Bioinformatics analysis of the prognosis and biological significance of VCAN in gastric cancer

SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell-cell communication

BACKGROUND

Cellular communication is vital for the proper functioning of multicellular organisms. A comprehensive analysis of cellular communication demands the consideration not only of the binding between ligands and receptors but also of a series of downstream signal transduction reactions within cells. Thanks to the advancements in spatial transcriptomics technology, we are now able to better decipher the process of cellular communication within the cellular microenvironment. Nevertheless, the majority of existing spatial cell-cell communication algorithms fail to take into account the downstream signals within cells.

RESULTS

In this study, we put forward SpaCcLink, a cell-cell communication analysis method that takes into account the downstream influence of individual receptors within cells and systematically investigates the spatial patterns of communication as well as downstream signal networks. Analyses conducted on real datasets derived from humans and mice have demonstrated that SpaCcLink can help in identifying more relevant ligands and receptors, thereby enabling us to systematically decode the downstream genes and signaling pathways that are influenced by cell-cell communication. Comparisons with other methods suggest that SpaCcLink can identify downstream genes that are more closely associated with biological processes and can also discover reliable ligand-receptor relationships.

CONCLUSIONS

By means of SpaCcLink, a more profound and all-encompassing comprehension of the mechanisms underlying cellular communication can be achieved, which in turn promotes and deepens our understanding of the intricate complexity within organisms.

Identification of Potential Biomarkers and Pathways in Acute Myeloid Leukemia: Correlation Between the Calcineurin Signaling Pathway and Vascular Brittleness in Acute Myeloid Leukemia

OBJECTIVE

In this study, clinical bioinformatics analysis was used to identify potential biomarkers of acute myeloid leukemia (AML) occurrence and development, drug resistance, and poor prognosis to provide a theoretical basis for the treatment of AML.

METHODS

On the basis of the TCGA, GEO, and GTEx databases, an AML secondary database was established, and differential expression analysis and WGCNA were carried out to identify genes related to the prognosis of AML patients. Survival analysis was carried out for internal verification of key genes, and GEO data were used for external verification to obtain core genes related to prognosis. For differentially expressed genes, the EpiMed platform independently developed by the team was used for drug prediction.

RESULTS

A total of 36 overlapping genes were obtained via difference analysis and WGCNA. Enrichment analysis revealed that the overlapping genes were associated with neutrophil activation, transcription dysregulation, AML, apoptosis, and other biological indicators. A protein interaction network was constructed for NCOA4, ACSL4, DPP4, ATL1, MT1G, ALOX15, and SLC7A11, which are key genes. Survival analysis revealed that NCOA4, ACSL4, DPP4, and ATL1 significantly affected the survival of patients with AML. The GSE142698 dataset verified that MPO, BCL2A1, and STMN1 had a statistically significant impact on the survival of AML patients.

CONCLUSION

NCOA4, ACSL4, DPP4, and ATL1 may be potential biomarkers related to the survival and prognosis of patients with AML, and the calcineurin signaling pathway is associated with the risk of vascular fragility in AML patients, which can provide a reference for further research and optimization of treatment regimens.

Bioinformatics Analysis and Experimental Validation of Differential Genes and Pathways in Bone Nonunions

Non-union fractures pose a significant clinical challenge, often leading to prolonged pain and disability. Understanding the molecular mechanisms underlying non-union fractures is crucial for developing effective therapeutic interventions. This study integrates bioinformatics analysis and experimental validation to unravel key genes and pathways associated with non-union fractures. We identified differentially expressed genes (DEGs) between non-union and fracture healing tissues using bioinformatics techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological processes and pathways involved. Common DEGs were identified, and a protein-protein interaction (PPI) network was constructed. Fibronectin-1 (FN1), Thrombospondin-1 (THBS1), and Biglycan (BGN) were pinpointed as critical target genes for non-union fracture treatment. Experimental validation involved alkaline phosphatase (ALP) and Alizarin Red staining to confirm osteogenic differentiation. Our analysis revealed significant alterations in pathways related to cell behavior, tissue regeneration, wound healing, infection, and immune responses in non-union fracture tissues. FN1, THBS1, and BGN were identified as key genes, with their upregulation indicating potential disruptions in the bone remodeling process. Experimental validation confirmed the induction of osteogenic differentiation. The study provides comprehensive insights into the molecular mechanisms of non-union fractures, emphasizing the pivotal roles of FN1, THBS1, and BGN in extracellular matrix dynamics and bone regeneration. The findings highlight potential therapeutic targets and pathways for further investigation. Future research should explore interactions between these genes, validate results using in vivo fracture models, and develop tailored treatment strategies for non-union fractures, promising significant advances in clinical management.

