The exploration of differential genes and prognosis in lymph node metastasis and visceral metastasis of prostate cancer based on GEO database

doi:10.3877/cma.j.issn.1674-3253.2025.05.006

Abstract

Abstract:

Objective

Based on the GEO database, bioinformatics methods were used to mine differentially expressed genes related to patients with lymph node metastasis and patients with visceral metastasis of prostate cancer, providing new ideas for prostate cancer metastasis diagnosis and treatment.

Methods

The dataset GSE6752 was downloaded from the GEO database to screen the differentially expressed genes in patients with prostate cancer lymph node metastasis and patients with visceral metastasis, and the protein interactions network was constructed by using the STRING database and Cytoscape software to screen the key genes from the differentially expressed genes. The expression levels of key genes in prostate cancer lymph node metastasis and visceral metastasis were analyzed by data processing of data set GSE6752 using R software. The correlation between key genes and PSA level, Gleason score and prognosis were analyzed using TCGA and GEPIA databases.

Results

71 genes were screened for differentially expressed genes in lymph node metastasis and visceral metastasis of prostate cancer, compared with lymph node metastasis, 41 genes were up-regulated and 30 genes were down-regulated in visceral metastasis. The key genes FTCD, GBA2 and PRKCA were screened and found to be more highly expressed in patients with visceral metastasis of prostate cancer than in those with lymph node metastasis, and were negatively correlated with the prognosis of prostate cancer.

Conclusion

FTCD, GBA2 genes are negatively associated with the prognosis of prostate cancer and may play an important role in the molecular mechanism of the development of different metastatic modalities of prostate cancer.

Key words: Prostate cancer, Metastasis, Prognosis, Bioinformatics, Differentially expressed genes (DEG)

Yuchun Chen, Qianqian Wang, Tianming Peng, Yong Li, Kaiwen Tian, Zhiye Liu, Kunlin Wu, Xiaoyong Pu, Jiumin Liu. The exploration of differential genes and prognosis in lymph node metastasis and visceral metastasis of prostate cancer based on GEO database[J]. Chinese Journal of Endourology(Electronic Edition), 2025, 19(05): 579-585.

