Identification of Prognostic Related Genes of Tumor Microenvironment Derived From Esophageal Cancer Patients

GRAP2 is a prognostic biomarker and correlated with immune infiltration in lung adenocarcinoma

BACKGROUND

GRAP2 is an adaptor protein involved in leukocyte signal activation; however, the prognostic value of GRAP2 and its correlation with immune infiltration in lung adenocarcinoma (LUAD) are unclear.

METHODS

Original data were downloaded from the TCGA database and Gene Expression Omnibus (GEO) database. GRAP2 expression was analyzed with the TCGA and TIMER databases. We evaluated the influence of GRAP2 on clinical prognosis using the Kaplan-Meier plotter, GEO, and GEPIA database. The TIMER and TISIDB databases were used to investigate correlations between GRAP2 expression and cancer immune characteristics. Finally, we confirmed the expression of GRAP2 in LUAD by immunohistochemistry staining.

RESULTS

The transcription levels of GRAP2 were significantly lower in several human cancer types, including LUAD, than in adjacent normal tissues. Immunohistochemistry staining confirmed that LUAD tumor tissues had lower GRAP2 protein expression levels than adjacent normal tissues. GRAP2 downregulation was associated with poorer overall survival, pathologic stage, T stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we found a hub gene set that included a total of 91 genes coexpressed with GRAP2, which were closely related to the immune response in LUAD. The expression levels of GRAP2 were positively correlated with the infiltration levels of multiple immune cells and the cumulative survival time of a few immune cells. GRAP2 expression was found to be positively correlated with that of multiple immune markers, chemokines, chemokine receptors, and MHC molecules in LUAD.

CONCLUSIONS

GRAP2 can be used as a biomarker for assessing prognosis and immune infiltration levels in LUAD.

Identification of FCER1G related to Activated Memory CD4+ T Cells Infiltration by Gene Co-expression Network and Construction of a Risk Prediction Module in Diffuse Large B-Cell Lymphoma

Diffuse large B cell lymphoma (DLBCL) is a group of biologically heterogeneous tumors with different prognoses. The tumor microenvironment plays a vital role in the tumorigenesis and development of DLBCL, and activated memory CD4⁺ T cells are an essential component of immunological cells in the lymphoma microenvironment. So far, there are few reports about activated memory CD4+T cells infiltration and related genes in the DLBCL tumor microenvironment. This study obtained the mRNA expression profile information of the testing GSE87371 dataset and another six validation datasets (GSE53786, GSE181063, GSE10846, GSE32918, GSE32018, GSE9327, GSE3892, TCGA-DLBC) from the GEO and TCGA databases. Weighted Gene Co-expression Network Analysis (WGCNA) screened gene module associated with activated memory CD4⁺ T cells infiltration. CIBERSORT and TIMER (immune cells infiltrating estimation analysis tools) were used to identify the relationship between activated memory CD4⁺ T cells and genes associated with immune infiltrating cells in the tumor microenvironment. The least absolute shrinkage and selection operator (LASSO) built the risk prediction model and verified it using nomogram and Kaplan-Meier analysis. Further functional characterization includes Gene Ontology, KEGG pathway analysis and Gene Set Enrichment Analysis (GSEA) to investigate the role and underlying mechanisms of these genes. These results suggest that the expression of FCER1G can reflect the invasion of activated memory CD4⁺ T cells in DLBCL, which provides a new idea for studying the tumor microenvironment and may become a potential predictive biomarker for the assessment of DLBCL.

Chemokines in the Landscape of Cancer Immunotherapy: How They and Their Receptors Can Be Used to Turn Cold Tumors into Hot Ones?

Over the last decade, monoclonal antibodies to immune checkpoint inhibitors (ICI), also known as immune checkpoint blockers (ICB), have been the most successful approach for cancer therapy. Starting with mAb to cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitors in metastatic melanoma and continuing with blockers of the interactions between program cell death 1 (PD-1) and its ligand program cell death ligand 1 (PDL-1) or program cell death ligand 2 (PDL-2), that have been approved for about 20 different indications. Yet for many cancers, ICI shows limited success. Several lines of evidence imply that the limited success in cancer immunotherapy is associated with attempts to treat patients with "cold tumors" that either lack effector T cells, or in which these cells are markedly suppressed by regulatory T cells (Tregs). Chemokines are a well-defined group of proteins that were so named due to their chemotactic properties. The current review focuses on key chemokines that not only attract leukocytes but also shape their biological properties. CXCR3 is a chemokine receptor with 3 ligands. We suggest using Ig-based fusion proteins of two of them: CXL9 and CXCL10, to enhance anti-tumor immunity and perhaps transform cold tumors into hot tumors. Potential differences between CXCL9 and CXCL10 regarding ICI are discussed. We also discuss the possibility of targeting the function or deleting a key subset of Tregs that are CCR8+ by monoclonal antibodies to CCR8. These cells are preferentially abundant in several tumors and are likely to be the key drivers in suppressing anti-cancer immune reactivity.