G3-MB presents a formidable challenge in pediatric oncology due to its poor prognosis and resistance to current treatment modalities. A key driver of this malignancy is the overexpression of MYC, an oncogene that orchestrates cellular processes promoting rapid proliferation and tumor aggressiveness. Unlike typical gene amplifications residing within chromosomes, MYC is often amplified on extrachromosomal DNA (ecDNA) in these tumors. EcDNA consists of circular DNA elements detached from chromosomes, which can replicate independently, resulting in variable gene copy numbers. This dynamic genomic structure confers a formidable adaptability to cancer cells, enabling sustained high-level MYC expression that drives malignant progression.

The St. Jude team employed a combination of cutting-edge genomic techniques, including three-dimensional genome mapping, chromatin profiling, and CRISPR-based functional screens, to interrogate the regulatory landscape governing MYC expression on ecDNA. Their investigations identified a crucial enhancer element within the ecDNA, termed ecMYC E1, that exerts strong control over MYC transcription. Enhancers are segments of DNA that facilitate gene activation by physically interacting with promoter regions, acting as molecular switches that modulate gene output. This discovery revealed a previously unrecognized regulatory circuit uniquely embedded within the extrachromosomal genetic architecture of G3-MB tumors.

What makes this finding particularly significant is that ecMYC E1 is highly active and exclusive to tumor cells harboring extrachromosomal MYC amplification, rendering it a promising therapeutic target. Functional interrogation using brain tumor organoid models—three-dimensional cultures that recapitulate the histological and molecular features of patient tumors—demonstrated that silencing this enhancer markedly reduced MYC transcription. This reduction in oncogenic expression translates to a potential strategy to curb tumor growth while sparing normal tissues. These organoid models retain the genetic heterogeneity of the original tumors, offering an unparalleled platform to study ecDNA-mediated oncogene regulation in a physiologically relevant context.

Despite the promising results, the researchers discovered a remarkable adaptive mechanism employed by cancer cells in response to ecMYC E1 inhibition. Initially, suppressing the enhancer led to diminished MYC levels; however, tumor cells counteracted this effect by increasing the copy number of MYC-carrying ecDNA. This ecDNA amplification restored oncogene expression, revealing an intrinsic resilience powered by the unique replication capability of extrachromosomal elements. Intriguingly, this adaptive response was absent in tumors where MYC amplification is integrated within chromosomes, underscoring the distinct biology of ecDNA-driven cancers.

To address this obstacle, the research team proposes a combinatorial therapeutic strategy. Enhancer silencing could be paired with agents that hinder the increase in ecDNA copy number, such as checkpoint kinase 1 (CHK1) inhibitors. CHK1 plays a key role in DNA replication and cell cycle regulation, and its inhibition could prevent the compensatory ecDNA amplification, thereby enhancing treatment efficacy. This dual-pronged approach targets both the regulatory circuitry and the resilient genomic architecture, potentially overcoming tumor resistance mechanisms.

The implications of these findings extend beyond medulloblastoma. Approximately 28% of cancers feature oncogene amplification on ecDNA, suggesting a broader applicability for therapies targeting ecDNA-associated enhancers. However, MYC’s intractable structure and central oncogenic role have historically stymied efforts to develop direct inhibitors. This study marks a conceptual shift, focusing on the regulatory elements that govern MYC expression rather than the protein itself. By exploiting the unique vulnerabilities of ecDNA in tumor cells, new treatment avenues may emerge for a spectrum of high-risk malignancies driven by MYC.

Key to this research was the integration of multi-dimensional genomic technologies with innovative functional assays. The 3D genome mapping techniques allowed visualization of physical interactions between enhancers and promoters within the spatial organization of the nucleus. Chromatin profiling illuminated the epigenetic landscape defining active regulatory elements, while CRISPR-based screens enabled functional validation by selectively silencing candidate enhancers. Together, these methodologies provided a comprehensive understanding of how ecDNA confers regulatory autonomy to MYC, a phenomenon absent in chromosomally encoded genes.

The study was spearheaded by Dr. Martine Roussel, a prominent figure in tumor cell biology at St. Jude, with doctoral candidate Jake Friske playing a pivotal role in executing and interpreting the experimental findings. The collaboration incorporated expertise across genetics, molecular biology, and bioinformatics, reflecting the multidisciplinary nature of contemporary cancer research. The work was supported by grants from the National Cancer Institute, American Cancer Society, Broad Institute’s Pediatric Cancer Dependencies Accelerator, and other partners, highlighting the critical need for investment in pediatric cancer science.

