1. Academic Validation
  2. A novel cuproptosis-related subtypes and gene signature associates with immunophenotype and predicts prognosis accurately in neuroblastoma

A novel cuproptosis-related subtypes and gene signature associates with immunophenotype and predicts prognosis accurately in neuroblastoma

  • Front Immunol. 2022 Sep 23;13:999849. doi: 10.3389/fimmu.2022.999849.
Xiao-Mao Tian 1 2 3 Bin Xiang 1 2 3 Yi-Hang Yu 1 2 3 Qi Li 1 2 3 Zhao-Xia Zhang 1 2 3 Chenghao Zhanghuang 2 3 Li-Ming Jin 1 2 3 Jin-Kui Wang 1 2 3 Tao Mi 1 2 3 Mei-Lin Chen 1 2 3 Feng Liu 1 2 3 Guang-Hui Wei 1 2 3
Affiliations

Affiliations

  • 1 Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • 2 Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.
  • 3 Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China.
Abstract

Background: Neuroblastoma (NB) is the most frequent solid tumor in pediatrics, which accounts for roughly 15% of cancer-related mortality in children. NB exhibited genetic, morphologic, and clinical heterogeneity, which limited the efficacy of available therapeutic approaches. Recently, a new term 'cuproptosis' has been used to denote a unique biological process triggered by the action of copper. In this instance, selectively inducing copper death is likely to successfully overcome the limitations of conventional Anticancer drugs. However, there is still a gap regarding the role of cuproptosis in Cancer, especially in pediatric neuroblastoma.

Methods: We characterized the specific expression of cuproptosis-related genes (CRGs) in NB samples based on publicly available mRNA expression profile data. Consensus clustering and Lasso-Cox regression analysis were applied for CRGs in three independent cohorts. ESTIMATE and Xcell algorithm was utilized to visualize TME score and immune cell subpopulations' relative abundances. Tumor Immune Dysfunction and Exclusion (TIDE) score was used to predict tumor response to immune checkpoint inhibitors. To decipher the underlying mechanism, GSVA was applied to explore enriched pathways associated with cuproptosis signature and Connectivity map (CMap) analysis for drug exploration. Finally, qPCR verified the expression levels of risk-genes in NB cell lines. In addition, PDHA1 was screened and further validated by immunofluorescence in human clinical samples and loss-of-function assays.

Results: We initially classified NB patients according to CRGs and identified two cuproptosis-related subtypes that were associated with prognosis and immunophenotype. After this, a cuproptosis-related prognostic model was constructed and validated by LASSO regression in three independent cohorts. This model can accurately predict prognosis, immune infiltration, and immunotherapy responses. These genes also showed differential expression in various characteristic groups of all three datasets and NB cell lines. Loss-of-function experiments indicated that PDHA1 silencing significantly suppressed the proliferation, migration, and invasion, in turn, promoted cell cycle arrest at the S phase and Apoptosis of NB cells.

Conclusions: Taken together, this study may shed LIGHT on new research areas for NB patients from the cuproptosis perspective.

Keywords

cuproptosis; immunotherapy; neuroblastoma; prognosis; tumor immune microenvironment.

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