Anita R. Iskandar

β-Cryptoxanthin Restores Nicotine-Reduced Lung SIRT1 to Normal Levels and Inhibits Nicotine-Promoted Lung Tumorigenesis and Emphysema in A/J Mice

Nicotine, a large constituent of cigarette smoke, is associated with an increased risk of lung cancer, but the data supporting this relationship are inconsistent. Here, we found that nicotine treatment not only induced emphysema but also increased both lung tumor multiplicity and volume in 4-nitrosamino-1-(3-pyridyl)-1-butanone (NNK)-initiated lung cancer in A/J mice. This tumor-promoting effect of nicotine was accompanied by significant reductions in survival probability and lung Sirtuin 1 (SIRT1) expression, which has been proposed as a tumor suppressor. The decreased level of SIRT1 was associated with increased levels of AKT phosphorylation and interleukin (il)-6 mRNA but decreased tumor suppressor p53 and retinoic acid receptor (RAR)-β mRNA levels in the lungs. Using this mouse model, we then determined whether β-cryptoxanthin (BCX), a xanthophyll that is strongly associated with a reduced risk of lung cancer in several cohort studies, can inhibit nicotine-induced emphysema and lung tumorigenesis. We found that BCX supplementation at two different doses was associated with reductions of the nicotine-promoted lung tumor multiplicity and volume, as well as emphysema in mice treated with both NNK and nicotine. Moreover, BCX supplementation restored the nicotine-suppressed expression of lung SIRT1, p53, and RAR-β to that of the control group, increased survival probability, and decreased the levels of lung il-6 mRNA and phosphorylation of AKT. The present study indicates that BCX is a preventive agent against emphysema and lung cancer with SIRT1 as a potential target. In addition, our study establishes a relevant animal lung cancer model for studying tumor growth within emphysematous microenvironments. Cancer Prev Res; 6(4); 309–20. ©2012 AACR.

Impact Assessment of Cigarette Smoke Exposure on Organotypic Bronchial Epithelial Tissue Cultures: A Comparison of Mono-Culture and Coculture Model Containing Fibroblasts

Organotypic 3D cultures of epithelial cells are grown at the air–liquid interface (ALI) and resemble the in vivo counterparts. Although the complexity of in vivo cellular responses could be better manifested in coculture models in which additional cell types such as fibroblasts were incorporated, the presence of another cell type could mask the response of the other. This study reports the impact of whole cigarette smoke (CS) exposure on organotypic mono- and coculture models to evaluate the relevancy of organotypic models for toxicological assessment of aerosols. Two organotypic bronchial models were directly exposed to low and high concentrations of CS of the reference research cigarette 3R4F: monoculture of bronchial epithelial cells without fibroblasts (BR) and coculture with fibroblasts (BRF) models. Adenylate kinase (AK)-based cytotoxicity, cytochrome P450 (CYP) 1A1/1B1 activity, tissue histology, and concentrations of secreted mediators into the basolateral media, as well as transcriptomes were evaluated following the CS exposure. The results demonstrated similar impact of CS on the AK-based cytotoxicity, CYP1A1/1B1 activity, and tissue histology in both models. However, a greater number of secreted mediators was identified in the basolateral media of the monoculture than in the coculture models. Furthermore, annotation analysis and network-based systems biology analysis of the transcriptomic profiles indicated a more prominent cellular stress and tissue damage following CS in the monoculture epithelium model without fibroblasts. Finally, our results indicated that an in vivo smoking-induced xenobiotic metabolism response of bronchial epithelial cells was better reflected from the in vitro CS-exposed coculture model.

