机构:[1]Department of General Surgery, the First People's Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, China云南省第一人民医院
Background. Gastric cancer (GC) is the fourth most frequently diagnosed malignancy and the second leading cause of cancer-associated mortality worldwide. The tumor microenvironment, especially tumor-infiltrating immune cells (TIICs), exhibits crucial roles both in promoting and inhibiting cancer growth. The aim of the present study was to evaluate the landscape of TIICs and develop a prognostic nomogram in GC. Materials and Methods. A gene expression profile obtained from a dataset from The Cancer Genome Atlas (TCGA) was used to quantify the proportion of 22 TIICs in GC by the CIBERSORT algorithm. LASSO regression analysis and multivariate Cox regression were applied to select the best survival-related TIICs and develop an immunoscore formula. Based on the immunoscore and clinical information, a prognostic nomogram was built, and the predictive accuracy of it was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration plot. Furthermore, the nomogram was validated by data from the International Cancer Genome Consortium (ICGC) dataset. Results. In the GC samples, macrophages (25.3%), resting memory CD4 T cells (16.2%) and CD8 T cells (9.7%) were the most abundant among 22 TIICs. Seven TIICs were filtered out and used to develop an immunoscore formula. The AUC of the prognostic nomogram in the TCGA set was 0.772, similar to that in the ICGC set (0.730) and whole set (0.748), and significantly superior to that of TNM staging alone (0.591). The calibration plot demonstrated an outstanding consistency between the prediction and actual observation. Survival analysis revealed that patients with GC in the high-immunoscore group exhibited a poor clinical outcome. The result of multivariate analysis revealed that the immunoscore was an independent prognostic factor. Discussion. The immunoscore could be used to reinforce the clinical outcome prediction ability of the TNM staging system and provide a convenient tool for risk assessment and treatment selection for patients with GC.
第一作者机构:[1]Department of General Surgery, the First People's Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
通讯作者:
推荐引用方式(GB/T 7714):
Li Linhai,Ouyang Yiming,Wang Wenrong,et al.The landscape and prognostic value of tumor-infiltrating immune cells in gastric cancer[J].PEERJ.2019,7:doi:10.7717/peerj.7993.
APA:
Li, Linhai,Ouyang, Yiming,Wang, Wenrong,Hou, Dezhi&Zhu, Yu.(2019).The landscape and prognostic value of tumor-infiltrating immune cells in gastric cancer.PEERJ,7,
MLA:
Li, Linhai,et al."The landscape and prognostic value of tumor-infiltrating immune cells in gastric cancer".PEERJ 7.(2019)