Prognostic and immunological roles of RSPO1 in pan-cancer and its correlation with LUAD proliferation and metastasis

Aberrant RSPO1 expression is implicated in tumor progression across various cancers and correlates with anti-cancer immune cell characteristics. However, the specific role of R-spondin 1 (RSPO1) in lung adenocarcinoma (LUAD) remains unclear. In this study, we utilized data from The Cancer Genome Atlas (TCGA) to assess RSPO1 expression across 33 tumor types. Kaplan-Meier (K-M) analysis revealed the prognostic significance of RSPO1 in various cancers. Using statistical software R, we examined RSPO1's associations with immune cell infiltration, methylation, mutation, and competing endogenous RNA (ceRNA) networks. Exploration via the Tumor Immune Single Cell Hub (TISCH) database uncovered RSPO1's link to the tumor microenvironment (TME) and identified potential small molecule drug targets. We further investigated RSPO1's impact on LUAD cell proliferation, metastasis, and the Wnt pathway in vitro. Our findings highlight RSPO1's role in cancer progression and suggest its potential as both a prognostic marker and therapeutic target in LUAD, implicating the modulation of the Wnt pathway.

Splicing variants of versican in CD133+/CD44+ prostate cancer stem cells

A cancer mass is composed of a heterogeneous group of cells, a small part of which constitutes the cancer stem cells since they are less differentiated and have a high capacity to develop cancer. Versican is an extracellular matrix protein located in many human tissues. The mRNA of versican has been shown to have "splicing patterns" as detected by RT-PCR, northern blot analysis, and cDNA sequencing. Based on this knowledge this study aims to reveal the splice variants of versican molecules, which are thought to be involved in the pathogenesis of the DU-145 human prostatic carcinoma cell line and prostatic cancer stem cells isolated from this cell line. In this study, RWPE-1 normal prostatic and DU-145 human prostate cancer cell lines have been used. Prostatic cancer stem cells and the remaining group of non-prostatic-cancer stem cells (bulk population) were isolated according to their CD133+/CD44+. RNA was isolated in all groups, and sequence analysis was accomplished for splicing variants by Illumina NextSeq 500 sequencing system. The results were analyzed by bioinformatic evaluation. As five isoforms of the versican gene in the differential transcript expression are analyzed, it was observed that a significant change was only found in the isoforms Versican 0 and Versican 1. In this study, we explored the function of this molecule which we think to be effective in cancer progression, and suggested that more valuable results can be obtained after the accomplishment of in vivo experiments.

Tumor purity-related genes for predicting the prognosis and drug sensitivity of DLBCL patients

Background

Diffuse large B-cell lymphoma (DLBCL) is the predominant type of malignant B-cell lymphoma. Although various treatments have been developed, the limited efficacy calls for more and further exploration of its characteristics.

Methods

Datasets from the Gene Expression Omnibus (GEO) database were used for identifying the tumor purity of DLBCL. Survival analysis was employed for analyzing the prognosis of DLBCL patients. Immunohistochemistry was conducted to detect the important factors that influenced the prognosis. Drug-sensitive prediction was performed to evaluate the value of the model.

Results

VCAN, CD3G, and C1QB were identified as three key genes that impacted the outcome of DLBCL patients both in GEO datasets and samples from our center. Among them, VCAN and CD3G+ T cells were correlated with favorable prognosis, and C1QB was correlated with worse prognosis. The ratio of CD68 + macrophages and CD8 + T cells was associated with better prognosis. In addition, CD3G+T cells ratio was significantly correlated with CD68 + macrophages, CD4 + T cells, and CD8 +T cells ratio, indicating it could play an important role in the anti-tumor immunity in DLBCL. The riskScore model constructed based on the RNASeq data of VCAN, C1QB, and CD3G work well in predicting the prognosis and drug sensitivity.

