IGFBP7 Drives Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibition in Lung Cancer

Wu, Shang‐Gin; Chang, Tzu‐Hua; Tsai, Meng‐Feng; Liu, Yinan; Hsu, Chia‐Lang; Chang, Yih‐Leong; Yu, Chong‐Jen; Shih, Jin‐Yuan

doi:10.3390/cancers11010036

Cited by 20 publications

(15 citation statements)

References 54 publications

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“…In our current study, GSE19188 was chosen to explore the expression of all CPNEs in lung cancer and adjacent normal tissues [28]. GSE103350 mRNA pro les identi ed potential targets that mediate EGFR-TKI tolerance and resistance (Ge tinib and AZD9291) in lung cancer [29]. GSE126988 revealed the results of gene regulation by the combination treatment of crizotinib plus cisplatin in established lung tumors [30].…”

Section: Methodsmentioning

confidence: 99%

Integrated Analysis of the Oncogenic Value of CPNE1 and CPNE3 in Non-Small Cell Lung Cancer

Pang

Chen

et al. 2022

Preprint

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Background Copines (CPNEs) are calcium-dependent, soluble and ubiquitous proteins found in eukaryotic organisms and protists. Recent evidence has also highlighted the roles of these protein play in regulating cancer immune responses and development. However, the specific expression, distribution and roles of CPNEs in NSCLC are poorly studied. Methods GSE and GEPIA2 database were selected to explore the expression levels of CPNEs in lung cancer tissues, which were verified by qRT-PCR analysis. The Kaplan-Meier plotter and GEPIA database were used to assess the effect of CPNE expression on patient survival. cBioportal database was used for genetic mutation analysis. FunRich database were used to predict the potential biological pathway. Finally, ssGSEA database was performed for immune infiltration analysis. Results Among all CPNEs, high expression of CPNE1 and CPNE3 were valuable for predicting both OS and DFS in lung cancer patients, which were associated with advanced TNM stages, lymph node metastasis and drug resistance to EGFR-TKIs. However, no statistical significance between CPNEs and the efficiency to immunotherapy was observed, which was further validated by weak correlation between CPNEs expression and immune cell infiltration levels. The processes of regulation of nucleobase and nucleotide, signal transduction, cell metabolism were involved in the effect of CPNE1 and CPNE3 on tumor pathogenesis. In terms of biological pathways, TGF-beta pathway, PI3K/AKT pathway, mTOR pathway and EGFR signaling pathway were most relevant to CPNE1 and CPNE3. Conclusions We highlighted the protumor role of CPNE1 and CPNE3 among all CPNEs, which may provide important therapeutic targets for lung cancer.

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Section: Methodsmentioning

confidence: 99%

Integrated Analysis of the Oncogenic Value of CPNE1 and CPNE3 in Non-Small Cell Lung Cancer

Pang

Chen

et al. 2022

Preprint

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“…Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) is a public functional genomic database that stores microarray and high-throughput sequencing data. The gene expression dataset GSE122005, based on GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array and submitted by Wu et al, 15 was downloaded from the GEO database. The GSE122005 dataset has 6 samples, including 3 gefitinib-sensitive lung cancer cell line samples and 3 acquired gefitinib-resistant lung cancer cell line samples.…”

