Summary
Tumor progression is dependent on the ability of malignant cells to escape the recognition and attack by the host immune system. The development of more efficient cancer immunotherapies has been hampered by the perplexity of immune escape mechanisms. I hypothesize that tumor genetic drivers dictate the immune escape mechanisms, and that these mechanisms can be exploited to develop more effective immunotherapeutic strategies for patients with high-grade serous ovarian cancer (HGSC), the most common and lethal ovarian cancer.
My group has developed an optimized algorithm based on homologous recombination (HR) DNA repair deficiency to enable clinically meaningful stratification of the complex HGSC genotypes. We will define the immunogenicity of the HGSC genotypes via profiling tumor somatic mutations and neoantigens, the cell-type specific gene expressions, and T/B cell receptor diversities using altogether >600 HGSC samples. Using a cutting-edge highly multiplexed technology and advanced image analysis, we will reveal the single-cell spatial landscapes of the tumor microenvironment in 200 immunogenetically-defined HGSCs. We will apply pioneering spatial analyses on the single-cell data and use artificial intelligence to uncover clinically relevant spatial biology of HGSCs. Via transcriptomic profiling of 384 spatial microregions, we will discover the detailed immune-escape mechanisms of the HGSC genotypes. For functional testing, we have developed a groundbreaking method to establish immune-competent patient-derived organoids (iPDOs), which faithfully recapitulate the patients' tumors. Using our high-throughput iPDO functional platform, we will test mechanism-specific immunotherapeutic approaches and capture the treatment responses at single-cell resolution. The discovery and functional targeting of the immune escape mechanisms gives us unprecedented potential to open new horizons in immunotherapeutic targeting of HGSC.
My group has developed an optimized algorithm based on homologous recombination (HR) DNA repair deficiency to enable clinically meaningful stratification of the complex HGSC genotypes. We will define the immunogenicity of the HGSC genotypes via profiling tumor somatic mutations and neoantigens, the cell-type specific gene expressions, and T/B cell receptor diversities using altogether >600 HGSC samples. Using a cutting-edge highly multiplexed technology and advanced image analysis, we will reveal the single-cell spatial landscapes of the tumor microenvironment in 200 immunogenetically-defined HGSCs. We will apply pioneering spatial analyses on the single-cell data and use artificial intelligence to uncover clinically relevant spatial biology of HGSCs. Via transcriptomic profiling of 384 spatial microregions, we will discover the detailed immune-escape mechanisms of the HGSC genotypes. For functional testing, we have developed a groundbreaking method to establish immune-competent patient-derived organoids (iPDOs), which faithfully recapitulate the patients' tumors. Using our high-throughput iPDO functional platform, we will test mechanism-specific immunotherapeutic approaches and capture the treatment responses at single-cell resolution. The discovery and functional targeting of the immune escape mechanisms gives us unprecedented potential to open new horizons in immunotherapeutic targeting of HGSC.
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| Web resources: | https://cordis.europa.eu/project/id/101076096 |
| Start date: | 01-02-2023 |
| End date: | 31-01-2028 |
| Total budget - Public funding: | 2 368 459,00 Euro - 2 368 459,00 Euro |
Cordis data
Original description
Tumor progression is dependent on the ability of malignant cells to escape the recognition and attack by the host immune system. The development of more efficient cancer immunotherapies has been hampered by the perplexity of immune escape mechanisms. I hypothesize that tumor genetic drivers dictate the immune escape mechanisms, and that these mechanisms can be exploited to develop more effective immunotherapeutic strategies for patients with high-grade serous ovarian cancer (HGSC), the most common and lethal ovarian cancer.My group has developed an optimized algorithm based on homologous recombination (HR) DNA repair deficiency to enable clinically meaningful stratification of the complex HGSC genotypes. We will define the immunogenicity of the HGSC genotypes via profiling tumor somatic mutations and neoantigens, the cell-type specific gene expressions, and T/B cell receptor diversities using altogether >600 HGSC samples. Using a cutting-edge highly multiplexed technology and advanced image analysis, we will reveal the single-cell spatial landscapes of the tumor microenvironment in 200 immunogenetically-defined HGSCs. We will apply pioneering spatial analyses on the single-cell data and use artificial intelligence to uncover clinically relevant spatial biology of HGSCs. Via transcriptomic profiling of 384 spatial microregions, we will discover the detailed immune-escape mechanisms of the HGSC genotypes. For functional testing, we have developed a groundbreaking method to establish immune-competent patient-derived organoids (iPDOs), which faithfully recapitulate the patients' tumors. Using our high-throughput iPDO functional platform, we will test mechanism-specific immunotherapeutic approaches and capture the treatment responses at single-cell resolution. The discovery and functional targeting of the immune escape mechanisms gives us unprecedented potential to open new horizons in immunotherapeutic targeting of HGSC.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
09-02-2023
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