Enhanced EMT Characteristics Associated with Unfavorable Tumor Microenvironment, Angiogenesis, and Poorer Prognosis in Gastric Cancer

Academic Background

Epithelial-Mesenchymal Transition (EMT) is an extremely important mechanism that promotes the metastasis of cancer cells. However, despite its apparent importance, the clinical significance of EMT in patients with gastric carcinoma (GC) remains unclear. This study aims to explore the clinical relevance of EMT characteristics in gastric cancer by analyzing transcriptome data from a large cohort of gastric cancer patients, especially its association with patient prognosis, tumor microenvironment, angiogenesis, and other factors.

Research Source

This study was authored by Masanori Oshi and colleagues from multiple institutions, including the Department of Gastrointestinal Surgery at Yokohama City University Graduate School of Medicine and the Roswell Park Comprehensive Cancer Center. It was published in the journal Cancer Gene Therapy in 2024.

Research Methods

Patient Data Set

The study selected two large gastric cancer patient cohorts: the TCGA (The Cancer Genome Atlas) cohort (375 patients) and the GSE84437 cohort (432 patients). The mRNA expression and clinical pathology data for these patients were obtained from the GDC data portal and the GEO repository, respectively. The data were processed with a log2 transformation.

EMT Scoring

To assess the level of EMT enhancement, we employed Gene Set Variation Analysis (GSVA) utilizing the “hallmark_epithelial_mesenchymal_transition” gene set from the Molecular Signatures Database (MSigDB). This scoring includes 200 EMT-related genes (detailed in Supplementary Table S2). Based on the gene expression profile of the samples and the given gene set, the GSVA method calculates a GSVA enrichment score for each sample.

Biological Function Analysis

To explore the differences in biological functions between low and high EMT gastric cancer groups, we used Gene Set Enrichment Analysis (GSEA) on the hallmark gene sets in the MSigDB to determine the enrichment status of each gene set, setting a statistical significance threshold of FDR < 0.25.

Tumor Microenvironment Analysis

The xCell algorithm was used to infer the infiltration scores of 64 types of immune and stromal cells, and enrichment analysis methods were used to calculate the cell type enrichment scores for each sample.

Statistical Analysis

Statistical analysis was performed using R software. Group comparisons were analyzed using the Kruskal-Wallis and Mann-Whitney U tests. Survival analyses were conducted using log-rank tests and Cox proportional hazards regression.

Research Results

Relationship Between EMT Characteristic Score and Patient Survival Rate

EMT activity was assessed using the GSVA method based on the mRNA expression of 200 EMT-related genes. The results showed that gastric cancer patients with high EMT scores exhibited significantly poorer disease-specific survival (DSS) and overall survival (OS) in both the TCGA and GSE84437 cohorts. Compared to the expression levels of key EMT-related genes (such as CDH1, CDH2, VIM, and FN1), EMT scores demonstrated stronger prognostic potential.

Relationship Between EMT Scores and Survival Rates in Different Cancers

After analyzing TCGA cohorts of multiple cancers, it was found that although EMT score levels did not significantly differ among various cancers, the EMT score was significantly associated with the survival rate of gastric cancer patients, whereas this association was not observed in other cancers.

Relationship Between EMT Scores and Tumor Invasion

The study found that EMT scores were significantly higher in aggressive pathological diagnoses (such as mucinous and diffuse types) and were significantly correlated with the progression of gastric cancer, including AJCC staging and invasion depth.

EMT Scores as Independent Prognostic Biomarkers

Through univariate and multivariate Cox regression analyses, it was found that EMT scores were an independent prognostic indicator, independent of other clinical factors (such as age, AJCC T- and N-categories).

Relationship Between EMT Scores and Immune Microenvironment

Gastric cancers with high EMT scores showed reduced infiltration of T helper 1 (Th1) cells, while showing increased infiltration of dendritic cells and M1 macrophages. At the same time, the high EMT group exhibited high T cell receptor (TCR) richness and lymphocyte infiltration scores, but no significant difference in interferon-gamma (IFN-γ) response.

Inverse Association Between EMT Scores and Cell Proliferation-Related Signals

Gastric cancers with high EMT scores exhibited lower scores of somatic and non-somatic mutations and segment alterations, as well as high stromal cell infiltration scores. This suggests that gastric cancers with high EMT scores might have lower cell proliferation signals, which could affect patient survival.

Association Between EMT Scores and Multiple Carcinogenic Gene Sets

GSEA analysis showed that gastric cancers with high EMT scores were significantly enriched in multiple carcinogenic gene sets, such as angiogenesis, apical junction, apoptosis, coagulation, hypoxia, Kras signaling upregulation, myogenesis, and TGF-β signaling pathways.

Discussion and Conclusion

This study demonstrates a significant association of EMT in gastric cancer, with high EMT characteristics tending to be associated with more aggressive clinical features and poorer prognosis. The interaction between EMT and multiple carcinogenic signaling pathways, such as angiogenesis, hypoxia, and TGF-β signaling, illustrates its complexity and role in cancer progression. Additionally, evaluating the overall tumor’s EMT characteristics can reveal more clinical significance, suggesting that EMT may play an important role in prognosis for gastric cancer patients.

Significance and Value of the Study

This study emphasizes the critical role of EMT in gastric cancer, particularly in patient prognosis and the tumor microenvironment. By gaining a more comprehensive understanding of EMT characteristics, we may develop more effective treatment strategies in the future to inhibit cancer metastasis and improve patient survival rates.