Identification of genes whose expression is upregulated in lung adenocarcinoma cells in comparison with type II alveolar cells and bronchiolar epithelial cells in vivo

Use of a human small airway epithelial cell line to study the interactions of Aspergillus fumigatus with pulmonary epithelial cells

During the initiation of invasive aspergillosis, inhaled Aspergillus fumigatus conidia are deposited on the epithelial cells lining the bronchi, terminal bronchioles, and alveoli. While the interactions of A. fumigatus with bronchial and type II alveolar cell lines have been investigated in vitro, little is known about the interactions of this fungus with terminal bronchiolar epithelial cells. Using the HSAEC1-KT human small airway epithelial (HSAE) cell line, we developed an in vitro model to study the interaction of two strains of A. fumigatus with these cells. We then compared the interactions of A. fumigatus with the A549 type II alveolar epithelial cell line and the HSAE cell line. We found that A. fumigatus conidia were poorly endocytosed by A549 cells, but avidly endocytosed by HSAE cells. A. fumigatus germlings invaded both cell types by induced endocytosis, but not by active penetration. A549 cell endocytosis of A. fumigatus was independent of fungal viability, more dependent on host microfilaments than microtubules, and induced by A. fumigatus CalA interacting with host cell integrin α5β1. By contrast, HSAE cell endocytosis required fungal viability, was more dependent on microtubules than microfilaments, and did not require CalA or integrin α5β1. HSAE cells were more susceptible than A549 cells to damage caused by direct contact with killed A. fumigatus germlings and by secreted fungal products. In response to A. fumigatus infection, A549 cells secreted a broader profile of cytokines and chemokines than HSAE cells. Taken together, these results demonstrate that studies of HSAE cells provide complementary data to A549 cells and thus represent a useful model for probing the interactions of A. fumigatus with bronchiolar epithelial cells in vitro. Importance During the initiation of invasive aspergillosis, Aspergillus fumigatus interacts with the epithelial cells that line the airways and alveoli. Previous studies of A. fumigatus-epithelial cell interactions in vitro used either large airway epithelial cell lines or the A549 type II alveolar epithelial cell line; the interactions of fungi with terminal bronchiolar epithelial cells were not investigated. Using the TERT-immortalized human small airway epithelial HSAEC1-KT (HSAE) cell line, we developed an in vitro model of the interactions of A. fumigatus with bronchiolar epithelial cells. We discovered that A. fumigatus invades and damages A549 and HSAE cell lines by distinct mechanisms. Also, the proinflammatory responses of the cell lines to A. fumigatus are different. These results provide insight into how A. fumigatus interacts with different types of epithelial cells during invasive aspergillosis and demonstrate that HSAE cells are useful in vitro model for investigating the interactions of this fungus with bronchiolar epithelial cells.

Use of a human small airway epithelial cell line to study the interactions of Aspergillus fumigatus with pulmonary epithelial cells

During the initiation of invasive aspergillosis, inhaled Aspergillus fumigatus conidia are deposited on the epithelial cells lining the bronchi, terminal bronchioles, and alveoli. While the interactions of A. fumigatus with bronchial and type II alveolar cell lines have been investigated in vitro , little is known about the interactions of this fungus with terminal bronchiolar epithelial cells. We compared the interactions of A. fumigatus with the A549 type II alveolar epithelial cell line and the HSAEC1-KT human small airway epithelial (HSAE) cell line. We found that A. fumigatus conidia were poorly endocytosed by A549 cells, but avidly endocytosed by HSAE cells. A. fumigatus germlings invaded both cell types by induced endocytosis, but not by active penetration. A549 cell endocytosis of A. fumigatus was independent of fungal viability, more dependent on host microfilaments than microtubules, and induced by A. fumigatus CalA interacting with host cell integrin α5β1. By contrast, HSAE cell endocytosis required fungal viability, was more dependent on microtubules than microfilaments, and did not require CalA or integrin α5β1. HSAE cells were more susceptible than A549 cells to damage caused by direct contact with killed A. fumigatus germlings and by secreted fungal products. In response to A. fumigatus infection, A549 cells secreted a broader profile of cytokines and chemokines than HSAE cells. Taken together, these results demonstrate that studies of HSAE cells provide complementary data to A549 cells and thus represent a useful model for probing the interactions of A. fumigatus with bronchiolar epithelial cells in vitro .

