The clinical significance of memory T cells and its subsets in gastric cancer

Predictive model using four ferroptosis-related genes accurately predicts gastric cancer prognosis

BACKGROUND

Gastric cancer (GC) is a common malignancy of the digestive system. According to global 2018 cancer data, GC has the fifth-highest incidence and the third-highest fatality rate among malignant tumors. More than 60% of GC are linked to infection with Helicobacter pylori (H. pylori), a gram-negative, active, microaerophilic, and helical bacterium. This parasite induces GC by producing toxic factors, such as cytotoxin-related gene A, vacuolar cytotoxin A, and outer membrane proteins. Ferroptosis, or iron-dependent programmed cell death, has been linked to GC, although there has been little research on the link between H. pylori infection-related GC and ferroptosis.

AIM

To identify coregulated differentially expressed genes among ferroptosis-related genes (FRGs) in GC patients and develop a ferroptosis-related prognostic model with discrimination ability.

METHODS

Gene expression profiles of GC patients and those with H. pylori-associated GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The FRGs were acquired from the FerrDb database. A ferroptosis-related gene prognostic index (FRGPI) was created using least absolute shrinkage and selection operator-Cox regression. The predictive ability of the FRGPI was validated in the GEO cohort. Finally, we verified the expression of the hub genes and the activity of the ferroptosis inducer FIN56 in GC cell lines and tissues.

RESULTS

Four hub genes were identified (NOX4, MTCH1, GABARAPL2, and SLC2A3) and shown to accurately predict GC and H. pylori-associated GC. The FRGPI based on the hub genes could independently predict GC patient survival; GC patients in the high-risk group had considerably worse overall survival than did those in the low-risk group. The FRGPI was a significant predictor of GC prognosis and was strongly correlated with disease progression. Moreover, the gene expression levels of common immune checkpoint proteins dramatically increased in the high-risk subgroup of the FRGPI cohort. The hub genes were also confirmed to be highly overexpressed in GC cell lines and tissues and were found to be primarily localized at the cell membrane. The ferroptosis inducer FIN56 inhibited GC cell proliferation in a dose-dependent manner.

CONCLUSION

In this study, we developed a predictive model based on four FRGs that can accurately predict the prognosis of GC patients and the efficacy of immunotherapy in this population.

Integrated single-cell sequencing, spatial transcriptome sequencing and bulk RNA sequencing highlights the molecular characteristics of parthanatos in gastric cancer

BACKGROUND

Parthanatos is a novel programmatic form of cell death based on DNA damage and PARP-1 dependency. Nevertheless, its specific role in the context of gastric cancer (GC) remains uncertain.

METHODS

In this study, we integrated multi-omics algorithms to investigate the molecular characteristics of parthanatos in GC. A series of bioinformatics algorithms were utilized to explore clinical heterogeneity of GC and further predict the clinical outcomes.

RESULTS

Firstly, we conducted a comprehensive analysis of the omics features of parthanatos in various human tumors, including genomic mutations, transcriptome expression, and prognostic relevance. We successfully identified 7 cell types within the GC microenvironment: myeloid cell, epithelial cell, T cell, stromal cell, proliferative cell, B cell, and NK cell. When compared to adjacent non-tumor tissues, single-cell sequencing results from GC tissues revealed elevated scores for the parthanatos pathway across multiple cell types. Spatial transcriptomics, for the first time, unveiled the spatial distribution characteristics of parthanatos signaling. GC patients with different parthanatos signals often exhibited distinct immune microenvironment and metabolic reprogramming features, leading to different clinical outcomes. The integration of parthanatos signaling and clinical indicators enabled the creation of novel survival curves that accurately assess patients' survival times and statuses.

CONCLUSIONS

In this study, the molecular characteristics of parthanatos' unicellular and spatial transcriptomics in GC were revealed for the first time. Our model based on parthanatos signals can be used to distinguish individual heterogeneity and predict clinical outcomes in patients with GC.

