Lung cancer in patients who have never smoked - an emerging disease

Abstract

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

Fig. 1 |. Smoking rates and lung cancer-related deaths.

a, Smoking prevalence in the USA from 1965 to 2022 as the percentage of adults aged ≥18 years who reported currently smoking cigarettes, overall and by sex. The data are derived from the National Health Interview Survey (NHIS) 1965–2018 and 2019–2022 (refs. 2,3,385,386) and are not available for all years. b, Estimated number of global deaths attributed to 37 cancer types in 2020 (ref. 6). Smoking-related lung cancer and lung cancer in individuals who have never smoked (LCINS) are shown in red as the first and fifth leading cause of cancer deaths, respectively.

Fig. 2 |. Prevalence of oncogenic somatic driver alterations in LCINS.

Data from somatic profiling studies of lung adenocarcinoma (LUAD) in individuals who have never smoked (LCINS). a, Whole-exome sequencing (WES) and RNA sequencing study of 160 samples, at an average depth of 20–30× for WES. The prevalence of each somatic driver alteration was calculated as a composite average using three individual cohorts included in the study, with values weighted proportionally to the number of samples in each cohort. Genetic ancestry was inferred by the authors based on germline sequencing data from matched peripheral blood. b, Whole-genome sequencing (WGS) study of 189 samples at an average depth of 85×. Genetic ancestry was inferred by the authors based on germline sequencing data from matched peripheral blood. c, Clinical panel-based next-generation sequencing (NGS) data from 1,508 LUADs, collected as part of the non-small-cell lung cancer (NSCLC) cohort of the AACR Project GENIE Biopharma Collaborative, across four large academic cancer cancers in North America (Dana-Farber Cancer Institute, Memorial Sloan Kettering Cancer Center, Vanderbilt-Ingram Cancer Center, and Princess Margaret Cancer Centre-University Health Network). Clinical data available for this cohort include tumour histology, patient self-reported primary ethnicity and cigarette use at time of diagnosis: never smoked; quit smoking >1 year prior to diagnosis (‘former smoking (remote)’); quit smoking <1 year prior to diagnosis (‘former smoking (recent)’); and current smoking. Self-reported primary ethnicity is shown for samples with never-smoking status only. Included for analysis were somatic mutations (EGFR, KRAS, ERBB2, BRAF and MET) and gene fusions (ALK, ROS1 and RET) annotated as ‘putative drivers’ based on prior knowledge (OncoKB^,) and statistical recurrence (Cancer Hotspots^,). The GENIE Biopharma Collaborative Public release is available for download (https://www.synapse.org/#!Synapse:syn27056172/wiki/616601) and can be visualized and analysed using the cBioPortal interface (https://genie.cbioportal.org/study/summary?id=nsclc_public_genie_bpc). Note, wide ranges in the prevalence of particular alterations across studies probably reflect differences in cohort ascertainment (for example, 25.0% versus only 1.7% of patients were of East Asian ancestry in the WES and WGS studies, respectively) and heterogeneity of testing assays used. ND, none of the above alterations detected.

Fig. 3 |. Annual average PM_2.5 concentrations across the world.

a, Mean annual average concentrations of particulate matter measuring ≤2.5 μm in diameter (PM_2.5) across the contiguous United States, plotted in 1-km grids, spanning years 2000–2016 (ref. 276). The annual estimates are averages of daily predictions for each year in each grid cell. The current US Environmental Protection Agency annual average primary, health-based national ambient air quality standard for PM_2.5 is ≤12.0 μg/m³, with a proposed revision to within 9.0–10.0 μg/m³ announced in January 2023 (ref. 275). b, Mean annual average PM_2.5 concentrations across the globe, spanning years 2003–2022, according to European Centre for Medium-range Weather Forecasts Atmospheric Composition Reanalysis 4. Performed by the Copernicus Atmosphere Monitoring Service, the reanalysis combines data from modelling studies with observations from across the world into a globally complete dataset. Annual estimates are averages of monthly predictions. The WHO air quality guidelines recommend annual mean PM_2.5 concentrations of ≤5 μg/m³.

Fig. 4 |. Germline–somatic and gene–environment interactions in the pathogenesis of LCINS.

a, Model of germline–somatic interactions in lung cancer in individuals who have never smoked (LCINS). Dashed lines and arrows indicate interactions, whereas solid lines and arrows indicate direct processes. Germline variants and acquired somatic alterations can interact to promote cancer development and progression (potential mechanisms are detailed in the main text). Moreover, germline variants affecting carcinogen metabolism, DNA repair and inflammatory processes can interact with environmental exposures and thereby influence the acquisition of somatic alterations and tumour development, and polymorphisms in genes underlying drug metabolism can affect responses to therapy or the development of treatment-related toxicities (the concept of pharmacogenomics). b, Risk factors promoting LCINS include environmental exposures such as radon, secondhand smoke, outdoor (air) and indoor (household) pollution, occupational carcinogens, and prior radiotherapy to the chest. Patient-level risk factors include female sex^b, Asian ethnicity and germline risk, the genetic architecture of which consists of common variants of small to moderate effect as well as rare and ultra-rare variants of large effect. Familial lung cancer syndromes are mediated by rare germline mutations in oncogenes such as EGFR. Interaction between genetics and environment can occur across any and/or multiple risk factors. GWAS, genome-wide association study; PRS, polygenic risk score; SNP, single-nucleotide polymorphism. ^aCopy number neutral loss of heterozygosity events can occur at loci harbouring either tumour-suppressor genes or oncogenes. ^bNote, environmental risks related to the socioeconomic and cultural aspects of female gender (such as historically greater exposure to household cooking fumes among women), and/or biological factors related to female sex, might contribute to the effect of female sex.

Fig. 5 |. Molecular diagnostic algorithm for advanced-stage LCINS.

The algorithm outlines a sequential approach to evaluating the presence of targetable oncogenic driver alterations in lung cancers in individuals who have never smoked (LCINS) or who have a limited smoking history, which are almost exclusively non-small-cell lung cancer (NSCLC) of adenocarcinoma histology. The National Comprehensive Cancer Network (NCCN) Guidelines recommend that molecular analysis of advanced-stage NSCLC should include assays to identify actionable alterations in EGFR, KRAS, ALK, ROS1, RET, ERBB2 (also known as HER2), NTRK1–3, BRAF (V600E) and MET exon 14, for which FDA-approved targeted therapies are available. Emerging therapeutic biomarkers include high-level MET amplification, with the current NCCN Guidelines (version 5.2023) noting that thresholds constituting high-level MET amplification are evolving; when next-generation sequencing (NGS) is used, a MET copy number of ≥10 is consistent with high-level MET amplification and is associated with clinical benefit from MET tyrosine kinase inhibitors. Although NGS is the preferred analytical modality, molecular profiling is defined as broad testing that identifies all relevant clinically actionable biomarkers in either a single assay or a combination of a limited number of assays and, ideally, also identifies emerging biomarkers. WES, whole-exome sequencing; WGS, whole-genome sequencing. ^aSimultaneous blood-based and tissue-based NGS testing recommended, with ideal turnaround times of 7–10 days and 2–3 weeks, respectively. ^bIf a matched targeted therapy is not approved in the first-line setting, may consider clinical trials offering first-line targeted therapy versus standard-of-care treatment (for example, NCT05048797 for HER2-mutant NSCLC). ^cClinical decision-making should include consideration of clinicopathological variables such as smoking history, histology, PD-L1 positivity and tumour mutational burden, noting that the majority of LCINS are associated with poor response to immunotherapy. ^dIf available, to maximize detection of fusion proteins and emerging targets.