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Unveiling the Molecular Complexity of Glioblastoma: Multi-Omics Insights and Therapeutic Prospects

Glioblastoma (GBM), one of the most aggressive and lethal forms of brain cancer, continues to pose a significant challenge to the medical and scientific communities. Its complex and heterogeneous nature has confounded attempts to unravel the underlying molecular mechanisms and develop effective treatments. Traditional genomic and transcriptomic studies have provided valuable insights, but they only scratch the surface of this intricate disease.

In recent years, a powerful arsenal of multi-omics technologies has emerged as a game-changer in cancer research. The integration of proteomics, with advanced techniques such as Tandem Mass Tag (TMT) technology, phosphoproteomics, acetylomics, metabolomics, and lipidomics, is poised to revolutionize our understanding of GBM. These approaches collectively offer a comprehensive view of the disease, revealing crucial information about the molecular subtypes, oncogenic pathways, immune subtypes, and metabolic characteristics that drive GBM.

This multi-omics approach provides a holistic perspective on GBM biology. It goes beyond the static view of the genome and transcriptome to capture dynamic protein expression, post-translational modifications, metabolic shifts, and lipid alterations. By doing so, it opens the door to the discovery of novel therapeutic targets and the development of more precise and personalized treatment strategies.

Case. Multi-Omics Analysis of Glioblastoma Reveals Key Oncogenic Pathways and Therapeutic Opportunities ^[1]

Background

Glioblastoma (GBM) is a highly aggressive brain cancer with limited treatment options. Previous studies have explored its genetic and transcriptomic aspects, but a comprehensive multi-omics analysis is needed to understand the complex molecular landscape of GBM.

Samples

The study analyzed GBM samples, encompassing a range of genetic subtypes and clinical characteristics, to investigate the intricate molecular profile of the disease.

Technical Methods

The research integrated multiple omics approaches, including genetics, RNA, protein, phosphoprotein, acetylome, metabolome, and lipidome analyses. Additionally, single-cell transcriptomics was employed to provide a holistic view of GBM.

Genetic Analysis: The study examined genetic alterations within critical oncogenic pathways, such as RTK/RAS, PI3K/AKT, and p53/cell cycle. It revealed subtype-specific genetic changes and highlighted the relevance of expression outliers in the RTK pathway.
RTK/RAS Pathway: GBM subtypes displayed distinct alterations in the RTK/RAS pathway. Amplified EGFR was prevalent in classical tumors, whereas proneural and IDH-mutant tumors exhibited amplified PDGFRA. Mesenchymal tumors showed increased MET and reduced NF1 protein levels.
PI3K Pathway: Alterations in the PI3K pathway, particularly related to PTEN, were observed in proneural, mesenchymal, and classical tumors. This could lead to activation of AKT1 and AKT2 through PIP3.
p53/Cell Cycle Pathway: Subtype-specific changes and increased expression of MDM2 in mesenchymal and MDM4 in proneural and classical tumors were found in the p53/cell cycle pathway. Differences in CDKN2A/B were also noted between IDH-WT and mutant tumors.
Druggable Pairs: Druggable pairs associated with specific signaling pathways and proteins were identified. For example, GSK3B phosphorylation was linked to downstream mTOR and Wnt signaling components, while EGFR phosphorylated CTNNB1 S33.
Therapeutic Opportunities: The study employed the LINCS database to identify compounds capable of reversing tumor signatures in GBM. Phosphoproteomic data proved more robust than transcriptional data, offering insights into potential therapeutic targets and compounds.
Immune Subtypes: Immune subtypes in GBM were identified, with variations in immune cell composition. The subtype "im3" exhibited a relative lack of immunosuppressive macrophage-microglia infiltration but an enrichment of T lymphocytes and NK cells, particularly associated with IDH-mutated tumors.
Mesenchymal Features: Mesenchymal GBM subtypes exhibited enhanced EMT signatures, with contributions from both tumor cells and stromal components.
Metabolomic and Lipidomic Characteristics: Metabolomic and lipidomic analyses uncovered distinctions in lipid profiles and metabolic vulnerabilities among GBM subtypes, with associations to neuronal phenotypes and IDH status.

Conclusion

The multi-omics analysis of GBM samples provided a comprehensive understanding of its molecular and genetic landscape, revealing key oncogenic pathways and potential therapeutic targets. This research offers valuable insights into patient stratification for clinical trials and the development of personalized treatment approaches.

Experimental Design

A multi-omics study was conducted on 99 cases of glioblastoma (GBM), a highly malignant brain tumor, along with 10 healthy control brain tissue samples. This comprehensive investigation encompassed genomics, transcriptomics, proteomics (utilizing TMT technology), post-translational modifications (phosphorylation and acetylation), metabolomics, and lipidomics.

Consistent with the genetic subtypes, three distinct subtypes, namely, nmf1 (proneural, n=29), nmf2 (mesenchymal, n=37), and nmf3 (classical, n=26), were identified in IDH-WT tumors. Pathway enrichment analysis based on the abundance of RNA, proteins, and phosphorylation sites revealed specific characteristics for each subtype:

1. Nmf1 subtype exhibited enrichment in synaptic vesicle cycling and neurotransmission pathways.

2. Nmf2 subtype showed enrichment in innate immunity-related pathways, including neutrophil degranulation, phagocytosis, and extracellular matrix organization.

