An atlas of epithelial cell states and plasticity in lung adenocarcinoma.

Understanding the cellular processes that underlie early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies1. Here we studied 246,102 single epithelial cells from 16 early-stage LUADs and 47 matched normal lung samples. Epithelial cells comprised diverse normal and cancer cell states, and diversity among cancer cells was strongly linked to LUAD-specific oncogenic drivers. KRAS mutant cancer cells showed distinct transcriptional features, reduced differentiation and low levels of aneuploidy. Non-malignant areas surrounding human LUAD samples were enriched with alveolar intermediate cells that displayed elevated KRT8 expression (termed KRT8+ alveolar intermediate cells (KACs) here), reduced differentiation, increased plasticity and driver KRAS mutations. Expression profiles of KACs were enriched in lung precancer cells and in LUAD cells and signified poor survival. In mice exposed to tobacco carcinogen, KACs emerged before lung tumours and persisted for months after cessation of carcinogen exposure. Moreover, they acquired Kras mutations and conveyed sensitivity to targeted KRAS inhibition in KAC-enriched organoids derived from alveolar type 2 (AT2) cells. Last, lineage-labelling of AT2 cells or KRT8+ cells following carcinogen exposure showed that KACs are possible intermediates in AT2-to-tumour cell transformation. This study provides new insights into epithelial cell states at the root of LUAD development, and such states could harbour potential targets for prevention or intervention.

Spatial mapping of mitochondrial networks and bioenergetics in lung cancer.

Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells1. The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity2,3. However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOSHI) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOSLO), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours.

Publisher Correction: In vivo imaging of mitochondrial membrane potential in non-small-cell lung cancer.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

In vivo imaging of mitochondrial membrane potential in non-small-cell lung cancer.

Mitochondria are essential regulators of cellular energy and metabolism, and have a crucial role in sustaining the growth and survival of cancer cells. A central function of mitochondria is the synthesis of ATP by oxidative phosphorylation, known as mitochondrial bioenergetics. Mitochondria maintain oxidative phosphorylation by creating a membrane potential gradient that is generated by the electron transport chain to drive the synthesis of ATP1. Mitochondria are essential for tumour initiation and maintaining tumour cell growth in cell culture and xenografts2,3. However, our understanding of oxidative mitochondrial metabolism in cancer is limited because most studies have been performed in vitro in cell culture models. This highlights a need for in vivo studies to better understand how oxidative metabolism supports tumour growth. Here we measure mitochondrial membrane potential in non-small-cell lung cancer in vivo using a voltage-sensitive, positron emission tomography (PET) radiotracer known as 4-[18F]fluorobenzyl-triphenylphosphonium (18F-BnTP)4. By using PET imaging of 18F-BnTP, we profile mitochondrial membrane potential in autochthonous mouse models of lung cancer, and find distinct functional mitochondrial heterogeneity within subtypes of lung tumours. The use of 18F-BnTP PET imaging enabled us to functionally profile mitochondrial membrane potential in live tumours.

Immune evasion in HPV- head and neck precancer-cancer transition is driven by an aneuploid switch involving chromosome 9p loss.

An aneuploid-immune paradox encompasses somatic copy-number alterations (SCNAs), unleashing a cytotoxic response in experimental precancer systems, while conversely being associated with immune suppression and cytotoxic-cell depletion in human tumors, especially head and neck cancer (HNSC). We present evidence from patient samples and cell lines that alterations in chromosome dosage contribute to an immune hot-to-cold switch during human papillomavirus-negative (HPV-) head and neck tumorigenesis. Overall SCNA (aneuploidy) level was associated with increased CD3+ and CD8+ T cell microenvironments in precancer (mostly CD3+, linked to trisomy and aneuploidy), but with T cell-deficient tumors. Early lesions with 9p21.3 loss were associated with depletion of cytotoxic T cell infiltration in TP53 mutant tumors; and with aneuploidy were associated with increased NK-cell infiltration. The strongest driver of cytotoxic T cell and Immune Score depletion in oral cancer was 9p-arm level loss, promoting profound decreases of pivotal IFN-γ-related chemokines (e.g., CXCL9) and pathway genes. Chromosome 9p21.3 deletion contributed mainly to cell-intrinsic senescence suppression, but deletion of the entire arm was necessary to diminish levels of cytokine, JAK-STAT, and Hallmark NF-κB pathways. Finally, 9p arm-level loss and JAK2-PD-L1 codeletion (at 9p24) were predictive markers of poor survival in recurrent HPV- HNSC after anti-PD-1 therapy; likely amplified by independent aneuploidy-induced immune-cold microenvironments observed here. We hypothesize that 9p21.3 arm-loss expansion and epistatic interactions allow oral precancer cells to acquire properties to overcome a proimmunogenic aneuploid checkpoint, transform and invade. These findings enable distinct HNSC interception and precision-therapeutic approaches, concepts that may apply to other CN-driven neoplastic, immune or aneuploid diseases, and immunotherapies.

