AccScience Publishing / CP / Online First / DOI: 10.36922/cp.4987
ORIGINAL RESEARCH ARTICLE

Association of Mitochondrial ribosomal protein S33 expression with poor prognosis in glioma

Zhongmin Li1 Xinxing Wang1 Qiang Li1 Xiangyang Wang1 Xinmin Ding1*
Show Less
1 Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
Received: 29 September 2024 | Revised: 1 April 2025 | Accepted: 7 April 2025 | Published online: 28 May 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

Despite advancements in diagnostic and therapeutic strategies, early detection and improved prognosis of gliomas remain challenging. A deeper understanding of glioma pathogenesis and the identification of reliable biomarkers are crucial for early diagnosis and the reduction of healthcare costs. Mitochondrial ribosomal protein S33 (MRPS33), a key component of mitochondrial protein synthesis, has not been well-characterized in terms of its expression profile, prognostic significance, and immunological relevance in glioma. This study aims to elucidate these aspects through bioinformatics analyses utilizing data from The Cancer Genome Atlas, Genotype-Tissue Expression Project, and Tumor Immune Estimation Resource databases through the Sangerbox platform. Our results indicate a pronounced upregulation of MRPS33 in glioma tissues, which is significantly associated with poor prognosis, heightened immune cell infiltration, and differential drug sensitivities. Furthermore, functional enrichment analyses suggest that MRPS33 is intricately involved in several key biological processes, thereby underscoring its potential role in glioma pathophysiology. In conclusion, our findings support the potential of MRPS33 as a prognostic biomarker and therapeutic target in glioma, providing insights that may advance our understanding of disease mechanisms and inform future clinical strategies.

Keywords
MRPS33
Glioma
Prognosis
Immune cell infiltration
Funding
This study was supported by the Clinical Key Specialty Program of Shanxi Bethune Hospital and grants from the Shanxi Provincial Basic Research Program (201901D1478).
Conflict of interest
The authors declare that they have no competing interests.
References
  1. Lin MD, Tsai AC, Abdullah KG, McBrayer SK, Shi DD. Treatment of IDH-mutant glioma in the INDIGO era. NPJ Precis Oncol. 2024;8(1):149. doi: 10.1038/s41698-024-00646-2

 

  1. Yin J, Liu G, Zhang Y, et al. Gender differences in gliomas: From epidemiological trends to changes at the hormonal and molecular levels. Cancer Lett. 2024;598:217114. doi: 10.1016/j.canlet.2024.217114

 

  1. Wei Y, Xu Y, Sun Q, et al. Targeting ferroptosis opens new avenues in gliomas. Int J Biol Sci. 2024;20(12):4674-4690. doi: 10.7150/ijbs.96476

 

  1. Agnihotri TG, Salave S, Shinde T, et al. Understanding the role of endothelial cells in brain tumor formation and metastasis: A proposition to be explored for better therapy. J Natl Cancer Cent. 2023;3(3):222-235. doi: 10.1016/j.jncc.2023.08.001

 

  1. Nicholson JG, Fine HA. Diffuse glioma heterogeneity and its therapeutic implications. Cancer Discov. 2021;11(3):575-590. doi: 10.1158/2159-8290.CD-20-1474

 

  1. Dai F, Yuan Y, Hao J, et al. PDCD2 as a prognostic biomarker in glioma correlates with malignant phenotype. Genes Dis. 2024;11(5):101106. doi: 10.1016/j.gendis.2023.101106

 

  1. Kros JM, Mustafa DM, Dekker LJ, Sillevis Smitt PA, Luider TM, Zheng PP. Circulating glioma biomarkers. Neuro Oncol. 2015;17(3):343-360. doi: 10.1093/neuonc/nou207

 

  1. Lukas RV, Wainwright DA, Horbinski CM, Iwamoto FM, Sonabend AM. Immunotherapy against gliomas: Is the breakthrough near. Drugs. 2019;79(17):1839-1848. doi: 10.1007/s40265-019-01203-z

 

  1. Bacon JM, Jones JL, Liu GS, Dickinson JL, Raspin K. Mitochondrial ribosomal proteins in metastasis and their potential use as prognostic and therapeutic targets. Cancer Metastasis Rev. 2024;43(4):1119-1135. doi: 10.1007/s10555-024-10216-4

 