3. Nmf3 subtype displayed enrichment in pathways related to mRNA splicing and RNA metabolism.

Mutations in Driver Genes Alter the Abundance and Phosphorylation of Oncogenic Proteins

By linking genetic alterations (mutations, CNVs, fusions, and SVs) to RNA, protein expression, and phosphorylation levels, a total of 95 cis-phosphorylation events were observed. The study revealed strong cis-effects of EGFR and PDGFRA, with significant increases in RNA and protein expression. Correspondingly, elevated phosphorylation levels were observed at S1166 and S1067/S1070. In contrast, EGFR genetic alterations led to decreased CTNNB1 mRNA levels but increased protein expression, along with elevated phosphorylation levels of PTPN11 and PLCG1.

TP53-mutant tumors exhibited an increase in phosphorylation sites associated with DNA repair genes, although protein expression levels remained unaltered. Tumor suppressor genes RB1, NF1, PTEN, and ATRX demonstrated good consistency between genetic alterations and the corresponding RNA, protein, and phosphorylation levels, all of which decreased.

Activation of RTK Signaling Cascades in GBM

Genomic loci associated with RTKs, such as EGFR, PDGFRA, and MET, are frequently amplified in GBM. We identified 45 tumors with EGFR structural variants (SVs), all of which exhibited copy number amplifications, indicating a high concordance between SV and CNV. Tumors with mutated EGFR and SVs showed correspondingly high levels of RNA, protein, and Y1172 phosphorylation, suggesting activation of the EGFR pathway.

In EGFR-altered samples, elevated EGFR autophosphorylation was observed, along with increased abundance and phosphorylation of various proteins, including PTPN11, PLCG1, RB1, and MAP3K1, as well as specific EGFR phosphorylation sites. Notably, PTPN11, GAB1, and GRB2 form a complex in glioblastoma, co-regulated by RTKs to activate the RAS pathway.

GBM Immune Subtyping

Different immune markers and epigenetic events can characterize the immune subtypes of GBM. Through single-sample gene set enrichment analysis (GSEA), we identified four distinct immune-based GBM subtypes.

Immune Subtype 1 (im1) exhibited an overall higher score, with elevated levels of microglia, macrophages, and lymphocytes. Immune Subtypes 2 and 3 (im2 and im3) showed reciprocal ratios of macrophages and lymphocytes, with im2 having a higher proportion of macrophages and lower lymphocytes, while im3 had a higher neuron score. Immune Subtype 4 (im4) stood apart from the others, with substantially lower enrichment for all immune cell types.

Histone Acetylation Cell Subtyping

Differences in histone acetylation are associated with specific subtypes and pathways. Histone acetylation regulates gene expression, but it is often dysregulated in cancer. Over 30 acetylation sites were identified on histones H1, H2A, H2B, H3.3, and H4, dividing the tumors into four distinct subtypes. Histone acetylation levels were generally elevated in tumors. Some pathways related to immune infiltration, such as ferroptosis, mast cells, and ROS pathways, were negatively correlated with H2B acetylation, while splicing factors, nuclear receptors, and SUMOylation modifications showed a positive correlation. Two key proteins in the SUMOylation pathway, SUMO1 and UBE2I, were upregulated in samples with high H2B acetylation. These observations suggest that H2B acetylation contributes to distinguishing immune cells from other cell types.

Metabolomic Analysis of GBM Subtypes

The authors identified 582 lipid species in 75 tumor samples and 7 normal control tissue samples, with over 500 lipids showing significant differences among the four subtypes in the multi-omics study. In the four subtypes, the mesenchymal subtype exhibited high levels of triglycerides (TGs) and low levels of phosphatidylcholines (PCs) and other phospholipids. The proneural subtype was enriched in very-long-chain fatty acid lipids and glycerophospholipids with long-chain polyunsaturated fatty acids. Regarding metabolites, the proneural-like cluster showed significantly elevated levels of creatinine and homocysteine, and there were differences in metabolite expression between IDH-mutant and IDH-WT tumors.

Key Oncogenic Pathways and Therapeutic Targets

Three critical oncogenic signaling pathways in GBM are RTK/RAS, PI3K/AKT, and p53/cell cycle. In the RTK/RAS pathway, classical tumors predominantly exhibit EGFR amplification, while proneural and IDH-mutant tumors show PDGFRA amplification. Both subtypes display higher RNA, protein, and phosphorylation abundances of EGFR and PDGFRA. In the PI3K pathway, PTEN is underexpressed in proneural, mesenchymal, and classical tumors, potentially leading to the activation of AKT1 and AKT2 through PIP3. In the p53/cell cycle pathway, subtype-specific amplifications are observed, with MDM2 overexpressed in mesenchymal tumors and MDM4 overexpressed in proneural and classical tumors. These findings highlight potential therapeutic targets for GBM.

Reference

Wang, Liang-Bo, et al. "Proteogenomic and metabolomic characterization of human glioblastoma." Cancer cell 39.4 (2021): 509-528.

* For Research Use Only. Not for use in diagnostic procedures.

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