This project is game-changing because it challenges the conventional approach of treating GBM with therapies that only induce apoptosis, a common cell death mechanism. Therapies that rely solely on triggering apoptosis is doomed to fail, as GBM cells often resist this type of cell death. We now know that apoptosis is just one of many ways a cell can die, and over the past decade, researchers have shown that alternative forms of cell death can also be induced. The Nathanson and Dixon Labs have discovered a new mechanism called palmoptosis, which could serve as a 'back door' to kill GBM cells resistant to apoptosis.

This project can help people with brain cancer by offering a new way to kill GBM cells, which are resistant to traditional treatments. The Nathanson and Dixon labs have discovered that a drug called tegavivint, already proven safe for humans, can penetrate the brain and kill cancer cells through activating a unique cell death mechanism called palmoptosis. Unlike the usual cell death process, apoptosis, palmoptosis provides a novel way to selectively target and kill GBM cells.

GBM is notoriously resistant to existing therapies, which primarily induce cell death through apoptosis. GBM cells often express high levels of anti-apoptotic proteins, rendering these treatments ineffective. Research from the Nathanson and Dixon labs indicate that therapies relying solely on apoptosis are destined to fail. Apoptosis is just one of many cell death mechanisms, and the combined research of the Nathanson and Dixon labs over the past decade has demonstrated the potential of triggering non-canonical forms of cell death. Both labs in collaboration have identified a novel mechanism, palmoptosis, which requires the lipid palmitate and related metabolic enzymes. Their preliminary data show that the drug tegavivint, currently in clinical trials, can selectively trigger palmoptosis in GBM cells. This collaborative grant between the Nathanson and Dixon labs combines expertise in GBM biology and drug discovery (Nathanson) with cell biology and chemical biology (Dixon) to establish palmoptosis as a new therapeutic approach for GBM.

The overarching aims of this collaborative grant includes:

Aim 1. Assess the role of lipid metabolism in mediating palmoptosis in glioblastoma.

Aim 2. Identify the molecular features of GBMs susceptible to palmoptosis

Aim 3. Evaluate the pharmacokinetics, anti-tumour efficacy of Tegavivint in orthotopic patient-derived xenograft models.

This project is game-changing because it tackles GBM in a novel way using advanced genomics and CRISPR lineage tracing techniques. It focuses on understanding the role of hypoxia, a condition of low oxygen levels within the tumour, and its contribution to the cancer’s aggressiveness and resistance to therapy. The researchers believe that special cells in these low-oxygen areas can survive treatment and cause the cancer to return. By identifying these resistant cells, the project could lead to new targeted therapies that halt tumour progression.

By understanding the role of hypoxia and cancer stem cells in tumour resistance and recurrence, the project could lead to the development of new therapies that target these aspects of GBM. This could potentially improve treatment outcomes, reduce the likelihood of recurrence, and ultimately, increase survival rates for patients with this aggressive form of cancer.

This grant is focused on studying the role of hypoxia in GBM recurrence. The team will use spatial transcriptomics and CRISPR/Cas-9 single-cell RNA-seq to understand the genomic and cellular aspects of hypoxia in GBM. They plan to identify hypoxic areas in tumours using pimonidazole, a hypoxia marker, in patients with primary and recurrent GBM as part of their ongoing clinical study. They will compare primary and recurrent patient samples to identify treatment-related alterations in the hypoxic tumour microenvironment. This project aims to understand how hypoxia influences tumour development by studying the lineage of cancer stem cells in hypoxic niches using CRISPR-based in-vivo single-cell lineage tracing xenograft models. The Zadeh lab hypothesize that these cells transition between cellular states to escape therapy mediated by hypoxia. The resulting data will generate a novel atlas of progressive adult gliomas that combines both spatial transcriptomics data and high-quality single-cell clonal information. This will allow them to investigate the regional relationship between cancer cells inside and outside of hypoxic niches, and to track how the cells within these hypoxic niches develop through the use of high-quality phylogenetic trees. The ultimate goal of the research is to uncover key hypoxia-driven signalling pathways that contribute to treatment resistance and GBM recurrence.

The overarching aims of this grant includes:

Aim 1: Decoding the spatial transcriptome architecture of hypoxia in GBM upon recurrence.
Aim 2: Tracing hypoxia-associated tumour cell lineages with CRISPR/Cas-9 Cellular Barcoding.

This project is game-changing because it proposes a novel approach to make immunotherapies effective against GBM. By genetically restoring T cell functionality and freeing them from the bone marrow in mice models, the researchers have observed that genetically altered mice can reject GBM and may survive long-term when administered immunotherapies that previously did not work. The project also involves the development of a new class of drug with the help of a Nobel Laureate and a group of medicinal chemists. This drug is anticipated to enhance the success of immunotherapies against GBM by restoring T cell number and function.

This project can help patients with brain cancer by potentially making immunotherapies effective against GBM. The new class of drug being developed could restore the number and function of T cells, enhancing the body’s immune response against the tumour. This could lead to improved survival rates and quality of life for patients with GBM and potentially other types of cancer that infiltrate the brain.

