Association of TNFRSF1A and IFNLR1 Gene Polymorphisms with the Risk of Developing Breast Cancer and Clinical Pathologic Features

Hausmann, Leili Daiane; Almeida, Bibiana Sgorla de; Souza, Ilíada Rainha de; Drehmer, Manuela Nunes; Fernandes, Bráulio Leal; Wilkens, Renato Salerno; Vieira, Dioracy Fonterrada; Löfgren, Sara Emelie; Lindenau, Juliana Dal-Ri; Silva, Guilherme de Toledo E; Muniz, Yara Costa Netto

doi:10.1007/s10528-021-10060-z

Cited by 4 publications

(2 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ensuing receptor experiences proteolytic cleavage, thereby releasing its soluble variant capable of interacting with unbound TNF-α, thereby mitigating inflammatory responses. This interaction assumes significance in cellular processes such as survival, apoptosis, and inflammation, as elucidated in prior investigations [49]. Earlier research has underscored the prognostic relevance of the pyroptosis-related gene TNFRSF1A concerning OS patients' survival [43].…”

Section: Discussionmentioning

confidence: 90%

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Yang,

Su,

et al. 2024

Journal of Immunology Research

View full text Add to dashboard Cite

Objective. Osteosarcoma (OS) represents a prevalent primary bone neoplasm predominantly affecting the pediatric and adolescent populations, presenting a considerable challenge to human health. The objective of this investigation is to develop a prognostic model centered on anoikis-related genes (ARGs), with the aim of accurately forecasting the survival outcomes of individuals diagnosed with OS and offering insights into modulating the immune microenvironment. Methods. The study’s training cohort comprised 86 OS patients sourced from The Cancer Genome Atlas database, while the validation cohort consisted of 53 OS patients extracted from the Gene Expression Omnibus database. Differential analysis utilized the GSE33382 dataset, encompassing three normal samples and 84 OS samples. Subsequently, the study executed gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses. Identification of differentially expressed ARGs associated with OS prognosis was carried out through univariate COX regression analysis, followed by LASSO regression analysis to mitigate overfitting risks and construct a robust prognostic model. Model accuracy was assessed via risk curves, survival curves, receiver operating characteristic curves, independent prognostic analysis, principal component analysis, and t-distributed stochastic neighbor embedding (t-SNE) analysis. Additionally, a nomogram model was devised, exhibiting promising potential in predicting OS patient prognosis. Further investigations incorporated gene set enrichment analysis to delineate active pathways in high- and low-risk groups. Furthermore, the impact of the risk prognostic model on the immune microenvironment of OS was evaluated through tumor microenvironment analysis, single-sample gene set enrichment analysis (ssGSEA), and immune infiltration cell correlation analysis. Drug sensitivity analysis was conducted to identify potentially effective drugs for OS treatment. Ultimately, the verification of the implicated ARGs in the model construction was conducted through the utilization of real-time quantitative polymerase chain reaction (RT-qPCR). Results. The ARGs risk prognostic model was developed, comprising seven high-risk ARGs (CBS, MYC, MMP3, CD36, SCD, COL13A1, and HSP90B1) and four low-risk ARGs (VASH1, TNFRSF1A, PIP5K1C, and CTNNBIP1). This prognostic model demonstrates a robust capability in predicting overall survival among patients. Analysis of immune correlations revealed that the high-risk group exhibited lower immune scores compared to the low-risk group within our prognostic model. Specifically, CD8+ T cells, neutrophils, and tumor-infiltrating lymphocytes were notably downregulated in the high-risk group, alongside significant downregulation of checkpoint and T cell coinhibition mechanisms. Additionally, three immune checkpoint-related genes (CD200R1, HAVCR2, and LAIR1) displayed significant differences between the high- and low-risk groups. The utilization of a nomogram model demonstrated significant efficacy in prognosticating the outcomes of OS patients. Furthermore, tumor metastasis emerged as an independent prognostic factor, suggesting a potential association between ARGs and OS metastasis. Notably, our study identified eight drugs—Bortezomib, Midostaurin, CHIR.99021, JNK.Inhibitor.VIII, Lenalidomide, Sunitinib, GDC0941, and GW.441756—as exhibiting sensitivity toward OS. The RT-qPCR findings indicate diminished expression levels of CBS, MYC, MMP3, and PIP5K1C within the context of OS. Conversely, elevated expression levels were observed for CD36, SCD, COL13A1, HSP90B1, VASH1, and CTNNBIP1 in OS. Conclusion. The outcomes of this investigation present an opportunity to predict the survival outcomes among individuals diagnosed with OS. Furthermore, these findings hold promise for progressing research endeavors focused on prognostic evaluation and therapeutic interventions pertaining to this particular ailment.

