Tumor-Associated Inflammation: The Tumor-Promoting Immunity in the Early Stages of Tumorigenesis

Bi, Qing; Wu, Jiyue; Qiu, Xue-Meng; Zhang, Jian-Dong; Sun, Zejia; Wang, Wei

doi:10.1155/2022/3128933

Cited by 17 publications

(8 citation statements)

References 143 publications

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“…Numerous studies have demonstrated that infiltrating immune cells in the microenvironment exert dual effects of promoting tumor and antitumor growth [18, 19]. On account of the destruction of blood‒brain barrier integrity by gliomas and the lymphatic outflow channels, the immune system can communicate with cells within the central nervous system [20, 21].…”

Section: Discussionmentioning

confidence: 99%

Diverse cell death signature based subtypes predict the prognosis and immune characteristics within glioma

Wang,

Song,

et al. 2024

Preprint

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BackgroundCell death plays an essential role in the pathogenesis, progression, drug resistance and recurrence of glioma. Although multiple cell death pathways are involved in glioma development, there is lack of a stratification and prognostic modelling for glioma based on the integration of diverse genes for cell deaths.MethodsIn this study, 1254 diverse cell death (DCD)-related genes were assessed using the ConsensusClusterPlus assessment to identify DCD patterns in glioma. CIBERSORT, ssGSEA, and ESTIMATE algorithms were applied to evaluate immune microenvironment differences between subtypes. LASSO Cox regression was used to screen prognosis-related DCD genes, and a risk score model was constructed. TMB, TIDE, immune infiltration, and immunotherapy response was analyzed to evaluate the immune characteristics.ResultsTwo DCD-related subgroups named Clusters 1 and 2, with distinct DCD levels, immune characteristics, and prognoses, were determined from glioma samples. A DCD-based risk score model was developed to assess DCD levels in glioma patients and divide patients into high- and low-risk groups. We found this risk model can be used as an independent prognostic factor for glioma patients. Notably, glioma patients with low risk scores exhibited subdued DCD activity, prolonged survival, and a favorable disposition towards benefiting from immune checkpoint blockade therapies.ConclusionsThis study established a novel signature classification and a risk model by comprehensively analyzing patterns of various DCDs to stratify glioma patients and to predict the prognosis and immune characteristics of glioma. We provided a theoretical basis for the clinical application of DCD-related genes in glioma prognosis and immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Diverse cell death signature based subtypes predict the prognosis and immune characteristics within glioma

Wang,

Song,

et al. 2024

Preprint

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“…TPICs chiefly comprise regulatory T cells (Tregs) and myeloid-derived suppressor cells. Tumor-related immune cells improve tumor development by secreting cytokines and promoting metastasis through the production of growth factors and matrix-degrading enzymes ( Bi et al, 2022 ). Immune infiltration could also influence the clinical prognosis.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis to construct a novel immune-related prognostic panel in aging-related gastric cancer based on the lncRNA‒miRNA-mRNA ceRNA network

Deng

Peng

Cheng

et al. 2023

Front. Mol. Biosci.

