Background Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesi...
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Background Stomach adenocarcinoma (STAD) is the fifth most prevalent cancer in the world and ranks third among cancer-related deaths worldwide. The tumour microenvironment (TME) plays an important role in tumorigenesis, development, and metastasis. Hence, we calculated the immune and stromal scores to find the potential prognosis-related genes in STAD using bioinformatics analysis. Methods The estimate algorithm was used to calculate the immune/stromal scores of the STAD samples. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, and overall survival analysis were then performed on differential genes. And we validated these genes using data from the Gene Expression Omnibus database. Finally, we used the Human Protein Atlas (HPA) databases to verify these genes at the protein levels by IHC. Results Data analysis revealed correlation between stromal/immune scores and the TNM staging system. The top 10 core genes extracted from the PPI network, and primarily involved in immune responses, extracellular matrix, and cell adhesion. There are 31 genes have been validated with poor prognosis and 16 genes were upregulated in tumour tissues compared with normal tissues at the protein level. Conclusions In summary, we identified genes associated with the tumour microenvironment with prognostic implications in STAD, which may become potential therapeutic markers leading to better clinical outcomes.
Background Gastric cancer remains one of the major causes for tumor-related deaths worldwide. Our study aimed to provide an understanding of primary gastric cancer and prompt its clinical diagnosis and treatment. Meth...
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Background Gastric cancer remains one of the major causes for tumor-related deaths worldwide. Our study aimed to provide an understanding of primary gastric cancer and prompt its clinical diagnosis and treatment. Methods We integrated the expression profiles and overall survival information of primary gastric cancer in TCGA and GEO database and estimated the stromal score of each sample by the estimate R package. Stromal score and clinicopathologic characteristics associated with overall survival were analyzed by using Cox regression and the Kaplan-Meier method. Gene set enrichment analysis (GSEA) and KEGG analysis were performed to explore the potential molecular mechanism in TCGA dataset. The relationship between immunotherapy-associated markers or immune cell types and stromal score was explored by using Pearson correlation analysis. Results A total of 796 samples were collected for the analysis. Patients with stromal score-high showed poor overall survival (P < .01, HR: 1.407, 95% CI: 1.144-1.731) and identified as an independent prognostic factor. KEGG analysis revealed that stromal score actively involved in diverse tumor-associated pathways. GSEA analysis also revealed stromal score associated with diverse immune-related biological processes. Furthermore, stromal score was related with immunotherapy-associated markers and multiple immune cells. Conclusion Our results showed that stromal score could serve as a potential prognostic biomarker in primary gastric cancer and play an important role in the recognition, surveillance, and prognosis of gastric cancer.
Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of differ...
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Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), estimate algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein-protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to th
Background: As a common pathological type of lung cancer, lung adenocarcinoma (LUAD) is mainly treated by surgery, chemotherapy, targeted therapy and radiotherapy. Although a relatively mature treatment system has bee...
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Background: As a common pathological type of lung cancer, lung adenocarcinoma (LUAD) is mainly treated by surgery, chemotherapy, targeted therapy and radiotherapy. Although a relatively mature treatment system has been established, there are few studies on the microenvironment of LUAD. Material and Methods: The immune and stromal scores of patients from the LUAD cohort in the TCGA database were obtained by using estimate. The relationship of immune and stromal scores with the clinicopathological characteristics and overall survival of LUAD patients was assessed by R. GO, KEGG and Cox regression analyses were employed to analyze intersecting genes and to identify reliable prognostic markers. The identified genes were also analyzed in the GEPIA database to assess their correlations with survival, and these relationships were verified with the Kaplan-Meier Plotter database. Results: The immune score was related to the survival time and tumor topography of LUAD patients. There was a significant correlation between stromal score and tumor metastasis. Through multivariate analysis, stage (HR = 1.640, 95% CI = 1.019-2.642, P = 0.042) and risk score (HR = 1.036, 95% CI = 1.026-1.046, P < 0.001). The genes (ARHGAP15, BTLA, CASS4, CLECL1, FAM129C, STAP1, TESPA1, and S100P) showed credible prognostic value in LUAD patients in TCGA through GEPIA database online analysis and verification in the Kaplan-Meier plotter database. Conclusions: In the microenvironment of lung adenocarcinoma, the differentially expressed genes screened by immune score and stromal score have certain value in evaluating the survival/prognosis of patients, as well as the invasion and progression of tumors.
OBJECTIVE: The tumor microenvironment greatly influences tumor formation, invasion, and progression. The estimate (Estimation of STromal and Immune cells in MAlignant Tumor tissues) algorithm quantifies stromal and im...
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OBJECTIVE: The tumor microenvironment greatly influences tumor formation, invasion, and progression. The estimate (Estimation of STromal and Immune cells in MAlignant Tumor tissues) algorithm quantifies stromal and immune components in a tumor, reflecting the tumor microenvironment. This study aimed to explore key prognostic genes in a grade II/III glioma microenvironment. METHODS: We obtained stromal/immune scores for the Cancer Genome Atlas (TCGA) grade II/III glioma cohort from the online estimate portal. The associations of stromal/immune scores with clinicopathologic characteristics and overall survival of patients with grade II/III glioma were assessed by the Mann-Whitney U test and the Kaplan-Meier method, respectively. Functional enrichment analysis and protein-protein interaction network assessments were employed to analyze differentially expressed genes (DEGs). The top 7 genes with 5 or more edges in the protein-protein interaction network were selected. For validation, CGGA grade II/III glioma data were analyzed. RESULTS: The results showed that elevated stromal/immune/estimate score was significantly associated with poor survival of patients with TCGA grade II/III glioma. Functional enrichment analysis showed that DEGs were associated with immune cell regulation, extracellular matrix, cytokine activation, and receptor binding. The selected DEGs (interleukin-10, beta-2 microglobulin, C-C motif chemokine ligand 5, cluster of differentiation 74, human leukocyte antigen-DRA, lymphocyte cytosolic protein 2, and myxovirus resistance protein 1) showed prognostic values in patients with grade II/III glioma of the TCGA and CGGA database. CONCLUSIONS: Stromal/immune/estimate scores have prognostic values in patients with grade II/III glioma. The selected DEGs, including interleukin-10, beta-2 microglobulin, C-C motif chemokine ligand 5, cluster of differentiation 74, human leukocyte antigen-DRA, lymphocyte cytosolic protein 2, and myxovirus resistance protein 1, a
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