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Tumor-infiltrating immune cells and prognosis in gastric cancer: a systematic review and meta-analysis.

ABSTRACT: Tumor-infiltrating immune cells are a pivotal component of the tumor microenvironment (TME), but their indicative role remains poorly defined. A meta-analysis was performed to reveal the prognostic efficiency of tumor-infiltrating immune cells in gastric cancer (GC). By searching PubMed and Embase, we identified a total of 35 eligible articles that involved 4888 patients. Random or fixed effect models were employed to extract pooled hazard ratios (HRs) with 95% confidence intervals (CIs). Our results indicated that high CD3+ lymphocyte infiltration in all the locations (AG), the tumor nest (TN), and the tumor stroma (TS) predicted better overall survival (OS) (HR=0.71, 95% CI=0.57-0.90; HR=0.58, 95% CI=0.42-0.80; and HR=0.50, 95% CI=0.37-0.68, respectively). CD8+ T cell infiltration in AG and FoxP3+ regulatory T cells (Tregs) in the tumor invasive margin (TM) were also associated with improved OS (HR=0.90, 95% CI=0.83-0.97; HR=0.65, 95% CI=0.48-0.87, respectively). However, contrasting results were found in the macrophage subset, with M2 in AG (HR=1.45, 95% CI=1.13-1.86) and the TN (HR=1.67, 95% CI=1.12-2.48) associated with worse OS. In summary, the combination of the densities and locations of tumor-infiltrating immune cells can be useful for predicting survival for GC patients, but additional research is needed to reinforce the reliability of this study's conclusions.

SUBMITTER: Jiang W

PROVIDER: S-EPMC5617507 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Tumor-infiltrating immune cells and prognosis in gastric cancer: a systematic review and meta-analysis.

Jiang Wen W Liu Ke K Guo Qing Q Cheng Ji J Shen Liming L Cao Yinghao Y Wu Jing J Shi Jianguo J Cao Heng H Liu Bo B Tao Kaixiong K Wang Guobin G Cai Kailin K

Oncotarget 20170503 37

Tumor-infiltrating immune cells are a pivotal component of the tumor microenvironment (TME), but their indicative role remains poorly defined. A meta-analysis was performed to reveal the prognostic efficiency of tumor-infiltrating immune cells in gastric cancer (GC). By searching PubMed and Embase, we identified a total of 35 eligible articles that involved 4888 patients. Random or fixed effect models were employed to extract pooled hazard ratios (HRs) with 95% confidence intervals (CIs). Our re ...[more]

PMID: 28977947

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Project description:Objective: Immune cells infiltrating has been proved to be associated with prognosis in gastric cancer (GC) by studies. This study aims to explore the prognosis value of infiltrating immune cells in gastric cancer. Methods: In our study, the CIBERSORT algorithm was used to calculate the fraction of 22 tumor-infiltrating immune cells (TIIC) in 100 normal and 300 tumor samples from the GEO cohort and 30 normal and 344 tumor samples from the TCGA cohort. Univariate and multivariate Cox regression were used to construct an immune risk score model. Multivariate cox regression was also used to validate whether our risk score model could predict prognosis in GC independently. Furthermore, the model was validated in different patient subgroups to test its independence. P<0.05 was considered statistically significant. Results: The results showed that the fraction of 3 immune cells increased in tumor tissues compared with normal tissues in both the GEO and TCGA cohort. Univariate cox regression analysis showed four cells significantly correlated with survival rate in GC (P<0.05). The immune risk score model was constructed based on the four cells through multivariate cox regression and further validated. The KM survival curve suggested that patients with high risk had poor prognosis than patients with low risk (P<0.05). ROC curve indicated the model was reliable (AUC= 0.67 in the GEO cohort, AUC = 0.65 in the TCGA cohort). Furthermore, multivariate Cox regression showed the model was an independent factor for overall survival predicting in GC (hazard ratio (HR) = 2.35, 95% confidence interval (CI) = 1.63~3.40 in the GEO cohort, HR = 2.87, 95% CI = 1.94~4.25 in the TCGA cohort). Finally, we validated the model in patient subgroups by the KM survival curve. Conclusion: In summary, tumor-infiltrating immune cells play an essential role in GC progression and affect the outcome of GC patients. The immune risk score can predict overall survival for GC independently, and high immune risk score is associated with poor prognosis.

Project description:BackgroundGastric 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 methodsA 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.ResultsIn 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.DiscussionThe 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.

Project description:BackgroundsThe high morbidity and mortality of lung cancer are serious public health problems. The prognosis of lung cancer and whether to apply immune checkpoint blockade (ICB) are currently urgent problems to be solved.MethodsUsing R software, we performed Kaplan-Meier (K-M) analysis, Cox regression analysis, functional enrichment analysis, Spearman correlation analysis, and the single-sample gene set enrichment analysis.ResultsOn the Tumor IMmune Estimation Resource (TIMER2.0) website, we calculated the abundance of tumor-infiltrating immune cells (TIICs) of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. B cell and myeloid dendritic cell (DC1) were independent prognostic factors for LUAD and LUSC patients, respectively. Enrichment analysis confirmed that genes highly related to B cell or DC1 were closely related to the immune activation of lung cancer patients. In terms of adaptive immune resistance markers, CD8A, CD8B, immunomodulators (immunostimulants, major histocompatibility complex, receptors, and chemokines), immune-related pathways, tumor microenvironment score, and TIICs, high B cell/DC1 infiltration tissue was inflamed and immune-activated and might benefit more from the ICB. Genes most related to B cell [CD19, toll-like receptor 10 (TLR10), and Fc receptor-like A (FCRLA)] and DC1 (ITGB2, LAPTM5, and SLC7A7) partially clarified the roles of B cell/DC1 in predicting ICB efficacy. Among the 186 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, there were three and four KEGG pathways, which partially explained the molecular mechanisms by which B cell and DC1 simultaneously predicted the prognosis and efficacy of immunotherapy, respectively. Among five immune subtypes, the abundance of B cell/DC1 and expression of six hub genes were higher in immune C2, C3, and C6.ConclusionB cell and DC1 could predict the prognosis and ICB efficacy of LUAD and LUSC patients, respectively. The six hub genes and seven KEGG pathways might be novel immunotherapy targets. Immune C2, C3, and C6 subtypes of lung cancer patients might benefit more from ICB therapy.

Dataset Information

Tumor-infiltrating immune cells and prognosis in gastric cancer: a systematic review and meta-analysis.

Publications

Tumor-infiltrating immune cells and prognosis in gastric cancer: a systematic review and meta-analysis.

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