Cell death pathway regulation by fatty acid metabolism-related genes in neuroblastoma: a multi-omics analysis identifying CHD5 as a novel biomarker - Yankun Chen; Junzhi Liu; Yubin Jia; Jiaxing Yang; Yan Jin; Yun Liu; Benfu Zhong; Qiang Zhao (Discover Oncology)
Abstract Background Neuroblastoma in children is commonly found as an extracranial solid tumor with poor prognosis in high-risk cases impeding successful treatment. While dysregulated cell death mechanisms and metabolic reprogramming are hallmarks of cancer progression, the interplay between fatty acid metabolism and cell death pathway regulation in neuroblastoma remains incompletely understood. Methods Identifying molecular subtypes influenced by fatty acid metabolism were built by consensus clustering analysis. Independent prognostic genes were identified through random survival forest analysis, acquiring a novel risk signature. Risk signatures were validated internally and externally, and their independent prognostic value, immune landscape, and drug susceptibility were explored. The study systematically analyzed correlations between signature genes and seven major cell death pathways (apoptosis, pyroptosis, ferroptosis, autophagy, necroptosis, cuproptosis, and disulfidptosis), encompassing over 1,200 genes to comprehensively explore the intricate relationships between these molecular signatures and diverse cell death mechanisms. Gene Set Enrichment Analysis (GSEA) was performed to assess pathway-level associations. Utilizing a single-cell dataset of neuroblastoma samples, cells were categorized and labeled based on UMAP analysis. Feature map visualization was employed to display the expression level and allocation of specific genes across various cell populations. Validation of CHD5 expression in NB cells and tissues was confirmed through Western blotting and immunohistochemical staining. Results The study identified 42 fatty acid metabolism key enzyme genes whose expression was significantly different within high-risk and non-high-risk neuroblastoma patients, by which acquiring two distinct prognostic clusters associated with fatty acid metabolism. A machine learning approach was used to select 4 hub genes (CHD5, TP63, XKR4, and CTAG1A) for the establishment of a fatty acid metabolism prognostic risk model. Cell death pathway analysis revealed that TP63 exhibited the strongest correlations across multiple death pathways, particularly with necroptosis (r = 0.684, p = 2.80e-23) and pyroptosis (r = 0.647, p = 3.12e-20), while XKR4 showed moderate correlations with autophagy (r = 0.398, p = 2.09e-07) and CHD5 displayed selective associations. High risk score and low risk score groups displayed notable variations in the immune microenvironment, characterized by reduced immune cell infiltration in the high group leading to immune escape, and conversely, heightened responsiveness of the low group to immune checkpoint blockade therapy. Single-cell dataset analysis highlighted significant expression of CHD5 in specific cell populations, suggesting its potential as a marker gene for neuroblastoma. Immunohistochemical staining revealed varying levels of CHD5 expression across different clinical stages of neuroblastoma, with decreased deposition observed as staging advances. Functionally, CHD5 expression was found to inhibit proliferation, migration, and invasion of neuroblastoma cells. Conclusion The developed fatty acid metabolism prognostic risk model underscores the significance of fatty acids in neuroblastoma prognosis and immune landscape, thereby facilitating the optimization of chemotherapy and immunotherapy strategies for this disease. The comprehensive analysis of cell death pathways revealed distinct regulatory mechanisms of signature genes, particularly highlighting TP63's central role in coordinating multiple cell death processes. CHD5, as an identified gene inhibiting the proliferation, invasion and metastasis of neuroblastoma cells, serves as a novel tumor biomarker.