Phosphorus Metabolism-Related Genes Serve as Novel Biomarkers for Predicting Prognosis in Bladder Cancer: A Bioinformatics Analysis
-
Yang He
,
Abai Xu
,
Li Xiao
,
Ying Yang
,
Boping Li
,
Zhe Liu
,
Peng Rao
,
Yicheng Wang
,
Li Ruan
,
Tao Zhang
Abstract
Background: Phosphorus metabolism might be associated with tumor initiation and progression. We aimed to screen out the phosphorus metabolism genes related to bladder cancer and construct a clinical prognosis model.
Methods: The dataset used for the analysis was obtained from TCGA database. GO and KEGG enrichment analyses were subsequently applied to differentially expressed genes. Consensus clustering was utilized, and different clusters of the tumor immune microenvironment and other features were compared. The phosphorus metabolism-related genes involved in prognosis were screened out by univariate Cox regression, LASSO regression and multivariate Cox regression analysis, and a nomogram was constructed. The performance of the nomogram was validated using TCGA dataset and the GEO dataset, respectively.
Results: Overall, 405 phosphorus metabolism-related differentially expressed genes from TCGA database were identified, which were associated with phosphorylation, cell proliferation, leukocyte activation, and signaling pathways. Two clusters were obtained by consistent clustering. After tumor immune microenvironment analysis, significant differences in immune cell infiltration between cluster 1 and cluster 2 were found. Four phosphorus metabolism-related genes (LIME1, LRP8, SPDYA, and MST1R) were associated with the prognosis of bladder cancer (BLCA) patients. We built a prognostic model and visualized the model as a nomogram. Calibration curves demonstrated the performance of this nomogram, in agreement with that shown by the ROC curves.
Conclusion: We successfully identified four phosphorus metabolism-related genes associated with prognosis, providing potential targets for biomarkers and therapeutics. A nomogram based on these genes was developed. Nevertheless, this study is based on bioinformatics, and experimental validation remains essential.
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30. Li L, Qu W-H, Ma H-P, et al (2022). LRP8, modulated by miR-1262, promotes tumour progression and forecasts the prognosis of patients in breast cancer. Arch Physiol Biochem, 128 (3):657-665.
31. Rey JP, Ellies DL (2010). Wnt modulators in the biotech pipeline. Dev Dyn, 239 (1):102-14.
32. Garnis C, Campbell J, Davies JJ, et al (2005). Involvement of multiple developmental genes on chromosome 1p in lung tumorigenesis. Hum Mol Genet, 14 (4):475-82.
33. Lin CC, Lo MC, Moody R, et al (2018). Targeting LRP8 inhibits breast cancer stem cells in triple-negative breast cancer. Cancer Lett, 438:165-173.
34. McAndrew CW, Gastwirt RF, Donoghue DJ (2009). The atypical CDK activator Spy1 regulates the intrinsic DNA damage response and is dependent upon p53 to inhibit apoptosis. Cell Cycle, 8 (1):66-75.
35. Lu S, Liu R, Su M, Wei Y, et al (2016). Spy1 participates in the proliferation and apoptosis of epithelial ovarian cancer. J Mol Histol, 47 (1):47-57.
36. Jin Q, Liu G, Bao L, et al (2018). High Spy1 expression predicts poor prognosis in colorectal cancer. Cancer Manag Res, 10:2757-2765.
37. An W, Kang JS, Oh S, et al (2023). MST1R as a potential new target antigen of chimeric antigen receptor T cells to treat solid tumors. Korean J Physiol Pharmacol, 27 (3):241-256.
38. Khan M, Hearn K, Parry C, et al (2023). Mechanism of Antitumor Effects of Saffron in Human Prostate Cancer Cells. Nutrients, 16 (1):114.
39. Jeong BC, Oh SH, Lee MN, et al (2020). Macrophage-Stimulating Protein Enhances Osteoblastic Differentiation via the Recepteur d'Origine Nantais Receptor and Extracellular Signal-Regulated Kinase Signaling Pathway. J Bone Metab, 27 (4):267-279.
40. Zou Y, Yuan G, Tan X, et al (2022). Immune-related gene risk score predicting the effect of immunotherapy and prognosis in bladder cancer patients. Front Genet, 13:1011390.
41. Kato A, Ng S, Thangasamy A, et al (2021). A potential signaling axis between RON kinase receptor and hypoxia-inducible factor-1 alpha in pancreatic cancer. Mol Carcinog, 60 (11):734-745.
42. Milan M, Benvenuti S, Balderacchi AM, et al (2018). RON tyrosine kinase mutations in brain metastases from lung cancer. ERJ Open Res, 4(1):00083-2017.
