A road map for the treatment of pediatric diffuse midline glioma

Abstract

Recent clinical trials for H3K27-altered Diffuse Midline Gliomas (DMGs) have shown much promise. We present a consensus roadmap and identify three major barriers: (a) Refinement of experimental models to include immune and brain-specific components. (b) Collaboration among researchers, clinicians, and industry to integrate patient-derived data through sharing, transparency, and regulatory considerations. (c) Streamlining clinical efforts including biopsy, CNS-drug delivery, endpoint determination, and response monitoring. We highlight the importance of comprehensive collaboration to advance the understanding, diagnostics and therapeutics for DMGs.

Diffuse Midline Gliomas (DMGs) including Diffuse Intrinsic Pontine Gliomas (DIPGs) are aggressive and highly malignant brain cancers that primarily affect children. These tumors arise from midline structures including the pons, thalamus, cerebellum, and spinal cord, and are frequently inoperable due to their location in vital and intricate brain structures. These are termed “diffuse” because they tend to grow and infiltrate into surrounding brain tissue, making them difficult to remove surgically. Current conventional treatments including radiation and chemotherapy are not effective, have not shown significant success in improving outcomes, and the median survival time after diagnosis is still 9–12 months.

A major breakthrough in understanding the biology of these cancers was the discovery of driver histone H3 lysine 27 to methionine (K27M) mutations involving histones H3.3 and less frequently H3.1 (collectively H3K27M)^1,2. Lysine residues on histone tails are subject to post-translational modifications, and H3K27M results in global reduction of the repressive mark H3K27me3 due to the suppression of Polycomb repressive complex 2 (PRC2) function³. A small subset (~4%) of DMGs overexpress a protein termed EZHIP (EZH inhibitory protein) which, similar to H3K27M, suppresses EZH2 function to facilitate global H3K27me3 reduction⁴. The 2021 World Health Organization (WHO) classification collectively designated these tumors DMG H3K27-altered⁴. These tumors are assigned a Central Nervous System (CNS)-WHO grade 4 reflective of their dismal prognosis⁴.

Excitingly, recent clinical studies in DMG/DIPG involving CAR-T^5,6 and ONC201^7,8 have established early efficacy signals that had eluded hundreds of previous experimental therapies, thus opening the possibility of making major strides in clinical outcomes in the current era. The ChadTough Defeat DIPG Research Consortium met in May 2023 to discuss and provide harmonized strategies that capitalize on this momentum to work towards a common goal of developing effective cures for these tumors. We highlight key aspects of three major barriers identified and consensus guidelines on addressing these issues below (Figure 1).

Figure 1. Overview of proposed assessment and banking of H3K27-altered diffuse midline gliomas.

Diffuse Midline Gliomas arise mainly in children and young adults within midline structures including the thalamus, brainstem, cerebellum, and spinal cord. We propose a comprehensive longitudinal assessment/banking of (a) patient clinical parameters including imaging, therapy response, toxicity, and quality of life; (b) tumor tissues from both biopsy and autopsy, and (c) factors such as CSF, plasma, urine, and stools for biomarker development. We suggest an integrated analysis using multiple platforms for biomarker development, hypothesis generation, refinement of tumor response definitions, clinical trials, and generation of preclinical models. Figure constructed using BioRender.

(a). Overcoming challenges in preclinical modeling

Various DMG preclinical models have played a pivotal role in advancing basic and translational research capabilities. H3K27M patient-derived cell lines, isogenic cell lines expressing H3.3/H3.1K27M versus H3WT overexpression or CRISPR mutation corrected cells, genetically engineered mouse models (GEMMs), cell line derived xenograft (CDX) orthotopic implanted animals, and patient-derived xenograft (PDX) models offer direct insights into human biology, enabling personalized investigations. Each model system offers specific advantages and challenges. A roadmap to guide future model development requires addressing existing limitations and capitalizing on novel opportunities (Figure 1).

Patient-derived cell line models enable personalized analysis but often lack the complexity of in vivo systems. Most are cultured as 2D adherent or 3D neurosphere cultures and there is a growing recognition that a key aspect missing in traditional cell culture models is interactions with cells within the brain/tumor microenvironment (i.e., immune and microglia cells, neurons, astrocytes, and endothelial cells), which are known to participate in DMG growth. Exploring more recently developed alternative culture systems like brain organoids that model unique microenvironments including thalamus and pons, tumor-bearing brain slice cultures to study tumor-neuron and immune cell interactions, patient-derived cell line models with immune components, and other advanced in vitro systems can enrich our understanding.

