TY - JOUR
T1 - Tumor-infiltrating immune cells in hepatocellular carcinoma
T2 - Tregs is correlated with poor overall survival
AU - Yu, Si Zhe
AU - Wang, Yu
AU - Hou, Jia
AU - Li, Wen Yuan
AU - Wang, Xiao
AU - Xiang, Luo Cheng Ling
AU - Tan, De Li
AU - Wang, Wen Juan
AU - Jiang, Li Li
AU - Claret, Francois X.
AU - Jiao, Min
AU - Guo, Hui
N1 - Publisher Copyright:
© 2020 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020
Y1 - 2020
N2 - Systematic interrogation of tumor-infiltrating immune cells (TIICs) is key to the prediction of clinical outcome and development of immunotherapies. However, little is known about the TIICs of hepatocellular carcinoma (HCC) and its impact on the prognosis of patients and potential for immunotherapy. We applied CIBERSORT of 1090 tumors to infer the infiltration of 22 subsets of TIICs using gene expression data. Unsupervised clustering analysis by 22 TIICs revealed 4 clusters of tumors, mainly defined by macrophages and T cells, with distinct prognosis and associations with immune checkpoint molecules, including PD-1, CD274, CTLA-4, LAG-3 and IFNG. We found tumors with decreased number of M1 macrophages or increased regulatory T cells were associated with poor prognosis. Based on the multivariate Cox analysis, a nomogram was also established for clinical application. In conclusion, composition of the TIICs in HCC was quite different, which is an important determinant of prognosis with great potential to identify candidates for immunotherapy.
AB - Systematic interrogation of tumor-infiltrating immune cells (TIICs) is key to the prediction of clinical outcome and development of immunotherapies. However, little is known about the TIICs of hepatocellular carcinoma (HCC) and its impact on the prognosis of patients and potential for immunotherapy. We applied CIBERSORT of 1090 tumors to infer the infiltration of 22 subsets of TIICs using gene expression data. Unsupervised clustering analysis by 22 TIICs revealed 4 clusters of tumors, mainly defined by macrophages and T cells, with distinct prognosis and associations with immune checkpoint molecules, including PD-1, CD274, CTLA-4, LAG-3 and IFNG. We found tumors with decreased number of M1 macrophages or increased regulatory T cells were associated with poor prognosis. Based on the multivariate Cox analysis, a nomogram was also established for clinical application. In conclusion, composition of the TIICs in HCC was quite different, which is an important determinant of prognosis with great potential to identify candidates for immunotherapy.
UR - https://www.scopus.com/pages/publications/85082828329
U2 - 10.1371/journal.pone.0231003
DO - 10.1371/journal.pone.0231003
M3 - 文章
C2 - 32240238
AN - SCOPUS:85082828329
SN - 1932-6203
VL - 15
JO - PLoS ONE
JF - PLoS ONE
IS - 4
M1 - e0231003
ER -