Importance

During the initiation of invasive aspergillosis, Aspergillus fumigatus invades, damages, and stimulates the epithelial cells that line the airways and alveoli. Previous studies of A. fumigatus - epithelial cell interactions in vitro have used either large airway epithelial cell lines or the A549 type II alveolar epithelial cell line. The interactions of fungi with terminal bronchiolar epithelial cells have not been investigated. Here, we compared the interactions of A. fumigatus with A549 cells and the Tert-immortalized human small airway epithelial HSAEC1-KT (HSAE) cell line. We discovered that A. fumigatus invades and damages these two cell lines by distinct mechanisms. Also, the proinflammatory responses of the cell lines to A. fumigatus are different. These results provide insight into how A. fumigatus interacts with different types of epithelial cells during invasive aspergillosis and demonstrate that HSAE cells are useful in vitro model for investigating the interactions of this fungus with bronchiolar epithelial cells.

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Mechanisms of Progression and Heterogeneity in Multiple Nodules of Lung Adenocarcinoma

Lung cancer remains the leading cause of cancer-related death worldwide. Lung adenocarcinoma (LUAD) is thought to be caused by precursor lesions of atypical adenoma-like hyperplasia and may have extensive in situ growth before infiltration. To explore the relevant factors in heterogeneity and evolution of lung adenocarcinoma subtypes, the authors perform single-cell RNA sequencing (scRNA-seq) on tumor and normal tissue from five multiple nodules' LUAD patients and conduct a thorough gene expression profiling of cancer cells and cells in their microenvironment at single-cell level. This study gives a deep understanding of heterogeneity and evolution in early glandular neoplasia of the lung. This dataset leads to discovery of the changes in the immune microenvironment during the development of LUAD, and the development process from adenocarcinoma in situ (AIS) to invasive adenocarcinoma (IAC). This work sheds light on the direction of early tumor development and whether they are homologous.

Identifying a Membrane-Type 2 Matrix Metalloproteinase-Targeting Peptide for Human Lung Cancer Detection and Targeting Chemotherapy with Functionalized Mesoporous Silica

Membrane-type 2 matrix metalloproteinase (MT2-MMP) is critical for the aggressive lung tumor growth, progression, and metastasis. Here, to obtain the peptides in binding specifically to MT2-MMP, a phage-displayed 12 peptide library was used and the affinity of peptides toward MT2-MMP was identified by multitest methods. The results showed that a specific MT2-MMP-targeting peptide with the sequence of HHRLHSAPPPQA (MT2-AF5p) exhibited a high specificity and strong affinity against lung tumors. To further achieve specific targeting and precise therapeutic effects, MT2-AF5p was conjugated onto fluorescent mesoporous silica nanoparticles (FMSN-NH₂) and loaded with doxorubicin (DOX) to construct a chemotherapeutic drug-targeting delivery system (DOX-loaded FMSN@MT2-AF5p). The DOX-loaded FMSN@MT2-AF5p achieved a boost in DOX release in an acidic environment. Most importantly, FMSN@MT2-AF5p efficiently targeted the tumor area, as seen in the fluorescent imaging ex vivo. The novel peptide-functionalized nanoparticles with a good biocompatibility are promising for clinical use as a precise targeting nanodrug for lung cancer diagnosis and therapy.