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References 29

[1]	Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023[J]. CA A Cancer J Clin, 2023, 73(1): 17-48. DOI: 10.3322/caac.21763.
[2]	Xia C, Dong X, Li H, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants[J]. Chin Med J (Engl), 2022, 135(5): 584-590. DOI: 10.1097/CM9.0000000000002108.
[3]	Zheng R, Zhang S, Zeng H, et al. Cancer incidence and mortality in China, 2016[J]. J Natl Cancer Cent, 2022, 2(1): 1-9. DOI: 10.1016/j.jncc.2022.02.002.
[4]	Ahmed ME, Mahmoud AM, Reitano G, et al. Survival patterns based on first-site-specific visceral metastatic prostate cancer: are outcomes of visceral metastases the same?[J]. Eur Urol Open Sci, 2024, 66: 38-45. DOI: 10.1016/j.euros.2024.06.006.
[5]	Rud E, Noor D, Galtung KF, et al. Validating the screening criteria for bone metastases in treatment-naïve unfavorable intermediate and high-risk prostate cancer - the prevalence and location of bone- and lymph node metastases[J]. Eur Radiol, 2022, 32(12): 8266-8275. DOI: 10.1007/s00330-022-08945-7.
[6]	Gandaglia G, Abdollah F, Schiffmann J, et al. Distribution of metastatic sites in patients with prostate cancer: a population-based analysis[J]. Prostate, 2014, 74(2): 210-216. DOI: 10.1002/pros.22742.
[7]	吴洪瀚, 范青洪, 瓦庆德. 前列腺癌骨转移治疗研究进展[J]. 遵义医科大学学报, 2024, 47(4): 424-431. DOI: 10.14169/j.cnki.zunyixuebao.2024.0052.
[8]	Moshref L, Abidullah M, Czaykowski P, et al. Prostate cancer metastasis to stomach: a case report and review of literature[J]. Curr Oncol, 2023, 30(4): 3901-3914. DOI: 10.3390/curroncol30040295.
[9]	徐一方, 韩海心, 杨旭. HPV16/18型感染与前列腺癌发病、分期、淋巴转移及肿瘤标志物的相关性[J]. 热带医学杂志, 2023, 23(1): 75-78, 83. DOI: 10.3969/j.issn.1672-3619.2023.01.017.
[10]	Labib OH, Harb OA, Khalil OH, et al. The diagnostic value of arginase-1, FTCD, and MOC-31 expression in early detection of hepatocellular carcinoma (HCC) and in differentiation between HCC and metastatic adenocarcinoma to the liver[J]. J Gastrointest Cancer, 2020, 51(1): 88-101. DOI: 10.1007/s12029-019-00211-2.
[11]	Kanarek N, Keys HR, Cantor JR, et al. Histidine catabolism is a major determinant of methotrexate sensitivity[J]. Nature, 2018, 559(7715): 632-636. DOI: 10.1038/s41586-018-0316-7.
[12]	Chen J, Chen Z, Huang Z, et al. Formiminotransferase cyclodeaminase suppresses hepatocellular carcinoma by modulating cell apoptosis, DNA damage, and phosphatidylinositol 3-kinases (PI3K)/Akt signaling pathway[J]. Med Sci Monit, 2019, 25: 4474-4484. DOI: 10.12659/MSM.916202.
[13]	Kaneko Y, Shimoda K, Ayala R, et al. p97 and p47 function in membrane tethering in cooperation with FTCD during mitotic Golgi reassembly[J]. EMBO J, 2021, 40(9): e105853. DOI: 10.15252/embj.2020105853.
[14]	Tian Y, Lu J, Qiao Y. A metabolism-associated gene signature for prognosis prediction of hepatocellular carcinoma[J]. Front Mol Biosci, 2022, 9: 988323. DOI: 10.3389/fmolb.2022.988323.
[15]	Zhang W, Wu C, Ni R, et al. Formimidoyltransferase cyclodeaminase prevents the starvation-induced liver hepatomegaly and dysfunction through downregulating mTORC1[J]. PLoS Genet, 2021, 17(12): e1009980. DOI: 10.1371/journal.pgen.1009980.
[16]	Xiao J, Wang J, Zhou C, et al. Development and validation of a propionate metabolism-related gene signature for prognostic prediction of hepatocellular carcinoma[J]. J Hepatocell Carcinoma, 2023, 10: 1673-1687. DOI: 10.2147/JHC.S420614.
[17]	Sorli SC, Colié S, Albinet V, et al. The nonlysosomal β-glucosidase GBA2 promotes endoplasmic reticulum stress and impairs tumorigenicity of human melanoma cells[J]. FASEB J, 2013, 27(2): 489-498. DOI: 10.1096/fj.12-215152.
[18]	Niu C, Li X, et al. Identification of novel prognostic biomarkers for colorectal cancer by bioinformatics analysis[J]. Turk J Gastroenterol, 2024, 35(1): 61-72. DOI: 10.5152/tjg.2024.23264.
[19]	Taghizadeh E, Heydarheydari S, Saberi A, et al. Breast cancer prediction with transcriptome profiling using feature selection and machine learning methods[J]. BMC Bioinformatics, 2022, 23(1): 410. DOI: 10.1186/s12859-022-04965-8.
[20]	Liu R, Chu W, Liu X, et al. Establishment of Golgi apparatus-related genes signature to predict the prognosis and immunotherapy response in gastric cancer patients[J]. Medicine (Baltimore), 2024, 103(11): e37439. DOI: 10.1097/MD.0000000000037439.
[21]	Wheeler S, Sillence DJ. Niemann-pick type C disease: cellular pathology and pharmacotherapy[J]. J Neurochem, 2020, 153(6): 674-692. DOI: 10.1111/jnc.14895.
[22]	Fu Q, Song X, Liu Z, et al. miRomics and proteomics reveal a miR-296-3p/PRKCA/FAK/Ras/c-Myc feedback loop modulated by HDGF/DDX5/β-catenin complex in lung adenocarcinoma[J]. Clin Cancer Res, 2017, 23(20): 6336-6350. DOI: 10.1158/1078-0432.CCR-16-2813.
[23]	Jiang H, Fu Q, Song X, et al. HDGF and PRKCA upregulation is associated with a poor prognosis in patients with lung adenocarcinoma[J]. Oncol Lett, 2019, 18(5): 4936-4946. DOI: 10.3892/ol.2019.10812.
[24]	Salama MF, Liu M, Clarke CJ, et al. PKCα is required for Akt-mTORC1 activation in non-small cell lung carcinoma (NSCLC) with EGFR mutation[J]. Oncogene, 2019, 38(48): 7311-7328. DOI: 10.1038/s41388-019-0950-z.
[25]	Liu J, Li J. PKCα and Netrin-1/UNC5B positive feedback control in relation with chemical therapy in bladder cancer[J]. Eur Rev Med Pharmacol Sci, 2020, 24(4): 1712-1717. DOI: 10.26355/eurrev_202002_20346.
[26]	Sun T, Zhang P, Zhang Q, et al. Transcriptome analysis reveals PRKCA as a potential therapeutic target for overcoming cisplatin resistance in lung cancer through ferroptosis[J]. Heliyon, 2024, 10(10): e30780. DOI: 10.1016/j.heliyon.2024.e30780.
[27]	Zhao J, Tian H, Zhao X, et al. PKCα induced the generation of extracellular vesicles in activated platelets to promote breast cancer metastasis[J]. Int J Biol Sci, 2024, 20(10): 3956-3971. DOI: 10.7150/ijbs.89822.
[28]	王素杰. PRKCA调控食管鳞癌增殖迁移侵袭的分子机制及临床意义[D]. 新乡: 新乡医学院, 2021. DOI: 10.27434/d.cnki.gxxyc.2021.000216.
[29]	Guo Y, Bao Y, Ma M, et al. Clinical significance of the correlation between PLCE 1 and PRKCA in esophageal inflammation and esophageal carcinoma[J]. Oncotarget, 2017, 8(20): 33285-33299. DOI: 10.18632/oncotarget.16635.

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