A framework for in vitro systems toxicology assessment of e-liquids

Abstract Various electronic nicotine delivery systems (ENDS), of which electronic cigarettes (e-cigs) are the most recognized prototype, have been quickly gaining ground on conventional cigarettes because they are perceived as less harmful. Research assessing the potential effects of ENDS exposure in humans is currently limited and inconclusive. New products are emerging with numerous variations in designs and performance parameters within and across brands. Acknowledging these challenges, we present here a proposed framework for an in vitro systems toxicology assessment of e-liquids and their aerosols, intended to complement the battery of assays for standard toxicity assessments. The proposed framework utilizes high-throughput toxicity assessments of e-liquids and their aerosols, in which the device-to-device variability is minimized, and a systems-level investigation of the cellular mechanisms of toxicity is an integral part. An analytical chemistry investigation is also included as a part of the framework to provide accurate and reliable chemistry data solidifying the toxicological assessment. In its simplest form, the framework comprises of three main layers: (1) high-throughput toxicity screening of e-liquids using primary human cell culture systems; (2) toxicity-related mechanistic assessment of selected e-liquids, and (3) toxicity-related mechanistic assessment of their aerosols using organotypic air–liquid interface airway culture systems. A systems toxicology assessment approach is leveraged to enable in-depth analyses of the toxicity-related cellular mechanisms of e-liquids and their aerosols. We present example use cases to demonstrate the suitability of the framework for a robust in vitro assessment of e-liquids and their aerosols.

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Cigarette smoke (CS) has a major impact on lung biology and may result in the development of lung diseases such as chronic obstructive pulmonary disease or lung cancer. To understand the underlying mechanisms of disease development, it would be important to examine the impact of CS exposure directly on lung tissues. However, this approach is difficult to implement in epidemiological studies because lung tissue sampling is complex and invasive. Alternatively, tissue culture models can facilitate the assessment of exposure impacts on the lung tissue. Submerged 2D cell cultures, such as normal human bronchial epithelial (NHBE) cell cultures, have traditionally been used for this purpose. However, they cannot be exposed directly to smoke in a similar manner to the in vivo exposure situation. Recently developed 3D tissue culture models better reflect the in vivo situation because they can be cultured at the air-liquid interface (ALI). Their basal sides are immersed in the culture medium; whereas, their apical sides are exposed to air. Moreover, organotypic tissue cultures that contain different type of cells, better represent the physiology of the tissue in vivo. In this work, the utilization of an in vitro exposure system to expose human organotypic bronchial and nasal tissue models to mainstream CS is demonstrated. Ciliary beating frequency and the activity of cytochrome P450s (CYP) 1A1/1B1 were measured to assess functional impacts of CS on the tissues. Furthermore, to examine CS-induced alterations at the molecular level, gene expression profiles were generated from the tissues following exposure. A slight increase in CYP1A1/1B1 activity was observed in CS-exposed tissues compared with air-exposed tissues. A network-and transcriptomics-based systems biology approach was sufficiently robust to demonstrate CS-induced alterations of xenobiotic metabolism that were similar to those observed in the bronchial and nasal epithelial cells obtained from smokers.

Systems Toxicology Assessment of the Biological Impact of a Candidate Modified Risk Tobacco Product on Human Organotypic Oral Epithelial Cultures