Construction of iron metabolism-related prognostic features of gastric cancer based on RNA sequencing and TCGA database

BACKGROUND

Researches have manifested that the disorder of iron metabolism is participated in Gastric cancer (GC), but whether iron metabolism-relevant genes (IMRGs) is related to the survival outcome of GC remain unknown.

METHODS

Eleven tumor as well as nine adjacent normal tissues from GC patients were underwent mRNA sequencing, and the The Cancer Genome Atlas Stomach Cancer (TCGA-STAD) datasets were acquired from the TCGA database. Cox analyses and least absolute shrinkage and selection operator (LASSO) regression were applied to build a IMRGs signature. The relationship between signature genes and the infiltration profiling of 24 immune cells were investigated using single-sample GSEA (ssGSEA). Meanwhile, the potential biological significance, genes that act synergistically with signature genes, and the upstream regulatory targets were predicted. Finally, the abundance of the signature genes were measured via the quantitative real-time PCR (qRT-PCR).

RESULTS

A IMRGs signature was constructed according to the expression and corresponding coefficient of DOHH, P4HA3 and MMP1 (The Schoenfeld individual test showed risk score was not significant with P values = 0.83). The prognostic outcome of patients in the high-risk group was terrible (p < 0.05). Receiver operating characteristic (ROC) curves confirmed that the IMRGs signature presented good efficiency for predicting GC prognosis (AUC > 0.6). The nomogram was performed well for clinical utilize (C-index = 0.60), and the MMP1 expression significantly increased in the cohorts at age > 60 and Stage II-IV (p < 0.05). The positive correlation of P4HA3 and MMP1 expression as well as the negative correlation of DOHH expression with risk score (p < 0.0001) and worse prognosis (p < 0.05) were detected as well. Furthermore, 11 differential immune cells were associated with these signature genes (most p < 0.01). Finally, qRT-PCR revealed that the abundance of DOHH, P4HA3 and MMP1 were high in tumor cases, indicating the complex mechanism between the high expression of DOHH as a protective factor and the high expression of P4HA3 and MMP1 as the risk factors in the development of GC.

CONCLUSION

An iron metabolism-related signature was constructed and has significant values for foretelling the OS of GC.

Identification and validation of a novel survival prediction model based on the T-cell phenotype in the tumor immune microenvironment and peripheral blood for gastric cancer prognosis

BACKGROUND

The correlation and difference in T-cell phenotypes between peripheral blood lymphocytes (PBLs) and the tumor immune microenvironment (TIME) in patients with gastric cancer (GC) is not clear. We aimed to characterize the phenotypes of CD8⁺ T cells in tumor infiltrating lymphocytes (TILs) and PBLs in patients with different outcomes and to establish a useful survival prediction model.

METHODS

Multiplex immunofluorescence staining and flow cytometry were used to detect the expression of inhibitory molecules (IMs) and active markers (AMs) in CD8⁺TILs and PBLs, respectively. The role of these parameters in the 3-year prognosis was assessed by receiver operating characteristic analysis. Then, we divided patients into two TIME clusters (TIME-A/B) and two PBL clusters (PBL-A/B) by unsupervised hierarchical clustering based on the results of multivariate analysis, and used the Kaplan-Meier method to analyze the difference in prognosis between each group. Finally, we constructed and compared three survival prediction models based on Cox regression analysis, and further validated the efficiency and accuracy in the internal and external cohorts.

