Identification of Key Genes and Pathways in Gefitinib-Resistant Lung Adenocarcinoma using Bioinformatics Analysis

Mao, Kailin; Lin, Fang; Zhang, Yingai; Zhou, Hailong

doi:10.1177/11769343211023767

Cited by 6 publications

(4 citation statements)

References 60 publications

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“…In this study, our results indicate that the expression level of CXCL1 is up-expressed in gefitinib-resistant NSCLC cells compared to the sensitive cells, and knockdown of CXCL1 significantly enhances the sensitivity of NSCLC cells to gefitinib. This finding is consistent with a recent report that demonstrated the upregulation of CXCL1 in lung cancer that is resistant to gefitinib [ 38 ]. To date, CXCL1 has been identified as a poor prognostic biomarker in NSCLC, and this might be attributed, at least in part, to its role in drug resistance.…”

Section: Discussionsupporting

confidence: 94%

IGFBP2/ITGA5 promotes gefitinib resistance via activating STAT3/CXCL1 axis in non-small cell lung cancer

Lu,

Ai,

Zheng

et al. 2024

Cell Death Dis

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There is a paucity of comprehensive knowledge pertaining to the underlying mechanisms leading to gefitinib resistance in individuals diagnosed NSCLC harboring EGFR-sensitive mutations who inevitably develop resistance to gefitinib treatment within six months to one year. In our preceding investigations, we have noted a marked upregulation of IGFBP2 in the neoplastic tissues of NSCLC, predominantly in the periphery of the tissue, implying its plausible significance in NSCLC. Consequently, in the current research, we delved into the matter and ascertained the molecular mechanisms that underlie the participation of IGFBP2 in the emergence of gefitinib resistance in NSCLC cells. Firstly, the expression of IGFBP2 in the bronchoalveolar lavage fluid and lung cancer tissues of 20 NSCLC patients with gefitinib tolerance was found to be significantly higher than that of non-tolerant patients. Furthermore, in vitro and in vivo experiments demonstrated that IGFBP2 plays a significant role in the acquisition of gefitinib resistance. Mechanistically, IGFBP2 can activate STAT3 to enhance the transcriptional activity of CXCL1, thereby increasing the intracellular expression level of CXCL1, which contributes to the survival of lung cancer cells in the gefitinib environment. Additionally, we identified ITGA5 as a key player in IGFBP2-mediated gefitinib resistance, but it does not function as a membrane receptor in the process of linking IGFBP2 to intracellular signaling transduction. In conclusion, this study demonstrates the promoting role and mechanism of IGFBP2 in acquired gefitinib resistance caused by non-EGFR secondary mutations, suggesting the potential of IGFBP2 as a biomarker for gefitinib resistance and a potential intervention target.

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Section: Discussionsupporting

confidence: 94%

IGFBP2/ITGA5 promotes gefitinib resistance via activating STAT3/CXCL1 axis in non-small cell lung cancer

Lu,

Ai,

Zheng

et al. 2024

Cell Death Dis

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“…Another important role of CCL20 is to determine resistance to treatment. For example, upregulations of CCL20 are associated with gefitinib resistance, and CCL20 can be used as a biomarker to predict gefitinib resistance [ 50 ]. Therefore, CCL20 can be used as an effective biomarker for the clinical monitoring of LUAD patients.…”

Section: Discussionmentioning

confidence: 99%

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

et al. 2022

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Objectives This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy. Methods LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed. Results Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model’s accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit. Conclusion A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

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“…CCL20-encoded proteins are capable of chemotaxis of lymphocytes, allowing the tumor to form an immune tolerance state ( Schutyser et al, 2003 ). In patients with NSCLC, the CCL20 gene and protein are overexpressed, and autocrine of CCL20 can promote the migration and proliferation of lung cancer cells ( Mao et al, 2021 ). MMP14 is a member of the matrix metalloproteinase family and contributes to a key function in cancer metastasis, its expression is significantly correlated with poor OS ( Stawowczyk et al, 2017 ; Infante et al, 2018 ; Zhang et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of Inflammatory Response-Related Gene Signature Associated With Immune Status and Prognosis of Lung Adenocarcinoma

Zou

Chen

Mao

et al. 2021

Front. Bioeng. Biotechnol.

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Background: Lung adenocarcinoma (LUAD) is an exceedingly diverse disease, making prognostication difficult. Inflammatory responses in the tumor or the tumor microenvironment can alter prognosis in the process of the ongoing cross-talk between the host and the tumor. Nonetheless, Inflammatory response-related genes’ prognostic significance in LUAD, on the other hand, has yet to be determined.Materials and Methods: The clinical data as well as the mRNA expression patterns of LUAD patients were obtained from a public dataset for this investigation. In the TCGA group, a multigene prognostic signature was built utilizing LASSO Cox analysis. Validation was executed on LUAD patients from the GEO cohort. The overall survival (OS) of low- and high-risk cohorts was compared utilizing the Kaplan-Meier analysis. The assessment of independent predictors of OS was carried out utilizing multivariate and univariate Cox analyses. The immune-associated pathway activity and immune cell infiltration score were computed utilizing single-sample gene set enrichment analysis. GO keywords and KEGG pathways were explored utilizing gene set enrichment analysis.Results: LASSO Cox regression analysis was employed to create an inflammatory response-related gene signature model. The high-risk cohort patients exhibited a considerably shorter OS as opposed to those in the low-risk cohort. The prognostic gene signature’s predictive ability was demonstrated using receiver operating characteristic curve analysis. The risk score was found to be an independent predictor of OS using multivariate Cox analysis. The functional analysis illustrated that the immune status and cancer-related pathways for the two-risk cohorts were clearly different. The tumor stage and kind of immune infiltrate were found to be substantially linked with the risk score. Furthermore, the cancer cells’ susceptibility to anti-tumor medication was substantially associated with the prognostic genes expression levels.Conclusion: In LUAD, a new signature made up of 8 inflammatory response-related genes may be utilized to forecast prognosis and influence immunological state. Inhibition of these genes could also be used as a treatment option.

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Identification of Key Genes and Pathways in Gefitinib-Resistant Lung Adenocarcinoma using Bioinformatics Analysis

Cited by 6 publications

References 60 publications

IGFBP2/ITGA5 promotes gefitinib resistance via activating STAT3/CXCL1 axis in non-small cell lung cancer

IGFBP2/ITGA5 promotes gefitinib resistance via activating STAT3/CXCL1 axis in non-small cell lung cancer

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

Identification of Inflammatory Response-Related Gene Signature Associated With Immune Status and Prognosis of Lung Adenocarcinoma

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