Analysis of prognostic and therapeutic values of drug resistance-related genes in the lung cancer microenvironment

Liang Zhu; Peixin Chen; Hao Wang; Lishu Zhao; Haoyue Guo; Minlin Jiang; Sha Zhao; Wei Li; Jun Zhu; Jia Yu; Jiawei Dai

doi:10.21037/tcr-21-1841

Analysis of prognostic and therapeutic values of drug resistance-related genes in the lung cancer microenvironment

Transl Cancer Res. 2022 Feb;11(2):339-357. doi: 10.21037/tcr-21-1841.

Authors

Liang Zhu^#^{1

2}, Peixin Chen^#^{1

2}, Hao Wang^{1

2}, Lishu Zhao^{1

2}, Haoyue Guo^{1

2}, Minlin Jiang^{1

2}, Sha Zhao^{1

2}, Wei Li^{1

2}, Jun Zhu^{1

2}, Jia Yu^{1

2}, Jiawei Dai³

Affiliations

¹ School of Medicine, Tongji University, Shanghai, China.
² Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China.
³ SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.

^# Contributed equally.

Abstract

Background: The interaction between cancer cells and stromal cells has a significant contribution in tumorigenesis and tumor development, and plays an anti-tumor immune effect under the regulation of drug resistance-related genes, which affects the outcome of patients. Coiled-coil domain-containing protein 73 (CCDC73), DLG associated protein 1 (DLGAP1), dermatan sulfate epimerase like (DSEL), estrogen receptor 1 (ESR1), and SEC14-like 5 (SEC14L5) were identified as drug resistance-related genes in lung cancer. However, these genes have no clear value in lung cancer in terms of expression and prognosis.

Methods: ONCOMINE, GEPIA, UALCAN, cBioPortal, GeneMANIA, STRING, and TIMER were utilized in this study.

Results: The transcriptional expression level of DLGAP1 was remarkably decreased in lung cancer tissues, while the transcriptional level of SEC14L5 was significantly increased. The pathological stage of lung adenocarcinoma (LUAD) was tightly correlated with the expression of SEC14L5. The lung cancer patients with high transcription level of CCDC73 gene tended to have a good prognosis. The function of drug resistance-related genes is mainly related to RNA polymerization. Our results showed that infiltration of six types of immune cells (dendritic cells, macrophages, neutrophils, B cells, CD4⁺ T cells, and CD8⁺ T cells) significantly correlated with the expression of these drug resistance-related genes.

Conclusions: Novel screening for immunotherapy targets and prognostic biomarkers in lung cancer may draw inspiration from our results.

Keywords: Lung cancer; bioinformatics analysis; biomarkers; prognosis; tumor microenvironment.