MT2-MMP induces proteolysis and leads to EMT in carcinomas

Epithelial-mesenchymal transition (EMT) is critical for carcinoma invasiveness and metastasis. To investigate the role of membrane-type-2 matrix metalloproteinase (MT2-MMP) in EMT, we generated lentiviral constructs of wild-type (WT) and an inactive Glu260Ala (E260A) mutant MT2-MMP and derived stably transfected HCT116 and A549 cell lines. WT-transfected cells appeared mesenchymal-like, whereas cells transfected with the E260A mutant were epithelial-like, as were cells treated with an MMP inhibitor (GM6001). Expression of E-cadherin, β-catenin, and zonula occludens-1 was lower in cells transfected with WT MT2-MMP compared to vector controls, cells treated with GM6001, or cells transfected with the E260A mutant. An 80-kD N-terminal fragment of E-cadherin was immunoprecipitated in conditioned medium from WT MT2-MMP cells, but not in the medium from vector controls, cells treated with GM6001, or E260A mutant cells. When endogenous expression of MT2-MMP in A2780 human ovarian cancer cells was inhibited using GM6001 or MT2-MMP-specific siRNA, levels of the 80-kD E-cadherin fragment in conditioned medium were decreased. Chick embryo chorioallantoic membrane invasion assays demonstrated that cells transfected with WT MT2-MMP were more invasive than cells transfected with control vector, treated with GM6001, or transfected with the E260A mutant. These results suggest that MT2-MMP degrades adherens and tight junction proteins and results in EMT, making it a potential mediator of EMT in carcinomas.

Uncovering Driver DNA Methylation Events in Nonsmoking Early Stage Lung Adenocarcinoma

As smoking rates decrease, proportionally more cases with lung adenocarcinoma occur in never-smokers, while aberrant DNA methylation has been suggested to contribute to the tumorigenesis of lung adenocarcinoma. It is extremely difficult to distinguish which genes play key roles in tumorigenic processes via DNA methylation-mediated gene silencing from a large number of differentially methylated genes. By integrating gene expression and DNA methylation data, a pipeline combined with the differential network analysis is designed to uncover driver methylation genes and responsive modules, which demonstrate distinctive expressions and network topology in tumors with aberrant DNA methylation. Totally, 135 genes are recognized as candidate driver genes in early stage lung adenocarcinoma and top ranked 30 genes are recognized as driver methylation genes. Functional annotation and the differential network analysis indicate the roles of identified driver genes in tumorigenesis, while literature study reveals significant correlations of the top 30 genes with early stage lung adenocarcinoma in never-smokers. The analysis pipeline can also be employed in identification of driver epigenetic events for other cancers characterized by matched gene expression data and DNA methylation data.

Identification of a multi-cancer gene expression biomarker for cancer clinical outcomes using a network-based algorithm

Cancer types are commonly classified by histopathology and more recently through molecular characteristics such as gene expression, mutations, copy number variations, and epigenetic alterations. These molecular characterizations have led to the proposal of prognostic biomarkers for many cancer types. Nevertheless, most of these biomarkers have been proposed for a specific cancer type or even specific subtypes. Although more challenging, it is useful to identify biomarkers that can be applied for multiple types of cancer. Here, we have used a network-based exploration approach to identify a multi-cancer gene expression biomarker highly connected by ESR1, PRKACA, LRP1, JUN and SMAD2 that can be predictive of clinical outcome in 12 types of cancer from The Cancer Genome Atlas (TCGA) repository. The gene signature of this biomarker is highly supported by cancer literature, biological terms, and prognostic power in other cancer types. Additionally, the signature does not seem to be highly associated with specific mutations or copy number alterations. Comparisons with cancer-type specific and other multi-cancer biomarkers in TCGA and other datasets showed that the performance of the proposed multi-cancer biomarker is superior, making the proposed approach and multi-cancer biomarker potentially useful in research and clinical settings.

