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

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Abstract

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.

Graphical Abstract

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Availability of data and materials

The datasets generated and/or analysed during the current study are available in the GEO and TCGA repository, [https://www.ncbi.nlm.nih.gov/geo/; https://portal.gdc.cancer.gov/].

Abbreviations

EGFR-TKIs:

Epithelial growth factor receptor-tyrosine kinase inhibitors

LUAD:

Lung adenocarcinoma

DEGs:

Differentially expressed genes

GEO:

Gene Expression Omnibus

TCGA:

The Cancer Genome Atlas

NSCLC:

Nonsmall cell lung cancer

LUSC:

Lung squamous cell carcinoma

LCC:

Large-cell lung carcinoma

ORDEGs:

Osimertinib-resistant differential expressed genes

NCBI:

National Center for Biotechnology Information

GO:

Gene ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

KM:

Kaplan − Meier

OS:

Overall survival

DFS:

Disease-free survival

ROC:

Receiver operating characteristic

AUC:

Area under the curve

DCA:

Decision curve analysis

TIDE:

Tumor Immune Dysfunction and Exclusion

GDSC:

Genomics of drug sensitivity in cancer

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Acknowledgements

The authors are thankful for the publicly available databases.

Funding

This work was supported by the Science, Technology, and Innovation Commission of Shenzhen Municipality (Nos. JCYJ20190808160407500, JCYJ20210324131204012, and JCYJ20220530141417038); Shenzhen Bao'an Traditional Chinese Medicine Hospital Research Program [BAZYY20200604, BAZYY20220701].

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Author notes

  1. Guixing Zhang and Huiting Guan have contributed equally to this work and share the first authorship.

Authors and Affiliations

  1. Shenzhen Bao’an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China

    Guixing Zhang, Huiting Guan, Yi-Le Ning, Kainan Yao, Hao Tang, Gulizeba Muhetaer, Hang Li & Jihong Zhou

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  1. Guixing Zhang
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Contributions

GZ and HG designed the study. HG and YN collected and assembled the data. GZ, KY and GM analyzed and counted the data. GZ, HG and HT drafted the initial manuscript. JZ, HL and KY provided financial support for this study. JZ and HL reviewed and edited the article. All authors contributed to the article and approved the submitted version.

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Correspondence to Hang Li or Jihong Zhou.

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Zhang, G., Guan, H., Ning, YL. et al. Osimertinib resistance prognostic gene signature: STRIP2 is associated with immune infiltration and tumor progression in lung adenocarcinoma. J Cancer Res Clin Oncol 149, 15573–15588 (2023). https://doi.org/10.1007/s00432-023-05294-w

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