Five EMT-related genes signature predicts overall survival and immune environment in microsatellite instability-high gastric cancer

The tumor immune composition of mismatch repair deficient and Epstein-Barr virus-positive gastric cancer: A systematic review

BACKGROUND

Gastric cancer (GC), known for its unfavorable prognosis, has been classified in four distinct molecular subtypes. These subtypes not only exhibit differences in their genome and transcriptome but also in the composition of their tumor immune microenvironment. The microsatellite instable (MSI) and Epstein-Barr virus (EBV) positive GC subtypes show clear clinical benefits from immune checkpoint blockade, likely due to a neoantigen-driven and virus-driven antitumor immune response and high expression of immune checkpoint molecule PD-L1. However, even within these subtypes response to checkpoint inhibition is variable, which is potentially related to heterogeneity in the tumor immune microenvironment (TIME) and expression of co-inhibitory molecules. We conducted a systematic review to outline the current knowledge about the immunological features on the TIME of MSI and EBV + GCs.

METHODS

A systematic search was performed in PubMed, EMBASE and Cochrane Library. All articles from the year 1990 and onwards addressing immune features of gastric adenocarcinoma were reviewed and included based on predefined in- and exclusion criteria.

RESULTS

In total 5962 records were screened, of which 139 were included that reported immunological data on molecular GC subtypes. MSI and EBV + GCs were reported to have a more inflamed TIME compared to non-MSI and EBV- GC subtypes. Compared to microsatellite stable (MSS) tumors, MSI tumors were characterized by higher numbers of CD8 + and FoxP3 + T cells, and tumor infiltrating pro- and anti-inflammatory macrophages. HLA-deficiency was most common in MSI tumors compared to other molecular GC subtypes and associated with lower T and B cell infiltrates compared to HLA-proficient tumors. EBV + was associated with a high number of CD8 + T cells, Tregs, NK cells and macrophages. Expression of PD-L1, CTLA-4, Granzyme A and B, Perforin and interferon-gamma was enriched in EBV + tumors. Overall, MSI tumors harbored a more heterogeneous TIME in terms of immune cell composition and immune checkpoints compared to the EBV + tumors.

DISCUSSION AND CONCLUSION

MSI and EBV + GCs are highly Handbook for Conducting a Literature-Based Health Assessment Using OHAT Approach for Systematic Review and Evidence Integration.; 2019pro-inflammatory immune cell populations. Although studies on the direct comparison of EBV + and MSI tumors are limited, EBV + tumors show less intra-subgroup heterogeneity compared to MSI tumors. More studies are needed to identify how Intra-subgroup heterogeneity impacts response to immunotherapy efficacy.

[Screening of differentially expressed genes in gastric cancer based on GEO database and function and pathway enrichment analysis]

OBJECTIVE

To explore the core genes related to the diagnosis and prognosis of gastric cancer (GC) based on Gene Expression Omnibus (GEO) database and screen the molecular targets involved in the occurrence and development of GC.

METHODS

GC microarray data GSE118916, GSE54129 and GSE79973 were downloaded from GEO database, and the differentially expressed genes (DEGs) were screened. Enrichment analysis of the signaling pathways and molecular functions were preformed and protein-protein interaction networks (PPI) were constructed to identify the hub genes, whose expression levels and diagnostic and prognostic values were verifies based on gastric adenocarcinoma data from TCGA. The expression levels of these core genes were also detected in different GC cell lines using qRT- PCR.

RESULTS

Seventy-seven DEGs were identified, which encodes proteins located mainly in the extracellular matrix and basement membrane with activities of oxidoreductase and extracellular matrix receptor and ligand, involving the biological processes of digestion and hormone metabolism and the signaling pathways in retinol metabolism and gastric acid secretion. Nine hub genes were obtained, among which SPARC, TIMP1, THBS2, COL6A3 and THY1 were significantly up- regulated and TFF1, GKN1, TFF2 and PGC were significantly down-regulated in GC. The abnormal expressions of SPARC, TIMP1, THBS2, COL6A3, TFF2 and THY1 were significantly correlated with the survival time of GC patients. ROC curve analysis showed that aberrant expression of TIMP1 SPARC, THY1 and THBS2 had high diagnostic value for GC. High expressions of SPARC, TIMP1, THBS2 and COL6A3 were detected in GC tissues. In the GC cell lines, qRT- PCR revealed different expression patterns of these hub genes, but their expressions were largely consistent with those found in bioinformatics analyses.

CONCLUSION

SPARC, TIMP1, THBS2 and other DEGs are probably involved in GC occurrence and progression and may serve as potential candidate molecular markers for early diagnosis and prognostic evaluation of GC.

Characterization and verification of CAF-relevant prognostic gene signature to aid therapy in bladder cancer

Cancer-associated fibroblasts (CAFs) are significantly involved in determining the patient's prognosis and response to bladder cancer (BLCA) therapy. CAFs can induce epithelial-mesenchymal transformation (EMT) as well as complex interaction with immune cells. Hence, it is imperative to identify potential markers for enhancing our understanding of CAFs in BLCA progression and immune regulation. A variety of algorithms and analyses were employed in the study, leading to the development of a novel prognostic feature for CAFs-Stromal-EMT (CSE)-prognostic feature. This feature was constructed based on the genes MFAP5, PCOLCE2, and JUN. Furthermore, we revealed that patients with higher CSE risk scores responded to immunotherapy better compared to those with lower. Finally, we verified two CSE-related genes using in vitro experiments. Our results suggested that the CSE-prognostic feature could predict the prognosis and evaluate the response of patients to immune and chemotherapies. This would aid clinicians in designing treatment strategies for patients with BLCA.

EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma

This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. Analyze the EMTRGs between HCC tissue and liver tissue in the TCGA cohort in the order of univariate COX regression, LASSO regression, and multivariate COX regression, and construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate COX regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients.

LncRNA THUMPD3-AS1 promotes invasion and EMT in gastric cancer by regulating the miR-1297/BCAT1 pathway

Long noncoding RNA (lncRNA) plays crucial roles in the development of gastric cancer (GC); however, studies of their mechanisms of action are needed to determine their clinical value. The aim of this study is to explore the effects and mechanisms of THUMPD3-AS1 in GC. Elevated levels of THUMPD3-AS1 were observed in GC and demonstrated a significant positive correlation with poor prognosis. Functionally, THUMPD3-AS1 promoted GC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) and induced tumor growth in vivo. THUMPD3-AS1 exerts its regulatory function on BCAT1 through competitive binding with miR-1297. Further investigations confirmed that both THUMPD3-AS1 and miR-1297 interact with BCAT1. These findings suggest that THUMPD3-AS1 promotes GC invasion and EMT by regulating the miR-1297/BCAT1 pathway, indicating that THUMPD3-AS1 may serve as a biomarker and therapeutic target for GC.

The crosstalk between anoikis and epithelial-mesenchymal transition and their synergistic roles in predicting prognosis in colon adenocarcinoma

Anoikis and epithelial-mesenchymal transition (EMT) are significant phenomena occurring in distant metastasis of colon adenocarcinoma (COAD). A comprehensive understanding of their crosstalk and the identification of key genes are vital for treating the distant metastasis of COAD. The objective of this study was to design and validate accurate prognostic predictors for COAD patients based on the anoikis and EMT processes. We obtained gene signatures from various databases and performed univariate and multivariate Cox regression analyses, principal component analysis (PCA). The COAD patients were categorized into the worst prognosis group, the Anoikis Potential Index (API) Low + EMT Potential Index (EPI) High group and the others group. Then we utilized gene set enrichment analysis (GSEA) to identify differentially expressed genes and to establish a prognostic risk model. The model classified patients into high- or low-risk groups, with patients in the high-risk group displaying worse survival status. A nomogram was established to predict overall survival rates, demonstrating high specificity and sensitivity. Additionally, we connected the risk model to the tumor microenvironment (TME) using single-sample GSEA and the MCP counter tool, as well as evaluated the sensitivity to common chemotherapeutic drugs, such as Gefitinib and Gemcitabine. Lastly, cell and tissue experiments suggested a positive correlation among anoikis resistance, EMT, and liver/lung metastasis of COAD. This is the first study to comprehensively analyze the crosstalk between anoikis and EMT and offers new therapeutic targets for COAD metastasis patients.

A Necroptosis-Related Gene Signature to Predict the Prognosis of Skin Cutaneous Melanoma

The prognosis of skin cutaneous melanoma (SKCM) remains poor, and patients with SKCM show a poor response to immunotherapy. Thus, we aimed to identify necroptosis-related biomarkers, which can help predict the prognosis of SKCM and improve the effectiveness of precision medicine. Data of SKCM were obtained from The Cancer Genome Atlas (TCGA) and GEO databases. TCGA samples were classified into two clusters by consensus clustering of necroptosis-related genes. Univariate Cox and least absolute shrinkage and selection operator regression analyses led to the identification of 11 genes, which were used to construct a prognostic model. GSE65904 was used as the test set. Principal component, t-distributed stochastic neighbor embedding, and Kaplan–Meier survival analyses indicated that samples in the train and test sets could be divided into two groups, with the high-risk group showing a worse prognosis. Univariate and multivariate Cox regression analyses were performed, and a nomogram, calibration curve, and time-dependent receiver operating characteristic curve were constructed to verify the efficacy of our model. The 1-, 3-, and 5-year areas under the receiver operating characteristic curves for the train set were 0.702, 0.663, and 0.701 and for the test set were 0.613, 0.627, and 0.637, respectively. Moreover, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses between the high- and low-risk groups. Single sample gene set enrichment analysis, immune cell infiltration analysis, tumor microenvironment scores, immune checkpoint analysis, and half-maximal inhibitory concentration prediction indicated that the high-risk group showed weaker antitumor immunity; further, the response to immune checkpoint inhibitors was worse, and the high-risk group was sensitive to fewer antitumor drugs. Tumor mutational burden analysis, Kaplan–Meier survival analysis, and correlation analysis between risk score and RNA stemness score revealed that the high-risk group with low tumor mutational burden and high RNA stemness score was potentially associated with poor prognosis. To conclude, our model, which was based on 11 necroptosis-related genes, could predict the prognosis of SKCM; in addition, it has guiding significance for the selection of clinical treatment and provides new research directions to enhance necroptosis against SKCM.