Moreover, the study’s use of brain tumor organoids represents a significant advance in modeling tumor biology. These organoid systems simulate tumor microenvironments and preserve genetic diversity, providing a more faithful representation of tumor behavior than traditional cell lines. This fidelity enabled detailed studies of enhancer function and resistance mechanisms in a controlled but biologically relevant setting. The findings underscore the value of such models in preclinical research and drug development pipelines.

This research not only broadens our understanding of MYC regulation but also exemplifies the adaptive complexity of cancer genomes. EcDNA offers tumors a genomic plasticity that facilitates rapid evolution under therapeutic pressure. By targeting both the regulatory elements and replication mechanisms of ecDNA, future treatments may effectively outmaneuver tumor adaptability, providing hope for improved outcomes in children afflicted with these devastating brain tumors.

In conclusion, the identification of the ecMYC E1 enhancer on extrachromosomal DNA represents a paradigm shift in targeting MYC-driven pediatric medulloblastoma. This enhancer acts as a linchpin in sustaining oncogenic MYC expression, and its inhibition, combined with blockade of ecDNA amplification, holds promise for refined, less toxic therapeutic strategies. As the scientific community continues to unravel the complexities of ecDNA biology, the strategies illuminated by this landmark study may pave the way for innovative interventions against some of the most intractable pediatric cancers.

Subject of Research: Regulatory mechanisms of MYC oncogene expression in pediatric Group 3 medulloblastoma and novel therapeutic targets on extrachromosomal DNA.

Article Title: Enhancer provides a potential target for ‘undruggable’ MYC in pediatric medulloblastoma.

News Publication Date: April 22, 2026.

Web References:

• St. Jude Children’s Research Hospital: https://www.stjude.org/
• Article DOI: http://dx.doi.org/10.1158/0008-5472.CAN-25-4691

Image Credits: St. Jude Children’s Research

Keywords: Medulloblastoma, Oncogenes, MYC, Extrachromosomal DNA, ecDNA, Enhancer, Chromatin profiling, CRISPR screening, Pediatric brain tumors, Tumor organoids, Cancer genomics, Therapeutic resistance

The MYC protein, long recognized as a central oncogenic driver implicated in up to 70% of human cancers, has historically been labeled “undruggable” due to its lack of conventional binding pockets suitable for small molecule inhibitors. MYC functions primarily by regulating gene transcription and cellular proliferation, but its oncogenic activity stems from complex protein–protein interactions that have resisted traditional pharmacological intervention. Recent insights revealed that the interaction between MYC and WDR5 is indispensable for the maintenance of MYC’s oncogenic functions, thereby spotlighting WDR5 as a novel and promising target in therapeutic development.

Breaking new ground, the research team employed Insilico’s generative AI-driven platform, Chemistry42, creating novel small molecules that precisely engage the WDR5 interface critical for MYC binding. The platform enabled a ligand-centric and scaffold-hopping strategy enhanced by ’anchor points,’ which preserved pharmacophoric features essential for high-affinity binding. Among the AI-generated candidates, two compounds distinguished themselves: compound 8 exhibited inhibitory potency with an IC50 value of 16.35 micromolar, while compound 9 demonstrated a significantly improved IC50 of 1.91 micromolar. These findings indicated marked improvements over a reference molecule, which displayed an IC50 of 20.86 micromolar, signaling notable enhancement in targeting this challenging PPI landscape.

Recognizing the potential of these initial hits, further optimization was carried out through rigorous physics-based modeling facilitated by Chemistry42’s AlChemistry module. This approach enabled deep structural analysis and refinement of molecular interactions and binding conformations within the WDR5-MYC interface. As a result, lead compounds with sub-micromolar affinities were engineered, culminating in the identification of the standout molecule 9c-1. This lead showed a remarkable 35-fold increase in inhibitory activity relative to earlier analogs, specifically compound 3, showcasing exceptional binding strength and specificity against WDR5. Such potency positions 9c-1 as a trailblazer in the design of efficacious inhibitors capable of disrupting MYC-driven oncogenesis through direct interference with its protein–protein engagement.