RESULTS

The percentage of PD-1⁺CD8⁺TILs, TIM-3⁺CD8⁺TILs, PD-L1⁺CD8⁺TILs, and PD-L1⁺CD8⁺PBLs and the density of PD-L1⁺CD8⁺TILs were independent risk factors, while the percentage of TIM-3⁺CD8⁺PBLs was an independent protective factor. The patients in the TIME-B group showed a worse 3-year overall survival (OS) (HR: 3.256, 95% CI 1.318-8.043, P = 0.006), with a higher density of PD-L1⁺CD8⁺TILs (P < 0.001) and percentage of PD-1⁺CD8⁺TILs (P = 0.017) and PD-L1⁺CD8⁺TILs (P < 0.001) compared to the TIME-A group. The patients in the PBL-B group showed higher positivity for PD-L1⁺CD8⁺PBLs (P = 0.042), LAG-3⁺CD8⁺PBLs (P < 0.001), TIM-3⁺CD8⁺PBLs (P = 0.003), PD-L1⁺CD4⁺PBLs (P = 0.001), and LAG-3⁺CD4⁺PBLs (P < 0.001) and poorer 3-year OS (HR: 0.124, 95% CI 0.017-0.929, P = 0.015) than those in the PBL-A group. In our three survival prediction models, Model 3, which was based on the percentage of TIM-3⁺CD8⁺PBLs, PD-L1⁺CD8⁺TILs and PD-1⁺CD8⁺TILs, showed the best sensitivity (0.950, 0.914), specificity (0.852, 0.857) and accuracy (κ = 0.787, P < 0.001; κ = 0.771, P < 0.001) in the internal and external cohorts, respectively.

CONCLUSION

We established a comprehensive and robust survival prediction model based on the T-cell phenotype in the TIME and PBLs for GC prognosis.

Construction of a novel prognostic signature based on the composition of tumor-infiltrating immune cells in clear cell renal cell carcinoma

Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research. The ImmuCellAI tool was employed to estimate the abundance of 24 TIICs and further survival analysis explored the prognostic values of TIICs in ccRCC. In addition, the expression levels of immunosuppressive molecules (PDL1, PD1, LAG3, and CTLA4) in the high- and low-risk groups were explored. Various subtypes of TIICs had distinct infiltrating features and most TIICs exhibited dysregulated abundance between normal and tumor tissues. Moreover, specific kinds of TIICs had encouraging prognostic values in ccRCC. Further analysis constructed a 4-TIICs signature to evaluate the prognosis of ccRCC patients. Cox regression analyses confirmed the independent prognostic role of the signature in ccRCC. Moreover, immunosuppressive molecules, including PD1, LAG3, and CTLA4, were significantly upregulated in the high-risk group and predicted poor prognosis. However, PDL1 was not changed between high- and low-risk groups and could not predict poor prognosis. To sum up, our research explored the landscape of TIICs in ccRCC and established a novel 4-TIIC prognostic signature, which could effectively predict the prognosis for patients with ccRCC. Based on this signature, we also concluded that PDL1 may not predict prognosis in ccRCC.

Single-cell analysis of gastric pre-cancerous and cancer lesions reveals cell lineage diversity and intratumoral heterogeneity

Single-cell transcriptomic profiles analysis has proposed new insights for understanding the behavior of human gastric cancer (GC). GC offers a unique model of intratumoral heterogeneity. However, the specific classes of cells involved in carcinogenetic passage, and the tumor microenvironment of stromal cells was poorly understood. We characterized the heterogeneous cell population of precancerous lesions and gastric cancer at the single-cell resolution by RNA sequencing. We identified 10 gastric cell subtypes and showed the intestinal and diffuse-type cancer were characterized by different cell population. We found that the intestinal and diffuse-type cancer cells have the differential metaplastic cell lineages: intestinal-type cancer cells differentiated along the intestinal metaplasia lineage while diffuse-type cancer cells resemble de novo pathway. We observed an enriched CCND1 mutation in premalignant disease state and discovered cancer-associated fibroblast cells harboring pro-stemness properties. In particular, tumor cells could be categorized into previously proposed molecular subtypes and harbored specific subtype of malignant cell with high expression level of epithelial-myofibroblast transition which was correlated with poor clinical prognosis. In addition to intratumoral heterogeneity, the analysis revealed different cellular lineages were responsible for potential carcinogenetic pathways. Single-cell transcriptomes analysis of gastric pre-cancerous lesions and cancer may provide insights for understanding GC cell behavior, suggesting potential targets for the diagnosis and treatment of GC.