Squamous Cell Carcinoma - Similarities and Differences among Anatomical Sites

Squamous cell carcinoma (SCC) is an epithelial malignancy involving many anatomical sites and is the most common cancer capable of metastatic spread. Development of early diagnosis methods and novel therapeutics are important for prevention and mortality reduction. In this effort, numerous molecular alterations have been described in SCCs. SCCs share many phenotypic and molecular characteristics, but they have not been extensively compared. This article reviews SCC as a disease, including: epidemiology, pathology, risk factors, molecular characteristics, prognostic markers, targeted therapy, and a new approach to studying SCCs. Through this comparison, several themes are apparent. For example, HPV infection is a common risk factor among the four major SCCs (NMSC, HNSC, ESCC, and NSCLC) and molecular abnormalities in cell-cycle regulation and signal transduction predominate. These data reveal that the molecular insights, new markers, and drug targets discovered in individual SCCs may shed light on this type of cancer as a whole.

Lung cancer transcriptomes refined with laser capture microdissection

We evaluated the importance of tumor cell selection for generating gene signatures in non-small cell lung cancer. Tumor and nontumor tissue from macroscopically dissected (Macro) surgical specimens (31 pairs from 32 subjects) was homogenized, extracted, amplified, and hybridized to microarrays. Adjacent scout sections were histologically mapped; sets of approximately 1000 tumor cells and nontumor cells (alveolar or bronchial) were procured by laser capture microdissection (LCM). Within histological strata, LCM and Macro specimens exhibited approximately 67% to 80% nonoverlap in differentially expressed (DE) genes. In a representative subset, LCM uniquely identified 300 DE genes in tumor versus nontumor specimens, largely attributable to cell selection; 382 DE genes were common to Macro, Macro with preamplification, and LCM platforms. RT-qPCR validation in a 33-gene subset was confirmatory (ρ = 0.789 to 0.964, P = 0.0013 to 0.0028). Pathway analysis of LCM data suggested alterations in known cancer pathways (cell growth, death, movement, cycle, and signaling components), among others (eg, immune, inflammatory). A unique nine-gene LCM signature had higher tumor-nontumor discriminatory accuracy (100%) than the corresponding Macro signature (87%). Comparison with Cancer Genome Atlas data sets (based on homogenized Macro tissue) revealed both substantial overlap and important differences from LCM specimen results. Thus, cell selection via LCM enhances expression profiling precision, and confirms both known and under-appreciated lung cancer genes and pathways.

Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung pairs, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent down-regulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways, and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and down-regulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell–cell and cell–matrix interactions, was recently shown to be a tumor suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by identifying novel epigenetically deregulated genes potentially involved in lung adenocarcinoma development/progression, and by describing an epigenetic subgroup of lung adenocarcinoma associated with characteristic molecular alterations.

Identification of novel candidate oncogenes in chromosome region 17p11.2-p12 in human osteosarcoma

Osteosarcoma is the most common primary malignancy of bone. The tumours are characterized by high genomic instability, including the occurrence of multiple regions of amplifications and deletions. Chromosome region 17p11.2–p12 is amplified in about 25% of cases. In previous studies, COPS3 and PMP22 have been identified as candidate oncogenes in this region. Considering the complexity and variation of the amplification profiles for this segment, the involvement of additional causative oncogenes is to be expected. The aim of the present investigation is to identify novel candidate oncogenes in 17p11.2–p12. We selected 26 of in total 85 osteosarcoma samples (31%) with amplification events in 17p11.2–p12, using quantitative PCR for 8 marker genes. These were subjected to high-resolution SNP array analysis and subsequent GISTIC analysis to identify the most significantly amplified regions. Two major amplification peaks were found in the 17p11.2–p12 region. Overexpression as a consequence of gene amplification is a major mechanism for oncogene activation in tumours. Therefore, to identify the causative oncogenes, we next determined expression levels of all genes within the two segments using expression array data that could be generated for 20 of the selected samples. We identified 11 genes that were overexpressed through amplification in at least 50% of cases. Nine of these, c17orf39, RICH2, c17orf45, TOP3A, COPS3, SHMT1, PRPSAP2, PMP22, and RASD1, demonstrated a significant association between copy number and expression level. We conclude that these genes, including COPS3 and PMP22, are candidate oncogenes in 17p11.2–p12 of importance in osteosarcoma tumourigenesis.

