APOBEC shapes tumor evolution and age at onset of lung cancer in smokers.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Genomic and evolutionary classification of lung cancer in never smokers.

Lung cancer in never smokers (LCINS) is a common cause of cancer mortality but its genomic landscape is poorly characterized. Here high-coverage whole-genome sequencing of 232 LCINS showed 3 subtypes defined by copy number aberrations. The dominant subtype (piano), which is rare in lung cancer in smokers, features somatic UBA1 mutations, germline AR variants and stem cell-like properties, including low mutational burden, high intratumor heterogeneity, long telomeres, frequent KRAS mutations and slow growth, as suggested by the occurrence of cancer drivers' progenitor cells many years before tumor diagnosis. The other subtypes are characterized by specific amplifications and EGFR mutations (mezzo-forte) and whole-genome doubling (forte). No strong tobacco smoking signatures were detected, even in cases with exposure to secondhand tobacco smoke. Genes within the receptor tyrosine kinase-Ras pathway had distinct impacts on survival; five genomic alterations independently doubled mortality. These findings create avenues for personalized treatment in LCINS.

Tracing Lung Cancer Risk Factors Through Mutational Signatures in Never-Smokers.

Epidemiologic studies often rely on questionnaire data, exposure measurement tools, and/or biomarkers to identify risk factors and the underlying carcinogenic processes. An emerging and promising complementary approach to investigate cancer etiology is the study of somatic "mutational signatures" that endogenous and exogenous processes imprint on the cellular genome. These signatures can be identified from a complex web of somatic mutations thanks to advances in DNA sequencing technology and analytical algorithms. This approach is at the core of the Sherlock-Lung study (2018-ongoing), a retrospective case-only study of over 2,000 lung cancers in never-smokers (LCINS), using different patterns of mutations observed within LCINS tumors to trace back possible exposures or endogenous processes. Whole genome and transcriptome sequencing, genome-wide methylation, microbiome, and other analyses are integrated with data from histological and radiological imaging, lifestyle, demographic characteristics, environmental and occupational exposures, and medical records to classify LCINS into subtypes that could reveal distinct risk factors. To date, we have received samples and data from 1,370 LCINS cases from 17 study sites worldwide and whole-genome sequencing has been completed on 1,257 samples. Here, we present the Sherlock-Lung study design and analytical strategy, also illustrating some empirical challenges and the potential for this approach in future epidemiologic studies.

Did death certificates and a death review process agree on lung cancer cause of death in the National Lung Screening Trial?

BACKGROUND/AIMS: Randomized controlled trials frequently use death review committees to assign a cause of death rather than relying on cause of death information from death certificates. The National Lung Screening Trial, a randomized controlled trial of lung cancer screening with low-dose computed tomography versus chest X-ray for heavy and/or long-term smokers ages 55-74 years at enrollment, used a committee blinded to arm assignment for a subset of deaths to determine whether cause of death was due to lung cancer. METHODS: Deaths were selected for review using a pre-determined computerized algorithm. The algorithm, which considered cancers diagnosed during the trial, causes and significant conditions listed on the death certificate, and the underlying cause of death derived from death certificate information by trained nosologists, selected deaths that were most likely to represent a death due to lung cancer (either directly or indirectly) and deaths that might have been erroneously assigned lung cancer as the cause of death. The algorithm also selected deaths that might be due to adverse events of diagnostic evaluation for lung cancer. Using the review cause of death as the gold standard and lung cancer cause of death as the outcome of interest (dichotomized as lung cancer versus not lung cancer), we calculated performance measures of the death certificate cause of death. We also recalculated the trial primary endpoint using the death certificate cause of death. RESULTS: In all, 1642 deaths were reviewed and assigned a cause of death (42% of the 3877 National Lung Screening Trial deaths). Sensitivity of death certificate cause of death was 91%; specificity, 97%; positive predictive value, 98%; and negative predictive value, 89%. About 40% of the deaths reclassified to lung cancer cause of death had a death certificate cause of death of a neoplasm other than lung. Using the death certificate cause of death, the lung cancer mortality reduction was 18% (95% confidence interval: 4.2-25.0), as compared with the published finding of 20% (95% confidence interval: 6.7-26.7). CONCLUSION: Death review may not be necessary for primary-outcome analyses in lung cancer screening trials. If deemed necessary, researchers should strive to streamline the death review process as much as possible.

The National Lung Screening Trial's Endpoint Verification Process: determining the cause of death.

BACKGROUND: Randomized controlled trials (RCTs) evaluating cancer screening modalities usually employ cause-specific mortality as their primary endpoint. Because death certificate cause of death can be inaccurate, RCTs frequently use review committees to assign an underlying cause of death. We describe the National Lung Screening Trial's (NLST's) death review approach, the Endpoint Verification Process (EVP), which strives to minimize errors in assignment of cause of death due to lung cancer. METHODS: Deaths selected for review include those with a notation of lung cancer on the death certificate and those occurring among participants ever diagnosed with lung cancer. Other criteria that trigger death review include, but are not limited to, death within 6 months of a screen suspicious for lung cancer and death within 60 days of certain diagnostic evaluation procedures associated with a screen suspicious for lung cancer or a lung cancer diagnosis. EVP requires concordance on whether death was due to lung cancer. Deaths are first reviewed by the EVP chair. If concordance is not achieved, the death is next reviewed by an Endpoint Verification Team (EVT) member. If concordance between the chair- and member-assigned cause of death is not achieved, the death is next reviewed by a group of at least three EVT members. Cause of death is assigned at the step in which concordance was achieved, or if necessary, at the team review. CONCLUSIONS: NLST's EVP is designed to produce a highly accurate count of lung cancer deaths.

Cutting edge: vasoactive intestinal peptide (VIP) induces differentiation of Th17 cells with a distinctive cytokine profile.

Immune cellular effects of vasoactive intestinal peptide (VIP) are transduced by VIP G protein-coupled receptors type 1 (VPAC1) and type 2 (VPAC2). We now show that VIP with TGFbeta stimulates the transformation of CD4 T cells to a distinctive type of Th17 cell that generates IL-17 but not IL-6 or IL-21. VIP induction of Th17 cells was higher in VPAC2 knockout mice than wild-type mice, suggesting that VPAC1 is the principal transducer. Compared with Th17 cells elicited by IL-6, those evoked by VIP were similar in the secretion of IL-17 and IL-22, but lacked IL-21 secretion. Suppression of VIP induction of Th17 cells by protein kinase A inhibitors and enhancement by pharmacologically increased cAMP supports a role for this signal. The ability of VIP-VPAC1 axis signals to evoke development of a novel type of Th17 cells demonstrates the unique specificity of neuroregulatory mechanisms in the immunological environment.