Volume 14, Issue 1 (Vol.14 No.1 Apr 2025)                   rbmb.net 2025, 14(1): 102-113 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zhang L, Fan C, Shang H, Wang X, Zhang X, Qiao Q, et al . Cross-Regional Transcriptome Data Reveal Transcriptional Abnormalities Associated with Lung Adenocarcinoma. rbmb.net 2025; 14 (1) :102-113
URL: http://rbmb.net/article-1-1318-en.html
Guangzhou Laboratory, Guangzhou 510005, China.
Abstract:   (633 Views)
Background: Lung cancer is the leading cause of cancer-related deaths worldwide, yet there has been little attention given to the correlation between the cancer transcriptome and the incidence and mortality of lung cancer across different geographic regions.

Methods: To analyze this correlation, we screened the transcriptome datasets of stage I lung adenocarcinoma (LAC) patients from the Lung Cancer Explorer and examined their correlation with the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and mortality-to-incidence ratio (MIR).

Results: The expression difference rates (DRs) of certain genes (SPARCL1, SRPX, PMP22, MSR1, BST1, AKAP12, MAOB, vimentin, serglycin, ILK, ESD, transgelin, NCOA1, and PLPP1) were significantly negatively correlated with the ASIR of female LAC. Additionally, the DR of KRT19 was significantly positively correlated with the ASIR of female LAC. Furthermore, the DRs of COL10A1, SMAD7, COL3A1, and AQP1 were significantly positively correlated with the ASMR and MIR of female LAC, while the DR of KRT15 was significantly negatively correlated with the ASMR and MIR of female LAC. In male LAC patients, the DR of RGS2 was significantly negatively correlated with the ASIR, while the DRs of SPARCL1, COX7A1, IL3RA, and ADH1B were significantly positively correlated with the ASMR and MIR. Additionally, the DR of AIMP2 was significantly negatively correlated with the ASMR and MIR.

Conclusions: Our findings suggest that the expression levels of serglycin, ILK, ESD, and PLPD1 may play a significant role in the development of LAC. This information can be valuable for identifying potential treatment targets for lung cancer.
Full-Text [PDF 460 kb]   (276 Downloads)    
Type of Article: Original Article | Subject: Molecular Biology
Received: 2024/01/3 | Accepted: 2025/08/5 | Published: 2025/12/9