Section: Methodsmentioning

confidence: 99%

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

Mao

Lin

Zhang

et al. 2021

Evol Bioinform Online

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Gefitinib resistance is a serious threat in the treatment of patients with non-small cell lung cancer (NSCLC). Elucidating the underlying mechanisms and developing effective therapies to overcome gefitinib resistance is urgently needed. The differentially expressed genes (DEGs) were screened from the gene expression profile GSE122005 between gefitinib-sensitive and resistant samples. GO and KEGG analyses were performed with DAVID. The protein-protein interaction (PPI) network was established to visualize DEGs and screen hub genes. The functional roles of CCL20 in lung adenocarcinoma (LUAD) were examined using gene set enrichment analysis (GSEA). Functional analysis revealed that the DEGs were mainly concentrated in inflammatory, cell chemotaxis, and PI3K signal regulation. Ten hub genes were identified based on the PPI network. The survival analysis of the hub genes showed that CCL20 had a significant effect on the prognosis of LUAD patients. GSEA analysis showed that CCL20 high expression group was mainly enriched in cytokine-related signaling pathways. In conclusion, our analysis suggests that changes in inflammation and cytokine-related signaling pathways are closely related to gefitinib resistance in patients with lung cancer. The CCL20 gene may promote the formation of gefitinib resistance, which may serve as a new biomarker for predicting gefitinib resistance in patients with lung cancer.

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“…13 And GEO is one of the largest public gene expression data resources now. We selected 3 profiles of gefitinib, erlotinib, and afatinib from the GEO database for analysis: GSE122005 14 based on GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array, GSE31625 15 based on GPL96 [HG-U133A] Affymetrix Human Genome U133A Array, and GSE62504 16 based on GPL6947 Illumina HumanHT-12 V3.0 expression beadchip. GSE122005 (gefitinib) contained 3 resistant samples and 3…”

Section: Access Datamentioning

confidence: 99%

The Multi-Omics Analysis of Key Genes Regulating EGFR-TKI Resistance, Immune Infiltration, SCLC Transformation in EGFR-Mutant NSCLC

Wang¹,

Zhang²,

Xu³

et al. 2022

JIR

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Background: Lung cancer is a high-risk malignancy worldwide. The harboring of epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) makes EGFR-tyrosine kinase inhibitor (EGFR-TKI) an attractive therapeutic option. However, patients usually suffer the primary and secondary resistance to EGFR-TKI. And the molecular alteration is still not fully clear and needs further study. Methods: The GEO database was utilized to find the differentially expressed genes (DEGs) in NSCLC profiles resistant to the 1st or 2nd generation EGFR-TKI. We analyzed the expression and pathway enrichment of hub genes, and the prognosis of EGFR mutant/ wild-type lung adenocarcinoma (LUAD). Moreover, small cell lung cancer (SCLC) and TKI-resistant profiles were used to find common DEGs, and construct miRNA regulatory network. Analysis was performed of hub genes' related immune infiltration, drug sensitivity, and methylation. Further, we analyzed hub gene expression in EGFR-mutant LUAD and paracancerous tissue by qRT-PCR. Results: A total of 107 DEGs were found related to TKI resistance. Eleven hub genes were obtained after visualization, of which 5 hub genes were co-expressed in SCLC with common miRNAs. Lower expression of SPP1 (hub gene) was associated with better survival in NSCLC. The immune infiltration analysis showed more CD4+ T cells in the resistant group with high expression of SPP1. SPP1 and CD44 promoters' methylations were independent prognostic factors of LUAD. And the expression level of SPP1 related to the sensitivity of EGFR-TKIs in multiple cancer cell lines. qRT-PCR validated the higher expression of SPP1 in EGFR-mutant LUAD than in normal tissue. Conclusion:Our study suggested that the upregulation of SPP1 might induce resistance to the 1st and 2nd generation EGFR-TKI, and influence tumor immune infiltration, resulting in poor survival. ZEB1, SPP1, MUC1, CD44, and ESRP1 might be molecular drivers of SCLC transformation of TKI resistance.

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IGFBP7 Drives Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibition in Lung Cancer

Cited by 20 publications

References 54 publications

Integrated Analysis of the Oncogenic Value of CPNE1 and CPNE3 in Non-Small Cell Lung Cancer

Integrated Analysis of the Oncogenic Value of CPNE1 and CPNE3 in Non-Small Cell Lung Cancer

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

The Multi-Omics Analysis of Key Genes Regulating EGFR-TKI Resistance, Immune Infiltration, SCLC Transformation in EGFR-Mutant NSCLC

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