Login Register Cart 0
Generic placeholder image

Recent Patents on Anti-Cancer Drug Discovery

Editor-in-Chief

ISSN (Print): 1574-8928
ISSN (Online): 2212-3970

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Prognostic Value of Fatty Acid Metabolism-related Genes in Patients with Bladder Cancer

Author(s): Qiuzheng Huang, Zhijia Li and Chao Liu*

Volume 19, Issue 3, 2024

Published on: 09 June, 2023

Page: [328 - 341] Pages: 14

DOI: 10.2174/1574892818666230516143945

Price: $65

Abstract

Introduction: This study aimed to explore the expression profiles of fatty acid metabolism- related genes (FAMRGs) in patients with bladder cancer (BLCA).

Methods: The corresponding clinicopathological features of BLCA patients and RNA sequencing data were downloaded from TCGA and GSE13507. Univariate Cox regression was used to determine the prognostic value of FRGS in BLCA patients. LASSO regression analysis was then performed to select potential risk genes and eliminate genes that might overfit the model. Based on the independent prognostication-related FRGs, the nomogram survival model was established using the root mean square value of the R packet to predict the 1-year, 3-year, and 5-year survival rates of BLCA patients. By determining the area under the curve (AUC) value, the time-dependent receiver operating characteristic curve (ROC) was used to evaluate the prognostic efficiency of our model.

Results: A total of 243 DEFRGs were identified. Twenty FRGs were found to be related to the prognosis of BLCA in the TCGA database. Survival curves showed that high-risk patients had significantly shorter OS than low-risk cases (p < 0.001). The AUC of risk was 0.784, which was superior to age, sex, and stage, suggesting that the risk score was more favorable in predicting OS than traditional pathologic prognostic factors. The AUC was 0.757 at 1 year, 0.732 at 3 years, and 0.733 at 5 year-OS.

Conclusion: In this study, we demonstrated that a FAMRG prognosis biomarker is associated with the tumor immune microenvironment in patients with BLCA.

Keywords: BLCA, fatty acid metabolism-related genes, survival, immune cells, tumor, infiltration.