This grant is aimed at deriving pharmacologic reversal of T cell sequestration and restoration of T cell function in an effort to license immunotherapeutic success against GBM. The Fecci Lab have previously identified that T cells are sequestered in the bone marrow of patients with intracranial tumours, due to loss of the S1P1 receptor from the T cell surface. They have genetically shown that when S1P1 is restored in mice models, these mice reject GBM and may survive long-term when administered immunotherapies that did not previously work. To translate their findings, they have discovered that a compound that can prevent the loss of S1P1, restoring T- cell function. While this compound works exceedingly well outside the body, it is currently too unstable in the body to be useful as a drug. The Fecci lab has teamed up with a local non-profit group of medicinal chemists from RTI whose expertise is in modifying compounds to make them into useable drugs. This grant proposal aims to take this discovery and invent an entirely new class of drug that they anticipate will newly license immunotherapies success against GBM by restoring T cell number and function.

Only the genomic features (gene mutations) of a patient’s tumour are analysed at the time of diagnosis due to the limited availability of biopsy material. Although this may identify some genetic characteristics driving tumour growth, few of these mutations are targetable, with even less providing a survival benefit to patients. As DMG tumours are known to be highly heterogeneous (driver mutations vary greatly between and within patient tumours), I-DIMENSIONS seeks to understand the multiple layers influencing DMG across a large selection of tumours so that better-informed treatment strategies can be developed.

I-DIMENSIONS aims to provide medical and research scientists with new data that unlocks effective treatment strategies for DMG. By looking at tumours as a sum of their biological systems (rather than via a single-featured lens), we hope that the developed subtyping system will inform the creation of a therapy selection tool used by clinicians to extend the survival of children diagnosed with brain cancer in the future.

 I-DIMENSIONS is an Integrated Dmg/hgg genomIc Methylomic EpigeNetic Spatial transcrIptomic prOteomic subtypiNg System integrating tumour genomics data (whole genome sequencing–WGS), DNA methylation data (EPIC array) and chromatin landscapes (ATAC-seq) to group patients into methylo-epi-genomic subtypes at diagnosis. Evaluating the spatial heterogeneity (scRNAseq) and the abundance and activity of all proteins (phospho- and proteomic profiling) present in each specimen will provide the most comprehensive picture of the elements sustaining tumour growth, revealing targets to be addressed using precision medicines. Our approach will be informed by utilising 210 samples collected from collaborators worldwide (including about 17 patient samples from the Charlie Teo Foundation Brain Tumour Bank) and be developed by a multi-disciplinary team of international experts.

Critically, I-DIMENSIONS will identify the highly significant influences on the regulation of a tumour’s posttranslational architecture i.e. the non-genomic elements relating to the geographical location of the tumour. The role that endogenous and exogenous microenvironmental influences (such as neurological cues, catecholamines, insulin, growth factors, growth hormones and immune related interactions - scRNAseq), as well as treatment-related neuronal effects from radiotherapy, and corticosteroid use will dictate posttranscriptional and posttranslational effects, that cannot be replicated in in vitro laboratory models.

Hypothesis:

The development of a methylo-epi-genomic subtyping system predictive of the proteomic/phosphoproteomic components of each sample will enable the future stratification of patients into subtypes that are indicative of treatment response.

Aim 1: Develop a novel methylo-epi-genomic subtyping system for DMG.

Aim 2: Identify the key proteomic/phosphoproteomic signatures (drug targets) of each specimen used in the DMG methylo-epi-genomic subtyping system.

Aim 3: Identify the spatial heterogeneity of the disease and relate this back to the proteomic/phosphoproteomic signatures.

This project will generate a large source of genomics data on brain cancers, a crucial step in understanding the genomic variability of brain cancer. Further, Prof Powell will leverage expertise from machine-learning, biology, genetics and advanced biotechnology domains in an effort to unravel the deep complexities of brain cancer and find effective treatment strategies for brain cancer patients.

Brain cancer is one of the most lethal cancers, with few effective treatments available for patients. Moreover, a hallmark of brain tumours is its ability to resist treatment due to its complex and variable genetic make-up. By understanding this genetic complexity, Prof Powell’s research team aims to find the ‘bad actors’ responsible for brain cancers resisting treatment and find effective treatments.

Identifying therapeutic targets from cell state models in gliomas

Glioblastoma is one of the deadliest human cancers, due to its strong resistance to treatment following surgical removal. This resistance is driven by an intrinsic intra-tumoral heterogeneity, which is a hallmark of these tumours. To develop new treatments to overcome this cellular heterogeneity, a more detailed understanding of the nature and drivers of this variation is needed. Single-cell RNA sequencing of human tumours provides a powerful means to systematically interrogate the diversity of malignant and normal cell states.

Recent studies, as well as Prof Powell's work, have highlighted transcriptional cell state diversity across tumour types that is often independent of genetic clonal heterogeneity. His team has developed highly accurate machine learning methods that are able to use the transcriptional signature of a single cell and are able to accurately classify it into a specific cell state. The researchers are able to ‘map’ the within-tumour heterogeneity from thousands of cells in a single patient sample. Doing so over a large clinical cohort across different subtypes of adult diffuse gliomas including astrocytomas, oligodendrogliomas and glioblastomas will allow them to identity the variation in the within-tumour heterogeneity between patients and correlate those cell states with clinical features, recurrence, and treatment resistance. The relationship between cell states and state dynamics will be tested against disease history and clinical features for each cancer classification type (following WHO CNS5 framework).

This project builds on Prof Powell's current research which has been supported by the Charlie Teo Foundation. His team will extend their research into the identification of the genomic drivers of cell states and state dynamics that correlate with clinical outcomes, generating new data on targeted glioblastoma patient cohort, and developing the high-throughput cancer organoid systems to be able to perform high-throughput drug screening against specific tumour cell states.