Poor Overall Survival In Gastric Cancer Patients Research Articles

Prognostic value of neutrophil-to-lymphocyte ratio in gastric cancer patients treated with immune checkpoint inhibitors: A meta-analysis.

The neutrophil-to-lymphocyte ratio (NLR) has been extensively studied in patients with gastric cancer (GC) treated with immune checkpoint inhibitors (ICIs), although the results are controversial. Therefore, we performed the present meta-analysis to systematically assess the correlation between NLR and prognosis and clinicopathological factors in GC patients undergoing treatment with ICIs. Among the electronic databases, PubMed, Web of Science, Embase, and Cochrane Library were thoroughly searched. To estimate the prognostic value of NLR for progression-free survival (PFS) and overall survival (OS), hazard ratios (HRs) were calculated, and their 95% confidence intervals were calculated. This meta-analysis included 10 studies with 830 patients. Based on the pooled data, a high NLR was associated with poor OS in GC patients receiving ICIs (HR = 2.13, 95% confidence interval [CI] = 1.70-2.66, p < 0.001). Elevated NLR was a significant biomarker for worse PFS in GC patients treated with ICIs (HR = 1.74, 95% CI = 1.22-2.48, p = 0.002). There was, however, no significant correlation between NLR and sex, age, and Eastern Cooperative Oncology Group Performance Status (PS) of the ECOG, differentiation, human epidermal growth factor receptor 2 (HER2) status, or PD-L1 status in GC patients treated with ICIs. High NLR before treatment was associated with poor OS and PFS in GC patients treated with ICIs, according to our meta-analysis. NLR is an effective biomarker for evaluating the prognosis of GC patients receiving ICIs and provide more valuable information for treatment decisions in the era of immunotherapy for GC.

Identification and validation of signature for prognosis and immune microenvironment in gastric cancer based on m6A demethylase ALKBH5.

N6-methyladenosine (m6A) RNA regulators play important roles in cancers, but their functions and mechanism have not been demonstrated clearly in gastric cancer (GC). In this study, the GC samples with clinical information and RNA transcriptome were downloaded from The Cancer Genome Atlas database. The different expression genes were compared by the absolute value and median ± standard deviation. Samples with complete information were randomly divided into a training dataset and a test dataset. The differential expression genes (DEGs) between ALKBH5-low and ALKBH5-high subgroups were identified in the training dataset and constructed a risk model by Cox and least absolute shrinkage and selection operator regression. The model was testified in test datasets, overall survival (OS) was compared with the Kaplan-Meier method, and immune cell infiltration was calculated by the CIBERSORT algorithm in the low-risk and high-risk subgroups based on the model. The protein levels of ALKBH5 were detected with immunohistochemistry. The relative expression of messenger-ribonucleic acid (mRNA) was detected with quantitative polymerase chain reaction. ALKBH5 was the only regulator whose expression was lower in tumor samples than that in normal samples. The low expression of ALKBH5 led to the poor OS of GC patients and seemed to be an independent protective factor. The model based on ALKBH5-regulated genes was validated in both datasets (training/test) and displayed a potential capacity to predict a clinical prognosis. Gene Ontology analysis implied that the DEGs were involved in the immune response; CIBERSORT results indicated that ALKBH5 and its related genes could alter the immune microenvironment of GC. The protein levels of ALKBH5 were verified as lowly expressed in GC tissues. SLC7A2 and CGB3 were downregulated with ALKBH5 knockdown. In this study, we found that ALKBH5 might be a suppressor of GC; ALKBH5 and its related genes were latent biomarkers and immunotherapy targets.

A Genomic Signature Reflecting Fibroblast Infiltration Into Gastric Cancer Is Associated With Prognosis and Treatment Outcomes of Immune Checkpoint Inhibitors.