For in vivo models, PDX and CDX animals capture tumor heterogeneity but do not faithfully emulate the human tumor microenvironment. Addressing these deficiencies involves incorporating immune-competent models and utilizing advanced technologies for more accurate representation. Immune competent GEMMs include traditional GEMMs with modification of key DMG oncogenes (H3–3A)^3,9 and in-utero electroporation (IUE)-derived GEMMs¹⁰. These model systems offer the opportunity to address complex immune-tumor interactions and study immune therapies. However, significant barriers to translating data from preclinical studies to human DMGs still remain. Gaps between murine data and clinical translation can be attributed to species-specific variations in biology and the complex interplay of human-specific factors. Preclinical treatment regimens rarely align with clinical scenarios, and aspects such as the starting time-point of treatment and incorporation of standard of care radiation and chemotherapy will need to be optimized to improve translational impact. Further advancement of immune-competent GEMM models may include patient-specific “avatars” with clonal and subclonal genetic perturbations introduced into the relevant midline region of the brain. Additionally, blood-brain barrier (BBB) penetration and disruption varies across models as brainstem DMG (DIPG) likely has a more restrictive BBB than CNS tumors in other non-midline locations, emphasizing the location of tumors in preclinical studies. Finally, while nearly all in vivo DMG model systems utilize mice, it is recognized that larger species better recapitulate many features of human physiology. With this in mind, developing DMG models in larger rodents (i.e., rats) or non-rodent species (i.e., swine or ferrets) could provide additional preclinical tools to help improve translation into the clinic.

Models like patient-derived cell lines, PDX/CDX, and GEMMs are powerful tools for advancing DMG understanding, each with unique attributes and limitations. Significant advancements require collaborative efforts and strategic investments. Collaborative efforts and investments in innovative model systems can bridge the gap between preclinical insights and improved patient outcomes, ushering in a new era of transformative translational research. Critical areas of investment for further understanding of DMGs include establishment of (1) relevant midline brain (e.g. pontine) organoid models to study in vitro tumor-brain interaction, (2) further advancement of immune-competent GEMM in vivo models and (3) development of DMG models in larger species. Collaborative efforts and investments in innovative model systems can bridge the gap between preclinical insights and improved patient outcomes, ushering in a new era of transformative translational research.

(b). Curation of data derived from DMG patient samples

Addressing the human disease and integrating preclinical data with patient-derived data is paramount to not only understanding the biology of H3K27-altered DMGs, but also to developing treatments to address DMG heterogeneity and treatment resistance. Critical biopsy and multi-focal autopsy samples form the basis of previous and ongoing discovery (Figure 1). There is a wealth of DMG molecular data from bulk RNA-seq and epigenetic studies including DNA methylation, genomic chromatin accessibility assessed by assay for transposase-accessible chromatin with sequencing (ATAC-seq), and genomic distribution of specific histone modifications using chromatin immunoprecipitation followed by sequencing (ChIP-seq)^11–15. Newer technologies including single cell RNA-seq and ATAC-seq offer unprecedented insights into tumor heterogeneity. Assaying precious patient-derived H3K27-altered DMG tumor tissues and curating these data in an easily accessible user-friendly resource is paramount. The success of this collaborative endeavor hinges upon several key factors. First, ensuring transparency throughout the process is important, as it fosters trust and accountability within the community. Gaining buy-in from both researchers and clinicians is critical to establish a unified effort and leverage diverse expertise. Clear articulation of community expectations will guide the collective endeavor. To facilitate streamlined communication and knowledge sharing, a central DMG data and tissue repository/resource should be established or built as a unique usable project/dataset within an existing infrastructure [e.g. DIPG/DMG Registry, Children’s Brain Tumor Network (CBTN), European Society for Paediatric Oncology (SIOPE), Childhood Cancer Data Initiative (CCDI)], acting as an accessible hub for information dissemination.

Navigating the complex landscape of local, national, and international regulatory requirements demands meticulous attention. Prioritizing actionable data from DMG/DIPG datasets collected and shared is essential to extract meaningful insights from the vast array of information amassed. The multi-dimensional nature of DMG data acquisition, spanning genomic, epigenomic, metabolomic, mitochondrial, proteomic, bulk, phospho-proteome, micro-environment, and dependency/vulnerability screens, underscores the depth of understanding sought.

To address unmet needs, a concerted approach involving harmonization and real-time sharing of DMG data generation is imperative. Correcting for batch effects and revisiting previously published samples to infill gaps with new data will enhance the comprehensiveness of the knowledge base. Rigorous attention to DMG cell lines and patient sample nomenclature and drift is indispensable for maintaining data integrity. Prospective data generation, seamlessly integrated with ongoing DMG/DIPG clinical trials, synergistically advances translational outcomes.

Collaboration should extend to data integration, analysis, and target discovery/validation. Tech development, encompassing low-input samples and cross-site data generation using novel technologies, propels the field forward. Functional data integration, uploading unpublished datasets to centralized designated platforms, preclinical drug testing, a drug repository particularly for failed particular preclinical or and clinical screening tests, and enhancing the DMG/DIPG samples within large-scale dependency efforts like DepMap and Hudson screens are pivotal components.