Cigarette smoke (CS) has been reported to increase predisposition to oral cancer and is also recognized as a risk factor for many conditions including periodontal diseases, gingivitis, and other benign mucosal disorders. Smoking cessation remains the most effective approach for minimizing the risk of smoking-related diseases. However, reduction of harmful constituents by heating rather than combusting tobacco, without modifying the amount of nicotine, is a promising new paradigm in harm reduction. In this study, we compared effects of exposure to aerosol derived from a candidate modified risk tobacco product, the tobacco heating system (THS) 2.2, with those of CS generated from the 3R4F reference cigarette. Human organotypic oral epithelial tissue cultures (EpiOral, MatTek Corporation) were exposed for 28 min to 3R4F CS or THS2.2 aerosol, both diluted with air to comparable nicotine concentrations (0.32 or 0.51 mg nicotine/L aerosol/CS for 3R4F and 0.31 or 0.46 mg/L for THS2.2). We also tested one higher concentration (1.09 mg/L) of THS2.2. A systems toxicology approach was employed combining cellular assays (i.e., cytotoxicity and cytochrome P450 activity assays), comprehensive molecular investigations of the buccal epithelial transcriptome (mRNA and miRNA) by means of computational network biology, measurements of secreted proinflammatory markers, and histopathological analysis. We observed that the impact of 3R4F CS was greater than THS2.2 aerosol in terms of cytotoxicity, morphological tissue alterations, and secretion of inflammatory mediators. Analysis of the transcriptomic changes in the exposed oral cultures revealed significant perturbations in various network models such as apoptosis, necroptosis, senescence, xenobiotic metabolism, oxidative stress, and nuclear factor (erythroid-derived 2)-like 2 (NFE2L2) signaling. The stress responses following THS2.2 aerosol exposure were markedly decreased, and the exposed cultures recovered more completely compared with those exposed to 3R4F CS.

A systems toxicology approach for comparative assessment: Biological impact of an aerosol from a candidate modified-risk tobacco product and cigarette smoke on human organotypic bronchial epithelial cultures

This study reports a comparative assessment of the biological impact of a heated tobacco aerosol from the tobacco heating system (THS) 2.2 and smoke from a combustible 3R4F cigarette. Human organotypic bronchial epithelial cultures were exposed to an aerosol from THS2.2 (a candidate modified-risk tobacco product) or 3R4F smoke at similar nicotine concentrations. A systems toxicology approach was applied to enable a comprehensive exposure impact assessment. Culture histology, cytotoxicity, secreted pro-inflammatory mediators, ciliary beating, and genome-wide mRNA/miRNA profiles were assessed at various time points post-exposure. Series of experimental repetitions were conducted to increase the robustness of the assessment. At similar nicotine concentrations, THS2.2 aerosol elicited lower cytotoxicity compared with 3R4F smoke. No morphological change was observed following exposure to THS2.2 aerosol, even at nicotine concentration three times that of 3R4F smoke. Lower levels of secreted mediators and fewer miRNA alterations were observed following exposure to THS2.2 aerosol than following 3R4F smoke. Based on the computational analysis of the gene expression changes, 3R4F (0.13 mg nicotine/L) elicited the highest biological impact (100%) in the context of Cell Fate, Cell Proliferation, Cell Stress, and Inflammatory Network Models at 4 h post-exposure. Whereas, the corresponding impact of THS2.2 (0.14 mg nicotine/L) was 7.6%.

Construction of biological networks from unstructured information based on a semi-automated curation workflow

Abstract Capture and representation of scientific knowledge in a structured format are essential to improve the understanding of biological mechanisms involved in complex diseases. Biological knowledge and knowledge about standardized terminologies are difficult to capture from literature in a usable form. A semi-automated knowledge extraction workflow is presented that was developed to allow users to extract causal and correlative relationships from scientific literature and to transcribe them into the computable and human readable Biological Expression Language (BEL). The workflow combines state-of-the-art linguistic tools for recognition of various entities and extraction of knowledge from literature sources. Unlike most other approaches, the workflow outputs the results to a curation interface for manual curation and converts them into BEL documents that can be compiled to form biological networks. We developed a new semi-automated knowledge extraction workflow that was designed to capture and organize scientific knowledge and reduce the required curation skills and effort for this task. The workflow was used to build a network that represents the cellular and molecular mechanisms implicated in atherosclerotic plaque destabilization in an apolipoprotein-E-deficient (ApoE −/− ) mouse model. The network was generated using knowledge extracted from the primary literature. The resultant atherosclerotic plaque destabilization network contains 304 nodes and 743 edges supported by 33 PubMed referenced articles. A comparison between the semi-automated and conventional curation processes showed similar results, but significantly reduced curation effort for the semi-automated process. Creating structured knowledge from unstructured text is an important step for the mechanistic interpretation and reusability of knowledge. Our new semi-automated knowledge extraction workflow reduced the curation skills and effort required to capture and organize scientific knowledge. The atherosclerotic plaque destabilization network that was generated is a causal network model for vascular disease demonstrating the usefulness of the workflow for knowledge extraction and construction of mechanistically meaningful biological networks.