show abstract

Section: Discussionmentioning

confidence: 90%

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Yang,

Su,

et al. 2024

Journal of Immunology Research

View full text Add to dashboard Cite

show abstract

“…Therefore, the fact a large amount of IFN-l is produced by DCs in response to STING activation warrants further investigation in the realms of cancer immunotherapy. However, as the IFN-l locus has been shown to be polymorphic in a subset of cancer patients and patients suffering from infectious diseases (8,29,65,66), moving forward, polymorphisms and differences in IFN-l gene expression will need to be taken into account when considering clinical STING immunotherapeutic approaches (29,35,67,68).…”

Section: Discussionmentioning

confidence: 99%

Discordance in STING-Induced Activation and Cell Death Between Mouse and Human Dendritic Cell Populations

et al. 2022

View full text Add to dashboard Cite

Stimulator of Interferon Genes (STING) is a cytosolic sensor of cyclic dinucleotides (CDNs). The activation of dendritic cells (DC) via the STING pathway, and their subsequent production of type I interferon (IFN) is considered central to eradicating tumours in mouse models. However, this contribution of STING in preclinical murine studies has not translated into positive outcomes of STING agonists in phase I & II clinical trials. We therefore questioned whether a difference in human DC responses could be critical to the lack of STING agonist efficacy in human settings. This study sought to directly compare mouse and human plasmacytoid DCs and conventional DC subset responses upon STING activation. We found all mouse and human DC subsets were potently activated by STING stimulation. As expected, Type I IFNs were produced by both mouse and human plasmacytoid DCs. However, mouse and human plasmacytoid and conventional DCs all produced type III IFNs (i.e., IFN-λs) in response to STING activation. Of particular interest, all human DCs produced large amounts of IFN-λ1, not expressed in the mouse genome. Furthermore, we also found differential cell death responses upon STING activation, observing rapid ablation of mouse, but not human, plasmacytoid DCs. STING-induced cell death in murine plasmacytoid DCs occurred in a cell-intrinsic manner and involved intrinsic apoptosis. These data highlight discordance between STING IFN and cell death responses in mouse and human DCs and caution against extrapolating STING-mediated events in mouse models to equivalent human outcomes.

show abstract

Molecular characteristics of rhesus macaque interferon-lambda receptor 1 (mmuIFNLR1): Sequence identity, distribution and alteration after simian-human immunodeficiency virus infection in the skin and buccal mucosa

Liu,

Yang

2024

Developmental & Comparative Immunology

View full text Add to dashboard Cite

Association of TNFRSF1A and IFNLR1 Gene Polymorphisms with the Risk of Developing Breast Cancer and Clinical Pathologic Features

Cited by 4 publications

References 54 publications

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes

Discordance in STING-Induced Activation and Cell Death Between Mouse and Human Dendritic Cell Populations

Molecular characteristics of rhesus macaque interferon-lambda receptor 1 (mmuIFNLR1): Sequence identity, distribution and alteration after simian-human immunodeficiency virus infection in the skin and buccal mucosa

Contact Info

Product

Resources

About