A Comprehensive Bioinformatic Analysis of NOTCH Pathway Involvement in Stomach Adenocarcinoma

Background

Activation of NOTCH signaling pathways, which are key regulators of multiple cellular functions, has been frequently implicated in cancer pathogenesis, and NOTCH inhibitors have received much recent focus in the context of cancer therapeutics. However, the role and possible involvement of NOTCH pathways in stomach adenocarcinoma (STAD) are unclear. Here, putative regulatory mechanisms and functions of NOTCH pathways in STAD were investigated.

Methods

Publicly available data from the TCGA-STAD database were utilized to explore the involvement of canonical NOTCH pathways in STAD by analyzing RNA expression levels of NOTCH receptors, ligands, and downstream genes. Statistical analysis of the data pertaining to cancer and noncancerous samples was performed using R software packages and public databases/webservers.

Results

Significant differential gene expression between control and STAD samples was noted for all NOTCH receptors (NOTCH1, 2, 3, and 4), the delta-like NOTCH ligands (DLL-3 and 4), and typical downstream genes (HES1 and HEY1). Four genes (NOTCH1, NOTCH2, NOTCH3, and HEY1) presented prognostic values for the STAD outcome in terms of overall survival. Functional enrichment analysis indicated that NOTCH family genes-strongly correlated genes were mainly enriched in several KEGG signaling pathways such as the PI3K-Akt signaling pathway, human papillomavirus infection, focal adhesion, Rap1 signaling pathway, and ECM-receptor interaction. Gene set enrichment analysis (GSEA) results showed that NOTCH family genes-significantly correlated genes were mainly enriched in four signaling pathways, ECM (extracellular matrix), tumor angiogenesis, inflammatory response, and immune regulation.

Conclusions

NOTCH family genes may play an essential role in the progression of STAD by modulating immune cells and mediating ECM synthesis, angiogenesis, focal adhesion, and PI3K-Akt signaling. Multiple NOTCH family genes are valuable candidate biomarkers or therapeutic targets for the management of STAD.

Immune Landscape of Gastric Carcinoma Tumor Microenvironment Identifies a Peritoneal Relapse Relevant Immune Signature

Background

Gastric cancer (GC) still represents the third leading cause of cancer-related death worldwide. Peritoneal relapse (PR) is the most frequent metastasis occurring among patients with advanced gastric cancer. Increasingly more evidence have clarified the tumor immune microenvironment (TIME) may predict survival and have clinical significance in GC. However, tumor-transcriptomics based immune signatures derived from immune profiling have not been established for predicting the peritoneal recurrence of the advanced GC.

Methods

In this study, we depict the immune landscape of GC by using transcriptome profiling and clinical characteristics retrieved from GSE62254 of Gene Expression Omnibus (GEO). Immune cell infiltration score was evaluated via single-sample gene set enrichment (ssGSEA) analysis algorithm. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to select the valuable immune cells and construct the final model for the prediction of PR. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to check the accuracy of PRIs. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to explore the molecular pathways associated with PRIs.

Results

A peritoneal recurrence related immune score (PRIs) with 10 immune cells was constructed. Compared to the low-PRIs group, the high-PRIs group had a greater risk. The upregulation of the focal adhesion signaling was observed in the high-PRIs subtype by GSEA and KEGG. Multivariate analysis found that both in the internal training cohort and the internal validation cohort, PRIs was a stable and independent predictor for PR. A nomogram that integrated clinicopathological features and PRIs to predict peritoneal relapse was constructed. Subgroup analysis indicated that the PRIs could obviously distinguish peritoneal recurrence in different molecular subtypes, pathological stages and Lauren subtypes, in which PRIs of Epithelial-Mesenchymal Transitions (EMT) subtype, III-IV stage and diffuse subtype are higher respectively.

Conclusion

Overall, we performed a comprehensive evaluation of the immune landscape of GC and constructed a predictive PR model based on the immune cell infiltration. The PRIs represents novel promising feature of predicting peritoneal recurrence of GC and sheds light on the improvement of the personalized management of GC patients after surgery.