References
1. Sharma R. Mapping of global, regional and national incidence, mortality and mortality-to-incidence ratio of lung cancer in 2020 and 2050. Int J Clin Oncol. 2022;27:665-675. [DOI:10.1007/s10147-021-02108-2] [PMID] []
2. Esfandi F, Fallah H, Arsang-Jang S, Taheri M, Ghafouri-Fard S. The expression of CCAT2, UCA1, PANDA and GHET1 long non-coding RNAs in lung cancer. Rep Biochem Mol Biol. 2019;8:36-41.
3. Barta JA, Powell CA, Wisnivesky JP. Global epidemiology of lung cancer. Ann Glob Health. 2019;85:1-16. [DOI:10.5334/aogh.2419] [PMID] []
4. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209-249. [DOI:10.3322/caac.21660] [PMID]
5. Cridelli C, Rossi A, Carbone DP, Guarize J, Karachaliou N, et al. Non-small-cell lung cancer. Nat Rev Dis Primers. 2015;1:15009. [DOI:10.1038/nrdp.2015.9] [PMID]
6. Bakhtiyari N, Sharifi A, Aftabi Y, Gilani N, Zafari V, Ansarin A, Seyedrezazadeh E. Association between NOX4 and Nrf2 genes in non-small-cell lung carcinoma: A case-control study. Rep Biochem Mol Biol. 2021;10:327-333. [DOI:10.52547/rbmb.10.2.327] [PMID] []
7. The Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511:543-550. [DOI:10.1038/nature13385] [PMID] []
8. Cai L, Lin S, Girard L, Zhou Y, Yang L, et al. LCE: an open web portal to explore gene expression and clinical associations in lung cancer. Oncogene. 2019;38:2551-2564. [DOI:10.1038/s41388-018-0588-2] [PMID] []
9. Zhu X, Luo H, Xu Y. Transcriptome analysis reveals and important candidate gene involved in both nodal metastasis and prognosis in lung adenocarcinoma. Cell Biosci. 2019;9:92. [DOI:10.1186/s13578-019-0356-1] [PMID] []
10. Wang Z, Li Z, Zhou K, Wang C, Jiang L, et al. Deciphering cell lineage specification of human lung adenocarcinoma with single-cell RNA sequencing. Nat Comm. 2021;12:6500. [DOI:10.1038/s41467-021-26770-2] [PMID] []
11. Parks DH, Tyson GW, Hugenholtz P, Beiko RG. STAMP: statistical analysis of taxonomic and functional profiles. Bioinformatics. 2014;30:3123-3124. [DOI:10.1093/bioinformatics/btu494] [PMID] []
12. Dembélé D, Kastner P. Fold change rank ordering statistics: a new method for detecting differentially expressed genes. BMC Bioinformatics. 2014;15:14. [DOI:10.1186/1471-2105-15-14] [PMID] []
13. Adler M, Alon U. Fold-change detection in biological systems. Curr Opin Syst Biol. 2018; 8:81-89. [DOI:10.1016/j.coisb.2017.12.005]
14. Hao Y, Li D, Xu Y, Ouyang J, Wang Y, et al. Investigation of lipid metabolism dysregulation and the effects on immune microenvironments in pan-cancer using multiple omics data. BMC Bioinformatics. 2019;20:195. [DOI:10.1186/s12859-019-2734-4] [PMID] []
15. Wang W, Bai L, Li W, Cui J. The lipid metabolic landscape of cancers and new therapeutic perspectives. Front Oncol. 2020;10:605154. [DOI:10.3389/fonc.2020.605154] [PMID] []
16. Lu J, Li J, Ji C, Yu W, Xu Z, et al. Expression of lipoprotein lipase associated with lung adenocarcinoma tissues. Mol Biol Rep. 2008;35:59-63. [DOI:10.1007/s11033-006-9053-3] [PMID]
17. Chang C-Y, Wu K-L, Chang Y-Y, Tsai P-H, Huang J-Y, et al. Amine oxidase, copper containing 3 exerts anti-mesenchymal transformation and enhances CD4+ T-cell recruitment to prolong survival in lung cancer. Oncol Rep. 2021;46:203. [DOI:10.3892/or.2021.8154] [PMID] []
18. Chen S, Wei Y, Liu H, Gong Y, Zhou Y, et al. Analysis of collagen type X alpha 1 (COL10A1) expression and prognostic significance in gastric cancer based on bioinformatics. Bioengineered. 2021;12:127-137. [DOI:10.1080/21655979.2020.1864912] [PMID] []
19. Klingler A, Regensburger D, Tenkerian C, Britzen-Laurent N, Hartmann A, et al. Species-, organ- and cell-type-dependent expression of SPARCL1 in human and mouse tissues. PLoS ONE. 2020;15:e0233422. [DOI:10.1371/journal.pone.0233422] [PMID] []
20. Qu H, Zhu M, Tao Y, Zhao Y. Suppression of peripheral myelin protein 22 (PMP22) expression by miR29 inhibits the progression of lung cancer. Neoplasma. 2015;62:881-886. [DOI:10.4149/neo_2015_107] [PMID]
21. Guo JY, Hsu HS, Tyan SW, Li FY, Shew JY, et al. Serglycin in tumor microenvironment promotes non-small cell lung cancer aggressiveness in a CD44-dependent manner. Oncogene. 2017;36:2457-2471. [DOI:10.1038/onc.2016.404] [PMID] []
22. Nikou S, Arbi M, Dimitrakopoulos FID, Sirinian C, Chadla P, et al. Integrin-linked kinase (ILK) regulates KRAS, IPP complex and Ras suppressor-1 (RSU1) promoting lung adenocarcinoma progression and poor survival. J Mol Histol. 2020;51:385-400. [DOI:10.1007/s10735-020-09888-3] [PMID]
23. Wiedl T, Arni S, Roschitzki B, Grossmann J, Collaud S, et al. Activity-based proteomics: Identification of ABHD11 and ESD activities as potential biomarkers for human lung adenocarcinoma. J Proteom. 2011;74:1884-1894. [DOI:10.1016/j.jprot.2011.04.030] [PMID]
24. Sun C, Zhang K, Ni C, Wan J, Duan X, et al. Transgelin promotes lung cancer progression via activation of cancer-associated fibroblasts with enhanced IL-6 release. Oncogenesis. 2023;12:18. [DOI:10.1038/s41389-023-00463-5] [PMID] []
25. Kuo T-C, Tan C-T, Chang Y-W, Hong C-C, Lee W-J, et al. Angiopoietin-like protein 1 suppresses SLUG to inhibit cancer cell motility. J Clin Inv. 2013;123:1082-1095. [DOI:10.1172/JCI64044] [PMID] []

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2015 All Rights Reserved | Reports of Biochemistry and Molecular Biology

Designed & Developed by : Yektaweb