Comparative biological impacts of an aerosol from carbon-heated tobacco and smoke from cigarettes on human respiratory epithelial cultures: A systems toxicology assessment

The biological impact of an aerosol of a potential modified-risk tobacco product, carbon heated tobacco product 1.2 (CHTP1.2), was comprehensively assessed for the first time in vitro using human small airway and nasal epithelial models following a systems toxicology approach. The potentially reduced effects of CHTP1.2 aerosol exposure were benchmarked against those of 3R4F cigarette smoke at similar nicotine concentrations. Experimental repetitions were conducted for which new batches of small airway and nasal cultures were exposed to CHTP1.2 aerosol or 3R4F smoke for 28 minutes. The biological impacts were determined based on a collection of endpoints including morphology, cytotoxicity, proinflammatory mediator profiles, cytochrome P450 1A1/1B1 activity, global mRNA and microRNA changes and proteome profiles. Alterations in mRNA expression were detected in cultures exposed to CHTP1.2 aerosol, without noticeable morphological changes and cytotoxicity, and minimal impact on proinflammatory mediator and proteome profiles. The changes linked to CHTP1.2 aerosol exposure, when observed, were transient. However, the impact of 3R4F smoke exposure persisted long post-exposure and greater than CHTP1.2 aerosol. Morphological changes were observed only in cultures exposed to 3R4F smoke. The lower biological effects of CHTP1.2 aerosol than 3R4F smoke exposure were observed similarly in both small airway and nasal epithelial cultures.

Organs-on-a-chip: A new paradigm for toxicological assessment and preclinical drug development

In the last few years, considerable attention has been given to in vitro models in an attempt to reduce the use of animals and to decrease the rate of preclinical failure associated with the development of new drugs. Simple two-dimensional cultures grown in a dish are now frequently replaced by organotypic cultures with three-dimensional (3-D) architecture, which enables interactions between cells, promoting their differentiation and increasing their in vivo likeness. Microengineering now enables the incorporation of small devices into 3-D culture models to reproduce the complex microenvironment of the modeled organ, often referred to as organs-on-a-chip (OoCs). This review describes various OoCs developed to mimic liver, brain, kidney, and lung tissues. Current challenges encountered in attempts to recreate the in vivo environment are described, as well as some examples of OoCs. Finally, attention is given to the ongoing evolution of OoCs with the aim of solving one of the major limitations in that they can only represent a single organ. Multi-organ-on-a-chip (MOC) systems mimic organ interactions observed in the human body and aim to provide the features of compound uptake, metabolism, and excretion, while simultaneously allowing for insights into biological effects. MOCs might therefore represent a new paradigm in drug development, providing a better understanding of dose responses and mechanisms of toxicity, enabling the detection of drug resistance and supporting the evaluation of pharmacokinetic–pharmacodynamics parameters.

Abstract B1-19: Computable cancer hallmarks - The construction of novel computable biological network models reflecting causal mechanisms of cancer hallmarks