Tumor-Infiltrating Lymphocyte-Based Risk Score for Predicting Prognosis in Gastric Cancer

Tumor-infiltrating lymphocytes (TILs) in gastric cancer are closely related to clinical prognosis; however, little is known regarding the immune microenvironment in this disease. Thus, RNA-sequencing data from gastric cancer patients were downloaded from the Gene Expression Omnibus (GEO). The proportion of immune cells was determined based on a deconvolution algorithm (CIBERSORT), and gene expression profiles were analyzed in the context of clinical outcomes to construct an immune risk score. Data were analyzed using least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression, to identify prognostic markers of gastric cancer survival. The model included four immune cell types: neutrophils, plasma cells, activated CD4+ memory T cells, and T follicular helper cells. Patients were classified into two subgroups based on risk score, and a significant difference in overall survival (OS) was seen between the subgroups in both the training and testing cohorts, particularly in patients with tumor stages ≥T3. Multivariable analysis revealed that both T-stage and risk score were independent prognostic factors for gastric cancer survival [hazard ratio (HR) 1.505; 95% confidence interval (CI) 1.043-2.173, HR 1.686; 95% CI 1.367-2.080]. Risk scores and clinical factors were then integrated into a nomogram to build a model with both good discriminatory power and accuracy in predicting clinical outcomes. Further analysis using gene set enrichment analysis (GSEA) identified strong associations of immune risk with TGF-β and tumor metastasis-related pathways, which could inform research on the molecular mechanisms of gastric cancer. Collectively, the data presented here suggest that an immune risk model can make an important contribution to predictions prognosis in gastric cancer patients.

Profiles of immune cell infiltration and their clinical significance in head and neck squamous cell carcinoma

It is well established that there exist comprehensive interactions between tumor immunology and tumor biology. Tumor-infiltrating immune cells (TIICs) have been appealing therapeutic targets due to their significance in regulating cancer progression. The purpose of this study was to illustrate the comprehensive landscape of TIICs composition in head and neck squamous cell carcinoma (HNSCC) and their clinical significance. CIBERSORT was applied to calculate the 22 immune cell types proportion in HNSCC and further analysis suggested that six kinds of immune cells (resting memory CD4 T cells, M1 macrophages, resting dendritic cells, resting mast cells, monocytes, and eosinophils) were closely correlated with HNSCC progression. Moreover, memory CD4 T cells may serve as prognosis indicator for HNSCC patients. Collectively, this study uncovered the immune cells infiltration landscape in HNSCC and illustrated their potential relationships with clinical parameters, thereby contributing to the development of customized treatment strategy.

Clinical Implications of Tumor-Infiltrating Immune Cells in Breast Cancer

The immune infiltration of tumors is closely related to clinical outcomes. The composition of tumor-infiltrating immune cells (TIICs) can serve as biomarkers for predicting response to treatment and survival in different patient subgroups in terms of chemotherapy and immunotherapy. This study is focused on investigating the clinical implications of TIICs in breast cancer patients. We performed several in silico analyses of gene expression profiles in 2976 nonmetastatic tumor samples. CIBERSORT was used to estimate the proportion of 22 immune cell types to analyze their correlation with overall survival (OS) and disease-free survival (DFS) in different breast cancer subtypes and stages. Our results showed that a higher fraction of plasma cells in estrogen receptor (ER)-positive breast cancer patients indicated an increase in DFS (hazard ratio [HR]=0.66, 95% confidence interval [CI] 0.54~0.82, p<0.01), while a decreased OS was correlated with a greater number of M0 macrophages (HR=2.02, 95% CI 1.27~3.30, p=0.01) and regulatory T cells (HR=1.90, 95% CI 1.20~3.02, p=0.02). In ER-negative or progesterone receptor (PR)-negative subtypes or in a combined subtype, the increase in activated memory CD4⁺ T cells was correlated with increased DFS (HR=0.46, 95% CI 0.33~0.63, p<0.01). In all breast cancer patients, a higher proportion of M0 macrophages indicated a decreased DFS (HR=1.67, 95% CI 1.22~2.27, p<0.01), while increased OS was associated with relatively larger fractions of resting memory CD4⁺ T cells (HR=0.70, 95% CI 0.55~0.90, p=0.02) and γδ T cells (HR=0.66, 95% CI 0.51~0.85, p<0.01). Therefore, this study revealed that the composition of TIICs is different in patients with various subtypes of breast cancer and is directly related to prognosis, suggesting that TIICs are important participants in tumor progression and may, potentially be used for future diagnosis and treatment.

