Search

In the TRACERx cohort of 171 patients with lung cancer, the ultrasensitive detection of ctDNA improves preoperative patient stratification, also in early-stage disease.

Circulating tumour DNA profiling in early-stage non-small-cell lung cancer can be used to track single-nucleotide variants in plasma to predict lung cancer relapse and identify tumour subclones involved in the metastatic process.

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.

Combination of epidemiology, preclinical models and ultradeep DNA profiling of clinical cohorts unpicks the inflammatory mechanism by which air pollution promotes lung cancer

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.

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.

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.

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.

Major histocompatibility complex (MHC) loss of heterozygosity, allele-specific mutation and measurement of expression and repression (MHC Hammer) detects disruption to human leukocyte antigens due to mutations, loss of heterogeneity, altered gene expression or alternative splicing. Applied to lung and breast cancer datasets, the tool shows that these aberrations are common across cancer and can have clinical implications.

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.

Patient-derived xenografts are important tools for cancer drug development. Here, the authors develop models from 22 non-small cell lung cancer patients. They show genomic differences between models created from different spatial regions of tumours and a bottleneck on model establishment.

Mixed responses to targeted therapy within a patient are a clinical challenge. Here the authors show that TP53 loss-of-function cooperates with whole genome doubling which increases chromosomal instability. This leads to greater cellular diversity and multiple routes of resistance, which in turn promotes mixed responses to treatment.

A robust, cost-effective technique based on whole-exome sequencing data can be used to characterize immune infiltrates, relate the extent of these infiltrates to somatic changes in tumours, and enables prediction of tumour responses to immune checkpoint inhibition therapy.

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.

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

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.

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.

Wu et al. utilize multiparametric analysis of early-stage human NSCLC to characterize a population of Vδ1 T cells displaying a resident memory and effector memory phenotype, which were associated with ongoing remission.

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.

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.

Liquid biopsy approaches hold great promise in early cancer diagnosis or minimal residual disease monitoring for cancer recurrence. Herein, the authors evaluate contemporary next-generation sequencing approaches to circulating tumour DNA detection in these contexts, with a focus on studies in patients with non-small-cell lung cancer. They discuss the feasibility of introducing these strategies into the clinic, highlighting the technical and analytical challenges, as well as possible solutions.

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.

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