Could tumour diversity be resulting in poor treatment outcomes?

Despite many years of clinical research into lung cancer, the outcomes for patients diagnosed with the disease remain poor. Most patients present with advanced disease, resulting in limited treatment options, and of the few diagnoses that occur during early-stage disease, many patients don’t receive curative treatment with the disease eventually recurring.

The most common form of lung cancer is non-small cell lung cancer (NSCLC).

Researchers understood that tumour evolution played a role in clinical outcomes and knew that different parts of a tumour could evolve independently. Researchers hypothesised that a broader diversity of genetic mutations and chromosomal abnormalities within a tumour might be associated with poorer outcomes.

The need for genetic profiling and role of NCRI Lung Group

Researchers from the NCRI Lung Group identified the need for genetic profiling to examine how lung cancers mutate, adapt and become resistant to treatments. Professor Charles Swanton and Dr Mariam Jamal-Hanjani presented the idea for TRACERx to the group in 2013. Members of the screening and early diagnosis and advanced disease subgroups, spanning surgery, pathology, radiology and oncology in addition to members of the NCRI Consumer Forum worked together to implement the ground-breaking study.

An image representing TRACERx being presented to the NCRI Lung Group
Professor Charles Swanton and Dr Mariam Jamal-Hanjani presented the idea for TRACERx to the group in 2013.

TRACERx (TRAcking Cancer Evolution through therapy (Rx))

TRACERx has brought together a network of experts from across the UK to transform the understanding of NSCLC by analysing intratumor heterogeneity in tumours and tracking their evolutionary trajectory from diagnosis through to relapse. This involves the study of the genetic landscape, but also the tumour microenvironment.

Researchers have recruited over 700 lung cancer patients and took tumour samples at the time of surgery and at relapse, where possible, as well as collecting blood samples to gather circulating DNA and circulating tumour cells. Each patient is followed up for five years resulting in one of the most extensive longitudinal data sets collected for lung cancer.

Clinical applications of TracerX

Early on during the study, researchers identified that copy number variation within tumour samples, specifically tumours that were more heterogeneous in copy number, corresponded directly to worse clinical outcomes.

When researchers looked at circulating tumour DNA, they identified that they could detect tumour DNA within blood samples and predict patient relapse ahead of a tumour becoming visible on a scan. This knowledge could determine which patients could benefit from additional treatment and will be investigated in future clinical trials.

Throughout the study, researchers monitored patients immune responses by analysing both blood and tissue and gathered evidence of immune system evasion within tumour cells, which may have implications for patients response to immunotherapy treatment. Researchers are now able to identify mutations present in every cell in a patient’s tumour, which offers the opportunity of developing personalised therapies.

By increasing the understanding of the tumour microenvironment, researchers can develop better tests that use AI to predict clinical outcomes from biopsies-giving clinicians more tools and information when making treatment decisions.

Demonstrating multi-disciplinary collaboration opportunities

The TRACERx study has led to a considerable number of additional collaborations.

TRACERx tumour evolutionary analyses have helped establish the scientific rationale for the targeting of clonal neo-antigens currently being investigated in the CHIRON study. Developed by Achilles Therapeutics, the trial is evaluating clonal neoantigen T cell therapy in patients with advance NSCLC. Achilles Therapeutics manufacture the personalised T cell therapy after predicting tumour neoantigens, using a platform developed and validated using TRACERx sequence data.

DARWIN I aims to explore whether patients with NSCLC with recurrent disease and EGFR/HER2 mutations, including several patients from the TRACERx study, have better outcomes after treatment with afatinib, compared with those who have a subclonal variation.

In patients with actionable BRAF mutations, HER2 amplification and HER2 IHC 3+, or ALK/RET gene fusions, DARWIN II aims to assess the role of clonal dominance and outcome after treatment with vemurafenib, trastuzumab emtansine, and alectinib, respectively.