MHC Hammer reveals genetic and non-genetic HLA disruption in cancer evolution.

Disruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. We developed major histocompatibility complex loss of heterozygosity (LOH), allele-specific mutation and measurement of expression and repression (MHC Hammer). We identified extensive variability in HLA allelic expression and pervasive HLA alternative splicing in normal lung and breast tissue. In lung TRACERx and lung and breast TCGA cohorts, 61% of lung adenocarcinoma (LUAD), 76% of lung squamous cell carcinoma (LUSC) and 35% of estrogen receptor-positive (ER+) cancers harbored class I HLA transcriptional repression, while HLA tumor-enriched alternative splicing occurred in 31%, 11% and 15% of LUAD, LUSC and ER+ cancers. Consistent with the importance of HLA dysfunction in tumor evolution, in LUADs, HLA LOH was associated with metastasis and LUAD primary tumor regions seeding a metastasis had a lower effective neoantigen burden than non-seeding regions. These data highlight the extent and importance of HLA transcriptomic disruption, including repression and alternative splicing in cancer evolution.

Understanding nightmares after traumatic events in Detroit (UNiTED): prospective associations with interpersonal violence and posttraumatic stress disorder symptoms.

ABSTRACTBackground: Research suggests trauma-related nightmares (TRNs) during the acute aftermath of trauma may contribute to posttraumatic stress disorder (PTSD). However, it is unknown who is most vulnerable to TRNs, which is critical to identify at-risk patients toward whom early nightmare-focused treatments can be targeted to prevent PTSD.Objective: We tested trauma type (interpersonal violence [e.g. assault] vs non-interpersonal trauma [e.g. motor vehicle collision]) as a risk factor for TRNs in a predominantly low-income, Black, urban sample in Detroit, MI, USA.Method: We recruited patients from the intensive care unit following traumatic injury (N = 88; Mage = 39.53 ± SD 14.31 years, 67.0% male, 67.0% Black, 47.7% annual income ≤ $20,000) and administered surveys at three post trauma timepoints: one week (T1), one month (T2; n = 61), and two months (T3; n = 59). Trauma type was assessed at T1 via electronic medical records. Participants reported the extent to which their dreams' content was similar to the trauma for which they were hospitalized across T1-T3. Participants then completed the PTSD Checklist for DSM-5 at T3.Results: TRNs were more prevalent over time among patients exposed to interpersonal violence (80%) vs non-interpersonal trauma (48.7%, p = .005). Patients hospitalized for interpersonal violence faced greater odds for TRNs across timepoints relative to non-interpersonal trauma patients (Odds Ratio = 4.95, p = .021). TRNs, in turn, prospectively predicted PTSD symptoms such that TRNs at T2 presaged more severe PTSD at T3 (p = .040, ηp2 = .31), above and beyond T1 PTSD status.Conclusions: This prospective study provides first evidence that interpersonal violence exposure is a robust risk factor for TRNs, which prospectively contribute to PTSD symptom development. Early intervention on TRNs after interpersonal violence exposure may decrease PTSD risk. Future studies are encouraged to use ambulatory methods to capture nightmares sooner after they occur.

Interpersonal violence exposure is a risk factor for trauma-related nightmaresTrauma-related nightmares predict PTSD symptoms, above and beyond baseline PTSDTreating nightmares early after interpersonal violence may decrease PTSD risk.

Second Primary Lung Cancer - An Emerging Issue in Lung Cancer Survivors.

As a result of an increased focus on early detection including lung cancer screening, combined with more curative treatment options, the 5-year survival rates for lung cancer are improving. Welcome though this is, it brings new, hitherto unseen challenges. As more patients are cured and survive longer, they are at risk of developing second primary cancers, particularly lung cancer. In this review, we examine the challenges that surveillance, diagnosis, and management of second primary lung cancer (SPLC) bring and how these can be addressed. Recent data from prospective follow-up studies suggests that the incidence of SPLC may be higher than previously appreciated, partly due to an increase in multi-focal adenocarcinoma spectrum disease. Over 5 years, up to 1 in 6 long-term lung cancer survivors may develop a SPLC. Although not routinely used in clinical practice at present, genomic approaches for differentiating SPLC from intrapulmonary metastases of the first primary are emerging, and we highlight how this could be used to help differentiate lesions. An accurate distinction between SPLC and the recurrence of the first primary is of paramount importance due to the very different management strategies that may be required. Wrongly classifying an SPLC as a recurrence of the first primary may have significant consequences for patient management and overall survival. Updated approaches to the classification of SPLC combining clinical history, histopathological assessment, and genomic profiling are needed. Finally, we review the potential role of early detection biomarkers in the identification of SPLC, focusing in particular on blood-based biomarkers that are being examined in a multi-center prospective study recruiting lung cancer survivors.

Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling.

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

Whole Genome Sequencing of Mycobacterium tuberculosis under routine conditions in a high-burden area of multidrug-resistant tuberculosis in Peru.

Whole Genome Sequencing (WGS) is a promising tool in the global fight against tuberculosis (TB). The aim of this study was to evaluate the use of WGS in routine conditions for detection of drug resistance markers and transmission clusters in a multidrug-resistant TB hot-spot area in Peru. For this, 140 drug-resistant Mycobacterium tuberculosis strains from Lima and Callao were prospectively selected and processed through routine (GenoType MTBDRsl and BACTEC MGIT) and WGS workflows, simultaneously. Resistance was determined in accordance with the World Health Organization mutation catalogue. Agreements between WGS and BACTEC results were calculated for rifampicin, isoniazid, pyrazinamide, moxifloxacin, levofloxacin, amikacin and capreomycin. Transmission clusters were determined using different cut-off values of Single Nucleotide Polymorphism differences. 100% (140/140) of strains had valid WGS results for 13 anti-TB drugs. However, the availability of final, definitive phenotypic BACTEC MGIT results varied by drug with 10-17% of invalid results for the seven compared drugs. The median time to obtain results of WGS for the complete set of drugs was 11.5 days, compared to 28.6-52.6 days for the routine workflow. Overall categorical agreement by WGS and BACTEC MGIT for the compared drugs was 96.5%. Kappa index was good (0.65≤k≤1.00), except for moxifloxacin, but the sensitivity and specificity values were high for all cases. 97.9% (137/140) of strains were characterized with only one sublineage (134 belonging to "lineage 4" and 3 to "lineage 2"), and 2.1% (3/140) were mixed strains presenting two different sublineages. Clustering rates of 3.6% (5/140), 17.9% (25/140) and 22.1% (31/140) were obtained for 5, 10 and 12 SNP cut-off values, respectively. In conclusion, routine WGS has a high diagnostic accuracy to detect resistance against key current anti-TB drugs, allowing results to be obtained through a single analysis and helping to cut quickly the chain of transmission of drug-resistant TB in Peru.

Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides.

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models.

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer.

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis. SIGNIFICANCE: This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma.

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma.

Short oral regimens for pulmonary rifampicin-resistant tuberculosis (TB-PRACTECAL): an open-label, randomised, controlled, phase 2B-3, multi-arm, multicentre, non-inferiority trial.

BACKGROUND: Around 500 000 people worldwide develop rifampicin-resistant tuberculosis each year. The proportion of successful treatment outcomes remains low and new treatments are needed. Following an interim analysis, we report the final safety and efficacy outcomes of the TB-PRACTECAL trial, evaluating the safety and efficacy of oral regimens for the treatment of rifampicin-resistant tuberculosis. METHODS: This open-label, randomised, controlled, multi-arm, multicentre, non-inferiority trial was conducted at seven hospital and community sites in Uzbekistan, Belarus, and South Africa, and enrolled participants aged 15 years and older with pulmonary rifampicin-resistant tuberculosis. Participants were randomly assigned, in a 1:1:1:1 ratio using variable block randomisation and stratified by trial site, to receive 36-80 week standard care; 24-week oral bedaquiline, pretomanid, and linezolid (BPaL); BPaL plus clofazimine (BPaLC); or BPaL plus moxifloxacin (BPaLM) in stage one of the trial, and in a 1:1 ratio to receive standard care or BPaLM in stage two of the trial, the results of which are described here. Laboratory staff and trial sponsors were masked to group assignment and outcomes were assessed by unmasked investigators. The primary outcome was the percentage of participants with a composite unfavourable outcome (treatment failure, death, treatment discontinuation, disease recurrence, or loss to follow-up) at 72 weeks after randomisation in the modified intention-to-treat population (all participants with rifampicin-resistant disease who received at least one dose of study medication) and the per-protocol population (a subset of the modified intention-to-treat population excluding participants who did not complete a protocol-adherent course of treatment (other than because of treatment failure or death) and those who discontinued treatment early because they violated at least one of the inclusion or exclusion criteria). Safety was measured in the safety population. The non-inferiority margin was 12%. This trial is registered with ClinicalTrials.gov, NCT02589782, and is complete. FINDINGS: Between Jan 16, 2017, and March 18, 2021, 680 patients were screened for eligibility, of whom 552 were enrolled and randomly assigned (152 to the standard care group, 151 to the BPaLM group, 126 to the BPaLC group, and 123 to the BPaL group). The standard care and BPaLM groups proceeded to stage two and are reported here, post-hoc analyses of the BPaLC and BPaL groups are also reported. 151 participants in the BPaLM group and 151 in the standard care group were included in the safety population, with 138 in the BPaLM group and 137 in the standard care group in the modified intention-to-treat population. In the modified intention-to-treat population, unfavourable outcomes were reported in 16 (12%) of 137 participants for whom outcome was assessable in the BPaLM group and 56 (41%) of 137 participants in the standard care group (risk difference -29·2 percentage points [96·6% CI -39·8 to -18·6]; non-inferiority and superiority p<0·0001). 34 (23%) of 151 participants receiving BPaLM had adverse events of grade 3 or higher or serious adverse events, compared with 72 (48%) of 151 participants receiving standard care (risk difference -25·2 percentage points [96·6% CI -36·4 to -13·9]). Five deaths were reported in the standard care group by week 72, of which one (COVID-19 pneumonia) was unrelated to treatment and four (acute pancreatitis, suicide, sudden death, and sudden cardiac death) were judged to be treatment-related. INTERPRETATION: The 24-week, all-oral BPaLM regimen is safe and efficacious for the treatment of pulmonary rifampicin-resistant tuberculosis, and was added to the WHO guidance for treatment of this condition in 2022. These findings will be key to BPaLM becoming the preferred regimen for adolescents and adults with pulmonary rifampicin-resistant tuberculosis. FUNDING: Médecins Sans Frontières.

