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Identification of Crucial Genes and Signaling Pathways in Alectinib-Resistant Lung Adenocarcinoma Using Bioinformatic Analysis

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Abstract

Alectinib, a second-generation anaplastic lymphoma kinase (ALK) inhibitor, has been shown to be effective for patients with ALK-positive non-small cell lung cancer (NSCLC). However, alectinib resistance is a serious problem worldwide. To the best of our knowledge, little information is available on its molecular mechanisms using the Gene Expression Omnibus (GEO) database. In this study, the differentially expressed genes (DEGs) were selected from the gene expression profile GSE73167 between parental and alectinib-resistant human lung adenocarcinoma (LUAD) cell samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) annotation enrichment analyses were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID). The construction of protein–protein interaction (PPI) network was performed to visualize DEGs. The hub genes were extracted based on the analysis of the PPI network using plug-in cytoHubba of Cytoscape software. The functional roles of the key genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer (UALCAN), Gene Set Enrichment Analysis (GSEA), and Tumor Immune Estimation Resource (TIMER) analysis. The networks of kinase, miRNA, and transcription-factor targets of SFTPD were explored using LinkedOmics. The drug sensitivity analysis of SFTPD was analyzed using the RNAactDrug database. Results showed a total of 144 DEGs were identified. Five hub genes were extracted, including mucin 5B (MUC5B), surfactant protein D (SFTPD), deleted in malignant brain tumors 1 (DMBT1), surfactant protein A2 (SFTPA2), and trefoil factor 3 (TFF3). The survival analysis using GEPIA displayed that low expression of SFTPD had a significantly negative effect on the prognosis of patients with LUAD. GSEA revealed that low expression of SFTPD was positively correlated with the pathways associated with drug resistance, such as DNA replication, cell cycle, drug metabolism, and DNA damage repair, including mismatch repair (MMR), base excision repair (BER), homologous recombination (HR), and nucleotide excision repair (NER). The SFTPD expression was negatively correlated with the drug sensitivity of alectinib according to RNAactDrug database. The expression of SFTPD was further validated in parental H3122 cells and alectinib-resistant H3122 cells by quantitative reverse transcription PCR (RT-qPCR). In conclusion, our study found that the five hub genes, especially low expression of SFTPD, are closely related to alectinib resistance in patients with LUAD.

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Data Availability

The data analyzed during the current study are derived from the following resources available in the public domain (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73167). The data used to support the findings of this study are included within the article.

Abbreviations

NSCLC:

Non-small cell lung cancer

LUAD:

Lung adenocarcinoma

LUSC:

Lung squamous cell carcinoma

EGFR:

Epidermal growth factor receptor

RET:

Rearranged during transfection

MET:

Mesenchymal-to-epithelial transition factor

KRAS:

Kirsten rat sarcoma 2 viral oncogene homolog

BRAF:

B-Raf proto-oncogene

ROS1:

ROS proto-oncogene 1

ALK:

Anaplastic lymphoma kinase

GEO:

Gene expression omnibus

DEGs:

Differentially expressed genes

FC:

Fold change

GO:

Gene ontology

KEGG:

Kyoto encyclopedia of genes and genomes

DAVID:

Database for annotation, visualization, and integrated discovery

PPI:

Protein–protein interaction

MCC:

Maximal clique centrality

MNC:

Maximal neighborhood component

EPC:

Edge percolated component

Degree:

Node connect degree

Closeness:

Node connect closeness

OS:

Overall survival

DFS:

Disease-free survival

GEPIA:

Gene expression profiling interactive analysis

UALCAN:

University of alabama at birmingham cancer

GSEA:

Gene set enrichment analysis

TIMER:

TUMOR immune estimation resource

RT-qPCR:

Quantitative reverse transcription PCR

H3122R:

H3122 alectinib-resistant

BP:

Biological process

CC:

Cellular component

MF:

Molecular function

MUC5B:

Mucin 5B

SFTPD:

Surfactant protein D

DMBT1:

Deleted in malignant brain tumors 1

SFTPA2:

Surfactant protein A2

TFF3:

Trefoil factor 3

MMR:

Mismatch repair

BER:

Base excision repair

HR:

Homologous recombination

NER:

Nucleotide excision repair

NMU:

Neuromedin U

SFTP:

Surfactant protein

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Acknowledgements

The datasets generated in this study are available from GEO that provide free resources.

Funding

This work was supported by the Health Commission of Shanxi Province research project of 2023 (Grant No. 2023045).

Author information

Author notes

  1. Zhilong Li, Yafeng Fan and Yong Ma have equally contributed to this work and share first authorship.

Authors and Affiliations

  1. Department of Thoracic Surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China

    Zhilong Li, Jianhong Lian & Chengguang Hu

  2. Respiratory Department, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China

    Yafeng Fan

  3. Thoracic Surgery Department II, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China

    Yong Ma

  4. Department of Translational Medicine, ChosenMed Technology (Zhejiang) Co., Ltd, Beijing, 100176, China

    Nan Meng, Dongbing Li & Dongliang Wang

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Contributions

JHL and CGH: designed the research study. ZLL, YFF, and YM: wrote the manuscript. NM, DBL, and DLW: analyzed the data. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Jianhong Lian or Chengguang Hu.

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Competing interests

NM, DBL, and DLW are employees of ChosenMed Technology. The remaining authors declare that they have no conflicts of interest.

Ethical Approval and Consent to Participate

Not applicable (GEO is an open database with ethical permission obtained for patients who participated. The data can be downloaded for free for research and publication. Open-source data are used in our research, so there are no ethical concerns).

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Supplementary Information

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12033_2023_973_MOESM1_ESM.tif

Supplementary file1 (TIF 11156 kb)—Supplementary Fig. 1 Co-expressed genes with SFTPD in LUAD. (a) Heat maps of the top 50 genes positively correlated with SFTPD in LUAD. (b) Heat maps of the top 50 genes negatively correlated with SFTPD in LUAD.Co-expressed genes with SFTPD in LUAD. (a) Heat maps of the top 50 genes positively correlated with SFTPD in LUAD. (b) Heat maps of the top 50 genes negatively correlated with SFTPD in LUAD.

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Li, Z., Fan, Y., Ma, Y. et al. Identification of Crucial Genes and Signaling Pathways in Alectinib-Resistant Lung Adenocarcinoma Using Bioinformatic Analysis. Mol Biotechnol (2023). https://doi.org/10.1007/s12033-023-00973-y

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