Construction of a disulfidptosis-related lncRNAs signature of the subtype, prognostic, and immunotherapy in neuroblastoma.

Abstract

Background: Disulfidptosis is an emerging form of regulated cell death distinguished by abnormal disulfide stress and the collapse of the actin network. This study was to construct a prognostic model based on disulfidptosis-related lncRNAs (DRLs) to enhance survival prediction and assess their viability as biomarkers for immunotherapy response in neuroblastoma (NB).

Methods: Transcriptomic and clinical data from NB patients were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. DRLs linked to overall survival (OS) were identified using Pearson correlation and univariate Cox regression analyses. Molecular subtypes of NB were determined through consensus clustering. Immune cell infiltration was assessed with multiple algorithms. A prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression. Tumor mutational burden (TMB) analysis on somatic mutations from the TARGET database explored the TMB and risk score relationship. Patient responses to immunotherapy and anti-tumor drugs were predicted using tumor immune dysfunction and exclusion (TIDE), Tumor Inflammation Signature (TIS), Genomics of Drug Sensitivity in Cancer (GDSC) database, and CellMiner tools.

Results: We identified 151 DRLs associated with OS and defined three distinct DRLs subtypes. Using eight of these, we created a prognostic model. This model was proven independently significant and divided NB patients into high and low-risk groups. The high-risk group showed poorer OS, reduced immune cell presence and infiltration, and weaker response to immunotherapy. Conversely, the low-risk group demonstrated potential immunotherapy effectiveness and increased sensitivity to anti-tumor drugs.

Conclusions: We established a prognostic model based on DRLs to predict the prognosis of NB patients, assess the immune cell infiltration, analyze TMB, evaluate the effectiveness of immunotherapy, and gauge sensitivity to anti-tumor drug treatments.