Novel Kras-mutant murine models of non-small cell lung cancer possessing co-occurring oncogenic mutations and increased tumor mutational burden.

Conditional genetically engineered mouse models (GEMMs) of non-small cell lung cancer (NSCLC) harbor common oncogenic driver mutations of the disease, but in contrast to human NSCLC these models possess low tumor mutational burden (TMB). As a result, these models often lack tumor antigens that can elicit host adaptive immune responses, which limits their utility in immunotherapy studies. Here, we establish Kras-mutant murine models of NSCLC bearing the common driver mutations associated with the disease and increased TMB, by in vitro exposure of cell lines derived from GEMMs of NSCLC [KrasG12D (K), KrasG12DTp53-/-(KP), KrasG12DTp53+/-Lkb1-/- (KPL)] to the alkylating agent N-methyl-N-nitrosourea (MNU). Increasing the TMB enhanced host anti-tumor T cell responses and improved anti-PD-1 efficacy in syngeneic models across all genetic backgrounds. However, limited anti-PD-1 efficacy was observed in the KPL cell lines with increased TMB, which possessed a distinct immunosuppressed tumor microenvironment (TME) primarily composed of granulocytic myeloid-derived suppressor cells (G-MDSCs). This KPL phenotype is consistent with findings in human KRAS-mutant NSCLC where LKB1 loss is a driver of primary resistance to PD-1 blockade. In summary, these novel Kras-mutant NSCLC murine models with known driver mutations and increased TMB have distinct TMEs and recapitulate the therapeutic vulnerabilities of human NSCLC. We anticipate that these immunogenic models will facilitate the development of innovative immunotherapies in NSCLC.

Functional profiling of circulating tumor cells with an integrated vortex capture and single-cell protease activity assay.

Tumor cells are hypothesized to use proteolytic enzymes to facilitate invasion. Whether circulating tumor cells (CTCs) secrete these enzymes to aid metastasis is unknown. A quantitative and high-throughput approach to assay CTC secretion is needed to address this question. We developed an integrated microfluidic system that concentrates rare cancer cells >100,000-fold from 1 mL of whole blood into ∼50,000 2-nL drops composed of assay reagents within 15 min. The system isolates CTCs by size, exchanges fluid around CTCs to remove contaminants, introduces a matrix metalloprotease (MMP) substrate, and encapsulates CTCs into microdroplets. We found CTCs from prostate cancer patients possessed above baseline levels of MMP activity (1.7- to 200-fold). Activity of CTCs was generally higher than leukocytes from the same patient (average CTC/leukocyte MMP activity ratio, 2.6 ± 1.5). Higher MMP activity of CTCs suggests active proteolytic processes that may facilitate invasion or immune evasion and be relevant phenotypic biomarkers enabling companion diagnostics for anti-MMP therapies.

Readmission Rates for Chronic Obstructive Pulmonary Disease Under the Hospital Readmissions Reduction Program: an Interrupted Time Series Analysis.

BACKGROUND: Hospital readmission rates decreased for myocardial infarction (AMI), heart failure (CHF), and pneumonia with implementation of the first phase of the Hospital Readmissions Reduction Program (HRRP). It is not established whether readmissions fell for chronic obstructive pulmonary disease (COPD), an HRRP condition added in 2014. OBJECTIVE: We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients. DESIGN: We analyzed a retrospective cohort, evaluating readmissions across implementation periods for HRRP penalties ("pre-HRRP" January 2010-April 2011, "implementation" May 2011-September 2012, "partial penalty" October 2012-September 2014, and "full penalty" October 2014-December 2016). PATIENTS: We assessed discharged patients ≥ 40 years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database. INTERVENTIONS: HRRP was announced and implemented during this period, forming a natural experiment. MEASUREMENTS: We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions. KEY RESULTS: COPD discharges for 1.2 million Medicare enrollees were compared with 22 million non-HRRP and 3.4 million HRRP Phase 1 discharges. COPD readmissions decreased from 19 to 17% over the study. This reduction was significantly greater than non-HRRP conditions (DID - 0.41%), but not HRRP Phase 1 (DID + 0.02%). A parallel trend was observed in the privately insured, with significant reduction compared with non-HRRP (DID - 0.83%), but not HRRP Phase 1 conditions (DID - 0.45%). Non-significant reductions occurred in Medicaid (DID - 0.52% vs. non-HRRP and - 0.21% vs. Phase 1 conditions). CONCLUSIONS: In Medicare, HRRP implementation was associated with reductions in COPD readmissions compared with non-HRRP controls but not versus other HRRP conditions. Parallel findings were observed in commercial insurance, but not in Medicaid. Condition-specific penalties may not reduce readmissions further than existing HRRP trends.