  1. Bao S, Wang X, Li M, et al. Potential of mitochondrial ribosomal genes as cancer biomarkers demonstrated by bioinformatics results. Front Oncol. 2022;12:835549. doi: 10.3389/fonc.2022.835549

 

  1. Lin X, Guo L, Lin X, Wang Y, Zhang G. Expression and prognosis analysis of mitochondrial ribosomal protein family in breast cancer. Sci Rep. 2022;12(1):10658. doi: 10.1038/s41598-022-14724-7

 

  1. Xie C, Hu J, Hu Q, Jiang L, Chen W. Classification of the mitochondrial ribosomal protein-associated molecular subtypes and identified a serological diagnostic biomarker in hepatocellular carcinoma. Front Surg. 2022;9:1062659. doi: 10.3389/fsurg.2022.1062659

 

  1. Huang G, Li H, Zhang H. Abnormal expression of mitochondrial ribosomal proteins and their encoding genes with cell apoptosis and diseases. Int J Mol Sci. 2020;21(22):8879. doi: 10.3390/ijms21228879

 

  1. Cheong A, Lingutla R, Mager J. Expression analysis of mammalian mitochondrial ribosomal protein genes. Gene Expr Patterns. 2020;38:119147. doi: 10.1016/j.gep.2020.119147

 

  1. Cade BE, Lee J, Sofer T, et al. Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program. Genome Med. 2021;13(1):136. doi: 10.1186/s13073-021-00917-8

 

  1. Xu J, Ma J, Zeng Y, et al. Transcriptome-wide association study identifies novel genes associated with bone mineral density and lean body mass in children. Endocrine. 2023;79(2):400-409. doi: 10.1007/s12020-022-03225-2

 

  1. Revathi Paramasivam O, Gopisetty G, Subramani J, Thangarajan R. Expression and affinity purification of recombinant mammalian mitochondrial ribosomal small subunit (MRPS) proteins and protein-protein interaction analysis indicate putative role in tumourigenic cellular processes. J Biochem. 2021;169(6):675-692. doi: 10.1093/jb/mvab004

 

  1. Shen W, Song Z, Zhong X, et al. Sangerbox: A comprehensive, interaction-friendly clinical bioinformatics analysis platform. Imeta. 2022;1(3):e36. doi: 10.1002/imt2.36

 

  1. Tomczak K, Czerwińska P, Wiznerowicz M. The cancer genome atlas (TCGA): An immeasurable source of knowledge. Contemp Oncol (Pozn). 2015;19(1A):A68-A77. doi: 10.5114/wo.2014.47136

 

  1. Gillette MA, Satpathy S, Cao S, et al. Proteogenomic characterization reveals therapeutic vulnerabilities in lung adenocarcinoma. Cell. 2020;182(1):200-25.e35. doi: 10.1016/j.cell.2020.06.013

 

  1. Gao Q, Zhu H, Dong L, et al. Integrated proteogenomic characterization of HBV-related hepatocellular carcinoma. Cell. 2019;179(2):561-577.e22. doi: 10.1016/j.cell.2019.08.052

 

  1. Hänzelmann S, Castelo R, Guinney J. GSVA: Gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013;14:7. doi: 10.1186/1471-2105-14-7

 

  1. Bindea G, Mlecnik B, Tosolini M, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39(4):782-795. doi: 10.1016/j.immuni.2013.10.003

 

  1. Warde-Farley D, Donaldson SL, Comes O, et al. The GeneMANIA prediction server: Biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38:W214-W220. doi: 10.1093/nar/gkq537

 

  1. Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-D613. doi: 10.1093/nar/gky1131

 

  1. Bou Zerdan M, Atoui A, Hijazi A, et al. Latest updates on cellular and molecular biomarkers of gliomas. Front Oncol. 2022;12:1030366. doi: 10.3389/fonc.2022.1030366

 

  1. Guo X, Sui R, Piao H. Exosomes-mediated crosstalk between glioma and immune cells in the tumor microenvironment. CNS Neurosci Ther. 2023;29(8):2074-2085. doi: 10.1111/cns.14239

 

  1. Sankowski R, Süß P, Benkendorff A, et al. Multiomic spatial landscape of innate immune cells at human central nervous system borders. Nat Med. 2024;30(1):186-198. doi: 10.1038/s41591-023-02673-1

 