Immune cells in the tumour: new routes of retinoids for chemoprevention and chemotherapeutics

Retinoids, vitamin A and its natural and synthetic analogues have various functions, including being involved in cell proliferation and differentiation and participating in the formation of vertebrate morphology. In addition, they may activate certain tumour suppressor genes that then act as tumour inhibitors. In the past decades, retinoids have been regarded as promising chemotherapeutic and chemopreventive agents; however, their mechanisms are still not fully understood. Immune cells that participate in or are associated with the immune response play vital roles in the initiation and development of many cancers. Interestingly, recent studies have demonstrated that retinoids can also exert various effects on immune cells including macrophages, T cells and dendritic cells in tumour tissues to execute anti-tumour actions, providing new insights into chemoprevention and chemotherapeutics. In this review, we focus on the effects of retinoids on immune cells in the tumour, which may provide new approaches for antineoplastic strategies.

Gene expression profiles for a prognostic immunoscore in gastric cancer

Background

Increasing evidence has indicated an association between immune infiltration in gastric cancer and clinical outcome. However, reliable prognostic signatures, based on systematic assessments of the immune landscape inferred from bulk tumour transcriptomes, have not been established. The aim was to develop an immune signature, based on the cellular composition of the immune infiltrate inferred from bulk tumour transcriptomes, to improve the prognostic predictions of gastric cancer.

Methods

Twenty‐two types of immune cell fraction were estimated based on large public gastric cancer cohorts from the Gene Expression Omnibus using CIBERSORT. An immunoscore based on the fraction of immune cell types was then constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model.

Results

Using the LASSO model, an immunoscore was established consisting of 11 types of immune cell fraction. In the training cohort (490 patients), significant differences were found between high‐ and low‐immunoscore groups in overall survival across and within subpopulations with an identical TNM stage. Multivariable analysis revealed that the immunoscore was an independent prognostic factor (hazard ratio 1·92, 95 per cent c.i. 1·54 to 2·40). The prognostic value of the immunoscore was also confirmed in the validation (210) and entire (700) cohorts.

Conclusion

The proposed immunoscore represents a promising signature for estimating overall survival in patients with gastric cancer.

Immunoscore predicts prognosis

Nutrition and Immune-Modulatory Intervention in Surgical Patients With Gastric Cancer

This study evaluated the effect of an immune-modulatory diet on patients with gastric cancer and identified the parameters associated with postoperative outcomes. This was a single-arm prospective intervention study. At baseline, patients were assessed for nutrition (Patient-Generated Subjective Global Assessment), inflammatory markers (albumin, C-reactive protein, and interleukin 6 [IL-6]), and immune markers (percentage NK, CD4, CD8, and CD4:CD8 ratio); they also received nutrition counseling and high-calorie/protein supplement. A week before surgery, they were assessed for nutrition and inflammatory/immune markers and started on an immune-modulatory supplement until the day before surgery, when they were evaluated again. On the second postoperative day, patients were assessed for inflammatory/immune parameters, and a final nutrition evaluation was performed until the day of discharge. Complications were recorded daily and up to 30 days after discharge. Thirty-seven patients (60 ± 10 years old) were included, and 57% were classified as malnourished. Maintenance of nutrition and immune parameters occurred throughout the study period, but we found a preoperative increase in C-reactive protein (0.1-1.5 mg/dL) and IL-6 (2.0-14.2 pg/mL) and a postoperative increase in the CD4:CD8 ratio (2.3 ± 1.0). Complications and death were seen in 35%, especially patients with higher preoperative IL-6 (2.2-46 pg/mL), lower CD4:CD8 ratio (1.7 ± 0.5), and lower protein (1.2 ± 0.5 g/kg/d) and calorie intake (1552 ± 584 kcal/kg/d). The high-calorie/protein supplementation with the immune-modulating diet was able to maintain the nutrition and immune status of patients with gastric cancer.

