Apoptosis-Inducing TNF Superfamily Ligands for Cancer Therapy

Arguello, Olivia Adaly Diaz; Haisma, Hidde J.

doi:10.3390/cancers13071543

Cited by 37 publications

(37 citation statements)

References 222 publications

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“…TNF is not only a pleiotropic cytokine that triggers NF- κ B activation or RIPK1 kinase-dependent cell death but also a major mediator in inflammation [ 20 ]. As a type II transmembrane protein, TNF- α binds to tumor necrosis factor receptor 1 (TNF-R1) and TNF-R2, which subsequently activates downstream signaling pathways [ 7 , 21 ]. Interestingly, TNF plays a “double-edged sword” role in cancer, largely depending on the role of TNF-R1 and TNF-R2 [ 22 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

“…TNF and TNF receptor (TNFR) superfamily (TNFSF/TNFRSF) consist of nineteen ligands and twenty-nine receptors [ 6 ]. TNF family members are expressed naturally by the immune system and kill tumor activity [ 7 ]. In addition, tumor necrosis factor- (TNF-) related ligands have high expectations in anticancer therapy due to their induction of apoptosis [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Molecular Analysis of Prognosis and Immune Pathways of Pancreatic Cancer Based on TNF Family Members

Zeng

Tang

et al. 2021

Journal of Oncology

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Background. Tumor necrosis factor (TNF) family members play a vital role in anticancer therapy. This study aimed to screen the critical markers for the prognostic analysis of pancreatic adenocarcinoma (PAAD) by analyzing the clustering patterns of TNF family members in PAAD. Methods. In this study, the NMF clustering method was adopted to cluster samples from The Cancer Genome Atlas (TCGA) to acquire the clustering pattern of the TNF family in PAAD. Differential gene analysis was performed according to TNF family gene clusters. The support vector machine (SVM) method was conducted for further gene screening, and the risk score model of the screened genes was constructed by Lasso. The single sample gene set enrichment analysis (ssGSEA) method was adopted for immunoenrichment analysis and tumor immune cycle analysis. Genes associated with risk scores were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results. We clustered PAAD into two groups based on TNF family genes. Nineteen TNF family genes were significantly associated with the clinical characteristics of PAAD patients. The risk score formula was composed of RHOD, UBE2C, KLHDC7b, MSLN, ADAM8, NME3, GNG2, and MCOLN3. GSE57495 and GSE62452 datasets verified that patients in the high-risk group had a worse prognosis than those in the low-risk group. The risk score-related genes analyzed by GO and KEGG were mainly involved in the modulation of chemical synaptic transmission and synaptic vesicle cycle pathway. There were significant differences in the expression of 15 immune cells between the high-risk group and the low-risk group. The risk score was positively correlated with HCK, interferon, MHC-I, and STAT1. The expression of genes relevant to chemokine, immunostimulator, MHC, and receptor was strongly associated with the risk score. Conclusion. The risk score model based on the TNF family can predict the prognosis and immune status of PAAD patients. Further research is needed to verify the clinical prognostic value of risk scores.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Molecular Analysis of Prognosis and Immune Pathways of Pancreatic Cancer Based on TNF Family Members

Zeng

Tang

et al. 2021

Journal of Oncology

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“…TNF-α also seems to have this logic, that is, it can regulate tumor apoptosis in the early stage, and it can increase tumor invasion and metastasis in the late stage. In most reports, it is described that the two should be used to effectively kill cancer in the early stage ( 133 , 134 ), and the two should be targeted for treatment in the late stage ( 135 , 136 ). However, we have proposed that the two play more antagonistic effects in the early stage and evolution of the tumor, and synergistic effects occur in the late stage of the tumor, and whether targeted therapy is needed or not needs to be distinguished according to different tissues and cells.…”

Section: The Application Of Tnf-α and Tgf-β In Tumor Treatmentmentioning

confidence: 99%

Duality of Interactions Between TGF-β and TNF-α During Tumor Formation

Liu

Zhang

et al. 2022

Front. Immunol.

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The tumor microenvironment is essential for the formation and development of tumors. Cytokines in the microenvironment may affect the growth, metastasis and prognosis of tumors, and play different roles in different stages of tumors, of which transforming growth factor β (TGF-β) and tumor necrosis factor α (TNF-α) are critical. The two have synergistic and antagonistic effect on tumor regulation. The inhibition of TGF-β can promote the formation rate of tumor, while TGF-β can promote the malignancy of tumor. TNF-α was initially determined to be a natural immune serum mediator that can induce tumor hemorrhagic necrosis, it has a wide range of biological activities and can be used clinically as a target to immune diseases as well as tumors. However, there are few reports on the interaction between the two in the tumor microenvironment. This paper combs the biological effect of the two in different aspects of different tumors. We summarized the changes and clinical medication rules of the two in different tissue cells, hoping to provide a new idea for the clinical application of the two cytokines.

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“…TRAIL, also known as Apo2 ligand (Apo2L), is a homotrimeric transmembrane protein, which has 28% sequence homology with FASL and 23% homology with TNF-α [62]. The membrane-bound TRAIL can be cleaved by proteases into soluble TRAIL that is released into the intercellular space [63]. Moreover, TRAIL selectively induces cell apoptosis in cancer cells and not in normal cells, which causes less side effects as compared to radiotherapy and chemotherapy.…”

Section: Trailmentioning

confidence: 99%

Receptor Specificity Engineering of TNF Superfamily Ligands

et al. 2022

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The tumor necrosis factor (TNF) ligand family has nine ligands that show promiscuity in binding multiple receptors. As different receptors transduce into diverse pathways, the study on the functional role of natural ligands is very complex. In this review, we discuss the TNF ligands engineering for receptor specificity and summarize the performance of the ligand variants in vivo and in vitro. Those variants have an increased binding affinity to specific receptors to enhance the cell signal conduction and have reduced side effects due to a lowered binding to untargeted receptors. Refining receptor specificity is a promising research strategy for improving the application of multi-receptor ligands. Further, the settled variants also provide experimental guidance for engineering receptor specificity on other proteins with multiple receptors.

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Apoptosis-Inducing TNF Superfamily Ligands for Cancer Therapy

Cited by 37 publications

References 222 publications

Molecular Analysis of Prognosis and Immune Pathways of Pancreatic Cancer Based on TNF Family Members

Molecular Analysis of Prognosis and Immune Pathways of Pancreatic Cancer Based on TNF Family Members

Duality of Interactions Between TGF-β and TNF-α During Tumor Formation

Receptor Specificity Engineering of TNF Superfamily Ligands

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