The neutrophil-lymphocyte ratio (NLR) and the platelet-lymphocyte ratio (PLR) are markers of systemic inflammation. However, there is little evidence of the value of inflammation in the early diagnosis of gastric cancer (GC). A total of 2,606 patients diagnosed with GC in the past three years and 3,219 healthy controls over the same period were included in this study. Peripheral blood samples were obtained to analyze the NLR, PLR, carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9). The optimal cutoff levels for the NLR and PLR were defined by receiver operating characteristic (ROC) curve analysis (NLR=2.258,PLR=147.368). The value of different biomarkers for diagnosing GC was compared by the area under the curve (AUC). The NLR and PLR showed diagnostic sensitivity in GC (AUC=0.715,AUC=0.707). Using the Bonferroni correction, the NLR and PLR were superior to CEA and CA19-9 in the diagnosis of GC (P<0.0001). The systemic inflammatory markers were significantly higher in the early stage of GC than tumor markers. After grouping patients and healthy controls by gender, we found that the diagnostic significance of combined NLR and PLR for GC was greater in male patients than in female patients (P<0.0001). The diagnostic value of the NLR and PLR in GC is higher than that of the traditional tumor markers CEA and CA19-9. Systemic markers of inflammation are more valuable in male than female patients.

Elastin (ELN) fibers are essential constituents of the tumor microenvironment of gastric cancer (GC). However, few studies have investigated the clinical prognostic significance of ELN in GC. We screened for molecular markers that were highly related to distant metastasis by transcriptome sequencing. The Cancer Genome Atlas (TCGA) and Harbin Medical University (HMU) validation cohorts were used to validate ELN expression and to explore molecular mechanisms. Immunohistochemistry for ELN, vimentin (VIM), and fibroblast activation protein, and elastic fiber‐specific staining were used to evaluate the relationship between ELN and prognosis. R studio was used to construct a nomogram prognostic model. In this study, we found that ELN mRNA levels were significantly higher in cancer tissues and were associated with poor prognosis in TCGA and HMU patients. Gene set enrichment analysis showed that ELN was mainly enriched in the epithelial–mesenchymal transition (EMT) pathway. The mRNA expression of ELN was positively correlated with fibroblast molecular markers, especially VIM. For validation, we collected a tissue microarray containing 180 pairs of samples. We found that ELN was positively correlated with VIM expression in cancer tissue but not in paracancerous tissues by immunohistochemistry staining. Univariate and multivariate analyses showed that the expression of ELN and lymph node metastasis rate were independent predictors for overall survival. Moreover, a nomogram model was used to evaluate the risk of death by combining the expression of ELN and lymph node metastasis rate. ELN may play an important role in the progression of GC by regulating EMT and is a useful prognostic indicator in predicting the prognosis of GC.

Annexin A2 (ANXA2) has been well known to associate with the progress of malignant tumor. However, the biological behavior of ANXA2 in gastric cancer (GC) remains unclear. We made a hypothesis in transcriptome level from TCGA datasets. Then, we used immunohistochemical staining to quantify the expression level of ANXA2 protein in GC tissues compared with adjacent tissues. Quantitative real-time PCR and western blot were used for analyzing ANXA2 expression in human GC (SGC-7901, MKN-45, BGC-823, and AGS) cell lines. We investigated the effect of a lentivirus-mediated knock-down of ANXA2 on the proliferation, invasion and migration of gastric cancer AGS cells. Cell proliferation was examined by MTT and colony formation tests. Cell apoptosis and cycle were measured by flow cytometry. Migration and invasion were detected by transwell assay. We found that high expression of ANXA2 can increase the mobility of cancer cells from TCGA datasets. ANXA2 was upregulated in GC tissues compared with adjacent tissues. AGS cell line displayed significantly higher expression of ANXA2 among the four GC cell lines. In addition, ANXA2 silencing led to a weakened ability of proliferation, invasion, and migration in GC cells; targeting of ANXA2 may be a potential therapeutic strategy for GC patients.