Working together to meet these unmet needs requires a DMG/DIPG data ecosystem marked by transparent communication, unified vision, and comprehensive resource-sharing. These types of large-scale data sharing efforts have had marked success in fields ranging from the brain connectome to astronomy where collaborative efforts are enhanced, competition is decreased thus improving transparency, discovery is accelerated and rigor/reproducibility is greatly improved, all of which are critical for rapid translation of scientific insights into clinical outcomes. This type of actionable, dynamic data sharing is worth the investment despite its challenges. Indeed, by harmonizing data generation, integrating insights, and collectively advancing technology, the community can revolutionize our understanding of complex biological systems, fueling innovations in diagnostics, therapeutics, and patient care.

(c). Streamlining clinical efforts

There are several major barriers to ongoing DMG/DIPG clinical efforts including (but not limited to) biopsy risk, restricted drug delivery, and unclear clinical endpoint determination and response. Ongoing innovative studies designed to address these include assessing pharmacokinetics (PK) and pharmacodynamics (PD) in patients with DMG/DIPG on investigational therapies, real-time assessment of treatment response with biomarker results shared back with patients, and international autopsy banking efforts (Figure 1).

The current landscape of DMG/DIPG biopsy approaches for treatment evaluation presents several considerations. While upfront biopsies remain the accepted standard, there is a need to explore the standardization of this approach. Delving into on-treatment biopsies, safety of re-biopsy remains a concern, with risks of neurologic worsening estimated at 2–5% for each biopsy. Exploring the feasibility of minimally invasive core sampling is also worth considering, given the pressing need to enhance the accuracy of biopsy risk assessment. Patient-specific benefits and the optimal timing for these biopsies should be thoroughly examined, including the possibility of shifting upfront biopsies to a later stage through a cohort-based approach. In light of the predominant reliance on data from single institutions, high-volume centers, there is a growing desire to establish a comprehensive global registry to capture a more accurate representation of biopsy risks. This endeavor should involve a multidisciplinary working group with the aim to create standardized procedures and guidelines for tissue sampling in DMGs. Questions regarding optimal biopsy targets, the number of required cores, the rationale behind frozen tissue interpretation, and the necessity of multiple targets are all vital aspects that should be addressed by this collaborative effort. Reassessing contemporary measurement practices for biopsy, now commonplace, presents a straightforward yet invaluable contribution to the field.

Phase 0 target validation (biopsy after taking experimental therapy) is an essential step, paving the way for subsequent DMG/DIPG investigations. Additionally, PK/PD rationales deserve attention, with the question of CLIA certification for testing needs and population PK analyses. Utilizing theoretical exposure models could be considered to design the assessment of interval plasma PK for targeting validation time points. An intriguing prospect is real-time assessment with results such as MRI and sequencing results shared back with patients with DMG/DIPG, determining the optimal timing for biopsies, as well as adjusting dosing based on real-time plasma PK data for each individual patient.

CNS-directed delivery strategies for DMG encompass various avenues. Convection enhanced delivery (CED) is one consideration with its potential therapeutic index advantage. Focused ultrasound (FUS) serves as a means to open the BBB to enhance drug delivery for feasibility studies, evaluating PK, and even preceding standard diagnostic biopsies. FUS in conjunction with experimental therapy, prior to standard diagnostic biopsies, and its combination with immunotherapy requires careful investigation, including the duration of BBB opening. Local delivery/FUS can adopt regional response criteria, possibly treating a portion of the tumor before surgery if feasible.

Establishment of DMG/DIPG clinical trial endpoint determination and real-time radiographic response monitoring are pivotal. Therapeutic designs should align with corresponding uniformly defined endpoints, incorporating patient-reported outcomes, tumor resampling when feasible, neuro-imaging, and patterns of relapse for comprehensive assessment. The potential of upfront liquid biopsy conduits in DIPG/DIPG patients, such as indwelling cerebrospinal (CSF) reservoirs, holds promise for longitudinal sampling and could be modeled after protocols that are currently being implemented. Recent work has established the feasibility and utility of monitoring H3K27M cell-free tumor DNA in prospective DMG patients undergoing therapy with ONC201.

The value of DIPG/DIPG autopsy as a resource is undeniable, with families expressing a desire to contribute. Integrating this discussion into the upfront setting raises questions about the handling of assent and the consistent return of results to families, Exploring the feasibility of tumor-only autopsy is also worth considering. Additionally, a system for providing families the option for feedback on how and when samples are used in published research is currently being established through a foundation that supports DIPG/DMG autopsy, Gift From a Child.

Summary/Conclusion

In summary, DIPG/DMG is among the most lethal human cancers but appears on the brink of unprecedented improvements in clinical outcomes. The next steps taken in translational efforts are critical to maintain this momentum. We have provided a comprehensive roadmap for (and from) the DMG/DIPG research community (Figure 1). The DMG/DIPG research and family foundation community is heavily connected and collaborative, thus uniquely positioned to achieve the roadmap steps outlined in this paper. The benefits reaped from these efforts will apply to future patients diagnosed with DMG/DIPG and will provide a blueprint for other deadly cancers.