Driver Mutations in Normal Airway Epithelium Elucidate Spatiotemporal Resolution of Lung Cancer.

Rationale: Uninvolved normal-appearing airway epithelium has been shown to exhibit specific mutations characteristic of nearby non-small cell lung cancers (NSCLCs). Yet, its somatic mutational landscape in patients with early-stage NSCLC is unknown.Objectives: To comprehensively survey the somatic mutational architecture of the normal airway epithelium in patients with early-stage NSCLC.Methods: Multiregion normal airways, comprising tumor-adjacent small airways, tumor-distant large airways, nasal epithelium and uninvolved normal lung (collectively airway field), matched NSCLCs, and blood cells (n = 498) from 48 patients were interrogated for somatic single-nucleotide variants by deep-targeted DNA sequencing and for chromosomal allelic imbalance events by genome-wide genotype array profiling. Spatiotemporal relationships between the airway field and NSCLCs were assessed by phylogenetic analysis.Measurements and Main Results: Genomic airway field carcinogenesis was observed in 25 cases (52%). The airway field epithelium exhibited a total of 269 somatic mutations in most patients (n = 36) including key drivers that were shared with the NSCLCs. Allele frequencies of these acquired variants were overall higher in NSCLCs. Integrative analysis of single-nucleotide variants and allelic imbalance events revealed driver genes with shared "two-hit" alterations in the airway field (e.g., TP53, KRAS, KEAP1, STK11, and CDKN2A) and those with single hits progressing to two in the NSCLCs (e.g., PIK3CA and NOTCH1).Conclusions: Tumor-adjacent and tumor-distant normal-appearing airway epithelia exhibit somatic driver alterations that undergo selection-driven clonal expansion in NSCLC. These events offer spatiotemporal insights into the development of NSCLC and, thus, potential targets for early treatment.

CCL21 Programs Immune Activity in Tumor Microenvironment.

CCL21 promotes immune activity in the tumor microenvironment (TME) by colocalizing dendritic cells (DC) and T cells programing ectopic lymph node architectural structures that correlate with cancer prognosis. Innovative strategies to deliver CCL21 in cancer patients will reactivate the downregulated immune activity in the TME. Immune escape mechanisms are upregulated in the TME that promote tumor immune evasion. CCL21 combined with inhibition of dominant pathways of immune evasion will aid in the development of effective immunotherapy for cancer.

Comorbidity and thirty-day hospital readmission odds in chronic obstructive pulmonary disease: a comparison of the Charlson and Elixhauser comorbidity indices.

BACKGROUND: Readmissions following exacerbations of chronic obstructive pulmonary disease (COPD) are prevalent and costly. Multimorbidity is common in COPD and understanding how comorbidity influences readmission risk will enable health systems to manage these complex patients. OBJECTIVES: We compared two commonly used comorbidity indices published by Charlson and Elixhauser regarding their ability to estimate readmission odds in COPD and determine which one provided a superior model. METHODS: We analyzed discharge records for COPD from the Nationwide Readmissions Database spanning 2010 to 2016. Inclusion and readmission criteria from the Hospital Readmissions Reduction Program were utilized. Elixhauser and Charlson Comorbidity Index scores were calculated from published methodology. A mixed-effects logistic regression model with random intercepts for hospital clusters was fit for each comorbidity index, including year, patient-level, and hospital-level covariates to estimate odds of thirty-day readmissions. Sensitivity analyses included testing age inclusion thresholds and model stability across time. RESULTS: In analysis of 1.6 million COPD discharges, readmission odds increased by 9% for each half standard deviation increase of Charlson Index scores and 13% per half standard deviation increase of Elixhauser Index scores. Model fit was slightly better for the Elixhauser Index using information criteria. Model parameters were stable in our sensitivity analyses. CONCLUSIONS: Both comorbidity indices provide meaningful information in prediction readmission odds in COPD with slightly better model fit in the Elixhauser model. Incorporation of comorbidity information into risk prediction models and hospital discharge planning may be informative to mitigate readmissions.

Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process.

MicroRNA 4423 is a primate-specific regulator of airway epithelial cell differentiation and lung carcinogenesis.

Smoking is a significant risk factor for lung cancer, the leading cause of cancer-related deaths worldwide. Although microRNAs are regulators of many airway gene-expression changes induced by smoking, their role in modulating changes associated with lung cancer in these cells remains unknown. Here, we use next-generation sequencing of small RNAs in the airway to identify microRNA 4423 (miR-4423) as a primate-specific microRNA associated with lung cancer and expressed primarily in mucociliary epithelium. The endogenous expression of miR-4423 increases as bronchial epithelial cells undergo differentiation into mucociliary epithelium in vitro, and its overexpression during this process causes an increase in the number of ciliated cells. Furthermore, expression of miR-4423 is reduced in most lung tumors and in cytologically normal epithelium of the mainstem bronchus of smokers with lung cancer. In addition, ectopic expression of miR-4423 in a subset of lung cancer cell lines reduces their anchorage-independent growth and significantly decreases the size of the tumors formed in a mouse xenograft model. Consistent with these phenotypes, overexpression of miR-4423 induces a differentiated-like pattern of airway epithelium gene expression and reverses the expression of many genes that are altered in lung cancer. Together, our results indicate that miR-4423 is a regulator of airway epithelium differentiation and that the abrogation of its function contributes to lung carcinogenesis.

Randomized phase 2 trial of erlotinib in combination with high-dose celecoxib or placebo in patients with advanced non-small cell lung cancer.

BACKGROUND: Cyclooxygenase 2 (COX-2)-dependent signaling represents a potential mechanism of resistance to therapy with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors. This is mediated in part through an EGFR-independent activation of mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (Erk) by prostaglandin E2 (PGE2). PGE2 promotes downregulation of E cadherin and epithelial to mesenchymal transition. The current study investigated EGFR and COX-2 inhibition in patients with non-small cell lung cancer (NSCLC) and elevated baseline urinary metabolite of PGE2 (PGEM). METHODS: Patients with stage IIIB/IV (AJCC 6th edition) NSCLC who progressed after at least 1 line of therapy or refused standard chemotherapy were randomized to receive erlotinib and celecoxib versus erlotinib and placebo. The primary endpoint was progression-free survival (PFS) with 80% power to detect a 50% improvement with a 1-sided significance level of .2 in the intent-to-treat and elevated baseline PGEM populations. Secondary endpoints included response rate, overall survival, and evaluation of molecular markers to assess targeting COX-2-related pathways and evaluate EGFR tyrosine kinase inhibitor resistance. RESULTS: A total of 107 patients were enrolled with comparable baseline characteristics. Among the patients treated with celecoxib, those with wild-type EGFR were found to have an increased PFS (3.2 months vs 1.8 months; P = .03). PFS was numerically improved among patients in the intent-to-treat group who received erlotinib and celecoxib compared with those treated with erlotinib and placebo (5.4 months vs 3.5 months; P = .33) and was increased in patients in the erlotinib and celecoxib arm with elevated baseline PGEM (5.4 months vs 2.2 months; P = .15). Adverse events were similar in both treatment arms. CONCLUSIONS: The combination of erlotinib and celecoxib did not appear to improve outcomes in an unselected population, but selection by elevated baseline PGEM led to an increase in PFS with this combination. Patients with EGFR wild-type status may benefit from the combination of erlotinib and celecoxib.

Distinguishing patients with stage I lung cancer versus control individuals using serum mass profiling.

Serum mass profiling can discern physiological changes associated with specific disease states and their progression. Sera (86 total) from control individuals and patients with stage I nonsmall cell lung cancer or benign small pulmonary nodules were discriminated retrospectively by serum changes discerned by mass profiling. Control individuals were distinguished from patients with Stage I lung cancer or benign nodules with test sensitivities of 89% and 83%. Lung cancer patients versus those with benign nodules were distinguished with 80% sensitivity. This study exhibits progress toward a minimally-invasive aid in early detection of lung cancer and monitoring small pulmonary nodules for malignancy.

Noninvasive lung cancer subtype classification using tumor-derived signatures and cfDNA methylome.

Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histological examination is the standard for determining histological lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.