Tobacco smoking causes lung cancer
, a process that is driven by more than 60 carcinogens in cigarette smoke that directly damage and mutate DNA
. The profound effects of tobacco on the genome of ...lung cancer cells are well-documented
, but equivalent data for normal bronchial cells are lacking. Here we sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. Tobacco smoking was the major influence on mutational burden, typically adding from 1,000 to 10,000 mutations per cell; massively increasing the variance both within and between subjects; and generating several distinct mutational signatures of substitutions and of insertions and deletions. A population of cells in individuals with a history of smoking had mutational burdens that were equivalent to those expected for people who had never smoked: these cells had less damage from tobacco-specific mutational processes, were fourfold more frequent in ex-smokers than current smokers and had considerably longer telomeres than their more-mutated counterparts. Driver mutations increased in frequency with age, affecting 4-14% of cells in middle-aged subjects who had never smoked. In current smokers, at least 25% of cells carried driver mutations and 0-6% of cells had two or even three drivers. Thus, tobacco smoking increases mutational burden, cell-to-cell heterogeneity and driver mutations, but quitting promotes replenishment of the bronchial epithelium from mitotically quiescent cells that have avoided tobacco mutagenesis.
The assessment of the risks exerted by nanoparticles is a key challenge for academic, industrial, and regulatory communities worldwide. Experimental evidence points towards significant toxicity for a ...range of nanoparticles both in vitro and in vivo. Worldwide efforts aim at uncovering the underlying mechanisms for this toxicity. Here, we show that the intracellular ion release elicited by the acidic conditions of the lysosomal cellular compartment--where particles are abundantly internalized--is responsible for the cascading events associated with nanoparticles-induced intracellular toxicity. We call this mechanism a "lysosome-enhanced Trojan horse effect" since, in the case of nanoparticles, the protective cellular machinery designed to degrade foreign objects is actually responsible for their toxicity. To test our hypothesis, we compare the toxicity of similar gold particles whose main difference is in the internalization pathways. We show that particles known to pass directly through cell membranes become more toxic when modified so as to be mostly internalized by endocytosis. Furthermore, using experiments with chelating and lysosomotropic agents, we found that the toxicity mechanism for different metal containing NPs (such as metallic, metal oxide, and semiconductor NPs) is mainly associated with the release of the corresponding toxic ions. Finally, we show that particles unable to release toxic ions (such as stably coated NPs, or diamond and silica NPs) are not harmful to intracellular environments.
The secret lives of cancer cell lines Hynds, Robert E; Vladimirou, Elina; Janes, Sam M
Disease models & mechanisms,
11/2018, Letnik:
11, Številka:
11
Journal Article
Recenzirano
Odprti dostop
The extent of genetic and epigenetic diversity between and within patient tumors is being mapped in ever more detail. It is clear that cancer is an evolutionary process in which tumor cell intrinsic ...and extrinsic forces shape clonal selection. The pre-clinical oncology pipeline uses model systems of human cancer - including mouse models, cell lines, patient-derived organoids and patient-derived xenografts - to study tumor biology and assess the efficacy of putative therapeutic agents. Model systems cannot completely replicate the environment of human tumors and, even within the same cancer model, data are often irreproducible between laboratories. One hypothesis is that ongoing evolutionary processes remain relevant in laboratory models, leading to divergence over time. In a recent edition of Nature, Ben-David and colleagues showed that different stocks of widely used cancer cell lines - a staple of cancer research over many decades - are highly heterogeneous in terms of their genetics, transcriptomics and responses to therapies. The authors find compelling evidence of positive selection based on ongoing mutational processes and chromosomal instability. Thus, the origin, culture conditions and cumulative number of population doublings of cell lines likely influence experimental outcomes. Here, we summarize the key findings of this important study and discuss the practical implications of this work for researchers using cell lines in the laboratory.
The molecular alterations that occur in cells before cancer is manifest are largely uncharted. Lung carcinoma in situ (CIS) lesions are the pre-invasive precursor to squamous cell carcinoma. Although ...microscopically identical, their future is in equipoise, with half progressing to invasive cancer and half regressing or remaining static. The cellular basis of this clinical observation is unknown. Here, we profile the genomic, transcriptomic, and epigenomic landscape of CIS in a unique patient cohort with longitudinally monitored pre-invasive disease. Predictive modeling identifies which lesions will progress with remarkable accuracy. We identify progression-specific methylation changes on a background of widespread heterogeneity, alongside a strong chromosomal instability signature. We observed mutations and copy number changes characteristic of cancer and chart their emergence, offering a window into early carcinogenesis. We anticipate that this new understanding of cancer precursor biology will improve early detection, reduce overtreatment, and foster preventative therapies targeting early clonal events in lung cancer.
