ImmuneMetTx

Lead Research Organisation: The Francis Crick Institute
Department Name: Research

Abstract

Immune checkpoint inhibitors (CPIs), which have revolutionised the treatment of metastatic NSCLC and other tumour types, increase the anti- tumour immune response through T-cell activation. However, clinical experience has revealed that more than 50% of patients present with intrinsic or develop acquired treatment resistance to immune therapies. It is unclear whether immunoediting, a set of processes that cause selection for cancer cells resilient to immune attacks, play an essential role in CPI resistance. To properly study immunoediting through cancer progression, it is essential to reconstruct the evolutionary history of cancer cell-intrinsic immunoediting processes - for example through loss of HLA alleles-, and the roles played by the tumour microenvironment in mediating immune selection pressures. To do that, comprehensive sampling and characterisation of a clinical cohort of primary tumours and the corresponding metastases are needed. Such datasets are scarce and where available, include data from only a few individuals
In this project, I aim to quantify mechanisms of immunoediting in longitudinal multi-region samples collected at the time of surgery, relapse, and autopsy to answer fundamental questions about how the immune system shapes cancer evolution and the role of immunoediting in CPI failure. This analysis will be made possible by the TRACERx, PEACE studies and the DARWIN II clinical trial, managed by the host lab. I will integrate different data, including 500X whole-exome sequencing, Imaging Mass Cytometry, evolutionary reconstruction and detailed clinical annotation, to do an unprecedented analysis of the spatial and temporal heterogeneity of immunoediting mechanisms, and how they relate to features of the cancer genome, transcriptome, tumour microenvironment and CPI responses.
 
Description By integrating data from multiple lung-cancer cohorts, together with cohorts where normal lung has been sequenced, we have seen the relationship between certain genomic alterations in the tumours and their impact on the surrounding cells (the microenvironment). For example, tumours from patients that never smoked tend to have a distinct microenvironment compared to those arising from patients that smoke or have smoked in the past. We are currently investigating how this influences the genomic make-up of the tumour (eg, whether the immune system deletes clones harbouring certain mutations that can generate strong immune responses).
The TRACERx and PEACE data also allows us to infer how much these states are heterogeneous within the same tumour - we are observing certain types of microenvironments that tend to cooccur in the same patient more than expected. Finally, the TRACERx data also allow us to study these changes across tumour evolution. For example, we observed how cisplatin, a common treatment in lung cancer, diminishes the amount of T cells (a type of immune cell). All these and other findings will be published in a peer reviewed journal.

Besides the scientific output of this work, we are also providing a framework to integrate both clinical, DNAseq and RNAseq using state-of-the-art methods that can be leveraged to study other tumour types, such as breast cancer or colorectal cancer.

In summary, the integration of several cohorts, including TRACERx, offers an unprecedented opportunity to study lung cancer evolution. One of the most important outcomes of this research will also be sharing the data with the scientific community so that further advances can be made upon our research.
Exploitation Route Our research opens the door to future endeavours related to cancer evolution in the context of certain microenvironments in other tumour types. Our generated dataset will also help lung cancer researchers as it is to the best of our knowledge the biggest cohort of lung cancer data uniformly processed to date.
Sectors Healthcare