Research Paper Volume 16, Issue 4 pp 3554—3582

Investigation of cuproptosis regulator-mediated modification patterns and SLC30A7 function in GBM

Wanli Yu1,2, *, , Shikai Gui1,2, *, , Jiabao Xie1,2, , Lunshan Peng1,2, , Juexian Xiao1, , Haitao Luo1, , Zhennan Tao3, , Zujue Cheng1, ,

  • 1 Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi 330006, China
  • 2 Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi 330036, China
  • 3 Department of Neurosurgery, Affiliated Drum Tower Hospital, School of Medicine, Nanjing University, Nanjing 210008, China
* Equal contribution and shared first authorship

Received: September 15, 2023       Accepted: January 8, 2024       Published: February 22, 2024      

https://doi.org/10.18632/aging.205545
How to Cite

Copyright: © 2024 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Copper-dependent controlled cell death (cuproptosis) is a novel cell death modality that is distinct from known cell death mechanisms. Nonetheless, the potential role of the cuproptosis regulator in tumour microenvironment (TME) of GBM remains unknown.

Methods: Based on 13 widely recognised cuproptosis regulators, the cuproptosis regulation patterns and the biological characteristics of each pattern were comprehensively assessed in GBMs. Machine learning strategies were used to construct a CupScore to quantify the cuproptosis regulation patterns of individual tumours. A PPI network was constructed to predict core-associated genes of cuproptosis regulators. The function of the novel cuproptosis regulators SLC30A7 was examined by in vitro and in vivo experiment.

Results: We identified three distinct cuproptosis regulation patterns, including immune activation, metabolic activation, and immunometabolic double deletion patterns. The CupScore was shown to predict the abundance of tumour inflammation, molecular subtype, stromal activity, gene variation, signalling pathways, and patient prognosis. The low CupScore subtype was characterised by immune activation, isocitrate dehydrogenase mutations, sensitivity to chemotherapy, and clinical benefits. The high CupScore subtype was characterised by activation of the stroma and metabolism and poor survival. Novel cuproptosis regulator SLC30A7 knockdown inhibited the cuproptosi via JAK2/STAT3/ATP7A pathway in GBM.

Conclusion: Cuproptosis regulators have been shown to play a vital role in TME complexity. Constructing CupScores were trained to evaluate the regulation patterns of cuproptosis in individual tumours. The novel cuproptosis-related genes SLC30A7 was involved in regulation the tumorigenicity of GBM cell via JAK2/STAT3/ATP7A pathway in vitro and in vivo.

Abbreviations

CGGA: Chinese Glioma Genome Atlas; CupScore: cuproptosis score; DEG: differentially expressed gene; EMT: epithelial-mesenchymal transition; GDC: Genomic Data Commons; GEO: Gene Expression Omnibus; CM: copper metabolism; LME: lipoylation modified enzyme; LMS: lipoylation modified substrates; TACe: tricarboxylic acid cycle enzymes; GO: gene ontology; GSVA: gene set variation analysis; IDH: isocitrate dehydrogenase; KEGG: Kyoto Encyclopedia of genes and genomes; PCA: principal component analysis; PDH: pyruvate dehydrogenase; PPI: protein-protein interaction; ROC: receiver operating characteristic; ssGSEA: single-sample gene set enrichment analysis; TCA: tricarboxylic acid cycle; TCGA: The Cancer Genome Atlas; TPM: transcripts per kilobase million; TME: tumour microenvironment; TMZ: temozolomide.