43. Zhou D, Zhu X, Wu X, et al (2021). The effect of splicing MST1R in gastric cancer was enhanced by lncRNA FENDRR. Exp Ther Med, 22 (2):798.
2. Miranda AF, Howard JM, McLaughlin M, et al (2021). Metastasis-directed radiation therapy after radical cystectomy for bladder cancer. Urol Oncol, 39 (11):790 e1-790.e7.
3. Venturelli S, Leischner C, Helling T, et al (2022). Minerals and Cancer: Overview of the Possible Diagnostic Value. Cancers (Basel), 14(5):1256.
4. Lacerda-Abreu MA, Dick CF, Meyer-Fernandes JR (2022). The Role of Inorganic Phosphate Transporters in Highly Proliferative Cells: From Protozoan Parasites to Cancer Cells. Membranes (Basel), 13 (1):42.
5. Brown RB, Bigelow P, Dubin JA (2023). Breast Cancer and Bone Mineral Density in a U.S. Cohort of Middle-Aged Women: Associations with Phosphate Toxicity. Cancers (Basel), 15 (20): 5093.
6. de Carvalho CC, Caramujo MJ (2012). Tumour metastasis as an adaptation of tumour cells to fulfil their phosphorus requirements. Med Hypotheses, 78 (5):664-7.
7. Castillo SP, Rebolledo RA, Arim M, et al (2023). Metastatic cells exploit their stoichiometric niche in the network of cancer ecosystems. Sci Adv, 9 (50): eadi7902.
8. Lacerda-Abreu MA, Russo-Abrahão T, Rocco-Machado N, et al (2021). Hydrogen Peroxide Generation as an Underlying Response to High Extracellular Inorganic Phosphate (Pi) in Breast Cancer Cells. Int J Mol Sci, 22(18):10096.
9. Lee JS, Leem SH, Lee SY, et al (2010). Expression signature of E2F1 and its associated genes predict superficial to invasive progression of bladder tumors. J Clin Oncol, 28 (16):2660-7.
10. Zhou Y, Zhou B, Pache L, et al (2019). Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun, 10 (1):1523.
11. Newman AM, Liu CL, Green MR, et al (2015). Robust enumeration of cell subsets from tissue expression profiles. Nat Methods, 12 (5):453-7.
12. Sullivan LM, Massaro JM, D'Agostino RB, Sr. (2004). Presentation of multivariate data for clinical use: The Framingham Study risk score functions. Stat Med, 23 (10):1631-60.
13. Calvo MS, Lamberg-Allardt CJ (2015). Phosphorus. Adv Nutr, 6 (6):860-2.
14. Papaloucas CD, Papaloucas MD, Kouloulias V, et al (2014). Measurement of blood phosphorus: a quick and inexpensive method for detection of the existence of cancer in the body. Too good to be true, or forgotten knowledge of the past? Med Hypotheses, 82 (1):24-5.
15. Donin NM, Lenis AT, Holden S, et al (2017). Immunotherapy for the Treatment of Urothelial Carcinoma. J Urol, 197 (1):14-22.
16. Wouters MCA, Nelson BH (2018). Prognostic Significance of Tumor-Infiltrating B Cells and Plasma Cells in Human Cancer. Clin Cancer Res, 24 (24):6125-6135.
17. Fridman WH, Petitprez F, Meylan M, et al (2021). B cells and cancer: To B or not to B? J Exp Med, 218(1):e20200851.
18. Wang SS, Liu W, Ly D, et al (2019). Tumor-infiltrating B cells: their role and application in anti-tumor immunity in lung cancer. Cell Mol Immunol, 16 (1):6-18.
19. Okita Y, Ohira M, Tanaka H, et al (2015). Alteration of CD4 T cell subsets in metastatic lymph nodes of human gastric cancer. Oncol Rep, 34 (2):639-47.
20. Ebert LM, Tan BS, Browning J, et al (2008). The regulatory T cell-associated transcription factor FoxP3 is expressed by tumor cells. Cancer Res, 68 (8):3001-9.
21. Olingy CE, Dinh HQ, Hedrick CC (2019). Monocyte heterogeneity and functions in cancer. J Leukoc Biol, 106 (2):309-322.
22. Ruffell B, Coussens LM (2015). Macrophages and therapeutic resistance in cancer. Cancer Cell, 27 (4):462-72.
23. Aponte-López A, Muñoz-Cruz S (2020). Mast Cells in the Tumor Microenvironment. Adv Exp Med Biol, 1273:159-173.
24. Zheng X, Xu H, Yi X, et al (2021). Tumor-antigens and immune landscapes identification for prostate adenocarcinoma mRNA vaccine. Mol Cancer, 20 (1):160.
