Karsta Luettich

Trans-splicing repair of CD40 ligand deficiency results in naturally regulated correction of a mouse model of hyper-IgM X-linked immunodeficiency

X-linked immunodeficiency with hyper-IgM (HIGM1), characterized by failure of immunoglobulin isotype switching, is caused by mutations of the CD40 ligand (CD40L), which is normally expressed on activated CD4+ T cells. As constitutive expression of CD40L induces lymphomas, we corrected the mutation while preserving the natural regulation of CD40L using pre-mRNA trans-splicing. Bone marrow from mice lacking CD40L was modified with a lentivirus trans-splicer encoding the normal CD40L exons 2–5 and was administered to syngenic CD40L-knockout mice. Recipient mice had corrected CD40L mRNA, antigen-specific IgG1 responses to keyhole limpet hemocyanin immunization, regulated CD4+ T-cell CD40L expression after CD3 stimulation in primary and secondary transplanted mice, attenuation of Pneumocystis carinii pneumonia, and no evidence of lymphoproliferative disease over 1 year. Thus, HIGM1 can be corrected by CD40L trans-splicing, leading to functional correction of the genetic defect without the adverse consequences of unregulated expression of the CD40L gene.

Gene expression profiling of human alveolar macrophages of phenotypically normal smokers and nonsmokers reveals a previously unrecognized subset of genes modulated by cigarette smoking

Cigarette smoking is the leading cause of the respiratory diseases collectively known as chronic obstructive pulmonary disease (COPD). While the pathogenesis of COPD is complex, there is abundant evidence that alveolar macrophages (AM) play an important role. Based on the concept that COPD is a slow-progressing disorder likely involving multiple mediators released by AM activated by cigarette smoke, the present study focuses on the identification of previously unrecognized genes that may be linked to early events in the molecular pathogenesis of COPD, as opposed to factors associated with the presence of disease. To accomplish this, microarray analysis using Affymetrix microarrays was used to carry out an unbiased survey of the differences in gene expression profiles in the AM of phenotypically normal, ∼20 pack-year smokers compared to healthy nonsmokers. Although smoking did not alter the global gene expression pattern of AM, 75 genes were modulated by smoking, with 40 genes up-regulated and 35 down-regulated in the AM of smokers compared to nonsmokers. Most of these genes belong to the functional categories of immune/inflammatory response, cell adhesion and extracellular matrix, proteolysis and antiproteolysis, lysosomal function, antioxidant-related function, signal transduction, and regulation of transcription. Of these 75 genes, 69 have not been previously recognized to be up- or down-regulated in AM in association with smoking or COPD, including genes coding for proteins belonging to all of the above categories, and others belonging to various functional categories or of unknown function. These observations suggest that gene expression responses of AM associated with the stress of cigarette smoking are more complex than previously thought, and offer a variety of new insights into the complex pathogenesis of smoking-induced lung diseases.

Retraction Note: TGFβ1 activates c-Jun and Erk1 via aVβ6 integrin

The data published in this article [1] and in a preceding article in Molecular Cancer [2] were generated by myself, the corresponding author, with collaborators in Germany. The data were originally part of a manuscript on which my collaborators were authors and which remains unpublished. When publishing the data in Molecular Cancer, I failed to obtain the agreement from my past collaborators or to acknowledge their contributions, resulting in an unfair representation of their ideas and thoughts. In light of this, I have decided to retract the two papers. I deeply apologize for any inconvenience this may have caused.

TGFβ1 activates c-Jun and Erk1 via αVβ6 integrin

Transforming growth factor β (TGFβ) plays an important role in animal development and many cellular processes. A variety of cellular functions that are required for tumor metastasis are controlled by integrins, a family of cell adhesion receptors. Overexpression of αVβ6 integrin is associated with lymph node metastasis of gastric carcinomas. It has been demonstrated that a full TGFβ1 signal requires both αVβ6 integrin and SMAD pathway. TGFβ1 binds to αVβ6 via the DLXXL motif, a freely accessible amino acid sequence in the mature form of TGFβ1. Binding of mature TGFβ1 to αVβ6 leads to immobilization and tyrosine phosphorylation of proteins, which are associated with focal adhesions, a hallmark of integrin-mediated signal transduction. Here, we show that binding of mature TGFβ1 recruits the mitogen-activated protein kinase kinase kinase 1 (MEKK1), a mediator of c-Jun activation, and the extracellular signaling-regulated kinase-1 (Erk1) to focal adhesions. In addition, the p21-activated kinase 1 (PAK1) is associated with focal adhesions and differentially phosphorylated upon TGFβ1 stimulation. We conclude that TGFβ1 activates c-Jun via the MEKK1/p38 MAP kinase pathway and influences cytoskeletal organization. These finding may provide a link between TGFβ1 and the metastatic behavior of cancers.

