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Integrated multi-omic analyses using samples from the TRACERx study highlight cross-talk between DNA hypermethylation and genomic lesions in non-small cell lung cancer.

Symbiotic fungi control network-level structure and flows to meet trade demands.

Immune lymphocyte estimation from nucleotide sequencing (ImmuneLENS) infers B cell and T cell fractions from whole-genome sequencing data. Applied to the 100,000 Genomes Project datasets, circulating T cell fraction provides sex-dependent and prognostic insights in patients.

Swanton and colleagues present a clonal expression signature, ORACLE, which, in combination with clinicopathological and molecular risk factors, can predict survival of patients with lung adenocarcinoma, and they prospectively validate its prognostic value.

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.

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.

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.

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

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.

The genome of the gibbon, a tree-dwelling ape from Asia positioned between Old World monkeys and the great apes, is presented, providing insights into the evolutionary history of gibbon species and their accelerated karyotypes, as well as evidence for selection of genes such as those for forelimb development and connective tissue that may be important for locomotion through trees.

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.

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

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.

In an inter-laboratory study, the authors compare the accuracy and performance of three optical density calibration protocols (colloidal silica, serial dilution of silica microspheres, and colony-forming unit (CFU) assay). They demonstrate that serial dilution of silica microspheres is the best of these tested protocols, allowing precise and robust calibration that is easily assessed for quality control and can also evaluate the effective linear range of an instrument.