TRACERx

RNA sequencing data and tumour pathology observations of non-small-cell lung cancers indicate that the immune cell microenvironment exerts strong evolutionary selection pressures that shape the immune-evasion capacity of tumours.

A survey of T cell repertoire evolution in the tumors, healthy tissue and blood of patients with early-stage untreated lung cancer offers an opportunity to monitor and identify neoantigen-specific T cells for personalized immunotherapy.

TRACERx Lung: Intratumoral transcriptional heterogeneity, which often hinders the development of clinically useful RNA-expression-biased biomarkers for cancer, can now be overcome with an approach for the identification of clonal expression biomarkers.

Pulmonary venous tumor cells disseminating before tumor resection are heterogeneous, predict relapse and seed future metastasis of lung cancer

Analysis of whole-genome doubling (WGD) by using cancer sequencing data combined with simulations of tumor evolution suggests that there is negative selection against homozygous loss of essential genes before WGD but not after.

Multiregion spatial histology, exome and transcriptome data from patients with non-small cell lung cancer suggest that cancer subclones from immune cold regions diversify later than subclones from immune hot regions

Ghorani et al. use a multiomics approach to characterize the effect of tumour mutational burden on the differentiation of CD4 and CD8 T cell subpopulations in non-small cell lung cancer.

Analyses of multiregional tumour samples from 421 patients with non-small cell lung cancer prospectively enrolled to the TRACERx study reveal determinants of tumour evolution and relationships between intratumour heterogeneity and clinical outcome.

A longitudinal evolutionary analysis of 126 lung cancer patients with metastatic disease reveals the timing of metastatic divergence, modes of dissemination and the genomic events subject to selection during the metastatic transition.

Computational and machine-learning approaches that integrate genomic and transcriptomic variation from paired primary and metastatic non-small cell lung cancer samples from the TRACERx cohort reveal the role of transcriptional events in tumour evolution.

Measurements of subclonal expansion of ctDNA in the plasma before surgery may enable the prediction of future metastatic subclones, offering the possibility for early intervention in patients with non-small-cell lung cancer.

In lung adenocarcinoma, antibodies against endogenous retroviruses promote anti-tumour activity, and expression of endogenous retroviruses can predict outcomes of immunotherapy.

Analyses of the TRACERx study unveil the relationship between tissue morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk of lung adenocarcinomas.

Results of the TRACERx study shed new light into the association between body composition and body weight with survival in individuals with non-small cell lung cancer, and delineate potential biological processes and mediators contributing to the development of cancer-associated cachexia.

Yuan and colleagues developed an artificial intelligence-based method to derive growth patterns and morphological features from hematoxylin and eosin-stained slides of lung adenocarcinoma samples, for improved tumor grading and patient prognostication.

The first long-term study of how lung cancer evolves is revealing that therapies targeting multiple proteins in tumour cells could help to outpace the disease.

TRACERx is a multimillion pound project funded by Cancer Research UK. By mapping the differences between individual cancer cells in hundreds of patients, it aims to track lung cancer evolution in unprecedented detail.