Prognostic signature detects homologous recombination deficient in glioblastoma

Abstract

Background: Glioblastoma (GBM) is a frequent malignant tumor in neurosurgery characterized by a high degree of heterogeneity and genetic instability. DNA double-strand breaks generated by homologous recombination deficiency (HRD) are a well-known contributor to genomic instability, which can encourage tumor development. It is unknown, however, whether the molecular characteristics linked with HRD have a predictive role in GBM. The study aims to assess the extent of genomic instability in GBM using HRD score and investigate the prognostic significance of HRD-related molecular features in GBM.

Methods: The discovery cohort comprised 567 GBM patients from The Cancer Genome Atlas (TCGA) database. We established HRD scores using the single nucleotide polymorphism (SNP) array data and analyzed transcriptomic data from patients with different HRD scores to identify biomarkers associated with HRD. A prognostic model was built by using HRD-related differentially expressed genes (DEGs) and validated in a distinct cohort from the Chinese Glioma Genome Atlas (CGGA) database.

Results: Based on the SNP array data, the gene expression profile data, and the clinical characteristics of GBM patients, we found that patients with a high HRD score had a better prognosis than those with a low HRD score. The DNA damage repair (DDR) signaling pathways were notably enriched in the HRD-positive subgroup. The prognostic model was developed by including HRD-related DEGs that could evaluate the clinical prognosis of patients more efficiently than the HRD score. In addition, patients with a low-risk score had a considerably augmented signature of γδT cells. Finally, through univariate and multivariate Cox regression analyses, it was demonstrated that the prognostic model was superior to other prognostic markers.

Conclusions: In conclusion, our research has not only demonstrated that a high HRD score is a valid prognostic biomarker in GBM patients but also built a stable prognosis model [odds ratio (OR) 0.18, 95% confidence interval (CI): 0.11-0.23, P<0.001] that is more accurate than conventional prognostic markers such as O6-methylguanine-DNA methyltransferase (MGMT) methylation (OR 0.55, 95% CI: 0.33-0.91, P=0.02).

Keywords: Glioblastoma (GBM); homologous recombination deficient (HRD); prognostic factor; risk scoring model.

Figure 1

Clinical significance of HRD in the TCGA-GBM cohort. (A) Left, Kaplan-Meier survival analysis revealed differences in OS between HRD and HRP patients in the TCGA discovery cohort. Right, 1-, 3-, and 5-year OS curves for patients in the TCGA discovery cohort. (B) Summary of the most prevalent genomic alterations in 567 GBMs. The mutational matrix shows Missense_Mutations (green), Nonsense_Mutations (red), Frame_shift_Deletions (blue), Splice_site mutations (orange), Frame_shift_Insertions (purple), In_Frame_Dels (yellow), In_Frame_Ins (brownness), Translation_Strat_Site mutations (light brown), Nonstop_Mutations (light blue). (C) Histogram of gene mutation frequency in the two subgroups (Wilcoxon signed-rank test, *, P<0.05; ***, P<0.001). (D) Violin plot of fraction genome altered in the HRD group and the HRP group (Wilcoxon signed-rank test, ****, P<0.0001). (E) Violin plot of MSI in the HRD group and the HRP group (Wilcoxon signed-rank test, **, P<0.01). HRD, homologous recombination deficiency; HRP, homologous recombination proficient; AUC, area under the curve; HR, hazard ratio; CI, confidence interval; FGA, fraction of genome altered; MSI, microsatellite instability; TCGA-GBM, The Cancer Genome Atlas-Glioblastoma; OS, overall survival.

Figure 2

Analyze the properties of the transcriptome and develop a genetic prognostic model. (A) DEGs between HRD and HRP subtypes, the red triangles represent differentially up-regulated genes and the green triangles represent differentially down-regulated genes. (B) The trajectory of each independent variable: the horizontal axis represents the log value of the independent variable lambda, and the vertical axis represents the coefficient of the independent variable. (C) The confidence interval under each lambda. (D) Kaplan-Meier survival analysis revealed differences in prognosis among the two subgroups. (E) In the TCGA discovery cohort, the risk scores of the cases were arranged in order from low to high, the existential state of the cases and the expression heat maps of the 14 genes. HR, hazard ratio; CI, confidence interval; DEGs, differentially expressed genes; HRD, homologous recombination deficiency; HRP, homologous recombination proficient; TCGA, The Cancer Genome Atlas.

Figure 3

The prognostic categorization of glioblastoma patients based on the prognostic model. (A) The violin diagram of the two subgroups’ HRD scores. (B) GSEA analysis of the most enriched pathways in the subgroup with the low-risk score relative to the subgroup with the high-risk score. (C) Immune cell infiltration signal enrichment violin diagram for the two TCGA subgroups in the tumor microenvironment (Wilcoxon signed-rank test, · and - P>0.05; *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001). (D) The heat map of the TCGA cohort’s immunity infiltrates cell signal enrichment. KEGG, Kyoto Encyclopedia of Genes and Genomes; NK, natural killer; HRD, homologous recombination deficiency; GSEA, gene set enrichment analysis; TCGA, The Cancer Genome Atlas.

Figure 4

The prognostic model was validated in the CGGA cohort. (A) A Kaplan-Meier survival analysis for the two groups. (B) GSEA analysis of the major enriched pathways of the low-risk subgroup in the CGGA cohort compared to the high-risk subgroup. (C) Immunity cell infiltration signal enrichment violin diagram for the two CGGA subgroups in the tumor microenvironment (Wilcoxon signed-rank test, · and - P>0.05; *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001). HR, hazard ratio; CI, confidence interval; KEGG, Kyoto Encyclopedia of Genes and Genomes; NK, natural killer; CGGA, Chinese Glioma Genome Atlas; GSEA, gene set enrichment analysis.

Figure 5

HRD can serve as a biomarker for PARP inhibitors in GBM. (A) Forest plot of clinical variables and the prognostic of GBM. (B) Loss of fitness score histograms of the two groups when PARP1 or PARP2 was eliminated. (C) Histograms of IC₅₀ values for olaparib and niraparib in the two groups. OR, odds ratio; CI, confidence interval; IDH, isocitrate dehydrogenase; Rx, primary or recurrent tumor; MGMT, O6-methylguanine-DNA methyltransferase; IC₅₀, half maximal inhibitory concentration; HRD, homologous recombination deficiency; GBM, glioblastoma.