Meta-analysis of associations between neutrophil-to-lymphocyte ratio and prognosis of gastric cancer

Background

The prognostic role of inflammation indices, such as the neutrophil-to-lymphocyte ratio (NLR) in gastric cancer (GC) remains controversial. We conducted a meta-analysis to determine the predictable value of NLR in the clinical outcome of GC patients.

Methods

We searched Embase, PubMed and the Cochrane Library database for relevant randomised controlled trials. Statistical analyses were conducted to calculate the hazard ratio (HR) and 95% confidence intervals of overall survival (OS) and progression-free survival (PFS) using either random-effect or fixed-effect models according to the heterogeneity of the included studies. An analysis was carried out based on data from nine studies to evaluate the association between NLR and OS in patients with GC.

Results

Our analysis indicated that elevated pre-treatment NLR predicted poorer OS (HR: 2.16, 95% CI: 1.86 to 2.51, P < 0.001) and PFS (HR 2.78, 95% CI: 1.95 to 3.96; P < 0.00001) in patients with GC. Over a 3-year follow-up period, high NLR was a significant predictor of poor outcomes at year 1 (HR 1.99; 95% CI: 1.39 to 2.85; P = 0.0002), year 2 (HR 2.24; 95% CI: 1.69 to 2.97; P < 0.00001) and year 3 (HR 2.80; 95% CI: 1.98 to 3.96; P < 0.00001).

Conclusions

Elevated preoperative NLR is associated with poorer rates of survival in GC patients and may play a role in GC surveillance programmes as a means of delivering more personalised cancer care.

Electronic supplementary material

The online version of this article (doi:10.1186/s12957-015-0530-9) contains supplementary material, which is available to authorized users.

The subsets of dendritic cells and memory T cells correspond to indoleamine 2,3-dioxygenase in stomach tumor microenvironment

The abnormal distributions of memory T cells (Tm) and dendritic cells (DC) in stomach cancer are not well understood. Indoleamine 2,3-dioxygenase (IDO), produced by DC, may be an important enzyme affecting function and proliferation of Tm. In this study, IDO expression was examined by immunohistochemical staining. The subsets of Tm and DC were counted by flow cytometry. The percentages of CD4 + Tm and CD4 + central Tm (Tcm) were lower in tumor tissues than in normal tissues (P < 0.05), while the CD4 + effector Tm (Tem) and CD8 + Tem percentages were higher in tumor tissues (P < 0.05). The ratio of myeloid DC (DC1)/plasmacytoid DC (DC2) was significantly lower in tumor tissues (P = 0.009). The high expression of IDO was more frequently observed in tumor tissues (P = 0.001). The percentages of CD4 + Tm and CD8 + Tm were positively associated with DC1 percentage and ratio of DC1/DC2 (P < 0.05). The higher CD8 + Tcm percentage was associated with higher DC2 percentage (P = 0.025). The patients with high IDO expression had significantly lower CD4 + Tm (P = 0.012) and CD8 + Tm percentages (P = 0.033), but higher CD8 + Tem percentage (P < 0.01). Concerning on clinicopathologic features, the higher DC2 percentage was associated with larger tumor size (P = 0.019). The CD4 + Tm and CD8 + Tem percentages were significantly associated with clinical stage and lymph node metastasis; the high IDO expressions were significantly associated with deeper tumor invasion (P = 0.016) and lymph node metastasis (P = 0.038). Thus, DC subsets, Tm subsets, and IDO expression were correlated with each other. They were associated with the established clinicopathologic features, such as tumor size, depth of invasion, lymph node metastasis, and clinical stage.