Similarity of Gene Expression Patterns in Human Alveolar Macrophages in Response to Pseudomonas aeruginosa and Burkholderia cepacia

ABSTRACT To determine if differences in the severity of pulmonary infection in cystic fibrosis seen with late isolates of Pseudomonas aeruginosa and Burkholderia cepacia are associated with differences in the initial response of alveolar macrophages (AM) to these pathogens, we assessed gene expression changes in human AM in response to infection with a laboratory strain, early and late clinical isolates of P. aeruginosa, and B. cepacia. Analysis of gene expression changes at the RNA level using oligonucleotide microarrays, following exposure to laboratory P. aeruginosa strain PAK, showed significant (P < 0.01) >2.5-fold upregulation of 42 genes and >2.5-fold downregulation of 45 genes. The majority of the changes in gene expression involved genes as part of inflammatory pathways and signaling systems. Interestingly, similar responses were observed following exposure of AM to early and late clinical isolates of P. aeruginosa, as well as with B. cepacia, suggesting that the more severe clinical outcome of infections with late clinical isolates of P. aeruginosa or with B. cepacia cannot be explained by differences in the early interactions of these organisms with the human AM, as reflected by the similarity of gene expression changes in response to exposure of AM to these pathogens.

Assessment of mitochondrial function following short- and long-term exposure of human bronchial epithelial cells to total particulate matter from a candidate modified-risk tobacco product and reference cigarettes

Mitochondrial dysfunction caused by cigarette smoke is involved in the oxidative stress-induced pathology of airway diseases. Reducing the levels of harmful and potentially harmful constituents by heating rather than combusting tobacco may reduce mitochondrial changes that contribute to oxidative stress and cell damage. We evaluated mitochondrial function and oxidative stress in human bronchial epithelial cells (BEAS 2B) following 1- and 12-week exposures to total particulate matter (TPM) from the aerosol of a candidate modified-risk tobacco product, the Tobacco Heating System 2.2 (THS2.2), in comparison with TPM from the 3R4F reference cigarette. After 1-week exposure, 3R4F TPM had a strong inhibitory effect on mitochondrial basal and maximal oxygen consumption rates compared to TPM from THS2.2. Alterations in oxidative phosphorylation were accompanied by increased mitochondrial superoxide levels and increased levels of oxidatively damaged proteins in cells exposed to 7.5 μg/mL of 3R4F TPM or 150 μg/mL of THS2.2 TPM, while cytosolic levels of reactive oxygen species were not affected. In contrast, the 12-week exposure indicated adaptation of BEAS-2B cells to long-term stress. Together, the findings indicate that 3R4F TPM had a stronger effect on oxidative phosphorylation, gene expression and proteins involved in oxidative stress than TPM from the candidate modified-risk tobacco product THS2.2.

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.

First anniversary of Molecular Cancer: achievements and future goals

Molecular Cancer has been launched for one year now. Here, we describe achievements of the past year and future goals of the journal.

Physiological and biological characterization of smokers with and without COPD

Chronic obstructive pulmonary disease (COPD) is a common inflammatory airway disease predominantly associated with cigarette smoking, and its incidence is increasing worldwide. According to the Global Initiative for Obstructive Lung Disease (GOLD) guidelines, spirometry is used to diagnose the disease. However, owing to its complexity, spirometry alone may not account for the multitude of COPD phenotypes or the early, asymptomatic lung damage seen in younger smokers. In addition, suitable biomarkers enabling early diagnosis, guiding treatment and estimating prognosis are still scarce, although large scale ‘omics analyses have added to the spectrum of potential biomarkers that could be used for these purposes. The aim of the current study was to comprehensively profile patients with mild-to-moderate COPD and compare the profiles to i) a group of currently smoking asymptomatic subjects, ii) a group of healthy former smokers, and iii) a group of healthy subjects that had never smoked. The assessment was conducted at the molecular level using proteomics, transcriptomics, and lipidomics and complemented by a series of measurements of traditional and emerging indicators of lung health (ClinicalTrials.gov identifier: NCT01780298). In this data note, we provide a comprehensive description of the study population’s physiological characteristics including full lung function, lung appearance on chest computed tomography, impulse oscillometry, and exercise tolerance and quality of life (QoL) measures.

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.