Publications

The conformational landscapes of peptide/human leucocyte antigen (pHLA) protein complexes encompassing tumor neoantigens provide a rationale for target selection towards autologous T cell, vaccine, and antibody-based therapeutic modalities. Here, using complementary biophysical and computational methods, we characterize recurrent RAS_55-64 Q61 neoepitopes presented by the common HLA-A*01:01 allotype. We integrate sparse NMR restraints with Rosetta docking to determine the solution structure of NRAS^Q61K/HLA-A*01:01, which enables modeling of other common RAS_55-64 neoepitopes. Hydrogen/deuterium exchange mass spectrometry experiments alongside molecular dynamics simulations reveal differences in solvent accessibility and conformational plasticity across a panel of common Q61 neoepitopes that are relevant for recognition by immunoreceptors. Finally, we predict binding and provide structural models of NRAS^Q61K antigens spanning the entire HLA allelic landscape, together with in vitro validation for HLA-A*01:191, HLA-B*15:01, and HLA-C*08:02. Our work provides a basis to delineate the solution surface features and immunogenicity of clinically relevant neoepitope/HLA targets for cancer therapy.

Peptide-centric chimeric antigen receptors (PC-CARs) recognize oncoprotein epitopes displayed by cell-surface human leukocyte antigens (HLAs) and offer a promising strategy for targeted cancer therapy. We have previously developed a PC-CAR targeting a neuroblastoma-associated PHOX2B peptide, leading to robust tumor cell lysis restricted by two common HLA allotypes. Here, we determine the 2.1-angstrom crystal structure of the PC-CAR–PHOX2B–HLA-A*24:02–β₂m complex, which reveals the basis for antigen-specific recognition through interactions with CAR complementarity-determining regions (CDRs). This PC-CAR adopts a diagonal docking mode, where interactions with both conserved and polymorphic HLA framework residues permit recognition of multiple HLA allotypes from the A9 serological cross-reactive group, covering a combined global population frequency of up to 46.7%. Biochemical binding assays, molecular dynamics simulations, and structural and functional analyses demonstrate that high-affinity PC-CAR recognition of cross-reactive pHLAs necessitates the presentation of a specific peptide backbone, where subtle structural adaptations of the peptide are critical for high-affinity complex formation, and CAR T cell killing. Our results provide a molecular blueprint for engineering CARs with optimal recognition of tumor-associated antigens in the context of different HLAs, while minimizing cross-reactivity with self-epitopes.

Physical networks are ubiquitous in nature, but many of them possess a complex organizational structure that is difficult to recapitulate in artificial systems. This is especially the case in biomedical and tissue engineering, where the microstructural details of 3D cell scaffolds are important. Studies of biological networks—such as fibroblastic reticular cell (FRC) networks—have revealed the crucial role of network topology in a range of biological functions. However, cell scaffolds are rarely analyzed, or designed, using graph theory. To understand how networks affect adhered cells, 3D culture platforms capturing the complex topological properties of biologically relevant networks would be needed. In this work, we took inspiration from the small-world organization (high clustering and low path length) of FRC networks to design cell scaffolds. An algorithmic toolset was created to generate the networks and process them to improve their 3D printability. We employed tools from graph theory to show that the networks were small-world (omega factor, ω = -0.10 ± 0.02; small-world propensity, SWP = 0.74 ± 0.01). 3D microprinting was employed to physicalize networks as scaffolds, which supported the survival of FRCs. This work, therefore, represents a bioinspired, graph theory-driven approach to control the networks of microscale cell niches.

Tumors are intrinsically heterogeneous and it is well established that this directs their evolution, hinders their classification and frustrates therapy^1,2,3. Consequently, spatially resolved omics-level analyses are gaining traction^4,5,6,7,8,9. Despite considerable therapeutic interest, tumor metabolism has been lagging behind this development and there is a paucity of data regarding its spatial organization. To address this shortcoming, we set out to study the local metabolic effects of the oncogene c-MYC, a pleiotropic transcription factor that accumulates with tumor progression and influences metabolism^10,11. Through correlative mass spectrometry imaging, we show that pantothenic acid (vitamin B₅) associates with MYC-high areas within both human and murine mammary tumors, where its conversion to coenzyme A fuels Krebs cycle activity. Mechanistically, we show that this is accomplished by MYC-mediated upregulation of its multivitamin transporter SLC5A6. Notably, we show that SLC5A6 over-expression alone can induce increased cell growth and a shift toward biosynthesis, whereas conversely, dietary restriction of pantothenic acid leads to a reversal of many MYC-mediated metabolic changes and results in hampered tumor growth. Our work thus establishes the availability of vitamins and cofactors as a potential bottleneck in tumor progression, which can be exploited therapeutically. Overall, we show that a spatial understanding of local metabolism facilitates the identification of clinically relevant, tractable metabolic targets.

Circular extrachromosomal DNA (ecDNA) in patient tumors is an important driver of oncogenic gene expression, evolution of drug resistance and poor patient outcomes. Applying computational methods for the detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA-positive medulloblastoma were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. A subset of tumors harbored multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging and CRISPR inhibition experiments in medulloblastoma models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative ‘enhancer rewiring’ events on ecDNA. This study reveals the frequency and diversity of ecDNA in medulloblastoma, stratified into molecular subgroups, and suggests copy number heterogeneity and enhancer rewiring as oncogenic features of ecDNA.