Comparative Analysis of Transcription Factors TWIST2, GATA3, and HES5 in Glioblastoma Multiforme : Evaluating Biomarker Potential and Therapeutic Targets Using in Silico Methods

Abstract

Objective: Glioblastoma multiforme (GBM) is characterized by substantial heterogeneity and limited therapeutic options. As molecular approaches to central nervous system tumors have gained prominence, this study examined the roles of three genes, TWIST2, GATA3, and HES5, known to be involved in oncogenesis, developmental processes, and maintenance of cancer stem cell properties, which have not yet been extensively studied in GBM. This study is the first to present gene expression data for TWIST2, GATA3, and HES5 specifically within the context of GBM patient survival.

Methods: Gene expression data for TWIST2, GATA3, and HES5 were collected from GBM and normal brain tissues using datasets from The Cancer Genome Atlas via the Genomic Data Commons portal and the Genotype-Tissue Expression database. These data were rigorously analyzed using in silico methods.

Results: All three genes were significantly more expressed in GBM tissues than in normal tissues. TWIST2 and GATA3 were linked to lower survival rates in GBM patients. Interestingly, higher HES5 levels were associated with better survival rates, suggesting a complex role that needs more investigation.

Conclusion: This study shows that TWIST2, GATA3, and HES5 could help predict outcomes in GBM patients. Our multigene model offers a better understanding of GBM and points to new treatment options, bringing hope for improved therapies and patient outcomes. This research advances our knowledge of GBM and highlights the potential of molecular diagnostics in oncology.

Keywords: GATA3; Gene expression; Glioblastoma; HES5; TWIST2.

Fig. 1.

A : Comparison of TWIST2 gene expression in glioblastoma multiforme (GBM) and normal tissues. TWIST2 expression is markedly elevated in GBM tissues relative to normal counterparts. The y-axis depicts expression levels in log2 (FPKM+1), while the x-axis distinguishes between ‘normal’ and ‘GBM’ tissue categories. The blue box indicates expression levels in normal tissues, and the red box represents those in GBM tissues. Each box plot illustrates the median, interquartile range, and potential outliers, offering a comprehensive visual representation of expression distribution. B : Kaplan-Meier survival analysis for TWIST2 expression. The Kaplan-Meier curves illustrate survival probabilities over time for patients stratified by TWIST2 expression levels. The high-expression group (red line) exhibits significantly lower OS compared to the low-expression group (blue line). The steep decline in the high-expression group’s curve indicates a higher rate of adverse events, underscoring the prognostic impact of elevated TWIST2 expression on patient survival. C : Receiver operating characteristic (ROC) curve for TWIST2. The ROC curve demonstrates the trade-off between sensitivity (true positive rate) and 1-specificity (false positive rate) for various thresholds of TWIST2 expression. The area under the ROC curve (AUC) of 0.567 reflects moderate discriminative power in distinguishing between positive and negative cases, highlighting the predictive performance of TWIST2 in this model. FPKM : fragments per kilobase of transcript per million mapped reads. OS : overall survival.

Fig. 2.

A : Comparative analysis of GATA3 gene expression in glioblastoma multiforme (GBM) and normal tissues. GATA3 expression is elevated in GBM tissues compared to normal brain tissues. The figure provides a visual representation of the differential expression levels between the two tissue types. B : Kaplan-Meier survival analysis for GATA3 expression. The Kaplan-Meier curve indicates that patients with higher GATA3 expression (red line) exhibit significantly lower overall survival compared to those with lower expression (blue line), with a statistically significant p-value of 0.0019. C : Receiver operating characteristic (ROC) curve for GATA3. The ROC curve illustrates the balance between sensitivity (true positive rate) and specificity (true negative rate) for GATA3 expression. With an area under the ROC curve (AUC) of 0.536, the figure reflects modest discriminative ability for GATA3 in distinguishing between positive and negative cases. FPKM : fragments per kilobase of transcript per million mapped reads.

Fig. 3.

A : Comparative analysis of HES5 gene expression in glioblastoma multiforme (GBM) and normal tissues. HES5 expression is significantly higher in GBM tissues compared to normal brain tissues, highlighting its differential expression between the two tissue types. B : Kaplan-Meier survival analysis for HES5 expression. The Kaplan-Meier curve demonstrates that patients with higher HES5 expression (red line) had significantly greater overall survival compared to those with lower expression (blue line), with a statistically significant p-value of 0.0039. C : Receiver operating characteristic (ROC) curve for HES5. The ROC curve demonstrates the balance between sensitivity (true positive rate) and specificity (true negative rate) for HES5 expression. With an area under the ROC curve (AUC) of 0.538, the figure indicates modest discriminative ability for HES5 in distinguishing between positive and negative cases. FPKM : fragments per kilobase of transcript per million mapped reads.

Fig. 4.

The predictive accuracy of GATA3, TWIST2, and HES5 as measured by Harrell’s C-index. The black squares represent the C-index values for each gene, with horizontal lines indicating the 95% confidence intervals (CIs). The p-values are displayed to the right of the plot. The combined model of TWIST2, GATA3, and HES5 yielded a C-index of 0.6260 (95% CI, 0.5620–0.6890), with a highly significant p-value of <0.001, demonstrating superior predictive performance.