The implications of this breakthrough are profound. The successful application of an AI-guided generative chemistry technique, integrated seamlessly with physics-anchored validation, underscores a paradigm shift in tackling traditionally “undruggable” targets. This study exemplifies how advanced computational platforms can rapidly generate candidate molecules with therapeutic promise, accelerating early-stage drug discovery timelines dramatically compared to conventional methodologies. Insilico Medicine’s innovative combination of machine learning and molecular modeling successfully circumvents longstanding challenges in drug design, especially for complex PPIs long deemed refractory to small molecule intervention.

Dr. Xiao Ding, Senior Vice President and Head of Chemistry & DMPK at Insilico Medicine, emphasized the significance of these findings, stating, “Our AI-powered platforms are transforming drug discovery by unlocking possibilities for targets previously considered inaccessible. This project demonstrates the synergistic power of generative chemistry aligned with physics-based modeling, delivering molecules that could herald new therapeutic paradigms for cancers driven by MYC.” The integration of computational creativity with empirical rigor has expedited the transition from conceptual targets to potent leads, offering hope for treating malignancies with profound unmet medical needs worldwide.

This achievement builds on a rich legacy of Insilico Medicine’s leadership in artificial intelligence applications for drug design. Initially conceptualized in 2016 within peer-reviewed literature as a pioneering use of generative AI for molecule creation, Insilico’s platforms have evolved to commercial maturity via Pharma.AI, a comprehensive digital ecosystem deployed extensively in early drug development pipelines. By uniting deep generative neural networks, reinforcement learning techniques, transformer architectures, and physics-based simulations, Insilico Medicine has optimized target identification and compound generation, significantly compressing drug discovery phases from an average 2.5–4 years down to 12–18 months per program.

Moreover, leveraging automated synthesis and high-throughput biological testing, Insilico Medicine has propelled over two dozen internal programs between 2021 and 2024, synthesizing and validating 60–200 molecules per candidate initiative. This integrated AI-drug discovery approach not only expedites lead identification but enhances molecular novelty and diversity—overcoming traditional attrition hurdles frequently encountered in medicinal chemistry campaigns focused on complex targets such as transcription factor PPIs.

The WDR5-MYC inhibitory compounds represent a new class of focused PPI disruptors, embodying a strategic shift to modulate oncogenic pathways at the protein interaction level rather than canonical enzymatic inhibition. Disrupting the assembly of oncogenic transcriptional complexes via WDR5 offers a promising intervention point with the potential to arrest cancer proliferation and survival mechanisms. Crucially, this approach illustrates the feasibility of rational PPI drug design supported by AI, challenging preconceived limitations in medicinal chemistry and expanding the therapeutic landscape for challenging targets across oncology and beyond.

Looking forward, the medicinal chemistry team aims to advance the 9c-1 lead through preclinical evaluations, exploring pharmacokinetics, toxicity profiles, and efficacy in cancer models. The translational potential of these findings opens avenues for addressing cancers driven by MYC dysregulation, including lymphoma, leukemia, and a spectrum of solid tumors. Furthermore, the AI-driven discovery methodology exemplified here serves as a model for future drug discovery efforts targeting other difficult proteins implicated in disease pathogenesis.

In conclusion, the collaboration between Insilico Medicine and Huadong Medicine Company showcases the transformative impact of integrating generative AI and physics-based modeling in uncovering novel therapeutic agents. This research not only delivers powerful WDR5 inhibitors with the potential to modulate the MYC oncogenic axis—a longstanding unmet challenge in oncology—but also validates an innovative drug discovery paradigm poised to revolutionize how next-generation medicines are designed and optimized.

Subject of Research: Discovery of small-molecule inhibitors targeting the WDR5-MYC protein–protein interaction using AI-driven generative chemistry and physics-based molecular modeling.

Article Title: (Not explicitly provided; refer to DOI link)

News Publication Date: May 28

Web References:

• Chemical Biology & Drug Design article: https://onlinelibrary.wiley.com/doi/10.1111/cbdd.70129
• Insilico Medicine website: https://insilico.com/
• Pharma.AI platform: https://pharma.ai/
• Previous Insilico concept article: https://pmc.ncbi.nlm.nih.gov/articles/PMC5355231/

References: DOI 10.1111/cbdd.70129 (journal article detailing the research)

Keywords

Medicinal chemistry, drug discovery, generative artificial intelligence, protein–protein interaction inhibitors, WDR5, MYC oncogene, pharmacophore modeling, molecular docking, physics-based molecular modeling, AI-driven chemistry, cancer therapeutics, small-molecule inhibitors