The Integrin Subunit Alpha 4 (ITGA4) plays important roles in cancers pathogenesis. However, the expression and association with clinicopathological and survival probability have not been previously assessed in gastric cancer (GC). Protein expression of ITGA4 was assessed in TMA using immunohistochemistry and correlated with clinicopathological factors and survival. The mRNA expression of ITGA4 was also assessed in the HMU-GC cohort. Bioinformatics function analysis was conducted through GSEA. The “CIBERSORT” package was used for immune infiltration analysis. “SvyNom” package is used to construct prognosis model. ITGA4 knock down using shRNA. The evaluation of cell function was performed by CCK-8 and Transwell invasion and migration experiments. ITGA4 was significantly associated with N classification ( ), tumor location ( ), WHO classification ( ), and poor prognosis in mRNA level. GSEA analysis of the validation cohort suggested that ITGA4 was associated with macrophage infiltration. Immunohistochemistry showed that ITGA4 was associated with poor prognosis. Multivariate Cox regression analysis found that ITGA4 ( ) and lymph node metastasis rate ( ) were independent prognostic factors and could construct a prognosis model. ITGA4 knockdown cell line significantly reduced the ability of proliferation, invasion, and metastasis. ITGA4 is associated with patient survival in GC and may be an important prognostic biomarker.

Background: Inflammatory indexes are considered to be potential prognostic biomarkers for patients with gastric cancer (GC). However, little evidence has defined the prognostic significance of inflammatory indexes for GC with different Lauren classification.Methods: A total of 852 patients with GC were randomly selected consecutively into intestinal type and diffuse/mixed type groups. Group bias was reduced by propensity score matching. The cutoff values of inflammatory indexes were analyzed by receiver operating characteristic curve. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival (OS). The chi‐square test was used to analyze the association between inflammatory indexes and clinical characteristics. The independent risk factor for prognosis in each group was analyzed by univariate and multivariate analyses based on logistic regression. The nomogram models were constructed by R studio.Results: Intestinal type GC patients (p < 0.05) had a lower percentage of neutrophils in stage I, higher percentage of neutrophils and higher platelet count in stage Ⅲ (p < 0.05). Systemic immune‐inflammation index (SII) (p < 0.001), pTNM stage (p < 0.001), and postoperative chemotherapy (p = 0.002) were independent risk factors for prognosis in the intestinal type group. Platelet–lymphocyte ratio (PLR) (p < 0.001) and pTNM stage (p = 0.001) were independent risk factors for prognosis in the diffuse/mixed type group. The area under the curve of the nomogram model in predicting 5‐year prognosis in the intestinal type group and diffuse/mixed type group were 0.807 and 0.788, respectively.Conclusion: SII combined with postoperative chemotherapy and pTNM stage were used to construct a nomogram model to predict the prognosis of intestinal type GC. PLR combined with pTNM stage can be used to construct a nomogram model for diffuse/mixed type GC patients.

Glutamine fructose‐6‐phosphate aminotransferase 2 (GFPT2) is a rate‐limiting enzyme in hexosamine biosynthesis involved in the occurrence and progress of many cancers. What role it plays in gastric cancer (GC) is still unclear. In this study, transcriptome sequencing data from the Harbin Medical University (HMU)‐GC cohort and The Cancer Genome Atlas (TCGA) dataset were combined with the HMU‐TCGA training cohort to analyze the biological function and clinical significance of GFPT2. The correlation of GFPT2 with immune cells and stromal cells was analyzed in the GC immune microenvironment through transcriptome sequencing data and a public single‐cell sequencing database. In cell lines, GC tissues, and the tissue microarray, GFPT2 protein expression was confirmed by western blotting and immunohistochemistry. The mRNA of GFPT2 was highly expressed in the tumor (p < 0.001), and GC cells and tumors expressed high levels of GFPT2 protein. Compared to low expression, high GFPT2 mRNA expression was associated with higher levels of tumor invasion, higher pathological stages, and poor prognosis (p = 0.02) in GC patients. In a drug susceptibility analysis, GFPT2 mRNA expression was associated with multiple chemotherapeutic drug sensitivity, including docetaxel, paclitaxel, and cisplatin. Gene enrichment analysis found that GFPT2 was mainly primarily involved in the extracellular matrix receptor interaction pathway. The ESTIMATE, CIBERSORT, and ssGSEA algorithms showed that GFPT2 was associated with immune cell infiltration. In addition, GFPT2 was more likely to be expressed within cancer‐associated fibroblasts (CAFs), and high levels of GFPT2 expression were highly correlated with four CAFs scores (all p < 0.05). Finally, a prognostic model to assess the risk of death in GC patients was constructed based on GFPT2 protein expression and lymph node metastasis rate. In conclusion, GFPT2 plays an essential role in the function of CAFs in GC. It can be used as a biomarker to assess GC prognosis and immune infiltration.