Environmental carcinogenic exposures are major contributors to global disease burden yet how they promote cancer is unclear. Over 70 years ago, the concept of tumour promoting agents driving latent clones to expand was rst proposed. In support of this model, recent evidence suggests that human tissue contains a patchwork of mutant clones, some of which harbour oncogenic mutations, and many environmental carcinogens lack a clear mutational signature. We hypothesised that the environmental carcinogen, <2.5μm particulate matter (PM2.5), might promote lung cancer promotion through nonmutagenic mechanisms by acting on pre-existing mutant clones within normal tissues in patients with lung cancer who have never smoked, a disease with a high frequency of EGFR activating mutations. We analysed PM2.5 levels and cancer incidence reported by UK Biobank, Public Health England, Taiwan Chang Gung Memorial Hospital (CGMH) and Korean Samsung Medical Centre (SMC) from a total of 463,679 individuals between 2006-2018. We report associations between PM2.5 levels and the incidence of several cancers, including EGFR mutant lung cancer. We nd that pollution on a background of EGFR mutant lung epithelium promotes a progenitor-like cell state and demonstrate that PM accelerates lung cancer progression in EGFR and Kras mutant mouse lung cancer models. Through parallel exposure studies in mouse and human participants, we nd evidence that in ammatory mediators, such as interleukin-1 , may act upon EGFR mutant clones to drive expansion of progenitor cells. Ultradeep mutational pro ling of histologically normal lung tissue from 247 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 33% of normal tissue samples, respectively. These results support a tumour-promoting role for PM acting on latent mutant clones in normal lung tissue and add to evidence providing an urgent mandate to address air pollution in urban areas.

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource.

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy 1,2 . However, measuring tumour infiltrating lymphocytes (TILs) is restricted by lack of appropriate data. Whole exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations.Here we develop a method for T cell fraction estimation from WES samples, utilising a signal from T cell receptor excision circle (TRECs) loss during VDJ recombination of the T cell receptor alpha (TCRA) gene. This score significantly correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma and using a meta-analysis of immunotherapy-treated tumours, we show that this score predicts immunotherapy response, providing value beyond tumour mutational burden. Applying this score to a multi-sample pancancer cohort revealed high diversity in immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, was associated with reduced TCRA T cell fraction. Our method, T cell ExTRECT (T cell Exome TREC Tool), quantifies the T cell infiltrate of WES samples.Here we propose a method for the estimation of the T cell fraction present in a WES sample. This method utilises a somatic copy number-based signal from VDJ recombination and the loss of TRECs. We explore the underlying features which predict T cell infiltrate in tumours and blood and evaluate determinants of immune heterogeneity within tumours. Finally, we demonstrate that our estimated T cell fraction can be used as a predictor of clinical response to CPI therapy. Results Inferring T cell fraction from WES dataT cell diversity, which is required for immune system recognition of foreign antigens, is a product of VDJ recombination, where segments within the T cell receptor genes recombine.The alpha chain of the T cell receptor is encoded by the TCRA gene (also known as TRA) and the result of VDJ recombination is the excision of unselected gene segments from TCRA as TRECs, with the T cell undergoing a deletion event within TCRA.Tools to infer cancer somatic copy number alteration (SCNA) [6][7][8][9] rely on the read depth ratio (RDR), reflecting the log of the ratio of reads between the tumour sample and its matched control (e.g. buffy coat in a centrifuged blood sample). Deviation in the RDR from zero is assumed to reflect a tumour SCNA. However, within TCRA this assumption does not hold; a deviance in the RDR may reflect T cell specific deletion events and SCNA tools may thus erroneously infer tumour SCNA. Indeed, in the TRACERx100 cohort multiple SCNA within TCRA were inferred in 165/327 tumour regions (Extended Data Fig. 1a). The RDR deviated the most within segments frequently included within TRECs (Extended Data Fig. 1b-c). This suggests that most detected SCNAs within TCRA...

Murine tissues harbor signature γδ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γδ cells are less well defined. In the present study, we show that human lung tissues harbor a resident Vδ1 γδ T cell population. Moreover, we demonstrate that Vδ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral Vδ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8+ T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA−CD27− effector memory Vδ1 T cells in tumors and, most strikingly, with the numbers of CD103+ tissue-resident Vδ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating Vδ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer.

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Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic–transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary–metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

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