Periodic Reporting for period 4 - BRAIN-MATCH (Matching CNS Lineage Maps with Molecular Brain Tumor Portraits for Translational Exploitation)
Okres sprawozdawczy: 2023-11-01 do 2024-12-31
Brain tumors are a leading cause of death among children. Despite recent advances in their diagnosis and classification, treatment strategies continue to fall short in significantly improving the overall quality of life for survivors. Current interventions, including surgery, radiation, and chemotherapy, often result in long-term cognitive and motor impairments. In some cases, these treatments fail to prevent tumor recurrence, which can be fatal.
Recent advances in molecular biology have highlighted the heterogeneity among tumors within a single class and their interactions with the surrounding tumor microenvironment. Comparing tumor tissue and normal brain development at the single-cell level has uncovered associations that were previously obscured in bulk analyses, while also revealing the complexity of tumor tissues.
This project proposes to deepen our understanding of pediatric brain tumor development by comparing it to normal human brain development. The objectives are as follows:
1. Enhance understanding of the tumor "cell of origin" by studying tumor and normal brain development at single-cell resolution.
2. Identify transcriptional regulatory mechanisms shared between tumors and their lineage of origin, while distinguishing genes specific to tumors.
3. Discover novel therapeutic targets, such as cell-surface proteins involved in cell-cell communication, signaling molecules, or intracellular regulatory proteins that may be addressed with existing or potential drugs.
4. Improve our understanding of tumor identity and heterogeneity, identifying key transcriptional regulators that govern these traits, which will enable the generation of more accurate tumor models.
5. Investigate mechanisms of tumor evolution, particularly focusing on the timing of oncogenic mutations that increase tumor aggressiveness, to inform new diagnostic strategies.
6. Create a detailed atlas of the hindbrain, including the cerebellum and lower brainstem, as these are common sites of pediatric brain tumors.
This comprehensive approach aimed to bridge gaps in current knowledge and advance therapeutic strategies for pediatric brain tumors.
Recent advances in molecular biology have highlighted the heterogeneity among tumors within a single class and their interactions with the surrounding tumor microenvironment. Comparing tumor tissue and normal brain development at the single-cell level has uncovered associations that were previously obscured in bulk analyses, while also revealing the complexity of tumor tissues.
This project proposes to deepen our understanding of pediatric brain tumor development by comparing it to normal human brain development. The objectives are as follows:
1. Enhance understanding of the tumor "cell of origin" by studying tumor and normal brain development at single-cell resolution.
2. Identify transcriptional regulatory mechanisms shared between tumors and their lineage of origin, while distinguishing genes specific to tumors.
3. Discover novel therapeutic targets, such as cell-surface proteins involved in cell-cell communication, signaling molecules, or intracellular regulatory proteins that may be addressed with existing or potential drugs.
4. Improve our understanding of tumor identity and heterogeneity, identifying key transcriptional regulators that govern these traits, which will enable the generation of more accurate tumor models.
5. Investigate mechanisms of tumor evolution, particularly focusing on the timing of oncogenic mutations that increase tumor aggressiveness, to inform new diagnostic strategies.
6. Create a detailed atlas of the hindbrain, including the cerebellum and lower brainstem, as these are common sites of pediatric brain tumors.
This comprehensive approach aimed to bridge gaps in current knowledge and advance therapeutic strategies for pediatric brain tumors.
