Notch3 signaling promotes colorectal tumor growth by enhancing immunosuppressive cells infiltration in the microenvironment.

BACKGROUND: Macrophage infiltration in the tumor microenvironment participates in the regulation of tumor progression. Previous studies have found that Notch signaling pathway is involved in regulating the progression of colorectal cancer (CRC), however, the specific mechanism is still unclear. METHODS: The correlation between Notch signaling pathway and macrophage infiltration was investigated in TCGA database and verified in clinical samples of patients with CRC using immunohistochemistry. Gene Set Enrichment Analysis was used to find out genes related to Notch3 expression. Colony formation assay, and flow cytometry were utilized to test tumor growth and immune cell infiltration in vitro and in vivo. RESULTS: Using bioinformatics analysis and clinical sample validation, we found that Notch3 was highly expressed in colon tumor tissues compared to adjacent normal tissues, and it participated in regulating the recruitment of macrophages to the tumor microenvironment. Furthermore, we found that the Notch3 expression was positively correlated with the expression of macrophage recruitment-related cytokines in colon tumor tissues. Finally, we demonstrated that depletion of Notch3 had no significant effect on the growth of colon tumor cells in vitro, while, attenuated the growth of colon cancer tumors in vivo. Simultaneous, immunosuppressive cells, macrophages and myeloid-derived suppressor cell (MDSC) infiltration were dramatically reduced in the tumor microenvironment. CONCLUSION: Our study illustrated that Notch3 could facilitate the progression of CRC by increasing the infiltration of macrophages and MDSCs to promote the immunosuppressive tumor microenvironment. Targeting Notch3 specifically is a potentially effective treatment for CRC.

Identification of three predictors of gastric cancer progression and prognosis.

Abnormal gene expression is an established cause of gastric cancer (GC) initiation and progression. In this study, we aimed to identify several key genes that could be used to effectively predict progression and prognosis in patients with GC. The Cancer Genome Atlas and the Gene Expression Omnibus database were used to identify candidate genes. Fourteen genes were found to associate highly with progress, metastasis, and survival of GC. Five of these genes were overexpressed in tumor tissue compared to adjacent normal tissue. This was confirmed by reverse transcription-polymerase chain reaction and western blotting for myosin-Va (MYO5A), phospholipid transfer protein (PLTP), and tripeptidyl peptidase 1 (TPP1), while the CCK8 assay was used to show that these three genes promote GC cell proliferation. In summary, we demonstrate that MYO5A, PLTP, and TPP1 expression may be suitable markers for the progression and prognosis of GC.

Bioinformatics analysis of microenvironment-related genes associated with radioresistance in glioblastoma.

BACKGROUND: Immune and stromal cells are the two major non-tumor cell types in the glioblastoma (GBM) microenvironment, which play critical roles in the prognostic assessment of tumors. Previous findings have identified genes with prognostic value in the GBM microenvironment; however, correlations between microenvironment-related genes and GBM radioresistance remain unclear. Therefore, in this study, we screened for vital microenvironment-related genes associated with radioresistance in GBM. METHODS: We analyzed the data from 348 patients with primary GBM that had undergone radiotherapy (patients with GBM-RT), in The Cancer Genome Atlas database. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to calculate stromal and immune scores to identify the differentially expressed genes (DEGs). Functional enrichment analyses and a protein-protein interaction (PPI) network construction were performed. Survival analysis was conducted to determine genes with prognostic value. The Chinese Glioma Genome Atlas (CGGA) cohort was utilized for validation. RESULTS: The stromal score was significantly correlated with the prognoses of patients with GBM-RT. Based on the stromal and immune scores, 139 common DEGs involved in inflammation or immune-related activities were identified. We also identified 86 DEGs associated with poor prognosis, which further intersected with the top nodes in the PPI network. Finally, we identified the shared DEGs using the CGGA database and found 10 genes with prognostic value that contributed to GBM radioresistance. These genes included TLR2, C3AR1, CD163, ALOX5AP, NCF2, CYBB, FCGR1A, FCGR2A, FCGR2B, and RNASE6. CONCLUSIONS: We identified several genes related to the immune microenvironment that may mediate GBM radioresistance. Our findings provide a theoretical basis for predicting the radioresponse and survival of patients with GBM.