Human Cytomegalovirus Immunoglobulin G Response and Pulmonary Tuberculosis in Adolescents: A Case-Control Study.

Background: Emerging evidence suggests a link between infection with herpes viruses, particularly human cytomegalovirus (HCMV) and Epstein-Barr virus (EBV), and progression to tuberculosis disease. Methods: An unmatched case-control study was conducted among adolescents aged 10-19 years enrolled in an observational study (Teen TB) between November 2020 and November 2021, in Cape Town, South Africa. Fifty individuals with pulmonary tuberculosis and 51 healthy tuberculosis-exposed individuals without tuberculosis were included. Demographics and clinical data were obtained, and serum samples collected at enrolment were tested for HCMV immunoglobulin G (IgG) and EBV nuclear antigen (EBNA) IgG using 2 automated enzyme immunoassays. Odds ratios were estimated using unconditional logistic regression. Results: The median age of 101 participants was 15 years (interquartile range, 13-17 years); 55 (54%) were female. All participants were HCMV IgG seropositive, and 95% were EBNA IgG seropositive. Individuals with tuberculosis had higher HCMV IgG titers than healthy controls (P = .04). Individuals with upper-tertile HCMV IgG titers had 3.67 times greater odds of pulmonary tuberculosis than those with IgG titers in the lower tertile (95% confidence interval, 1.05-12.84; P = .04). There was a trend for increasing odds of pulmonary tuberculosis with increasing titers of HCMV IgG (P = .04). In contrast, there was no association between tuberculosis and higher EBNA IgG values. Conclusions: There is a high prevalence of sensitization to HCMV and EBV among adolescents in this high-tuberculosis-burden setting. Higher HCMV IgG titers were associated with pulmonary tuberculosis in adolescents.

Baseline Cytomegalovirus Viremia at Cryptococcal Meningitis Diagnosis Is Associated With Long-term Increased Incident TB Disease and Mortality in a Prospective Cohort of Ugandan Adults With HIV.

Background: Adults with HIV-associated cryptococcal meningitis have overlapping burdens of cytomegalovirus (CMV) and tuberculosis (TB) coinfections. CMV infection/reactivation is strongly associated with CMV-specific memory T-cell activation and upregulation of type 1 interferons, which may lead to increased risk of TB disease and poor outcomes. Methods: We conducted a cohort study of 2-week survivors of cryptococcal meningitis during 2010-2021 to determine TB incidence and all-cause mortality over time stratified by baseline CMV status. Results: We followed 497 Ugandans with HIV-associated cryptococcal meningitis for a median (interquartile range) of 4.6 (2.6-53.9) months. Overall, 42% (210/497) developed incident TB disease or died. One-fifth (98/497, 19.7%) developed incident TB disease, and 29% (142/497) of participants died during follow-up. Of 259 participants with CMV viral load measured at baseline, 37% (96/259) had concurrent CMV viremia (defined as anyone with detectable CMV DNA in plasma/serum by qualitative polymerase chain reaction [PCR] detection). Of 59 with measured CMV immunoglobulin G (IgG), 100% had positive CMV IgG antibody serology (≥10 enzyme-linked immunosorbent assay units/mL). CMV viremia was positively associated with higher HIV viral load (196 667 vs 73 295 copies/mL; P = .002) and higher cerebrospinal fluid fungal burden (68 500 vs 14 000 cfu/mL; P = .002) compared with those without. Participants with high-level CMV viremia (defined as CMV viral load ≥1000 IU/mL) had twice the risk of incident TB (subdistribution adjusted hazard ratio [aHR], 2.18; 95% CI, 1.11-4.27) and death (aHR, 1.99; 95% CI, 1.14-3.49) compared with participants with no or low-level CMV viremia. There was no association between the CMV IgG index and the incidence of TB/death (P = .75). Conclusions: CMV viremia >1000 IU/mL at meningitis diagnosis was associated with increased incident TB disease and mortality during long-term follow-up. Future studies to determine the causal relationship and potential for therapeutic intervention are warranted.