Background: The immunotherapy efficacy in gastric cancer (GC) is limited. Cancer-associated fibroblasts (CAFs) induce primary resistance to immunotherapy. However, CAF infiltration in tumors is difficult to evaluate due to the lack of validated and standardized quantified methods. This study aimed to investigate the impact of infiltrating CAFs alternatively using fibroblast-associated mutation scoring (FAMscore). Methods: In a GC cohort from Affiliated Hospital of Jiangsu University (AHJU), whole exon sequencing of genomic mutations, whole transcriptome sequencing of mRNA expression profiles, and immunofluorescence staining of tumor-infiltrating immune cells were performed. GC data from The Cancer Genome Atlas were used to identify genetic mutations which were associated with overall survival (OS) and impacted infiltrating CAF abundance determined by transcriptome-based estimation. FAMscore was then constructed through a least absolute shrinkage and selection operator Cox regression model and further validated in AHJU. The predictive role of FAMscore for immunotherapy outcomes was tested in 1 GC, one melanoma, and two non-small-cell lung cancer (NSCLC-1 and -2) cohorts wherein participants were treated by immune checkpoint inhibitors. Results: FAMscore was calculated based on a mutation signature consisting of 16 genes. In both TCGA and AHJU, a high FAMscore was an independent predictor for poor OS of GC patients. FAMscore was associated with immune-associated genome biomarkers, immune cell infiltration, and signaling pathways of abnormal immunity. Importantly, patients with high FAMscore presented inferiority in the objective response rate of immunotherapy compared to those with low FAMscore, with 14.6% vs. 66.7% (p<0.001) in GC, 19.6% vs. 68.2% (p<0.001) in NSCLC-1, 23.1% vs 75% (p = 0.007) in NSCLC-2, and 40.9% vs 75% (p = 0.037) in melanoma. For available survival data, a high FAMscore was also an independent predictor of poor progression-free survival in NSCLC-1 (HR = 2.55, 95% CI: 1.16–5.62, p = 0.02) and NSCLC-2 (HR = 5.0, 95% CI: 1.13–22.19, p = 0.034) and poor OS in melanoma (HR = 3.48, 95% CI: 1.27–9.55, p = 0.015). Conclusions: Alternative evaluation of CAF infiltration in GC by determining the FAMscore could independently predict prognosis and immunotherapy outcomes. The FAMscore may be used to optimize patient selection for immunotherapy.

Exploration in the Mechanism of Kaempferol for the Treatment of Gastric Cancer Based on Network Pharmacology.

Background Kaempferol is a natural polyphenol in lots of Chinese herbs, which has shown promising treatment for gastric cancer (GC). However, the molecular mechanisms of its action have not been systematically revealed yet. In this work, a network pharmacology approach was used to elucidate the potential mechanisms of kaempferol in the treatment of GC. Methods The kaempferol was input into the PharmMapper and SwissTargetPrediction database to get its targets, and the targets of GC were obtained by retrieving the Online Mendelian Inheritance in Man (OMIM) database, MalaCards database, Therapeutic Target Database (TTD), and Coolgen database. The molecular docking was performed to assess the interactions between kaempferol and these targets. Next, the overlap targets of kaempferol and GC were identified for GO and KEGG enrichment analyses. Afterward, a protein-protein interaction (PPI) network was constructed to get the hub targets, and the expression and overall survival analysis of the hub target were investigated. Finally, the overall survival (OS) analysis of hub targets was performed using the Kaplan-Meier Plotter online tool. Results A total of 990 genes related to GC and 10 overlapping genes were determined through matching the 24 potential targets of kaempferol with disease-associated genes. The result of molecular docking indicated that kaempferol can bind with these hub targets with good binding scores. These targets were further mapped to 140 GO biological process terms and 11 remarkable pathways. In the PPI network analysis, 3 key targets were identified, including ESR1, EGFR, and SRC. The mRNA and protein expression levels of EGFR and SRC were obviously higher in GC tissues. High expression of these targets was related to poor OS in GC patients. Conclusions This study provided a novel approach to reveal the therapeutic mechanisms of kaempferol on GC, which will ease the future clinical application of kaempferol in the treatment of GC.

Systematic Elucidation of the Mechanism of Quercetin against Gastric Cancer via Network Pharmacology Approach.

This study was aimed at elucidating the potential mechanisms of quercetin in the treatment of gastric cancer (GC). A network pharmacology approach was used to analyze the targets and pathways of quercetin in treating GC. The predicted targets of quercetin against GC were obtained through database mining, and the correlation of these targets with GC was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, the protein-protein interaction (PPI) network was constructed, and overall survival (OS) analysis of hub targets was performed using the Kaplan–Meier Plotter online tool. Finally, the mechanism was further analyzed via molecular docking of quercetin with the hub targets. Thirty-six quercetin-related genes were identified, 15 of which overlapped with GC-related targets. These targets were further mapped to 319 GO biological process terms and 10 remarkable pathways. In the PPI network analysis, six hub targets were identified, including AKT1, EGFR, SRC, IGF1R, PTK2, and KDR. The high expression of these targets was related to poor OS in GC patients. Molecular docking analysis confirmed that quercetin can bind to these hub targets. In conclusion, this study provided a novel approach to reveal the therapeutic mechanisms of quercetin on GC, which will ease the future clinical application of quercetin in the treatment of GC.