Summary
Immune checkpoint blockade (ICB) has revolutionised treatment of patients with non-small cell lung cancer (NSCLC), but is effective in only ~20% of patients. Anti-tumour immunity is highly heterogeneous within tumours, and intra-tumour heterogeneity (ITH) is a major driver for treatment resistance. However, the mechanistic basis of intra-tumour immune heterogeneity (ITIH) is unclear, largely due to the absence of appropriate functional models.
Here, I aim to identify the genetic or transcriptomic drivers of ITIH, and their impact on immune surveillance and control. I have recently developed an organoid – T-cell co-culture system that I will use to generate personalised models of ITIH. Leveraging the TRACERx lung cancer evolution study, I will establish multiple clonal organoid lines from the same tumour from NSCLC multi-region biopsies. Each organoid subline will be co-cultured with autologous T-cells to evaluate how they differ in sensitivity to T-cells. For each patient, the 6 most sensitive and 6 most resistant sublines will be used for DNA and RNA sequencing to identify mutations (including neo-antigens), copy number alterations and differentially expressed genes associated with resistance to T-cells. Candidate subclonal immune evasion factors will be validated in organoids by CRISPR-Cas9. I will prioritise genes by cross-referencing with genes associated with immune-cold regions in the TRACERx cohort. I will also perform pooled enrichment screens as a less biased approach.
The integration of novel organoid technology with ‘big data’ from TRACERx allows moving beyond merely descriptive studies of ITIH. This will result in the most fine-grained mechanistic study of ITIH to date.
Here, I aim to identify the genetic or transcriptomic drivers of ITIH, and their impact on immune surveillance and control. I have recently developed an organoid – T-cell co-culture system that I will use to generate personalised models of ITIH. Leveraging the TRACERx lung cancer evolution study, I will establish multiple clonal organoid lines from the same tumour from NSCLC multi-region biopsies. Each organoid subline will be co-cultured with autologous T-cells to evaluate how they differ in sensitivity to T-cells. For each patient, the 6 most sensitive and 6 most resistant sublines will be used for DNA and RNA sequencing to identify mutations (including neo-antigens), copy number alterations and differentially expressed genes associated with resistance to T-cells. Candidate subclonal immune evasion factors will be validated in organoids by CRISPR-Cas9. I will prioritise genes by cross-referencing with genes associated with immune-cold regions in the TRACERx cohort. I will also perform pooled enrichment screens as a less biased approach.
The integration of novel organoid technology with ‘big data’ from TRACERx allows moving beyond merely descriptive studies of ITIH. This will result in the most fine-grained mechanistic study of ITIH to date.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101024529 |
| Start date: | 01-08-2021 |
| End date: | 31-07-2023 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original description
Immune checkpoint blockade (ICB) has revolutionised treatment of patients with non-small cell lung cancer (NSCLC), but is effective in only ~20% of patients. Anti-tumour immunity is highly heterogeneous within tumours, and intra-tumour heterogeneity (ITH) is a major driver for treatment resistance. However, the mechanistic basis of intra-tumour immune heterogeneity (ITIH) is unclear, largely due to the absence of appropriate functional models.Here, I aim to identify the genetic or transcriptomic drivers of ITIH, and their impact on immune surveillance and control. I have recently developed an organoid – T-cell co-culture system that I will use to generate personalised models of ITIH. Leveraging the TRACERx lung cancer evolution study, I will establish multiple clonal organoid lines from the same tumour from NSCLC multi-region biopsies. Each organoid subline will be co-cultured with autologous T-cells to evaluate how they differ in sensitivity to T-cells. For each patient, the 6 most sensitive and 6 most resistant sublines will be used for DNA and RNA sequencing to identify mutations (including neo-antigens), copy number alterations and differentially expressed genes associated with resistance to T-cells. Candidate subclonal immune evasion factors will be validated in organoids by CRISPR-Cas9. I will prioritise genes by cross-referencing with genes associated with immune-cold regions in the TRACERx cohort. I will also perform pooled enrichment screens as a less biased approach.
The integration of novel organoid technology with ‘big data’ from TRACERx allows moving beyond merely descriptive studies of ITIH. This will result in the most fine-grained mechanistic study of ITIH to date.
Status
TERMINATEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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