Targeting 14-3-3ζ Overcomes Resistance to Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors in Lung Adenocarcinoma via BMP2/Smad/ID1 Signaling

Osimertinib resistance prognostic gene signature: STRIP2 is associated with immune infiltration and tumor progression in lung adenocarcinoma

OBJECTIVE

Although the use of osimertinib can significantly improve the survival time of lung adenocarcinoma (LUAD) patients with epithelial growth factor receptor mutation, eventually drug resistance will limit the survival benefit of most patients. This study aimed to develop a novel prognostic predictive signature based on genes associated with osimertinib resistance.

METHODS

The differentially expressed genes (DEGs) associated with osimertinib resistance in LUAD were screened from Gene Expression Omnibus datasets and The Cancer Genome Atlas datasets. Multivariate cox regression was used to establish a prognostic signature, and then a nomogram was developed to predict the survival probability of LUAD patients. We used ROC curve and DCA curve to evaluate its clinical prediction accuracy and net benefit. In addition, the differentially expressed genes significantly associated with prognosis were selected for immune infiltration analysis and drug sensitivity analysis, and their roles in the progression of lung adenocarcinoma were verified by in vitro experiments.

RESULTS

Our evaluation results indicated that the new nomogram had higher clinical prediction accuracy and net benefit value than the TN nomogram. Further analysis showed that patients with low STRIP2 expression had a higher level of immune response, and may be more likely to benefit from immune checkpoint inhibitors and conventional antitumor drugs. This may help to select more precise and appropriate therapy for LUAD patients with osimertinib resistance. Furthermore, in vitro experiments showed that STRIP2 promoted the LUAD cells proliferation, migration and invasion. This further demonstrates the importance of this gene signature for prognostic prediction.

CONCLUSION

We developed a reliable prognostic model based on DEGs associated with osimertinib resistance and screened for biomarker that can predict the immune response in LUAD patients, which may help in the selection of treatment regimens after osimertinib resistance.

Inetetamab, a novel anti-HER2 monoclonal antibody, exhibits potent synergistic anticancer effects with cisplatin by inducing pyroptosis in lung adenocarcinoma

Cisplatin is a first-line chemotherapy drug for lung adenocarcinoma (LUAD). However, its therapeutic efficacy is limited because of serious side effects and acquired drug resistance. Targeting HER2 has been proven to be a viable therapeutic strategy against LUAD. Moreover, inetetamab, an innovative anti-HER2 monoclonal antibody, has a more potent antibody-dependent cell-mediated cytotoxicity (ADCC)-inducing effect than trastuzumab, which has been shown to be an effective and rational strategy in the clinic when combined with multiple chemotherapeutic agents. Thus, the present study aimed to explore the synergistic effects of cisplatin (DDP) and inetetamab in LUAD cells and investigate the detailed underlying mechanisms. Here, in vitro and in vivo, we found that the combination of inetetamab and cisplatin induced synergistic effects, including induction of pyroptosis, in LUAD. Mechanistic studies revealed that inetetamab combined with cisplatin inhibited HER2/AKT/Nrf2 signaling to increase ROS levels, which triggered NLRP3/caspase-1/GSDMB-mediated pyroptosis to synergistically enhance antitumor efficacy in LUAD cells. In addition, cisplatin enhanced the PBMC-killing ability of inetetamab by inducing GSDMB-mediated pyroptosis, which can be explained by increased secretion of IFN-γ. Our study reveals that the anti-HER2 monoclonal antibody inetetamab may be an attractive candidate for LUAD therapy, which opens new avenues for therapeutic interventions for LUAD.

