Response to Antiangiogenic Therapy Is Associated with AIMP Protein Family Expression in Glioblastoma and Lower-Grade Gliomas

Abstract

Glioblastoma (GBM) is a highly vascularized, heterogeneous tumor, yet antiangiogenic therapies have yielded limited survival benefits. The lack of validated predictive biomarkers for treatment response stratification remains a major challenge. Aminoacyl tRNA synthetase complex-interacting multicomplex proteins (AIMP) 1/2/3 have been implicated in central nervous system diseases, but their roles in gliomas remain unexplored. We investigated their association with angiogenesis and their significance as predictive biomarkers for antiangiogenic treatment response. In this multi-cohort retrospective study, we analyzed glioma samples from The Cancer Genome Atlas, Chinese Glioma Genome Atlas, REMBRANDT, Gravendeel, BELOB, and REGOMA trials, and four single-cell transcriptomic datasets. Multiomic analyses incorporated transcriptomic, epigenetic, and proteomic data. Kaplan-Meier and Cox proportional hazards models were used to assess the potential prognostic value of AIMPs in heterogeneous and homogeneous treatment groups. Using single-cell transcriptomics, we explored spatial and cell type-specific AIMP2 expression in GBM. AIMP1/2/3 expressions correlated significantly with angiogenesis across The Cancer Genome Atlas cancers. In gliomas, AIMPs were upregulated in tumor versus normal tissues, higher- versus lower-grade gliomas, and recurrent versus primary tumors (P < 0.05). Upon retrospective analysis of two clinical trials assessing different antiangiogenic drugs, we found that high-AIMP2 subgroups had improved response to therapies in GBM [REGOMA: HR, 4.75 (1.96-11.5), P < 0.001; BELOB: HR, 2.3 (1.17-4.49), P = 0.015]. AIMP2-cg04317940methylation emerged as a clinically applicable stratification marker. Single-cell analysis revealed homogeneous AIMP2 expression in tumor tissues, particularly in astrocyte-like cells, suggesting a mechanistic link to tumor angiogenesis. These findings provide novel insights into the role of AIMPs in angiogenesis, offering improved patient stratification and therapeutic outcomes in recurrent GBM.

Significance: This study identifies AIMP2 as a novel biomarker predictive of antiangiogenic treatment response in recurrent GBM. Through multiomic and single-cell analyses, AIMP2 is shown to be upregulated in aggressive gliomas and linked to angiogenesis. Its expression and methylation status offer a clinically applicable stratification tool, enabling more personalized therapeutic approaches and improved outcomes in patients receiving antiangiogenic therapies.

Figure 1.

AIMP1/2/3 correlates with angiogenesis pathway gene sets. Correlation between AIMP1/2/3 mRNA expression in 33 TCGA cancers and (A) 141 Panther pathway “angiogenesis gene set” and (B) 76 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway “VEGF Signaling pathway” gene set. The color map represents Pearson correlation coefficient R values. *asterisk represents statistically significant correlation (P < 0.05). ns represents statistically insignificant cases. ACC, Adenocortical Carcinoma; BLCA, Bladder Urothelial Carcinoma; BRCA, Breast Invasive Carcinoma; CESC, Cervical Squamous Cell Carcionoma; CHOL, Cholangiocarcinoma; COAD, Colon Adenocarcinoma; DLBC, Lymphoid Neoplasm Diffuse Large B Cell Lymphoma; ESCA, Esophageal Carcinoma; GBM, Glioblastoma Multiforme; HNSC, Head and Neck Squamous Cell Carcinoma; KICH, Kidney Chromophobe; KIRP, Kidney Renal Papillary Cell Carcinoma; LAML, Acute Myeloid Leukemia; LGG, Lower-grade Glioma; LIHC, Liver Hepatocellular Carcinoma; LUAD, Lung Adenocarcinoma; LUSC, Lung Squamous Cell Carcinoma; MESO, Mesothelioma; OV, Ovarian Serous Cystadenocarcinoma; PAAD, Pancreatic Adenocarcinoma; PCPG, Pheochromocytoma and Paraganglioma; PRAD, Prostate Adenocarcinoma; READ, Rectum Adenocarcinoma; SARC, Sarcoma; SKCM, Skin Cutaneous Melanoma; STAD, Stomach Adenocarcinoma; TGCT, Testicular Germ Cell Tumors; THCA, Thyroid Carcinoma; THYM, Thymoma; UCEC, Uterine Corpus Endometrial Carcinoma; UCS, Uterine Carcinosarcoma; UVM, Uveal Melanoma.

Figure 2.

AIMP1, AIMP2, and AIMP3 are differentially expressed in glioma tissues. AIMP1/2/3 (A) mRNA (red bars: tumor samples; gray bars: normal samples) and (B and C) protein expression in TCGA-GBM, TCGA-LGG, and normal brain (GTEx) tissues. Data for (B) and (C) were collected from the Human Protein Atlas. A Student t test was used *, P < 0.05.

Figure 3.

AIMPs are associated with tumor aggressiveness, recurrence, and prognosis. AIMP mRNA expression levels in (Ai) low-grade (II; n = 103) and high-grade (III and IV; n = 218) gliomas (P values 0.011, < 0.001, and 0.014 for AIMP1, AIMP2, and AIMP3, respectively), and (Aii) primary (n = 229) and recurrent gliomas (n = 62) in CGGA dataset (P values 0.058, P < 0.001, and P < 0.001 for AIMP1, AIMP2, and AIMP3, respectively). A Mann–Whitney test P value < 0.05 was considered statistically significant. B, Kaplan–Meier survival curves depicting prognostic effects of AIMP1/2/3 mRNA expressions in CGGA, TCGA, REMBRANDT, and Gravendeel cohorts of GBM. Red = high expression and green = low expression based on median cutoff; A log-rank P value < 0.05 is considered significant.

Figure 4.

High AIMP mRNA expression subgroups are more responsive to antiangiogenic therapies. Kaplan–Meier survival analysis on retrospective clinical trials of recurrent GBM (REGOMA and BELOB trials). High expression sub-groups are stratified by median mRNA expressions of AIMP1/2/3. A log-rank P value < 0.05 is considered significant.

Figure 5.

Bevacizumab treatment response is associated with specific AIMP CpG site methylation status in gliomas. A, Significant association between two CpG sites and astrocytoma (n = 22) pathologic response to bevacizumab treatment. A Student t test P value < 0.05 was considered significant. B, Forest plots depicting Cox proportional hazards model univariate (i) and multivariate (ii) analysis for the effects of AIMP1/2/3 CpG methylation status in GBM (n = 27) and astrocytoma (n = 24).

Figure 6.

Spatial and cell type–specific expression of AIMP2 in GBM tumors. A, Spatial distribution of AIMP2 expression across tumor tissues in two representative GBM slides (i: slide 334_T and ii: slide 268_T) analyzed using a spatial transcriptomic dataset. The heatmaps display homogeneous expression of AIMP2 with varying intensity from low (purple) to high (yellow), indicating the absence of localized expression hotspots. B, Violin plots representing AIMP2 expression across GBM cellular subtypes. i,AIMP2 expression in key GBM subtypes, including MES-like, AC-like, oligodendrocyte progenitor cell (OPC)–like, and neural progenitor cell (NPC)–like cells from a concatenated single-cell RNA-seq cohort (Kruskal–Wallis P = 2.32e−02). ii,AIMP2 expression across malignant GBM subtypes from a spatial transcriptomic dataset. (Kruskal–Wallis P = 1.32e−03).