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Introduction: Gastric cancer (GC) is the fifth frequent malignancy and is responsible for the third leading cause of cancer-related deaths. Gastric cancer is an aging-related disease, with incidence and mortality rates increasing with aging. The development of GC is affected by lncRNAs, miRNAs, and mRNAs at the transcriptional and posttranscriptional levels. This study aimed to establish a prognostic panel for GC based on competing endogenous RNA (ceRNA) networks.Methods: RNA sequences were obtained from the TCGA database. Different expressions of RNAs were scrutinized with the EdgeR package. The ceRNA network was built using the starBase database and the Cytoscape. The prognostic panel was constituted with the LASSO algorithm. We developed a nomogram comprising clinical characteristic and risk score. The receiver operating characteristic (ROC) was used to evaluate the accuracy of the nomogram prediction. Hub RNAs expressions were detected by qPCR, immunohistochemistry and western blot respectively. Clinical relevance and survival analyses were analyzed. The relationship between RNAs and immune infiltrations, as well as immune checkpoints, was analyzed and evaluated using the CIBERSORT, TIMER and TISIDB databases.Results: Four DElncRNAs, 21 DEmiRNAs and 45 DEmRNAs were included in the ceRNA network. A 3-element panel (comprising lncRNA PVT1, hsa-miR-130a-3p and RECK) with poor overall survival (OS) was established and qPCR was applied to validate the expressions of hub RNAs. Hub RNAs were firmly associated with T, M, and N stage. The CIBERSORT database showed that the high lassoScore group exhibited a significantly high ratio of resting memory CD4+ T cells, M2 macrophages and a significantly low ratio of activated memory CD4+ T cells and M1 macrophages. According to the TIMER database, this panel was linked to immune infiltrations and immune cell gene markers. TISIDB database indicated that RECK was positively correlated with immune checkpoints (including CD160, CD244, PDCD1, and TGFBR1).Discussion: A novel triple prognostic panel of GC constructed based on the ceRNA network was associated with clinical prognostic, clinicopathological features, immune infiltrations, immune checkpoints and immune gene markers. This panel might provide potential therapeutic targets for GC and more experimental verification research is needed.

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“…Tumor-associated immune cells can promote tumor progression by producing cytokines and assist tumor metastasis by secreting growth factors or matrix-degrading enzymes ( 43 ). Our study found that the SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 expressions were positively linked with the infiltration of CD8 + T cells CD4 + T cells, macrophages, neutrophils, and dendritic cells.…”

Section: Discussionmentioning

confidence: 99%

Schlafen family is a prognostic biomarker and corresponds with immune infiltration in gastric cancer

Chen

Liang

et al. 2022

Front. Immunol.

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The Schlafen (SLFN) gene family plays an important role in immune cell differentiation and immune regulation. Previous studies have found that the increased SLFN5 expression in patients with intestinal metaplasia correlates with gastric cancer (GC) progression. However, no investigation has been conducted on the SLFN family in GC. Therefore, we systematically explore the expression and prognostic value of SLFN family members in patients with GC, elucidating their possible biological function and its correlation with tumor immune cells infiltration. TCGA database results indicated that the SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN13 expression was significantly higher in GC. The UALCAN and KM plotter databases indicated that enhanced the SLFN family expression was associated with lymph node metastasis, tumor stage, and tumor grade and predicted an adverse prognosis. cBioportal database revealed that the SLFN family had a high frequency of genetic alterations in GC (about 12%), including mutations and amplification. The GeneMANIA and STRING databases identified 20 interacting genes and 16 interacting proteins that act as potential targets of the SLFN family. SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 may be implicated in the immunological response, according to Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, Timer and TISIDB databases indicate that SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 are involved in the immune response. Furthermore, Timer, TCGA, and TISIDB databases suggested that the SLFN5, SLFN11, SLFN12, SLFN12L, and SLFN14 expression in GC is highly linked with immune cell infiltration levels, immune checkpoint, and the many immune cell marker sets expression. We isolated three samples of peripheral blood mononuclear cell (PBMC) and activated T cells; the results showed the expression of SLFN family members decreased significantly when T cell active. In conclusion, the SLFN family of proteins may act as a prognostic indicator of GC and is associated with immune cell infiltration and immune checkpoint expression in GC. Additionally, it may be involved in tumor immune evasion by regulating T cell activation.

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Tumor-Associated Inflammation: The Tumor-Promoting Immunity in the Early Stages of Tumorigenesis

Cited by 17 publications

References 143 publications

Diverse cell death signature based subtypes predict the prognosis and immune characteristics within glioma

Diverse cell death signature based subtypes predict the prognosis and immune characteristics within glioma

Comprehensive analysis to construct a novel immune-related prognostic panel in aging-related gastric cancer based on the lncRNA‒miRNA-mRNA ceRNA network

Schlafen family is a prognostic biomarker and corresponds with immune infiltration in gastric cancer

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