Over the past few years, we constructed a number of biological network models representing comprehensive connectivity maps of fundamental molecular mechanisms regulating cell proliferation, cellular stress, and cell fate in the healthy and inflamed lung and cardiovascular system [1, 2, 3, 4]. These network models are based on causal and correlative biological relationships expressed in Biological Expression Language (BEL). We further developed a method that quantifies network response as a whole in an interpretable manner by integrating these causal networks with systems biology data (e.g. transcriptomics) and could show that quantitative network perturbation was in agreement with experimental endpoint data for many of the mechanistic effects of interest [5]. Recently, we extended our efforts in an attempt to build a comprehensive set of computational models reflecting the biology of cancer hallmarks as described by Hanahan and Weinberg [6] with specific attention to mechanisms occurring in the early stages of non-small cell lung cancer (NSCLC) development and progression. Using a dual approach of curating relevant literature and supplementing this information with experimental data sets from a variety of NSCLC microarray studies, we thus far completed the construction of a “Sustaining Proliferative Signaling/Evading Growth Suppressors” hallmark model that describes multiple autocrine and paracrine signaling pathways responsible for driving continuous growth of tumor cells (e.g. growth factor/growth factor receptor, MAPK, JAK/STAT signaling etc.) and deregulating cell cycle check points, as well as a “Resisting Cell Death” hallmark model combining biological mechanisms indicative of intrinsic and extrinsic apoptosis pathways, necroptosis and autophagy that ensure (lung) tumor maintenance and survival. Processes related to VEGF- and other growth factor-driven angiogenesis, vascular sprouting and tubulogenesis, HIF1A signaling and endothelial cell activation were included in an “Inducing Angiogenesis” hallmark model. The latter is closely connected to the hallmark model “Activating Invasion and Metastasis” which also considers the mechanisms associated with the acquisition of invasive capabilities by e.g. epithelial-mesenchymal transition, the degradation of extracellular matrix, and epithelial and endothelial permeability permitting tumor cell dissemination. We further built a “Deregulating Cellular Energetics” hallmark model reflecting the metabolic switch in tumor cells to aerobic glycolysis including various aspects of hypoxia and autophagy. Our focus at the current time is to address the features associated with tumor immune surveillance as exemplified by the complex interplay between tumor cells and tumor-infiltrating lymphocytes, macrophages, dendritic cells and natural killer cells which could be reflected in an “Avoiding Immune Destruction” hallmark model. As a next step we wish to integrate specific mechanisms that contribute to persistent pro-inflammatory signaling into a “Tumor-promoting Inflammation” hallmark network model. This will be followed by a comprehensive review of the newly constructed models and, if necessary, further augmentation by literature and validation with molecular data. Ultimately, we will employ our previously developed network quantification approach together with a number of publicly available lung cancer data sets to objectively evaluate the predictability of disease mechanisms in silico using transcriptomics data, and we hope that, if successful in this endeavor, various applications from drug development to environmental impact analysis could benefit from employing this portfolio of network models in unraveling disease-specific mechanisms and identifying new therapeutic targets. [1] Westra JW, Schlage WK, Frushour BP et al. (2011). Construction of a computable cell proliferation network focused on non-diseased lung cells. BMC Syst Biol. 5, 105. [2] Gebel S, Lichtner RB, Frushour B et al. (2013). Construction of a computable network model for DNA damage, autophagy, cell death, and senescence. Bioinform Biol Insights 7, 97-117. [3] Westra JW, Schlage WK, Hengstermann A et al. (2013). A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue. Bioinform Biol Insights 7, 167-192. [4] De Leon H, Boue S, Schlage WK et al. (2014). A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability. J Transl Med. 12, 185. [5] Thomson TM, Sewer A, Martin F et al. (2013). Quantitative assessment of biological impact using transcriptomic data and mechanistic network models. Toxicol Appl Pharmacol. 272(3), 863-878. [6] Hanahan D & Weinberg RA (2011). Hallmarks of Cancer: The Next Generation. Cell 144(5), 646–674. Citation Format: Karsta Luettich, Marja Talikka, Anita Iskandar, Justyna Szostak, Ulrike Kogel, Walter Schlage, Yang Xiang, Vered Katz Ben-Yair, Shay Rotkopf, Brett Fields, Jennifer Park, Julia Hoeng, Manuel Peitsch. Computable cancer hallmarks - The construction of novel computable biological network models reflecting causal mechanisms of cancer hallmarks. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-19.