured with distinct clinical outcomes. Strikingly, significant inter-tumoral and intra-tumoral immune heterogeneity was further identified according to the in-depth interrogation of the immune landscape. CONCLUSION: This work represents a potential useful resource for the immunoscore establishment for prognostic prediction in HCC patients.
BACKGROUND: Therapies targeting immune molecules have rapidly been adopted and advanced the treatment of hepatocellular carcinoma (HCC). Nonetheless, no studies have reported a systematic analysis between immunological profiles and clinical significance in HCC. METHODS: We comprehensively investigated immune patterns and systematically correlated 22 types of both adaptive and innate immune cells with genomic characteristics and clinical outcomes based on 370 HCC patients from The Cancer Genome Atlas (TCGA) database through a metagene approach (known as CIBERSORT). Based on the Quantitative Pathology Imaging and Analysis System coupled with integrated high-dimensional bioinformatics analysis, we further independently validated six immune subsets (CD4+ T cells, CD8+ T cells, CD20+ B cells, CD14+ monocytes, CD56+ NK cells, and CD68+ macrophages), and shortlisted three (CD4+ T cells, CD8+ T cells, and CD56+ NK cells) of which to investigate their association with clinical outcomes in two independent Zhongshan cohorts of HCC patients (n = 258 and n = 178). Patient prognosis was further evaluated by Kaplan-Meier analysis and univariate and multivariate regression analysis. RESULTS: By using the CIBERSORT method, the immunome landscape of HCC was constructed based on integrated transcriptomics analysis and multiplexed sequential immunohistochemistry. Further, the patients were categorized into four immune subgroups featured with distinct clinical outcomes. Strikingly, significant inter-tumoral and intra-tumoral immune heterogeneity was further identified according to the in-depth interrogation of the immune landscape. CONCLUSION: This work represents a potential useful resource for the immunoscore establishment for prognostic prediction in HCC patients.
Authors: Andrew X Zhu; Richard S Finn; Julien Edeline; Stephane Cattan; Sadahisa Ogasawara; Daniel Palmer; Chris Verslype; Vittorina Zagonel; Laetitia Fartoux; Arndt Vogel; Debashis Sarker; Gontran Verset; Stephen L Chan; Jennifer Knox; Bruno Daniele; Andrea L Webber; Scot W Ebbinghaus; Junshui Ma; Abby B Siegel; Ann-Lii Cheng; Masatoshi Kudo Journal: Lancet Oncol Date: 2018-06-03 Impact factor: 41.316
Authors: Lichun Ma; Maria O Hernandez; Yongmei Zhao; Monika Mehta; Bao Tran; Michael Kelly; Zachary Rae; Jonathan M Hernandez; Jeremy L Davis; Sean P Martin; David E Kleiner; Stephen M Hewitt; Kris Ylaya; Bradford J Wood; Tim F Greten; Xin Wei Wang Journal: Cancer Cell Date: 2019-10-03 Impact factor: 31.743