Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies

Abstract

Diffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9-11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including, HIST1H3B/C (H3.1K27M) or H3F3A (H3.3K27M), or through overexpression of EZHIP in patients harboring wildtype H3. The recent World Health Organization's 5th Classification of CNS Tumors now designates DMG as, 'H3 K27-altered', suggesting that global H3K27me3 hypomethylation is a ubiquitous feature of DMG and drives devastating transcriptional programs for which there are no treatments. H3-alterations co-segregate with various other somatic driver mutations, highlighting the high-level of intertumoral heterogeneity of DMG. Furthermore, DMG is also characterized by very high-level intratumoral diversity with tumors harboring multiple subclones within each primary tumor. Each subclone contains their own combinations of driver and passenger lesions that continually evolve, making precision-based medicine challenging to successful execute. Whilst the intertumoral heterogeneity of DMG has been extensively investigated, this is yet to translate to an increase in patient survival. Conversely, our understanding of the non-genomic factors that drive the rapid growth and fatal nature of DMG, including endogenous and exogenous microenvironmental influences, neurological cues, and the posttranscriptional and posttranslational architecture of DMG remains enigmatic or at best, immature. However, these factors are likely to play a significant role in the complex biological sequelae that drives the disease. Here we summarize the heterogeneity of DMG and emphasize how analysis of the posttranslational architecture may improve treatment paradigms. We describe factors that contribute to treatment response and disease progression, as well as highlight the potential for pharmaco-proteogenomics (i.e., the integration of genomics, proteomics and pharmacology) in the management of this uniformly fatal cancer.

Fig. 1. Gene-RNA-protein alignments of the mutant histone H3 genes that give rise to diffuse midline glioma.

A The HIST1H3B (H3.1) gene is a short (511 nt) intronless gene, translated into a 136 amino acid, 15,404 (Da) protein. B Comparatively, the H3F3A gene is a long (10,189 nt), intron-containing gene, translated into a 136 amino acid, 15,328 (Da) protein.

Fig. 2. H3-altered diffuse midline glioma recurrent somatic mutations associated with each midline localization.

A Most frequently, diffuse midline glioma (DMG) is localized in the pons (green), midbrain (pink) and thalamus (orange). B Venn diagram of recurrent somatic mutations seen in each H3-altered subtype, H3.1K27M (purple), H3.3K27M (light blue) and EZHIP (sky blue). Identity of recurrent somatic mutations in C H3.1K27M, D H3.3K27M and E EZHIP DMG H3-altered. Genomic information obtained by examining the comprehensive data published by whole-exome and whole-genome studies, references are including in Table 1.

Fig. 3. Clonal evolution, tumor burden and non-genomic contributions to diffuse midline gliomas development and progression.

A Diffuse midline glioma (DMG) tumor burden continually increases following diagnosis. Similarly, the clonal heterogeneity of DMG evolves throughout a patient’s disease, potentially influenced by endogenous and exogeneous factors, including microsatellite instability, treatment, and steroids. B Representation of tumor evolution beginning with a single tumor cell harboring a HIST1H3B mutation, cell outlined in pink. As the tumor grows and diversifies, it gains new driver and passenger mutations. Driver mutations in this example include ACVR1 in light blue, TGFBR2 in purple, TP53 in dark blue, PIK3CA in green, NCOR1 in yellow and BCOR in red. C In addition to the increased clonal heterogeneity and tumor burden, non-genomic factors fluctuate throughout disease progression and likely contribute to growth and survival. The patient’s degree of motor function, represented by a blue line, is inversely proportional to tumor burden, whereas corticosteroids anti-inflammatory medications (dexamethasone), represent by a green line, is relatively proportional to tumor burden beginning with a sharp increase at diagnosis, sustained then decreased during radiotherapy, and adjusted to meet the patient’s symptoms [100]. D Representative magnetic resonance imaging (MRI) of tumor development and progression throughout a DMG patient’s journey.

Fig. 4. Non-genomic contributions to diffuse midline glioma growth and progression.

Diffuse midline gliomas (DMG) are vastly complex tumors localized in the midline structures of the brain. At diagnosis (primary tumor) DMG harbor numerous driver mutations, (highlighted by tumor cells of varying color), that contribute to drive the evolution of the cancer. Surrounding cells and structures of the midline of the brain such as blood vessels, neurons, astrocytes, microglia, and oligodendrocytes contribute to the gliomagenesis of DMG, whether through direct physical connections or by more indirect mechanisms, such as electrical signals (yellow lightening blots) between glioma and normal cells or the contribution of growth hormones, NGF, VEGF, TGF-β, and prolactin, or even, endogenous factors, such as hypoxia, dopamine, insulin, catecholamines. The extracellular cues drive posttranslational modifications (PTMs) that influence the activity of oncoproteins that contribute to the aggressive nature of the disease. It is likely that exogenous factors, such as radiotherapy (radioactive symbol) and corticosteroids (dexamethasone), also contribute to the disease, the impact on tumor growth and treatment resistance yet to be fully understood. The diffuse and infiltrative growth of this cancer also leads to dissemination throughout the brain. Disseminated subclones, however, can differ in genomic and proteomic characteristics to that of the primary tumor, influenced by clonal selection supported by non-genomic factors from each different region of the brain, and lead to distinct survival and proliferative advantages, highlighting the challenge we face in developing treatment strategies that will lead to long-term survival for patients diagnosed with DMG.