SARS-CoV-2 infection and pulmonary tuberculosis in children and adolescents: a case-control study.

BACKGROUND: The Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) pandemic has had an impact on the global tuberculosis (TB) epidemic but evidence on the possible interaction between SARS-CoV-2 and TB, especially in children and adolescents, remains limited. We aimed to evaluate the relationship between previous infection with SARS-CoV-2 and the risk of TB in children and adolescents. METHODS: An unmatched case-control study was conducted using SARS-CoV-2 unvaccinated children and adolescents recruited into two observational TB studies (Teen TB and Umoya), between November 2020 and November 2021, in Cape Town, South Africa. Sixty-four individuals with pulmonary TB (aged < 20 years) and 99 individuals without pulmonary TB (aged < 20 years) were included. Demographics and clinical data were obtained. Serum samples collected at enrolment underwent quantitative SARS-CoV-2 anti-spike immunoglobulin G (IgG) testing using the Abbott SARS-CoV-2 IgG II Quant assay. Odds ratios (ORs) for TB were estimated using unconditional logistic regression. RESULTS: There was no statistically significant difference in the odds of having pulmonary TB between those who were SARS-CoV-2 IgG seropositive and those who were seronegative (adjusted OR 0.51; 95% CI: 0.23-1.11; n = 163; p = 0.09). Of those with positive SARS-CoV-2 serology indicating prior infection, baseline IgG titres were higher in individuals with TB compared to those without TB (p = 0.04) and individuals with IgG titres in the highest tertile were more likely to have pulmonary TB compared to those with IgG levels in the lowest tertile (OR: 4.00; 95%CI: 1.13- 14.21; p = 0.03). CONCLUSIONS: Our study did not find convincing evidence that SARS-CoV-2 seropositivity was associated with subsequent pulmonary TB disease; however, the association between magnitude of SARS-CoV-2 IgG response and pulmonary TB warrants further investigation. Future prospective studies, evaluating the effects of sex, age and puberty on host immune responses to M. tuberculosis and SARS-CoV-2, will also provide more clarity on the interplay between these two infections.

Phenotyping of lymphoproliferative tumours generated in xenografts of non-small cell lung cancer.

Background: Patient-derived xenograft (PDX) models involve the engraftment of tumour tissue in immunocompromised mice and represent an important pre-clinical oncology research method. A limitation of non-small cell lung cancer (NSCLC) PDX model derivation in NOD-scid IL2Rgammanull (NSG) mice is that a subset of initial engraftments are of lymphocytic, rather than tumour origin. Methods: The immunophenotype of lymphoproliferations arising in the lung TRACERx PDX pipeline were characterised. To present the histology data herein, we developed a Python-based tool for generating patient-level pathology overview figures from whole-slide image files; PATHOverview is available on GitHub (https://github.com/EpiCENTR-Lab/PATHOverview). Results: Lymphoproliferations occurred in 17.8% of lung adenocarcinoma and 10% of lung squamous cell carcinoma transplantations, despite none of these patients having a prior or subsequent clinical history of lymphoproliferative disease. Lymphoproliferations were predominantly human CD20+ B cells and had the immunophenotype expected for post-transplantation diffuse large B cell lymphoma with plasma cell features. All lymphoproliferations expressed Epstein-Barr-encoded RNAs (EBER). Analysis of immunoglobulin light chain gene rearrangements in three tumours where multiple tumour regions had resulted in lymphoproliferations suggested that each had independent clonal origins. Discussion: Overall, these data suggest that B cell clones with lymphoproliferative potential are present within primary NSCLC tumours, and that these are under continuous immune surveillance. Since these cells can be expanded following transplantation into NSG mice, our data highlight the value of quality control measures to identify lymphoproliferations within xenograft pipelines and support the incorporation of strategies to minimise lymphoproliferations during the early stages of xenograft establishment pipelines.

Lung adenocarcinoma promotion by air pollutants.

A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 µm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1ß. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for  PM2.5 air pollutants  and provide impetus for public health policy initiatives to address air pollution to reduce disease burden.