Prognostic and functional roles of EIF4G1 in lung squamous cell carcinoma

Bai, Baoxin; Dong, Lin; Feng, Minghao; Zhang, Zhiwen; Lü, Ying; Xu, Zeng‐Guang; Liu, Yali

doi:10.1007/s13577-023-00884-9

Cited by 2 publications

(3 citation statements)

References 21 publications

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“…The translation initiation factor, EIF4G1, is highly expressed in a variety of tumors, and its ability to regulate the expression of numerous proteins has an important impact on tumor proliferation, migration, secretion of cytokines, and tumor angiogenesis (Fan et al, 2010;Hsieh et al, 2012;Robichaud et al, 2015). Previously, our group found that EIF4G1 expression is significantly higher in NSCLC tissues than in paraneoplastic tissues and affects patient prognosis, such that high expression of EIF4G1 in tumor tissues predicts shorter patient survival (Bai et al, 2023). The present study further explored the functions of EIF4G1 in tumors.…”

Section: Discussionmentioning

confidence: 99%

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Knockdown of EIF4G1 in NSCLC induces CXCL8 secretion

He,

Li,

Zhang

et al. 2024

Front. Pharmacol.

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Non-small cell lung cancer (NSCLC) is the most common type of lung tumor; however, we lack effective early detection indicators and therapeutic targets. Eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) is vital to initiate protein synthesis, acting as a scaffolding protein for the eukaryotic protein translation initiation factor complex, EIF4F, which regulates protein synthesis together with EIF4A, EIF4E, and other translation initiation factors. However, EIF4G1’s function in NSCLC cancer is unclear. Herein, transcriptome sequencing showed that knockdown of EIF4G1 in H1299 NSCLC cells upregulated the expression of various inflammation-related factors. Inflammatory cytokines were also significantly overexpressed in NSCLC tumor tissues, among which CXCL8 (encoding C-X-C motif chemokine ligand 8) showed the most significant changes in both in the transcriptome sequencing data and tumor tissues. We revealed that EIF4G1 regulates the protein level of TNF receptor superfamily member 10a (TNFRSF10A) resulting in activation of the mitogen activated protein kinase (MAPK) and nuclear factor kappa B (NFκB) pathways, which induces CXCL8 secretion, leading to targeted chemotaxis of immune cells. We verified that H1299 cells with EIF4G1 knockdown showed increased chemotaxis compared with the control group and promoted increased chemotaxis of macrophages. These data suggested that EIF4G1 is an important molecule in the inflammatory response of cancer tissues in NSCLC.

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Section: Discussionmentioning

confidence: 99%

“…Based on our previous research, we found that the expression of EIF4G1 changes during tumor development. Future studies will investigate whether chemotactic macrophages entering the TME are affected by varying levels of EIF4G1 expression (Bai et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

Knockdown of EIF4G1 in NSCLC induces CXCL8 secretion

He,

Li,

Zhang

et al. 2024

Front. Pharmacol.

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“…EGF is an epidermal growth factor and is associated with cell proliferation in several types of cancer. EIF4G1 is associated with tumor microenvironment regulation and metastasis in breast cancer [72], and other studies report it as a possible prognostic indicator in squamous cell lung carcinoma [73]. FOXG1 is associated with the proliferation and invasion of renal clear cell carcinoma, as well as improved accuracy in prognosis prediction models [74].…”

Section: Cluster Molecular Profile and Lusc Genetic Signaturesmentioning

confidence: 96%

An Integrated Data Analysis Using Bioinformatics and Random Forest to Predict Prognosis of Patients With Squamous Cell Lung Cancer

Lima,

Terrematte,

Stransky

et al. 2024

IEEE Access

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Lung cancer is the leading cause of cancer death worldwide, regardless of gender. Among the types of lung cancer, Lung Squamous Cell Carcinoma (LUSC) is the second most common type, characterized by a diagnosis in advanced stages, a poor prognosis, and a high association with smoking. Due to the severity of lung cancer, it is essential to understand its molecular mechanisms. In this context, this study uses transcriptomic and clinical data to implement bioinformatics pipelines, and machine learning, through random forest models to predict patients' overall survival and obtain a gene signature of LUSC for tumor progression. We analyzed clinical and molecular data from the project LUSC-TCGA, and we performed differential expression analyses (DEA) comparing normal tissues against tumor tissues. Based on DEA-selected genes, the patients were divided into three clusters, followed by a feature selection and classification. Finally, it was possible to obtain classifications results close to 70% of accuracy for the three clusters. Finally, we also performed a functional enrichment analysis. The clustering analysis revealed in cluster 2, enriched genes such as CDT1, CENPI, and NLGN1, associated with the molecular EMT (epithelialto-mesenchymal transition) process. Our approach facilitated the identification of genes that are biologically relevant to the LUSC development process, holding significant genes for predicting patient survival, such as gene ALDH3B1, C7, FAM83A, FOSB, GCGR, BMP7, PPP1R27 and AQP1, and putative therapeutic targets for LUSC such as gene FAM83A, CAV1, TNS4, EIF4G1, TFAP2A, GCGR and PPP1R27.

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Prognostic and functional roles of EIF4G1 in lung squamous cell carcinoma

Cited by 2 publications

References 21 publications

Knockdown of EIF4G1 in NSCLC induces CXCL8 secretion

Knockdown of EIF4G1 in NSCLC induces CXCL8 secretion

An Integrated Data Analysis Using Bioinformatics and Random Forest to Predict Prognosis of Patients With Squamous Cell Lung Cancer

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