To identify tumor “cells of origin,” we created a single-cell RNA sequencing (scRNA-seq) atlas of the human cerebellum, spanning neurogenesis to adulthood. This atlas captures all major neuronal and glial types—Purkinje neurons, granule cells, Bergman glia—and maps their developmental trajectories. We compared cerebellar tumors—medulloblastoma, posterior fossa ependymoma, pilocytic astrocytoma, and radiation-induced glioma (RIG)—to normal populations. Each tumor aligned with a distinct cerebellar lineage, revealing tumor-specific biology (PMIDs: 38029793, 37534924).Using this reference, we identified transcriptomic features shared between tumors and their matched normal cells, as well as tumor-specific differences. MHCII gene upregulation in pilocytic astrocytomas aligned with oligodendrocyte lineage. RIGs displayed unique profiles, supporting their classification as distinct tumor types (PMID: 37534924). We initiated functional studies on selected targets, including testing whether MHCII-expressing gliomas present tumor-specific peptides for CAR-T therapy. While key pathways have been identified, follow-up validation is ongoing and beyond the proposal scope. To study tumor heterogeneity, we generated a single-cell multiomic atlas of Group 3/4 medulloblastoma—the most comprehensive to date. It revealed transcription factor–gene regulatory networks (TF-GRNs) driving intra- and inter-tumor variation. We validated TFs that can reprogram tumor identity in vitro and in vivo, enabling models of underrepresented subtypes like non-MYC–driven tumors. For tumor evolution, we analyzed oncogene-driven subsets within this atlas. Single-cell copy number analysis showed MYC and MYCN as late events, while early tumorigenesis likely begins with large chromosomal alterations. Whole-genome sequencing and modeling placed tumor origin in the first trimester, with clonal expansion near birth—matching predicted cells of origin. Spatial single-cell profiling linked subclonal tumor regions to microenvironmental features, highlighting heterogeneity’s impact on tumor structure. These insights, published in Nature (PMID pending), reshape our understanding of medulloblastoma development.
We also built a single-nucleus RNA-seq atlas of the human lower brainstem (pons and medulla), profiling 400,000 cells across development. Like the cerebellar atlas, it maps glial and neuronal trajectories and represents the most complete dataset of human hindbrain development to date. Additionally, we produced single-nucleus ATAC-seq atlases of mouse (90,000 cells) and human (110,000 cells) cerebellar development. Integrated with RNA-seq data, these reveal gene regulatory elements and programs guiding hindbrain differentiation. Together, these efforts provide a high-resolution framework for understanding brain development and pediatric brain tumors—from origins and regulatory control to evolution and heterogeneity—informing future diagnostics and therapies.
We also built a single-nucleus RNA-seq atlas of the human lower brainstem (pons and medulla), profiling 400,000 cells across development. Like the cerebellar atlas, it maps glial and neuronal trajectories and represents the most complete dataset of human hindbrain development to date. Additionally, we produced single-nucleus ATAC-seq atlases of mouse (90,000 cells) and human (110,000 cells) cerebellar development. Integrated with RNA-seq data, these reveal gene regulatory elements and programs guiding hindbrain differentiation. Together, these efforts provide a high-resolution framework for understanding brain development and pediatric brain tumors—from origins and regulatory control to evolution and heterogeneity—informing future diagnostics and therapies.
We have generated single-nucleus ATAC-seq (snATAC-seq) datasets to profile cerebellar development in both mouse and human models. The mouse dataset comprises 90,000 cells across 11 developmental stages (published), while the human dataset includes 110,000 cells spanning 10 stages. Analysis of these data enabled the identification of putative cis-regulatory elements active during cerebellar development, the characterization of gene regulatory networks, and identification of core regulators defining cerebellar cell identity. Additionally, we developed sequence-based predictive models to estimate DNA accessibility in cerebellar cell types, which can be applied in future studies to assess the effects of cancer-related mutations and genomic rearrangements. We are also advancing a single-cell methylome protocol to compare cell type-specific methylation profiles between normal development and tumor types classified by methylation signatures. These methods are expected to complement our single-nucleus RNA-seq (snRNA-seq) atlases, as proposed, to enable more precise mapping of tumor classes and subtypes. Our single-cell multiomic human hindbrain atlas represents the most comprehensive dataset to date, cataloguing the diversity of neural cell types in this region and delineating their developmental trajectories. The analysis provides critical insights into gene regulatory mechanisms governing hindbrain cell types. Furthermore, we have generated a state-of-the-art Group 3/4 medulloblastoma single-cell multiomic atlas that has significantly refined our understanding of the regulatory networks driving tumor heterogeneity and development. This atlas also enabled tracing the evolutionary history and subclonality of oncogenic events contributing to tumor identity and aggressiveness. Findings were validated using two independent single-cell multiomic datasets (RNA & ATAC and DNA & RNA). To further enhance our analyses, we developed a novel computational method to identify copy number variations at the subclonal level using single-cell chromatin accessibility data. This method, freely available at https://github.com/kokonech/atacInferCnv(odnośnik otworzy się w nowym oknie) provides a valuable tool for characterizing tumor somatic genomic architecture at single-cell resolution.