&lt;p&gt;An Iron Metabolism-Related &lt;em&gt;SLC22A17&lt;/em&gt; for the Prognostic Value of Gastric Cancer&lt;/p&gt;

Wei, Jianming; Gao, Xibo; Qin, Yanmin; Liu, Tong Tong; Kang, Yani

doi:10.2147/ott.s287811

Cited by 15 publications

(10 citation statements)

References 41 publications

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“…Two authors have also reported that SLC22A17 could be a prognosis biomarker of gastric cancer. Specifically, SLC22A17 was identified as a prognosis gene which may affect immune cell infiltration and iron metabolism in gastric (Hu C. et al, 2018;Wang et al, 2020;Wei et al, 2020). Although these two genes have been reported to be involved in gastric cancer, the specific mechanism of their regulation of gastric cancer is still unclear, which needs further research.…”

Section: Discussionmentioning

confidence: 99%

Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer

et al. 2021

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Gastric cancer (GC) is a serious malignant tumor with high mortality and poor prognosis. The prognosis and survival are much worse for advanced gastric cancer (AGC). Recently, immunotherapy has been widely promoted for AGC patients, and studies have shown that tumor mutation burden (TMB) is closely related to immunotherapy response. Here, RNA-seq data, matched clinical information, and MAF files were downloaded from the cancer genome atlas (TCGA)-STAD project in the TCGA database. The collation and visual analysis of mutation data were implemented by the “maftools” package in R. We calculated the TMB values for AGC patients and divided the patients into high- and low-TMB groups according to the median value of TMB. Then, the correlation between high or low TMB and clinicopathological parameters was calculated. Next, we examined the differences in gene expression patterns between the two groups by using the “limma” R package and identified the immune-related genes among the DEGs. Through univariate Cox regression analysis, 15 genes related to prognosis were obtained. Furthermore, the two hub genes (APOD and SLC22A17) were used to construct a risk model to evaluate the prognosis of AGC patients. ROC and survival curves and GEO data were used as a validation set to verify the reliability of this risk model. In addition, the correlation between TMB and tumor-infiltrating immune cells was examined. In conclusion, our results suggest that AGC patients with high TMB have a better prognosis. By testing the patient’s TMB, we could better guide immunotherapy and understand patient response to immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer

et al. 2021

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“…Interestingly, several studies reported that TME regulates the expression of LCN2, SLC22A17, and MMP9, which, in turn, modify the TME dynamism demonstrating a reciprocal modulation (Kessenbrock et al, 2010;Candido et al, 2016a;Wei et al, 2020;Crescenzi et al, 2021). This crosstalk is mediated Frontiers in Cell and Developmental Biology frontiersin.org by several chemokines, cytokines, and fibrillar proteins that activate the transcription of LCN2, SLC22A17, and MMP9 (Chinni et al, 2006;Iannetti et al, 2008;Xu et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic analysis of the LCN2–SLC22A17–MMP9 network in cancer: The role of DNA methylation in the modulation of tumor microenvironment

Candido

Tomasello

Lavoro

et al. 2022

Front. Cell Dev. Biol.

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Several features of cancer cells such as proliferation, invasion, metastatic spreading, and drug resistance are affected by their interaction with several tumor microenvironment (TME) components, including neutrophil gelatinase-associated lipocalin (NGAL), solute carrier family 22 member 17 (SLC22A17), and matrix metallopeptidase 9 (MMP9). These molecules play a key role in tumor growth, invasion, and iron-dependent metabolism of cancer cells. However, the precise epigenetic mechanisms underlying the gene regulation of Lipocalin 2 (LCN2), SLC22A17, and MMP9 in cancer still remain unclear. To this purpose, computational analysis was performed on TCGA and GTEx datasets to evaluate the expression and DNA methylation status of LCN2, SLC22A17, and MMP9 genes in different tumor types. Correlation analysis between gene/isoforms expression and DNA methylation levels of LCN2, SLC22A17, and MMP9 was performed to investigate the role of DNA methylation in the modulation of these genes. Protein network analysis was carried out using reverse phase protein arrays (RPPA) data to identify protein–protein interactions of the LCN2–SLC22A17–MMP9 network. Furthermore, survival analysis was performed according to gene expression and DNA methylation levels. Our results demonstrated that LCN2 and MMP9 were mainly upregulated in most tumor types, whereas SLC22A17 was largely downregulated, representing a specific hallmark signature for all gastrointestinal tumors. Notably, the expression of LCN2, SLC22A17, and MMP9 genes was negatively affected by promoter methylation. Conversely, intragenic hypermethylation was associated with the overexpression of SLC22A17 and MMP9 genes. Protein network analysis highlighted the role of the LCN2–SLC22A17–MMP9 network in TME by the interaction with fibronectin 1 and claudin 7, especially in rectal tumors. Moreover, the impact of expression and methylation status of LCN2, SLC22A17, and MMP9 on overall survival and progression free interval was tumor type–dependent. Overall, our analyses provide a detailed overview of the expression and methylation status of LCN2, SLC22A17, and MMP9 in all TCGA tumors, indicating that the LCN2–SLC22A17–MMP9 network was strictly regulated by DNA methylation within TME. Our findings pave the way for the identification of novel DNA methylation hotspots with diagnostic and prognostic values and suitable for epi-drug targeting.

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“…COAD gene expression profiles and corresponding clinical information were downloaded from the TCGA database ( n = 512) and GEO database (GSE39582, n = 576). Seventy iron metabolism-related genes are listed in Supplementary Table S1 , which were derived from a previous study ( Wei et al, 2020 ). The GSE39582 dataset was used to validate the established signature.…”

Section: Methodsmentioning

confidence: 99%

An Iron Metabolism-Related Gene Signature for the Prognosis of Colon Cancer

Yuan

Liu

Zhang

2022

Front. Cell Dev. Biol.

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As an essential microelement, the iron ion is involved in cell proliferation, metabolism, and differentiation. Iron metabolism plays a crucial role in the occurrence and development of colon adenocarcinoma (COAD). In this study, univariate and multivariate Cox regression, and least absolute shrinkage and selection operator analyses were conducted to construct the gene signature, based on a dataset from The Cancer Genome Atlas. We identified the prognostic value of two iron metabolism-related genes [SLC39A8 (encoding solute carrier family 39 member 8) and SLC48A1 (encoding solute carrier family 48 member 1)] in COAD. A nomogram model was established to predict the overall survival of patients with COAD. Functional analysis showed that the tumor microenvironment and immune cell infiltrate were different between the low risk and high risk subgroups. This study verified that the iron metabolism-related gene signature (SLC39A8 and SLC48A1) could be used as a prognostic biomarker for patients with COAD.

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<p>An Iron Metabolism-Related <em>SLC22A17</em> for the Prognostic Value of Gastric Cancer</p>

Cited by 15 publications

References 41 publications

Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer

Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer

Bioinformatic analysis of the LCN2–SLC22A17–MMP9 network in cancer: The role of DNA methylation in the modulation of tumor microenvironment

An Iron Metabolism-Related Gene Signature for the Prognosis of Colon Cancer

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