Identification of a novel gene signature of lung adenocarcinoma based on epidermal growth factor receptor-tyrosine kinase inhibitor resistance

E Zhou; Feng Wu; Mengfei Guo; Zhengrong Yin; Yumei Li; Minglei Li; Hui Xia; Jingjing Deng; Guanghai Yang; Yang Jin

doi:10.3389/fonc.2022.1008283

Identification of a novel gene signature of lung adenocarcinoma based on epidermal growth factor receptor-tyrosine kinase inhibitor resistance

Front Oncol. 2022 Dec 1:12:1008283. doi: 10.3389/fonc.2022.1008283. eCollection 2022.

Authors

E Zhou^{1

2}, Feng Wu^{1

2}, Mengfei Guo^{1

2}, Zhengrong Yin^{1

2}, Yumei Li^{1

2}, Minglei Li^{1

2}, Hui Xia^{1

2}, Jingjing Deng^{1

2}, Guanghai Yang³, Yang Jin^{1

2}

Affiliations

¹ Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
² Hubei Province Engineering Research Center for Tumor-Targeted Biochemotherapy, Key Laboratory of Biological Targeted Therapy, the Ministry of Education, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
³ Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Abstract

Introduction: Tyrosine kinase inhibitors (TKIs) that target epidermal growth factor receptor (EGFR) mutations are commonly administered to EGFR-positive lung cancer patients. However, resistance to EGFR-TKIs (mostly gefitinib and erlotinib) is presently a significant problem. Limited studies have focused on an EGFR-TKI resistance-related gene signature (ERS) in lung adenocarcinoma (LUAD).

Methods: Gefitinib and erlotinib resistance-related genes were obtained through the differential analyses of three Gene Expression Omnibus datasets. These genes were investigated further in LUAD patients from The Cancer Genome Atlas (TCGA). Patients in the TCGA-LUAD cohort were split into two groups: one for training and one for testing. The training cohort was used to build the ERS, and the testing cohort was used to test it. GO and KEGG analyses were explored for the enriched pathways between the high-risk and low-risk groups. Various software, mainly CIBERSORT and ssGSEA, were used for immune infiltration profiles. Somatic mutation and drug sensitivity analyses were also explored.

Results: An ERS based on five genes (FGD3, PCDH7, DEPDC1B, SATB2, and S100P) was constructed and validated using the TCGA-LUAD cohort, resulting in the significant stratification of LUAD patients into high-risk and low-risk groups. Multivariable Cox analyses confirmed that ERS had an independent prognostic value in LUAD. The pathway enrichment analyses showed that most of the genes that were different between the two risk groups were related to the immune system. Further immune infiltration results revealed that a lower immune infiltration score was observed in high-risk patients, and that various leukocytes were significantly related to the ERS. Importantly, samples from the high-risk group showed lower levels of PD-1, PD-L1, and CTLA-4, which are important biomarkers for immunotherapy responses. Patients in the high-risk group also had more gene mutation changes and were more sensitive to chemotherapy drugs like docetaxel and sorafenib. The ERS was also validated in the GSE30219, GSE11969 and GSE72094, and showed a favorable prognostic value for LUAD patients.

Discussion: The ERS established during this study was able to predict a poor prognosis for LUAD patients and had great potential for predicting drug responses.

Keywords: drug sensitivity; epidermal growth factor receptor-tyrosine kinase inhibitor resistance; immune microenvironment; lung adenocarcinoma; prognostic signature.