Multi-Omics Mining of Necrosis by Sodium Overload(NECSO)-Related Genes in Colorectal Cancer Highlights NOL3 as a Core Oncogene: Functional Characterization via In Vitro Biological Experiments

Objective: The present research sought to pinpoint crucial prognostic genes associated with colorectal cancer (CRC), develop a robust Necrosis by Sodium Overload-related prognostic model, investigate the biological roles of NOL3 — a core gene in this context, and ultimately lay a theoretical foundation for the evaluation of CRC prognosis and the advancement of targeted therapeutic strategies. Methods: Transcriptome profiles and survival datasets related to colorectal cancer (CRC) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Data preprocessing was executed using R software, with the assistance of packages including limma, pheatmap, survival, glmnet, and clusterProfiler. The Wilcoxon test was employed to screen for differentially expressed genes, applying the thresholds of |log2 fold change (log ₂ FC)| > 0.585 and adjusted false discovery rate ( P _FDR ) < 0.05. To annotate the functions of these differential genes, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted. For prognostic analysis, the Necrosis by Overload gene set obtained from GeneCard was utilized, and circular univariate COX regression was performed with a significance level of P < 0.05. Based on TCGA data, a multivariate COX prognostic model was built through stepwise selection, and its validity was further confirmed using GEO data. SHAP (SHapley Additive exPlanations) analysis was adopted to assess the importance of each gene incorporated in the model. Time-dependent receiver operating characteristic (ROC) curves corresponding to 1-, 3-, and 5-year survival were generated to evaluate the predictive accuracy of the constructed model. To visualize the expression patterns of the genes in the model, single-cell analysis (implemented with tools such as Seurat and SingleR) and spatial transcriptome analysis (conducted using software like Seurat and ggplot2) were carried out. For the core gene NOL3, a series of supplementary analyses and experiments were performed: clinical correlation analysis (leveraging online databases), prediction of biological mechanisms (via Gene Set Enrichment Analysis, GSEA), cell function experiments (SW620 cell lines), reverse transcription-polymerase chain reaction (RT-PCR) validation, and subcellular localization detection (using immunofluorescence technology). Results: Differential analysis of TCGA CRC data identified 5511 downregulated genes and 9451 upregulated genes (all P < 0.05). KEGG enrichment analysis revealed changes in signal pathways and molecular functions of differential genes. Prognostic analysis of Necrosis by Sodium Overload-related differential genes obtained 82 prognostic genes. Results from the constructed prognostic model revealed that patients in the high-risk group exhibited significantly poorer overall survival (OS) compared to those in the low-risk group ( P < 0.05). For the risk scores derived from this model, the area under the curve (AUC) values were 0.745 for 1-year survival, 0.761 for 3-year survival, and 0.820 for 5-year survival. Additionally, multivariate COX regression analysis verified that the risk score served as an independent prognostic indicator for colorectal cancer (CRC), with statistical significance ( P < 0.05). The nomogram incorporating age and risk score had good calibration, with AUC values of 0.754 (3-year), 0.787 (5-year), and 0.848 (10-year). SHAP analysis indicated that CPT2 had the highest importance in the 25-gene model, while PGF and NOL3 had positive contributions. Single-cell and spatial transcriptome analyses visualized the expression of model genes in specific cell types and tissue regions. Clinical analysis showed that NOL3 was upregulated in CRC tissues (both mRNA and protein levels), widely distributed in normal human tissues, and served as a prognostic factor for CRC. GSEA analysis suggested that NOL3 might affect CRC cell function through pathways such as ECM. RT-PCR confirmed that NOL3 was significantly upregulated in HCT116, SW620, and RKO cells, and immunofluorescence showed its localization in the cell nucleus and cytoplasm. Through biological experiments, NOL3 was shown to regulate the proliferative capacity of the colorectal cancer cell line (SW620). Conclusion: This study successfully constructed a stable and reliable CRC prognostic model. The core gene NOL3 is upregulated in CRC, affects CRC cell function, and serves as a potential prognostic biomarker and therapeutic target for CRC.