Cancer is a leading cause of mortality throughout the world and new treatments are urgently needed. Recent studies suggest that bone marrow-derived mesenchymal stem cells (MSC) home to and ...incorporate within tumor tissue. We hypothesized that MSCs engineered to produce and deliver tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), a transmembrane protein that causes selective apoptosis of tumor cells, would home to and kill cancer cells in a lung metastatic cancer model. Human MSCs were transduced with TRAIL and the IRES-eGFP reporter gene under the control of a tetracycline promoter using a lentiviral vector. Transduced and activated MSCs caused lung (A549), breast (MDAMB231), squamous (H357), and cervical (Hela) cancer cell apoptosis and death in coculture experiments. Subcutaneous xenograft experiments confirmed that directly delivered TRAIL-expressing MSCs were able to significantly reduce tumor growth 0.12 cm(3) (0.04-0.21) versus 0.66 cm(3) (0.21-1.11); P < 0.001. We then found, using a pulmonary metastasis model, systemically delivered MSCs localized to lung metastases and the controlled local delivery of TRAIL completely cleared the metastatic disease in 38% of mice compared with 0% of controls (P < 0.05). This is the first study to show a significant reduction in metastatic tumor burden with frequent eradication of metastases using inducible TRAIL-expressing MSCs. This has a wide potential therapeutic role, which includes the treatment of both primary tumors and their metastases, possibly as an adjuvant therapy in clearing micrometastatic disease following primary tumor resection.
Risk-based screening for lung cancer is currently being considered in several countries; however, the optimal approach to determine eligibility remains unclear. Ensemble machine learning could ...support the development of highly parsimonious prediction models that maintain the performance of more complex models while maximising simplicity and generalisability, supporting the widespread adoption of personalised screening. In this work, we aimed to develop and validate ensemble machine learning models to determine eligibility for risk-based lung cancer screening.
For model development, we used data from 216,714 ever-smokers recruited between 2006 and 2010 to the UK Biobank prospective cohort and 26,616 high-risk ever-smokers recruited between 2002 and 2004 to the control arm of the US National Lung Screening (NLST) randomised controlled trial. The NLST trial randomised high-risk smokers from 33 US centres with at least a 30 pack-year smoking history and fewer than 15 quit-years to annual CT or chest radiography screening for lung cancer. We externally validated our models among 49,593 participants in the chest radiography arm and all 80,659 ever-smoking participants in the US Prostate, Lung, Colorectal and Ovarian (PLCO) Screening Trial. The PLCO trial, recruiting from 1993 to 2001, analysed the impact of chest radiography or no chest radiography for lung cancer screening. We primarily validated in the PLCO chest radiography arm such that we could benchmark against comparator models developed within the PLCO control arm. Models were developed to predict the risk of 2 outcomes within 5 years from baseline: diagnosis of lung cancer and death from lung cancer. We assessed model discrimination (area under the receiver operating curve, AUC), calibration (calibration curves and expected/observed ratio), overall performance (Brier scores), and net benefit with decision curve analysis. Models predicting lung cancer death (UCL-D) and incidence (UCL-I) using 3 variables-age, smoking duration, and pack-years-achieved or exceeded parity in discrimination, overall performance, and net benefit with comparators currently in use, despite requiring only one-quarter of the predictors. In external validation in the PLCO trial, UCL-D had an AUC of 0.803 (95% CI: 0.783, 0.824) and was well calibrated with an expected/observed (E/O) ratio of 1.05 (95% CI: 0.95, 1.19). UCL-I had an AUC of 0.787 (95% CI: 0.771, 0.802), an E/O ratio of 1.0 (95% CI: 0.92, 1.07). The sensitivity of UCL-D was 85.5% and UCL-I was 83.9%, at 5-year risk thresholds of 0.68% and 1.17%, respectively, 7.9% and 6.2% higher than the USPSTF-2021 criteria at the same specificity. The main limitation of this study is that the models have not been validated outside of UK and US cohorts.
We present parsimonious ensemble machine learning models to predict the risk of lung cancer in ever-smokers, demonstrating a novel approach that could simplify the implementation of risk-based lung cancer screening in multiple settings.
Stem cell-based tracheal replacement represents an emerging therapeutic option for patients with otherwise untreatable airway diseases including long-segment congenital tracheal stenosis and upper ...airway tumors. Clinical experience demonstrates that restoration of mucociliary clearance in the lungs after transplantation of tissue-engineered grafts is critical, with preclinical studies showing that seeding scaffolds with autologous mucosa improves regeneration. High epithelial cell-seeding densities are required in regenerative medicine, and existing techniques are inadequate to achieve coverage of clinically suitable grafts.
To define a scalable cell culture system to deliver airway epithelium to clinical grafts.
Human respiratory epithelial cells derived from endobronchial biopsies were cultured using a combination of mitotically inactivated fibroblasts and Rho-associated protein kinase (ROCK) inhibition using Y-27632 (3T3+Y). Cells were analyzed by immunofluorescence, quantitative polymerase chain reaction, and flow cytometry to assess airway stem cell marker expression. Karyotyping and multiplex ligation-dependent probe amplification were performed to assess cell safety. Differentiation capacity was tested in three-dimensional tracheospheres, organotypic cultures, air-liquid interface cultures, and an in vivo tracheal xenograft model. Ciliary function was assessed in air-liquid interface cultures.
3T3-J2 feeder cells and ROCK inhibition allowed rapid expansion of airway basal cells. These cells were capable of multipotent differentiation in vitro, generating both ciliated and goblet cell lineages. Cilia were functional with normal beat frequency and pattern. Cultured cells repopulated tracheal scaffolds in a heterotopic transplantation xenograft model.
Our method generates large numbers of functional airway basal epithelial cells with the efficiency demanded by clinical transplantation, suggesting its suitability for use in tracheal reconstruction.