Ischemic stroke (IS) is a multifactorial disease caused by the interaction of multiple environmental and genetic risk factors, and it is the most common cause of disability. The immune microenvironment and inflammatory response participate in the whole process of IS occurrence and development. Therefore, the rational use of relevant markers or characteristic pathways in the immune microenvironment will become one of the important therapeutic strategies for the treatment of IS. We collected peripheral blood samples from 10 patients diagnosed with IS at the First Affiliated Hospital of Gannan Medical University and First Affiliated Hospital, Jinan" University, and from 10 normal people. The GSE16561 dataset was downloaded from the Gene Expression Omnibus (GEO) database. xCell, gene set enrichment analysis (GSEA), single-sample GSEA (ssGSEA) and immune-related gene analysis were used to evaluate the differences in the immune microenvironment and characteristic pathways between the IS and control groups of the two datasets. xCell analysis showed that the IS-24h group had significantly reduced central memory CD8+ T cell, effector memory CD8+ T cell, B cell and Th1 cell scores and significantly increased M1 macrophage and macrophage scores. GSEA showed that the IS-24h group had significantly increased inflammation-related pathway activity(myeloid leukocyte activation, positive regulation of tumor necrosis factor biosynthetic process, myeloid leukocyte migration and leukocyte chemotaxis), platelet-related pathway activity(platelet activation, signaling and aggregation; protein polymerization; platelet degranulation; cell-cell contact zone) and pathology-related pathway activity (ERBB signaling pathway, positive regulation of ERK1 and ERK2 cascade, vascular endothelial growth factor receptor signaling pathway, and regulation of MAP kinase activity). Immune-related signature analysis showed that the macrophage signature, antigen presentation-related signature, cytotoxicity-related signature, B cell-related signature and inflammation-related signature were significantly lower in the IS-24h group than in the control group. In this study, we found that there were significant differences in the immune microenvironment between the peripheral blood of IS patients and control patients, as shown by the IS group having significantly reduced CD8+ Tcm, CD8+ Tem, B cell and Th1 cell scores and significantly increased macrophage and M1 macrophage scores. Additionally, inflammation-related, pathological, and platelet-related pathway activities were significantly higher in the IS group than in the control group.
Cervical cancer (CC) remains high morbidity and mortality. We aimed to identify critical pathways underlying cervical carcinogenesis and establish a prognostic signature. Six datasets from the gene expression omnibus (GEO) database were used to screen the differentially expressed genes (DEGs) between CC and normal tissues. We used the unions of the DEGs to perform functional analysis. The 108 overlapped DEGs were analyzed to determine a prognostic signature by Cox regression and Lasso analysis based on The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Immune Cell Abundance Identifier (ImmuCellAI) were used to determine the relationships between the signature and biological functions. The PI3K-Akt signaling pathway, the Ras signaling pathway, and the viral carcinogenesis pathway may be critical for CC development. We identified seven genes (PLOD2, DSG2, SPP1, CXCL8, MCM5, HLTF, and KLF4) to construct a risk score formula. Survival analysis showed that the high-risk group indicated a worse prognosis than the low-risk group p < 0.0001 . The AUC of the prognostic signature was 0.7449, 0.7641, and 0.8146 at 1, 3, and 5 years. We also identified that the signature is an independent prognostic factor. GSEA showed five pathways were relevant to the signature, such as the adherens junction pathway. The signature also affected the abundances of various types of immune cells, such as B cell, CD4+ T cell, and CD8+ T cell. Further, we found that SPP1 was co-expressed with HK3, CD163, CCL3, CLEC5A, MMP8, TREM1, OLR1, and TREM2. The results of Gene Ontology analysis showed that SPP1 and its co-expressed related proteins mainly affected metabolic process, multicellular organismal process, cell communication, cell proliferation, protein binding, and transporter activity. In conclusion, the present study explored the key pathways for CC development and the seven-gene signature can effectively make the prognosis evaluation of CC patients.