  1. Vasaikar SV, Straub P, Wang J, Zhang B. LinkedOmics: Analyzing multi-omics data within and across 32 cancer types. Nucleic Acids Res. 2018;46(D1):D956-D963. doi: 10.1093/nar/gkx1090

 

  1. Liu CJ, Hu FF, Xie GY, et al. GSCA: An integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels. Brief Bioinform. 2023;24(1):bbac558. doi: 10.1093/bib/bbac558

 

  1. Yang W, Soares J, Greninger P, et al. Genomics of drug sensitivity in cancer (GDSC): A resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 2013;41:D955-D961. doi: 10.1093/nar/gks1111

 

  1. Basu A, Bodycombe NE, Cheah JH, et al. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules. Cell. 2013;154(5):1151-1161. doi: 10.1016/j.cell.2013.08.003

 

  1. Cortés-Ciriano I, Gulhan DC, Lee JJ, Melloni G, Park PJ. Computational analysis of cancer genome sequencing data. Nat Rev Genet. 2022;23(5):298-314. doi: 10.1038/s41576-021-00431-y

 

  1. Jiang P, Sinha S, Aldape K, Hannenhalli S, Sahinalp C, Ruppin E. Big data in basic and translational cancer research. Nat Rev Cancer. 2022;22(11):625-639. doi: 10.1038/s41568-022-00502-0

 

  1. Yang L, Wang J, Altreuter J, et al. Tutorial: Integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA. Nat Protoc. 2023;18(8):2404-2414. doi: 10.1038/s41596-023-00841-8

 

  1. Xu S, Tang L, Li X, Fan F, Liu Z. Immunotherapy for glioma: Current management and future application. Cancer Lett. 2020;476:1-12. doi: 10.1016/j.canlet.2020.02.002

 

  1. Liu H, Zhao Q, Tan L, et al. Neutralizing IL-8 potentiates immune checkpoint blockade efficacy for glioma. Cancer Cell. 2023;41(4):693-710.e8. doi: 10.1016/j.ccell.2023.03.004

 

  1. Thomas BC, Staudt DE, Douglas AM, Monje M, Vitanza NA, Dun MD. CAR T cell therapies for diffuse midline glioma. Trends Cancer. 2023;9(10):791-804. doi: 10.1016/j.trecan.2023.07.007

 

  1. Fan X, Li J, Huang B, et al. Noninvasive radiomics model reveals macrophage infiltration in glioma. Cancer Lett. 2023;573:216380. doi: 10.1016/j.canlet.2023.216380

 

  1. Wei J, Marisetty A, Schrand B, et al. Osteopontin mediates glioblastoma-associated macrophage infiltration and is a potential therapeutic target. J Clin Invest. 2019;129(1):137-149. doi: 10.1172/JCI121266

 

  1. Wei C, Wang B, Peng D, et al. Pan-cancer analysis shows that ALKBH5 is a potential prognostic and immunotherapeutic biomarker for multiple cancer types including gliomas. Front Immunol. 2022;13:849592. doi: 10.3389/fimmu.2022.849592

 

  1. Liu L, Zhang X, Ding H, et al. Arginine and lysine methylation of MRPS23 promotes breast cancer metastasis through regulating OXPHOS. Oncogene. 2021;40(20):3548-3563. doi: 10.1038/s41388-021-01785-7

 

  1. Oviya RP, Thangaretnam KP, Ramachandran B, et al. Mitochondrial ribosomal small subunit (MRPS) MRPS23 protein-protein interaction reveals phosphorylation by CDK11-p58 affecting cell proliferation and knockdown of MRPS23 sensitizes breast cancer cells to CDK1 inhibitors. Mol Biol Rep. 2022;49(10):9521-9534. doi: 10.1007/s11033-022-07842-y

 

  1. Wang Q, Chen G, Liu L, et al. MRPS23 is a novel prognostic biomarker and promotes glioma progression. Aging (Albany NY). 2024;16(3):2457-2474. doi: 10.18632/aging.205493

 

  1. Weller M, Wen PY, Chang SM, et al. Glioma. Nat Rev Dis Primers. 2024;10(1):33. doi: 10.1038/s41572-024-00516-y

 

Share
Back to top
Cancer Plus, Electronic ISSN: 2661-3840 Print ISSN: 2661-3832, Published by AccScience Publishing