Conclusions

VCAN, CD3G, and C1QB were three key genes that influenced the tumor purity of DLBCL, and could also exert certain impact on drug sensitivity and prognosis of DLBCL patients.

Funding

This work is supported by the Shenzhen High-level Hospital Construction Fund and CAMS Innovation Fund for Medical Sciences (CIFMS) (2022-I2M-C&T-B-062).

Identification of the Expression of TIE1 and Its Mediated Immunosuppression in Gastric Cancer

Background: Recently, various evidence has confirmed that Tyrosine Kinase with Immunoglobulin-like and EGF-like domains 1 (TIE1) promotes tumor growth in many cancers. However, the precise mechanism underlying TIE1's involvement in Gastric Cancer (GC) remains elusive. This research aimed to investigate the biological function of TIE1 in regulating GC progression. Methods: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), GEPIA2.0, Sangerbox3.0 and TIMER databases were used to analyze the TIE1 expression. Immunohistochemistry (IHC) was used to demonstrate the expression of TIE1. TCGA, GEPIA2.0 and Kaplan-Meier were utilized for survival analysis and to explore the association of TIE1 with clinicopathological features. Protein-Protein Interaction (PPI) networks were constructed using Cytoscape. The potential molecular mechanism of TIE1 was investigated by Gene Ontology (GO), Kyoto Encyclopedia of Gene Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We studied the relationships between TIE1 and mutations, immune checkpoints (ICs), tumor mutational burden (TMB), as well as microsatellite instability (MSI) to explore the underlying mechanism of immunity in GC. Results: Compared with normal tissue, TIE1 was significantly overexpressed in GC tissues (p = 0.0072) and was associated with poor survival (P < 0.05). According to GO and KEGG enrichment analyses, TIE1 was enriched in signal pathways related to the occurrence, invasion, and migration of malignant tumors (i.e., PI3K-Akt signaling pathway, Calcium signaling pathway, etc.). Immune infiltration analysis suggested that TIE1 is positively correlated with macrophages M2 and negatively correlated with Mast cells, naive B cells and Follicular helper T cells (TFH), which may be a contributing factor to tumor progression. Furthermore, the research on the tumor microenvironment (TME) and tumor purity also proved that TIE1 may be an oncogene. Mutation analysis showed that the high expression group of TIE1 had a higher frequency of mutations in TP53 and ARID1, while the TMB score was lower. Conclusion: TIE1 might be an oncogene via regulating dysregulated immune infiltration to cause immunosuppression in GC and could be identified as a biomarker for prognosis and a therapeutic target for GC.

m5 C regulator-mediated methylation modification patterns and tumor microenvironment infiltration characteristics in acute myeloid leukemia

BACKGROUND

Recently, many studies have been conducted to examine immune response modification at epigenetic level, but the candidate effect of RNA 5-methylcytosine (m5 C) modification on tumor microenvironment (TME) of acute myeloid leukemia (AML) is still unknown at present.

METHODS

We assessed the patterns of m5 C modification among 417 AML cases by using nine m5 C regulators. Thereafter, we associated those identified modification patterns with TME cell infiltration features. Additionally, stepwise regression and LASSO Cox regression analyses were conducted for quantifying patterns of m5 C modification among AML cases to establish the m5 C-score. Meanwhile, we validated the expression of genes in the m5C-score model by qRT-PCR. Finally, the present work analyzed the association between m5 C-score and AML clinical characteristics and prognostic outcomes.

RESULTS

In total, three different patterns of m5 C modification (m5 C-clusters) were identified, and highly differentiated TME cell infiltration features were also identified. On this basis, evaluating patterns of m5 C modification in single cancer samples was important for evaluating the immune/stromal activities in TME and for predicting prognosis. In addition, the m5 C-score was established, which showed a close relation with the overall survival (OS) of test and training set samples. Moreover, multivariate Cox analysis suggested that our constructed m5 C-score served as the independent predicting factor for the prognosis of AML (hazard ratio = 1.57, 95% confidence interval = 1.38-1.79, p < 1e-5 ).

