An anti-EGFR/anti- HER2 Bispecific Antibody with Enhanced Antitumor Activity Against Acquired Gefitinib-Resistant NSCLC Cells

Tumor-associated macrophages mediate resistance of EGFR-TKIs in non-small cell lung cancer: mechanisms and prospects

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are the first-line standard treatment for advanced non-small cell lung cancer (NSCLC) with EGFR mutation. However, resistance to EGFR-TKIs is inevitable. Currently, most studies on the mechanism of EGFR-TKIs resistance mainly focus on the spontaneous resistance phenotype of NSCLC cells. Studies have shown that the tumor microenvironment (TME) also mediates EGFR-TKIs resistance in NSCLC. Tumor-associated macrophages (TAMs), one of the central immune cells in the TME of NSCLC, play an essential role in mediating EGFR-TKIs resistance. This study aims to comprehensively review the current mechanisms underlying TAM-mediated resistance to EGFR-TKIs and discuss the potential efficacy of combining EGFR-TKIs with targeted TAMs therapy. Combining EGFR-TKIs with TAMs targeting may improve the prognosis of NSCLC with EGFR mutation to some extent.

Identification of Gefitinib Resistance-Related lncRNA-miRNA-mRNA Regulatory Networks and Corresponding Prognostic Signature in Patients with Lung Adenocarcinoma

Purpose

To identify and characterize gefitinib resistance-related (GefR-related) lncRNAs and construct a prediction model for lung adenocarcinoma (LUAD).

Methods

Differential expression analysis between PC9 and gefitinib-resistant PC9 (PC9GR) cell samples was performed to screen GefR-related lncRNAs and mRNAs based on the GSE34228 dataset. These lncRNAs, mRNAs, and their corresponding microRNAs (miRNAs) were used to construct the GefR-related network and PPI networks. Functional enrichment analyses were conducted using the STRING database. A prognostic signature was developed using the TCGA dataset. The reliability of the signature was tested using the Kaplan–Meier method and ROC curve. Lastly, the FZD4-associated ceRNA subnetwork was selected to confirm the in vitro expressions of the GefR-related lncRNAs using RT-qPCR assay.

Results

A GefR-related ceRNA network that consists of 35 miRNAs, 26 lncRNAs, and 179 mRNAs was constructed. Then, 20 hub genes were screened from the targeted mRNAs of the constructed PPI network, and enrichment analysis identified relevant enriched pathways. We also constructed a prognostic signature for LUAD based on nine mRNAs in the GefR-related ceRNA network. The 9-mRNA signature was an independent predictor of LUAD, the AUC produced by ROC analysis showed a good predictive power of the model, and Kaplan–Meier analysis showed poorer outcomes in the high-risk group, relative to the low-risk group. Lastly, MIR137HG and ZNF295-AS1 levels were found to be associated with gefitinib resistance and exerted their functions through the ceRNA mechanism.

Conclusion

We established a prognostic signature and identified two lncRNAs (MIR137HG and ZNF295-AS1) with potential significant roles in gefitinib resistance.