Background: Cisplatin is the basis of the primary treatment for SCLC chemotherapy. However, the limited objective response rate and definite drug resistance greatly restrict the clinical potential and therapeutic benefits of cisplatin use. Therefore, it is essential to identify biomarkers that can discern the sensitivity of SCLC patients to cisplatin treatment.Methods: We collected two SCLC cohorts treated with cisplatin that included mutation data, prognosis data and expression data. The sensitivity of cisplatin was evaluated by the pRRophetic algorithm. MCPcounter, quanTIseq, and xCell algorithms were used to evaluate immune cell score. GSEA and ssGSEA algorithms were used to calculate immune-related pathway scores. Univariate and multivariate Cox regression models were employed, and survival analysis was used to evaluate the prognostic value of the candidate genes.Results: MMP9-High is related to improved clinical prognoses of patients with SCLC (HR = 0.425, p = 0.0085; HR = 0.365, p = 0.0219). Multivariate results showed that MMP-High could be used as an independent predictor of the prognosis of SCLC after cisplatin treatment (HR = 0.216, p = 0.00153; HR = 0.352; p = 0.0199). In addition, MMP9-High displayed a significantly lower IC50 value of cisplatin and higher immunogenicity than MMP9-Low SCLC. Compared with MMP9-Low SCLC, MMP9-High included significantly increased levels of T-cells, cytoxic lymphocytes, B-cells, NK-cells, and dense cells (DCS). Similarly, the activity of cytokine binding, B-cell, NK-cell mediated immune response chemokine binding, and antigen presentation pathways in MMP9-High was significantly higher than that in MMP9-Low.Conclusion: In this study, we identified that MMP9-High could be potentially considered a novel biomarker used to ascertain the improved prognosis of SCLC patients after cisplatin treatment. Furthermore, we indicated that the tumor immune microenvironment of MMP9-High SCLC is mainly characterized by a large number of infiltrated activated immune cells as well as activated immune-related pathways.
IntroductionGlioblastoma(GBM) is a highly malignant primary brain tumor. Even after undergoing surgery and chemotherapy, patients with this affliction still have little to no chance of survival. Current research on immunotherapy treatment for GBM shows that immune-checkpoint inhibitors (ICIs) may be a promising new treatment method. However, at present, the relationship between the fatty acid metabolic process and the prognosis of GBM patients who are receiving immunotherapy is not clear.MethodsFirst, we downloaded a GBM cohort that had been treated with immunotherapy, which included the mutation and prognosis data, and the TCGA-GBM and Jonsson-GBM queues. CIBERSORT and single sample gene set enrichment analysis(ssGSEA) were used to evaluate immune cell scores. Gene set enrichment analysis (GSEA) was used to evaluate the patient’s accessment score. The pRRophetic algorithm was used to evaluate the drug sensitivity of each patient. Univariable and multivariate cox regression analyses, as well as the Kaplan-Meier (KM) method, were used to evaluate the relationship between the fatty acid metabolic process and the prognosis of GBM patients.ResultsThe univariate and multivariate cox regression models showed that the fatty acid metabolic process mutant-type (MT) can be used as an independent predictor of the efficacy of immunotherapy for GBM patients. In addition, fatty acid metabolic process MT is related with significantly longer overall survival (OS) time than the wild-type(WT) variant. However, the mutation status of the fatty acid metabolic process has nothing to do with the prognosis of GBM patients who are receiving conventional treatment. Our analysis showed that fatty acid metabolic process MT correlated with significantly increased natural killer T (NKT) cells and significantly decreased CD8+T cells. At the same time, GSEA analysis revealed that fatty acid metabolic process MT was associated with significantly increased immune activation pathways and an enriched fraction of cytokine secretion compared with WT.ConclusionsWe found that fatty acid metabolic process MT may be used as an independent predictor of the efficacy of ICI treatment in GBM patients. Use of the fatty acid metabolic process MT will result in higher immunogenicity rates, a significant increase in the proportion of activated immune cells, and improvement of the immune microenvironment.
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