Divide and conquer using patient derived tumour organoids to dissect intra tumo...
Divide and conquer using patient derived tumour organoids to dissect intra tumour immune heterogeneity of non small cell lung cancer
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-t...
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Project Information TxImmuneOrganoids
Project duration: 28 months
Date Start: 2021-03-30
End date: 2023-07-31
participation deadline
Sin fecha límite de participación.
Project 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.