The AGEs/RAGE Transduction Signaling Prompts IL-8/CXCR1/2-Mediated Interaction between Cancer-Associated Fibroblasts (CAFs) and Breast Cancer Cells

Santolla, Maria Francesca; Talia, Marianna; Cirillo, Francesca; Scordamaglia, Domenica; Rosis, Salvatore De; Spinelli, Asia; Miglietta, Antonella; Nardo, Bruno; Filippelli, Gianfranco; Francesco, Ernestina Marianna De; Belfiore, Antonino; Lappano, Rosamaria; Maggiolini, Marcello

doi:10.3390/cells11152402

Cited by 12 publications

(8 citation statements)

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“…The protein encoded by this gene is a cell-surface receptor found on phagocytic cells, such as macrophages and neutrophils, and is involved in the processes of phagocytosis and immune complex clearance [ 37 ]. CXCR1 is able to bind to the inflammatory cytokine IL-8 and trigger a cascade of events through intracellular G proteins that activate multiple signaling pathways [ 38 ]. Through bioinformatic analysis, researchers conducted an in-depth analysis of alveolar lavage fluid datasets for COVID-19 and asthma.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients

Liu

Duo

et al. 2022

Cell Commun Signal

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Background Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 19 (COVID-19). The number of confirmed cases of COVID-19 is also rapidly increasing worldwide, posing a significant challenge to human safety. Asthma is a risk factor for COVID-19, but the underlying molecular mechanisms of the asthma–COVID-19 interaction remain unclear. Methods We used transcriptome analysis to discover molecular biomarkers common to asthma and COVID-19. Gene Expression Omnibus database RNA-seq datasets (GSE195599 and GSE196822) were used to identify differentially expressed genes (DEGs) in asthma and COVID-19 patients. After intersecting the differentially expressed mRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify the common pathogenic molecular mechanism. Bioinformatic methods were used to construct protein–protein interaction (PPI) networks and identify key genes from the networks. An online database was used to predict interactions between transcription factors and key genes. The differentially expressed long noncoding RNAs (lncRNAs) in the GSE195599 and GSE196822 datasets were intersected to construct a competing endogenous RNA (ceRNA) regulatory network. Interaction networks were constructed for key genes with RNA-binding proteins (RBPs) and oxidative stress-related proteins. The diagnostic efficacy of key genes in COVID-19 was verified with the GSE171110 dataset. The differential expression of key genes in asthma was verified with the GSE69683 dataset. An asthma cell model was established with interleukins (IL-4, IL-13 and IL-17A) and transfected with siRNA-CXCR1. The role of CXCR1 in asthma development was preliminarily confirmed. Results By intersecting the differentially expressed genes for COVID-19 and asthma, 393 common DEGs were obtained. GO and KEGG enrichment analyses of the DEGs showed that they mainly affected inflammation-, cytokine- and immune-related functions and inflammation-related signaling pathways. By analyzing the PPI network, we obtained 10 key genes: TLR4, TLR2, MMP9, EGF, HCK, FCGR2A, SELP, NFKBIA, CXCR1, and SELL. By intersecting the differentially expressed lncRNAs for COVID-19 and asthma, 13 common differentially expressed lncRNAs were obtained. LncRNAs that regulated microRNAs (miRNAs) were mainly concentrated in intercellular signal transduction, apoptosis, immunity and other related functional pathways. The ceRNA network suggested that there were a variety of regulatory miRNAs and lncRNAs upstream of the key genes. The key genes could also bind a variety of RBPs and oxidative stress-related genes. The key genes also had good diagnostic value in the verification set. In the validation set, the expression of key genes was statistically significant in both the COVID-19 group and the asthma group compared with the healthy control group. CXCR1 expression was upregulated in asthma cell models, and interference with CXCR1 expression significantly reduced cell viability. Conclusions Key genes may become diagnostic and predictive biomarkers of outcomes in COVID-19 and asthma.

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Section: Discussionmentioning

confidence: 99%

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients

Liu

Duo

et al. 2022

Cell Commun Signal

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“…It’s known that different immune cell subsets can be recruited into TME via interactions between chemokines and chemokine receptors, and affect tumor progression and therapeutic outcome [ 66 ]. Chemokines (CXCL12 [ 67 ], CXCL8 [ 68 ], CXCL5 [ 69 ]) and chemokine receptors (CXCR1/2 [ 70 ], CCR4 [ 71 , 72 ], CCR8 [ 73 ]) are well-known to deeply participate in the tumor development and progression in various cancers, including LUAD [ 74 ]. In the present study, we found that the expression of KIAA1199 was correlated with the levels of many chemokines (CXCL12, CXCL8, CXCL5) and chemokine receptors (CXCR1/2, CXCR4, CCR8) in LUAD.…”

Section: Discussionmentioning

confidence: 99%

KIAA1199 Correlates With Tumor Microenvironment and Immune Infiltration in Lung Adenocarcinoma as a Potential Prognostic Biomarker

Shen¹,

Mo²,

Tan³

et al. 2022

Pathol. Oncol. Res.