« Previous Next »
[1]
Sung H, Ferlay J, Siegel RL, 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(3): 209-49.
[http://dx.doi.org/10.3322/caac.21660] [PMID: 33538338]
[2]
Lenis AT, Lec PM, Chamie K, Mshs M. Bladder Cancer. JAMA 2020; 324(19): 1980-91.
[http://dx.doi.org/10.1001/jama.2020.17598] [PMID: 33201207]
[3]
Ritch CR, Velasquez MC, Kwon D, et al. Use and validation of the AUA/SUO risk grouping for nonmuscle invasive bladder cancer in a contemporary cohort. J Urol 2020; 203(3): 505-11.
[http://dx.doi.org/10.1097/JU.0000000000000593] [PMID: 31609178]
[4]
Witjes JA, Bruins HM, Cathomas R, et al. European association of urology guidelines on muscle-invasive and metastatic bladder cancer: Summary of the 2020 guidelines. Eur Urol 2021; 79(1): 82-104.
[http://dx.doi.org/10.1016/j.eururo.2020.03.055] [PMID: 32360052]
[5]
Itadani H, Mizuarai S, Kotani H. Can systems biology understand pathway activation? Gene expression signatures as surrogate markers for understanding the complexity of pathway activation. Curr Genomics 2008; 9(5): 349-60.
[http://dx.doi.org/10.2174/138920208785133235] [PMID: 19517027]
[6]
McDermott U, Downing JR, Stratton MR. Genomics and the continuum of cancer care. N Engl J Med 2011; 364(4): 340-50.
[http://dx.doi.org/10.1056/NEJMra0907178] [PMID: 21268726]
[7]
Guo CC, Czerniak B. Bladder cancer in the genomic era. Arch Pathol Lab Med 2019; 143(6): 695-704.
[http://dx.doi.org/10.5858/arpa.2018-0329-RA] [PMID: 30672335]
[8]
Hamaidi I, Zhang L, Kim N, et al. Sirt2 inhibition enhances metabolic fitness and effector functions of tumor-reactive T cells. Cell Metab 2020; 32(3): 420-436.e12.
[http://dx.doi.org/10.1016/j.cmet.2020.07.008] [PMID: 32768387]
[9]
Liu J, Peng Y, Shi L, et al. Skp2 dictates cell cycle-dependent metabolic oscillation between glycolysis and TCA cycle. Cell Res 2021; 31(1): 80-93.
[http://dx.doi.org/10.1038/s41422-020-0372-z] [PMID: 32669607]
[10]
Li T, Han J, Jia L, Hu X, Chen L, Wang Y. PKM2 coordinates glycolysis with mitochondrial fusion and oxidative phosphorylation. Protein Cell 2019; 10(8): 583-94.
[http://dx.doi.org/10.1007/s13238-019-0618-z] [PMID: 30887444]
[11]
Sun X, Zhan L, Chen Y, et al. Increased mtDNA copy number promotes cancer progression by enhancing mitochondrial oxidative phosphorylation in microsatellite-stable colorectal cancer. Signal Transduct Target Ther 2018; 3(1): 8.
[http://dx.doi.org/10.1038/s41392-018-0011-z] [PMID: 29610678]
[12]
Butler LM, Perone Y, Dehairs J, et al. Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention. Adv Drug Deliv Rev 2020; 159: 245-93.
[http://dx.doi.org/10.1016/j.addr.2020.07.013] [PMID: 32711004]
[13]
Khatua B, El-Kurdi B, Patel K, et al. Adipose saturation reduces lipotoxic systemic inflammation and explains the obesity paradox. Sci Adv 2021; 7(5): eabd6449.
[http://dx.doi.org/10.1126/sciadv.abd6449] [PMID: 33514548]
[14]
Sengupta D, Pratx G. Imaging metabolic heterogeneity in cancer. Mol Cancer 2016; 15(1): 4.
[http://dx.doi.org/10.1186/s12943-015-0481-3] [PMID: 26739333]
[15]
Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer. Br J Cancer 2020; 122(1): 4-22.
[http://dx.doi.org/10.1038/s41416-019-0650-z] [PMID: 31819192]
[16]
Hoy AJ, Nagarajan SR, Butler LM. Tumour fatty acid metabolism in the context of therapy resistance and obesity. Nat Rev Cancer 2021; 21(12): 753-66.
[http://dx.doi.org/10.1038/s41568-021-00388-4] [PMID: 34417571]
[17]
Röhrig F, Schulze A. The multifaceted roles of fatty acid synthesis in cancer. Nat Rev Cancer 2016; 16(11): 732-49.
[http://dx.doi.org/10.1038/nrc.2016.89] [PMID: 27658529]
[18]
Snaebjornsson MT, Janaki-Raman S, Schulze A. Greasing the wheels of the cancer machine: The role of lipid metabolism in cancer. Cell Metab 2020; 31(1): 62-76.
[http://dx.doi.org/10.1016/j.cmet.2019.11.010] [PMID: 31813823]
[19]
Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005; 102(43): 15545-50.
[http://dx.doi.org/10.1073/pnas.0506580102] [PMID: 16199517]
[20]
Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 2015; 12(5): 453-7.
[http://dx.doi.org/10.1038/nmeth.3337] [PMID: 25822800]
[21]
Hanahan D, Weinberg RA. Hallmarks of cancer: The next generation. Cell 2011; 144(5): 646-74.
[http://dx.doi.org/10.1016/j.cell.2011.02.013] [PMID: 21376230]
[22]
Currie E, Schulze A, Zechner R, Walther TC, Farese RV Jr. Cellular fatty acid metabolism and cancer. Cell Metab 2013; 18(2): 153-61.
[http://dx.doi.org/10.1016/j.cmet.2013.05.017] [PMID: 23791484]
[23]
Li F, Zhu W, Gonzalez FJ. Potential role of CYP1B1 in the development and treatment of metabolic diseases. Pharmacol Ther 2017; 178: 18-30.
[http://dx.doi.org/10.1016/j.pharmthera.2017.03.007] [PMID: 28322972]
[24]
Alsubait A, Aldossary W, Rashid M, Algamdi A, Alrfaei BM. CYP1B1 gene: Implications in glaucoma and cancer. J Cancer 2020; 11(16): 4652-61.
[http://dx.doi.org/10.7150/jca.42669] [PMID: 32626511]
[25]
Zhu Z, Mu Y, Qi C, et al. CYP1B1 enhances the resistance of epithelial ovarian cancer cells to paclitaxel in vivo and in vitro . Int J Mol Med 2015; 35(2): 340-8.
[http://dx.doi.org/10.3892/ijmm.2014.2041] [PMID: 25516145]
[26]
Rochat B, Morsman JM, Murray GI, Figg WD, McLeod HL. Human CYP1B1 and anticancer agent metabolism: Mechanism for tumor-specific drug inactivation? J Pharmacol Exp Ther 2001; 296(2): 537-41.
[PMID: 11160641]
[27]
Tokizane T, Shiina H, Igawa M, et al. Cytochrome P450 1B1 is overexpressed and regulated by hypomethylation in prostate cancer. Clin Cancer Res 2005; 11(16): 5793-801.
[http://dx.doi.org/10.1158/1078-0432.CCR-04-2545] [PMID: 16115918]
[28]
Vaclavikova R, Hubackova M, Stribrna-Sarmanova J, et al. RNA expression of cytochrome P450 in breast cancer patients. Anticancer Res 2007; 27(6C): 4443-50.
[PMID: 18214058]
[29]
Al-saraireh YM, Alshammari FOFO, Youssef AMM, et al. Profiling of CYP4Z1 and CYP1B1 expression in bladder cancers. Sci Rep 2021; 11(1): 5581.
[http://dx.doi.org/10.1038/s41598-021-85188-4] [PMID: 33692504]
[30]
Cutler NS, Graves-Deal R, LaFleur BJ, et al. Stromal production of prostacyclin confers an antiapoptotic effect to colonic epithelial cells. Cancer Res 2003; 63(8): 1748-51.
[PMID: 12702555]
[31]
Lichao S, Liang P, Chunguang G, Fang L, Zhihua Y, Yuliang R. Overexpression of PTGIS could predict liver metastasis and is correlated with poor prognosis in colon cancer patients. Pathol Oncol Res 2012; 18(3): 563-9.
[http://dx.doi.org/10.1007/s12253-011-9478-4] [PMID: 22109564]

Rights & Permissions Print Cite
Article Metrics
13
2
© 2024 Bentham Science Publishers | Privacy Policy