25. Park I, Son M, Ahn E, et al (2020). The Transmembrane Adaptor Protein LIME Is Essential for Chemokine-Mediated Migration of Effector T Cells to Inflammatiory Sites. Mol Cells, 43 (11):921-934.
26. Brdickova N, Brdicka T, Angelisova P, et al (2003). LIME: a new membrane Raft-associated adaptor protein involved in CD4 and CD8 coreceptor signaling. J Exp Med, 198 (10):1453-62.
27. Hur EM, Son M, Lee OH, et al (2003). LIME, a novel transmembrane adaptor protein, associates with p56lck and mediates T cell activation. J Exp Med, 198 (10):1463-73.
28. Li SC, Kuo HC, Huang LH, et al (2021). DNA Methylation in LIME1 and SPTBN2 Genes Is Associated with Attention Deficit in Children. Children (Basel), 8 (2):92.
29. Bommhardt U, Schraven B, Simeoni L (2019). Beyond TCR Signaling: Emerging Functions of Lck in Cancer and Immunotherapy. Int J Mol Sci, 20 (14): 3500.
30. Li L, Qu W-H, Ma H-P, et al (2022). LRP8, modulated by miR-1262, promotes tumour progression and forecasts the prognosis of patients in breast cancer. Arch Physiol Biochem, 128 (3):657-665.
31. Rey JP, Ellies DL (2010). Wnt modulators in the biotech pipeline. Dev Dyn, 239 (1):102-14.
32. Garnis C, Campbell J, Davies JJ, et al (2005). Involvement of multiple developmental genes on chromosome 1p in lung tumorigenesis. Hum Mol Genet, 14 (4):475-82.
33. Lin CC, Lo MC, Moody R, et al (2018). Targeting LRP8 inhibits breast cancer stem cells in triple-negative breast cancer. Cancer Lett, 438:165-173.
34. McAndrew CW, Gastwirt RF, Donoghue DJ (2009). The atypical CDK activator Spy1 regulates the intrinsic DNA damage response and is dependent upon p53 to inhibit apoptosis. Cell Cycle, 8 (1):66-75.
35. Lu S, Liu R, Su M, Wei Y, et al (2016). Spy1 participates in the proliferation and apoptosis of epithelial ovarian cancer. J Mol Histol, 47 (1):47-57.
36. Jin Q, Liu G, Bao L, et al (2018). High Spy1 expression predicts poor prognosis in colorectal cancer. Cancer Manag Res, 10:2757-2765.
37. An W, Kang JS, Oh S, et al (2023). MST1R as a potential new target antigen of chimeric antigen receptor T cells to treat solid tumors. Korean J Physiol Pharmacol, 27 (3):241-256.
38. Khan M, Hearn K, Parry C, et al (2023). Mechanism of Antitumor Effects of Saffron in Human Prostate Cancer Cells. Nutrients, 16 (1):114.
39. Jeong BC, Oh SH, Lee MN, et al (2020). Macrophage-Stimulating Protein Enhances Osteoblastic Differentiation via the Recepteur d'Origine Nantais Receptor and Extracellular Signal-Regulated Kinase Signaling Pathway. J Bone Metab, 27 (4):267-279.
40. Zou Y, Yuan G, Tan X, et al (2022). Immune-related gene risk score predicting the effect of immunotherapy and prognosis in bladder cancer patients. Front Genet, 13:1011390.
41. Kato A, Ng S, Thangasamy A, et al (2021). A potential signaling axis between RON kinase receptor and hypoxia-inducible factor-1 alpha in pancreatic cancer. Mol Carcinog, 60 (11):734-745.
42. Milan M, Benvenuti S, Balderacchi AM, et al (2018). RON tyrosine kinase mutations in brain metastases from lung cancer. ERJ Open Res, 4(1):00083-2017.
43. Zhou D, Zhu X, Wu X, et al (2021). The effect of splicing MST1R in gastric cancer was enhanced by lncRNA FENDRR. Exp Ther Med, 22 (2):798.
| Files | ||
| Issue | Vol 53 No 9 (2024) | |
| Section | Review Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v53i9.16449 | |
| Keywords | ||
| Bladder cancer (BLCA) Phosphorus metabolism Prognosis Nomogram | ||
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How to Cite
1.
He Y, Xu A, Xiao L, Yang Y, Li B, Liu Z, Rao P, Wang Y, Ruan L, Zhang T. Phosphorus Metabolism-Related Genes Serve as Novel Biomarkers for Predicting Prognosis in Bladder Cancer: A Bioinformatics Analysis. Iran J Public Health. 2024;53(9):1935-1950.
