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Identification of tumor-suppressor genes in lung squamous cell carcinoma through integrated bioinformatics analyses

HENG LI1,#, YOUMING LEI3,#, GAOFENG LI1, YUNCHAO HUANG2,*

1 The 2nd Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Tumor Hospital, Kunming, 650118, China
2 The 1st Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Tumor Hospital, Kunming, 650118, China
3 Department of Geriatric Thoracic Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, China

* Corresponding Author: YUNCHAO HUANG. Email: email
# These authors contributed equally

Oncology Research 2024, 32(1), 187-197. https://doi.org/10.32604/or.2023.030656

Abstract

Lung cancer is a prevalent malignancy, and fatalities of the disease exceed 400,000 cases worldwide. Lung squamous cell carcinoma (LUSC) has been recognized as the most common pathological form of lung cancer. The comprehensive understanding of molecular features related to LUSC progression has great significance in LUSC prognosis assessment and clinical management. In this study, we aim to identify a panel of signature genes closely associated with LUSC, which can provide novel insights into the progression of LUSC. Gene expression profiles were retrieved from public resources including gene expression omnibus (GEO) and the cancer genome atlas (TCGA) database. Differentially expressed genes (DEGs) between LUSC specimens and normal lung tissues were identified by bioinformatics analyses. A total of 66 DEGs were identified based on two cohorts of data. CytoHubba plugin of Cytoscape software was utilized for the further analyses of the top 10 candidate hub genes including OGN, ABI3BP, MAMDC2, FGF7, FAM107A, SPARCL1, DCN, COL14A1, and MFAP4 and CHRDL1, which showed significant downregulation in LUSC. Two LUSC cell lines were used to validate the functions of CHRDL1 and FAM107A through overexpression experiment. Together, our data revealed novel candidate tumor-suppressor genes in LUSC, suggesting previously unappreciated mechanisms in the progression of LUSC.

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APA Style
LI, H., LEI, Y., LI, G., HUANG, Y. (2024). Identification of tumor-suppressor genes in lung squamous cell carcinoma through integrated bioinformatics analyses. Oncology Research, 32(1), 187-197. https://doi.org/10.32604/or.2023.030656
Vancouver Style
LI H, LEI Y, LI G, HUANG Y. Identification of tumor-suppressor genes in lung squamous cell carcinoma through integrated bioinformatics analyses. Oncol Res. 2024;32(1):187-197 https://doi.org/10.32604/or.2023.030656
IEEE Style
H. LI, Y. LEI, G. LI, and Y. HUANG, “Identification of tumor-suppressor genes in lung squamous cell carcinoma through integrated bioinformatics analyses,” Oncol. Res., vol. 32, no. 1, pp. 187-197, 2024. https://doi.org/10.32604/or.2023.030656



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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