Loss of ubiquitin-specific peptidase 18 destabilizes 14-3-3ζ protein and represses lung cancer metastasis

Cancer metastasis is a major cause of cancer-related mortality. Strategies to reduce metastases are needed especially in lung cancer, the most common cause of cancer mortality. We previously reported increased ubiquitin-specific peptidase 18 (USP18) expression in lung and other cancers. Engineered reduction of USP18 expression repressed lung cancer growth and promoted apoptosis. This deubiquitinase (DUB) stabilized targeted proteins by removing the complex interferon-stimulated gene 15 (ISG15). This study explores if the loss of USP18 reduced lung cancer metastasis. USP18 knock-down in lung cancer cells was independently achieved using small hairpin RNAs (shRNAs) and small interfering RNAs (siRNAs). USP18 knock-down reduced lung cancer growth, wound-healing, migration, and invasion versus controls (P < .001) and markedly decreased murine lung cancer metastases (P < .001). Reverse Phase Protein Arrays (RPPAs) in shRNA knock-down lung cancer cells showed that 14-3-3ζ protein was regulated by loss of USP18. ISG15 complexed with 14-3-3ζ protein reducing its stability. Survival in lung adenocarcinomas (P < .0015) and other cancers was linked to elevated 14-3-3ζ expression as assessed by The Cancer Genome Atlas (TCGA). The findings were confirmed and extended using 14-3-3ζ immunohistochemical assays of human lung cancer arrays and syngeneic murine lung cancer metastasis models. A direct 14-3-3ζ role in controlling lung cancer metastasis came from engineered 14-3-3ζ knock-down in lung cancer cell lines and 14-3-3ζ rescue experiments that reversed migration and invasion inhibition. Findings presented here revealed that USP18 controlled metastasis by regulating 14-3-3ζ expression. These data provide a strong rationale for developing a USP18 inhibitor to combat metastases.

A Prognostic Risk Score Based on Hypoxia-, Immunity-, and Epithelialto-Mesenchymal Transition-Related Genes for the Prognosis and Immunotherapy Response of Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD), the most common subtype of non-small cell lung cancer (NSCLC), is associated with poor prognosis. However, current stage-based clinical methods are insufficient for survival prediction and decision-making. This study aimed to establish a novel model for evaluating the risk of LUAD based on hypoxia, immunity, and epithelial-mesenchymal transition (EMT) gene signatures.

Methods: In this study, we used data from TCGA-LUAD for the training cohort and GSE68465 and GSE72094 for the validation cohorts. Immunotherapy datasets GSE135222, GSE126044, and IMvigor210 were obtained from a previous study. Using bioinformatic and machine algorithms, we established a risk model based on hypoxia, immune, and EMT gene signatures, which was then used to divide patients into the high and low risk groups. We analyzed differences in enriched pathways between the two groups, following which we investigated whether the risk score was correlated with stemness scores, genes related to m6A, m5C, m1A and m7G modification, the immune microenvironment, immunotherapy response, and multiple anti-cancer drug sensitivity.

Results: Overall survival differed significantly between the high-risk and low-risk groups (HR = 4.26). The AUCs for predicting 1-, 3-, and 5-year survival were 0.763, 0.766, and 0.728, respectively. In the GSE68465 dataset, the HR was 2.03, while the AUCs for predicting 1-, 3-, and 5-year survival were 0.69, 0.651, and 0.618, respectively. The corresponding values in the GSE72094 dataset were an HR of 2.36 and AUCs of 0.653, 0.662, and 0.749, respectively. The risk score model could independently predict OS in patients with LUAD, and highly correlated with stemness scores and numerous m6A, m5C, m1A and m7G modification-related genes. Furthermore, the risk model was significantly correlated with multiple immune microenvironment characteristics. In the GSE135222 dataset, the HR was 4.26 and the AUC was 0.702. Evaluation of the GSE126044 and IMvigor210 cohorts indicated that PD-1/PD-LI inhibitor treatment may be indicated in patients with low risk scores, while anti-cancer therapy with various drugs may be indicated in patients with high risk scores.

Conclusion: Our novel risk model developed based on hypoxia, immune, and EMT gene signatures can aid in predicting clinical prognosis and guiding treatment in patients with LUAD.