Novel endoplasmic reticulum stress-related gene signature unveils CDKN3 as a prognosticator in neuroblastoma

Abstract

Background: Neuroblastoma (NB) is the most common extracranial solid tumor in children and a major cause of pediatric cancer mortality. This study aims to develop an endoplasmic reticulum (ER) stress-based risk model to evaluate patient prognosis, identify novel therapeutic targets, and predict immunotherapy responses.

Methods: NB cases with transcriptome and clinical data were obtained from Gene Expression Omnibus (GEO) and ArrayExpress databases. ER stress-related genes were extracted from GeneCards. Differentially expressed genes (DEGs) were identified to construct an ER stress-related gene signature for prognosis prediction. The predictive ability was assessed using survival analysis, receiver operating characteristic (ROC) curves, and statistical tools. The relationship between the ER stress risk score and clinicopathological features, immune infiltration, and drug sensitivity was evaluated. A predictive nomogram was developed for prognostic accuracy. Immunohistochemistry (IHC) validated the hub gene using NB clinical specimens.

Results: A five-gene signature (PINK1, IL7, CDKN3, C1S, MMP9) was established, effectively stratifying patients into high- and low-risk groups with significant differences in overall survival. The model demonstrated robust predictive performance in training and testing datasets. High-risk NB patients exhibited poorer clinicopathological characteristics and a higher likelihood of being unresponsive to immunotherapy. Specific targeted agents were identified for high-risk patients. A nomogram integrating the gene signature and clinical variables enhanced prognostic accuracy. IHC analysis of CDKN3 supported its role as a biomarker for poor prognosis in NB.

Conclusions: This five-gene model linked to ER stress can independently forecast NB prognosis and correlates with immune and antitumor agent susceptibility, providing a basis for personalized treatment strategies.

Keywords: CDKN3; Neuroblastoma (NB); endoplasmic reticulum stress (ER stress); risk score model.

Figure 1

Identification and clustering of ER stress-related DEGs in neuroblastoma. (A) Volcano plot displaying the distribution of ER stress-related DEGs between MYCN amplified and non-amplified NB patients. Red dots represent upregulated genes, and green dots represent downregulated genes. (B) Heatmap showing the clustering of ER stress-related DEGs in MYCN amplified and non-amplified NB patients. Each column represents a patient sample, and each row represents a gene. (C) Forest plot from univariate Cox regression analysis indicating the HR of the 19 identified ER stress-related DEGs. (D) LASSO regression analysis to select the hub ER stress-related DEGs. (E) Cross-validation plot for tuning parameter selection in the LASSO model. CI, confidence interval; DEGs, differentially expressed genes; ER, endoplasmic reticulum; FC, fold change; HR, hazard ratio; LASSO, least absolute shrinkage and selection operator; NB, neuroblastoma.

Figure 2

Development and validation of the ER stress-related five-gene risk signature. (A) Heatmap of the expression levels of the five genes (PINK1, IL7, CDKN3, C1S, MMP9) in high- and low-risk groups, along with the corresponding risk score distribution and survival status. (B) K-M survival curves comparing overall survival between high- and low-risk groups in the training set. (C) ROC curves showing the predictive accuracy of the five-gene risk signature for 1-, 3-, and 5-year OS in the training set. K-M, Kaplan-Meier; OS, overall survival; ROC, receiver operating characteristic.

Figure 3

Correlation between risk scores and clinicopathological features. (A) Boxplot showing the distribution of risk scores across different age groups. (B) Boxplot displaying risk scores according to INSS stages. (C) Boxplot indicating the relationship between risk scores and tumor progression. (D) Risk score distribution in relation to high risk status. (E) Boxplot correlating risk scores with histology types. (F) Distribution of risk scores across different genders. (G) Boxplot showing the correlation between risk scores and MYCN status. (H) Boxplot comparing risk scores between death from disease. INSS, International Neuroblastoma Staging System; FH, favorable histology; UFH, unfavorable histology.

Figure 4

Subgroup survival analysis based on the five-gene risk signature. (A) K-M survival curves for patients age <18 months comparing high- and low-risk groups. (B) K-M survival curves for patients age ≥18 months comparing high- and low-risk groups. (C) K-M survival curves for patients with INSS stage 1, 2, 3 and 4S comparing high- and low-risk groups. (D) K-M survival curves for patients with INSS stage 4 comparing high- and low-risk groups. (E) K-M Survival curves for clinically considered high-risk NB patients comparing high- and low-risk groups. (F) K-M survival curves for patients experiencing tumor progression comparing high- and low-risk groups. INSS, International Neuroblastoma Staging System; K-M, Kaplan-Meier; NB, neuroblastoma.

Figure 5

Immune infiltration and drug sensitivity analysis based on ER risk groups. (A) Scatterplot comparing the infiltration levels of immunocyte between high- and low-risk groups. (B) Boxplot showing the ESTIMATE algorithm results for stromal and immune cell infiltration in the tumor microenvironment of high- and low-risk groups. (C) Boxplot indicating the expression levels of crucial immune checkpoints in high- and low-risk groups. *, P<0.05; **, P<0.01; ***, P<0.001. (D) Boxplot comparing the predicted IC₅₀ values for various anticancer drugs between high-risk and low-risk groups. ER, endoplasmic reticulum; ESTIMATE, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data; IC₅₀, half maximal inhibitory concentration.

Figure 6

Independent prognostic analysis and nomogram construction. (A) Forest plot from univariate Cox regression analysis showing the prognostic significance of the five-gene risk score and other clinical variables. (B) Multivariate Cox regression analysis indicating the independent prognostic value of the five-gene risk score. (C) Nomogram integrating the five-gene risk score and clinical variables to predict overall survival for neuroblastoma patients. (D) ROC curves evaluating the predictive accuracy of the nomogram for overall survival. (E) Calibration curves demonstrating the agreement between predicted and observed survival outcomes using the nomogram. (F) DCA illustrating the clinical benefit of the nomogram. DCA, decision curve analysis; ROC, receiver operating characteristic.

Figure 7

Immunohistochemical validation of CDKN3 expression in neuroblastoma tissues. (A) Representative IHC images showing CDKN3 expression in neuroblastoma tissues. (B) K-M survival curves comparing DFS between patients with high and low CDKN3 expression. (C) K-M survival curves comparing OS between patients with high and low CDKN3 expression. (D) Boxplot showing the correlation between CDKN3 expression and MYCN amplification status. (E) Boxplot indicating the relationship between CDKN3 expression and INSS stages. (F) Boxplot displaying the association between CDKN3 expression and metastasis at diagnosis. (G) Boxplot showing the correlation between CDKN3 expression and NSE levels. IHC, immunohistochemistry; K-M, Kaplan-Meier; DFS, disease-free survival; OS, overall survival; INSS, International Neuroblastoma Staging System; NSE, Neuron-Specific Enolase.

Figure 8

Down-regulation of CDKN3 inhibit the cell proliferation of NB cells. (A,B) RT-qPCR analysis of CDKN3 knockdown efficiency in SK-N-SH and SK-N-BE2 cells. (C,D) Images of siCDKN3 and control group cells at 0 and 48 h were collected by using the Cellaview System (AF-100), 10× objective lens . (E,F) Cell confluence curves of NB cells transfected with siCDKN3 and control from 0 to 48 h. ns, no significant; *, P<0.05; ***, P<0.001; ****, P<0.0001. NB, neuroblastoma; RT-qPCR, reverse transcription quantitative polymerase chain reaction.