CONCLUSIONS

This study shows that m5 C modification may be one of the key roles in the formation of diversity and complexity of TME. Meanwhile, assessing the patterns of m5 C modification among individual cancer samples is of great importance, which provides insights into cell infiltration features within TME, thereby helping to develop relevant immunotherapy and predict patient prognostic outcomes.

Versican core protein aids in the diagnosis and grading of breast phyllodes tumor

Phyllodes tumors (PTs) are biphasic fibroepithelial lesions that occur in the breast. Diagnosing and grading PTs remains a challenge in a small proportion of cases, due to the lack of reliable specific biomarkers. We screened a potential marker versican core protein (VCAN) through microproteomics analysis, validated its role for the grading of PTs by immunohistochemistry, and analyzed the correlation between VCAN expression and clinicopathological characteristics. Cytoplasmic immunoreactivity for VCAN was identified in all benign PT samples, among which 40 (93.0 %) showed VCAN-positive staining in ≥50 % of tumor cells. Eight (21.6 %) borderline PT samples showed VCAN-positive staining in ≥50 % of the cells with weak to moderate staining intensity, whereas 29 samples (78.4 %) showed VCAN-positive staining in <50 % of the cells. In malignant PTs, 16 (84.2 %) and three (15.8 %) samples showed VCAN-positive staining in <5 % and 5-25 % of stromal cells, respectively. Fibroadenomas showed a similar expression pattern to benign PTs. Fisher's exact test showed that the percentages of positive cells (P < .001) and staining intensities (P < .001) of tumor cells were significantly different between the five groups. VCAN positivity was associated with tumor categories (P < .0001) and CD34 expression (P < .0001). The expression of VCAN gradually decreases as the tumor categories increases, following recurrence. To the best of our knowledge, our results are the first in the literature to reveal that VCAN is useful for diagnosing and grading PTs. The expression level of VCAN appeared to be negatively associated with PT categories, suggesting that dysregulation of VCAN may be involved in the tumor progression of PTs.

The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation

Objective. This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods. The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results. A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion. Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

Versican enrichment predicts poor prognosis and response to adjuvant therapy and immunotherapy in gastric cancer

Background

Increasing evidence has revealed an important role of versican (VCAN) on various aspects of cancer progression. Here, we assessed the impact of VCAN expression on prognosis and the response to adjuvant therapy and immunotherapy in patients with gastric cancer (GC).

Methods

Four independent cohorts containing 1353 patients with GC, were utilized to investigate the effect of VCAN expression on prognosis and response to adjuvant therapy in GC. Two cohorts treated with immune checkpoint blockades were included to assess the predict value of VCAN expression on response to immunotherapy. Moreover, the bulk RNA-seq and single-cell RNA-seq data were analyzed to illustrate the role of VCAN in tumor microenvironment. Clinical outcomes of patient subgroups were compared by Kaplan-Meier curves with the log-rank test.

Result

High VCAN expression was associated with poor prognosis for patients with GC. Compared with patients with high VCAN expression, patients with low VCAN expression benefited more from adjuvant chemotherapy and adjuvant chemoradiotherapy. Moreover, patients with high VCAN expression tended to be resistant to immunotherapy, and VCAN could serve as a promising indicator for predicting the response to immunotherapy. VCANhigh tumors showed a specific microenvironment with more cancer associated fibroblasts infiltration and significant enrichment of stromal relevant signaling pathways.

Conclusion

VCAN could predict the response to adjuvant chemotherapy, adjuvant chemoradiotherapy and immunotherapy in GC, and designing new medicine target to VCAN might be an effective way to improve the efficacy of several treatment options for GC.

Achaete-scute complex-like 2 regulated inflammatory mechanism through Toll-like receptor 4 activating in stomach adenocarcinoma

Background

To investigate the role of achaete-scute complex-like 2 (ASCL2) in stomach adenocarcinoma (STAD), we analyze whether ASCL2 suppression could retard cancer development and further observe the relevance between ASCL2 and inflammation via Toll-like receptor 4 (TLR4) activation in STAD, both in vitro and in vivo.