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Background: KIAA1199 has been considered a key regulator of carcinogenesis. However, the relationship between KIAA1199 and immune infiltrates, as well as its prognostic value in lung adenocarcinoma (LUAD) remains unclear.Methods: The expression of KIAA1199 and its influence on tumor prognosis were analyzed using a series of databases, comprising TIMER, GEPIA, UALCAN, LCE, Prognoscan and Kaplan-Meier Plotter. Further, immunohistochemistry (IHC), western blot (WB) and receiver operating characteristic (ROC) curve analyses were performed to verify our findings. The cBioPortal was used to investigate the genomic alterations of KIAA1199. Prediction of candidate microRNA (miRNAs) and transcription factor (TF) targeting KIAA1199, as well as GO and KEGG analyses, were performed based on LinkedOmics. TIMER and TISIDB databases were used to explore the relationship between KIAA1199 and tumor immune infiltration.Results: High expression of KIAA1199 was identified in LUAD and Lung squamous cell carcinoma (LUSC) patients. High expression of KIAA1199 indicated a worse prognosis in LUAD patients. The results of IHC and WB analyses showed that the expression level of KIAA1199 in tumor tissues was higher than that in adjacent tissues. GO and KEGG analyses indicated KIAA1199 was mainly involved in extracellular matrix (ECM)-receptor interaction and extracellular matrix structure constituent. KIAA1199 was positively correlated with infiltrating levels of CD4+ T cells, macrophages, neutrophil cells, dendritic cells, and showed positive relationship with immune marker subsets expression of a variety of immunosuppressive cells.Conclusion: High expression of KIAA1199 predicts a poor prognosis of LUAD patients. KIAA1199 might exert its carcinogenic role in the tumor microenvironment via participating in the extracellular matrix formation and regulating the infiltration of immune cells in LUAD. The results indicate that KIAA1199 might be a novel biomarker for evaluating prognosis and immune cell infiltration in LUAD.

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“…Santolla et al. ( 52 ) demonstrated that the paracrine signaling of IL-8/CXCR1/2 could effectively activate and induce the migration and invasion properties of MDA-MB-231 breast cancer cells. Similarly, Sun et al.…”

Section: The Role and Mechanism Of Cafs In Breast Cancermentioning

confidence: 99%

The importance of cancer-associated fibroblasts in targeted therapies and drug resistance in breast cancer

Zheng,

Hao

2024

Front. Oncol.

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Cancer-associated fibroblasts (CAFs) play a substantial role in the tumor microenvironment, exhibiting a strong association with the advancement of various types of cancer, including breast, pancreatic, and prostate cancer. CAFs represent the most abundant mesenchymal cell population in breast cancer. Through diverse mechanisms, including the release of cytokines and exosomes, CAFs contribute to the progression of breast cancer by influencing tumor energy metabolism, promoting angiogenesis, impairing immune cell function, and remodeling the extracellular matrix. Moreover, CAFs considerably impact the response to treatment in breast cancer. Consequently, the development of interventions targeting CAFs has emerged as a promising therapeutic approach in the management of breast cancer. This article provides an analysis of the role of CAFs in breast cancer, specifically in relation to diagnosis, treatment, drug resistance, and prognosis. The paper succinctly outlines the diverse mechanisms through which CAFs contribute to the malignant behavior of breast cancer cells, including proliferation, invasion, metastasis, and drug resistance. Furthermore, the article emphasizes the potential of CAFs as valuable tools for early diagnosis, targeted therapy, treatment resistance, and prognosis assessment in breast cancer, thereby offering novel approaches for targeted therapy and overcoming treatment resistance in this disease.

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The AGEs/RAGE Transduction Signaling Prompts IL-8/CXCR1/2-Mediated Interaction between Cancer-Associated Fibroblasts (CAFs) and Breast Cancer Cells

Cited by 12 publications

References 126 publications

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients

KIAA1199 Correlates With Tumor Microenvironment and Immune Infiltration in Lung Adenocarcinoma as a Potential Prognostic Biomarker

The importance of cancer-associated fibroblasts in targeted therapies and drug resistance in breast cancer

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