Methods

Proliferation, development, inflammation, and apoptosis in STAD are observed using sh-ASCL2 lentivirus via TLR4 activation in vitro and in vivo. The relationship between ASCL2 and inflammation is analyzed. Western blotting of ASCL2 with the target protein of immune-associated cells is performed. The prognosis of STAD and associated ASCL2 mutation are analyzed.

Results

The ASCL2 level in STAD tumor tissues is increased, compared to normal tissues, and brings a worse prognosis. The ASCL2 shows a negative correlation with inflammation, and TLR4 reveals a positive correlation with gastric cancer. ASCL2 expression is high in MGC803 cells. Sh-ASCL2 could reduce STAD development by decreasing proliferation, tumor volume, and biomarker levels and increasing apoptosis in vitro and in vivo. The inflammatory role of ASCL2 is regulated through TLR4 activation. ASCL2 levels may be related to CNTNAP3, CLIP1, C9orf84, ARIH2, and IL1R2 mutations; positively correlated with M2 macrophage and T follicular helper cell levels; negatively correlated with neutrophil, dendritic cell, monocyte, CD8 T cell, and M1 macrophage levels; and involved in STAD prognosis.

Conclusions

The ASCL2 may adjust inflammation in STAD through TLR4 activation and may be associated with related immune cells. ASCL2 is possibly an upstream target factor of the TLR4 signaling pathway.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

Identification of Versican as an Independent Prognostic Factor in Uveal Melanoma

OBJECTIVE

To assess the role of versican (VCAN) in uveal melanoma (UVM) from its expression, prognostic value and biological function.

METHODS

The general profile of VCAN mRNA and protein expression levels were obtained using bioinformatic approaches. Then, UALCAN database was adopted to examine the association of VCAN mRNA expression and clinical factors in UVM. The prognostic value of VCAN was assessed by UALCAN, GEPIA and TISIDB databases. Besides, Cox regression analysis was performed to predict the independent prognostic factors for UVM. Further, functional enrichment analysis was conducted to reveal the biological functions of VCAN involved in UVM through DAVID, Cytoscape and GSEA analyses.

RESULTS

VCAN showed a relative low expression level in normal eye but was highly expressed in UVM cell lines. Tumor histology and stage in UVM were significantly related to VCAN mRNA expression (all P <0.05). Besides, high VCAN mRNA expression led to unfavorable prognosis of UVM patients, especially in female patients and those aged <60 years (all P <0.05). Cox regression analysis indicated that VCAN mRNA expression was an independent prognostic factor for overall survival in UVM. Enrichment analysis suggested that VCAN was mainly involved in cytokine-cytokine receptor interaction, chemokine signaling pathway and T cell receptor signaling pathway (all P <0.05). Meanwhile, hyaluronic acid was revealed to be a potential drug for the UVM treatment.

CONCLUSION

VCAN served as an independent prognostic factor for UVM. Further analysis found that VCAN was positively correlated with metastasis-related pathway, which might imply the metastasis risk of UVM. Our study initially revealed the vital role of VCAN in the process of UVM and provided a therapeutic target for UVM treatment.

Bioinformatics analysis of the prognosis and biological significance of VCAN in gastric cancer

Gastric cancer (GC) is one of the most common cancers in the world, and the tumor microenvironment (TME) plays a vital role in the occurrence and development of GC. In this study, we obtained differential expressed genes in GC tissues from The Cancer Genome Atlas. After ESTIMATE and weighted correlation network analysis, we obtained differentially expressed genes (DEGs). With further screening DEGs of immune infiltration and then through Kaplan‐Meier survival analysis, least absolute shrinkage and selection operator regression analysis and COX analysis, we found that VCAN was a gene positively correlated with high immune infiltration and poor prognosis of patients in GC. In addition, we selected a Gene Expression Omnibus dataset (GSE84433) to verify the effect of VCAN on the patient's prognosis, and analyzed the value of VCAN in immunotherapy through TIMER database and TISIDB. In conclusion, we hold the view that VCAN may affect the development of GC by regulating the TME, which may act as a potential therapeutic target for GC.