A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma

BACKGROUND

Lung cancer is the leading cause of cancer deaths in the world. The most common type of lung cancer is lung adenocarcinoma (AC). The genetic mechanisms of the early stages and lung AC progression steps are poorly understood. There is currently no clinically applicable gene test for the early diagnosis and AC aggressiveness. Among the major reasons for the lack of reliable diagnostic biomarkers are the extraordinary heterogeneity of the cancer cells, complex and poorly understudied interactions of the AC cells with adjacent tissue and immune system, gene variation across patient cohorts, measurement variability, small sample sizes and sub-optimal analytical methods. We suggest that gene expression profiling of the primary tumours and adjacent tissues (PT-AT) handled with a rational statistical and bioinformatics strategy of biomarker prediction and validation could provide significant progress in the identification of clinical biomarkers of AC. To minimise sample-to-sample variability, repeated multivariate measurements in the same object (organ or tissue, e.g. PT-AT in lung) across patients should be designed, but prediction and validation on the genome scale with small sample size is a great methodical challenge.

RESULTS

To analyse PT-AT relationships efficiently in the statistical modelling, we propose an Extreme Class Discrimination (ECD) feature selection method that identifies a sub-set of the most discriminative variables (e.g. expressed genes). Our method consists of a paired Cross-normalization (CN) step followed by a modified sign Wilcoxon test with multivariate adjustment carried out for each variable. Using an Affymetrix U133A microarray paired dataset of 27 AC patients, we reviewed the global reprogramming of the transcriptome in human lung AC tissue versus normal lung tissue, which is associated with about 2,300 genes discriminating the tissues with 100% accuracy. Cluster analysis applied to these genes resulted in four distinct gene groups which we classified as associated with (i) up-regulated genes in the mitotic cell cycle lung AC, (ii) silenced/suppressed gene specific for normal lung tissue, (iii) cell communication and cell motility and (iv) the immune system features. The genes related to mutagenesis, specific lung cancers, early stage of AC development, tumour aggressiveness and metabolic pathway alterations and adaptations of cancer cells are strongly enriched in the AC PT-AT discriminative gene set. Two AC diagnostic biomarkers SPP1 and CENPA were successfully validated on RT-RCR tissue array. ECD method was systematically compared to several alternative methods and proved to be of better performance and as well as it was validated by comparison of the predicted gene set with literature meta-signature.

CONCLUSIONS

We developed a method that identifies and selects highly discriminative variables from high dimensional data spaces of potential biomarkers based on a statistical analysis of paired samples when the number of samples is small. This method provides superior selection in comparison to conventional methods and can be widely used in different applications. Our method revealed at least 23 hundreds patho-biologically essential genes associated with the global transcriptional reprogramming of human lung epithelium cells and lung AC aggressiveness. This gene set includes many previously published AC biomarkers reflecting inherent disease complexity and specifies the mechanisms of carcinogenesis in the lung AC. SPP1, CENPA and many other PT-AT discriminative genes could be considered as the prospective diagnostic and prognostic biomarkers of lung AC.

Human matrix metalloproteinases: an ubiquitarian class of enzymes involved in several pathological processes

Human matrix metalloproteinases (MMPs) belong to the M10 family of the MA clan of endopeptidases. They are ubiquitarian enzymes, structurally characterized by an active site where a Zn(2+) atom, coordinated by three histidines, plays the catalytic role, assisted by a glutamic acid as a general base. Various MMPs display different domain composition, which is very important for macromolecular substrates recognition. Substrate specificity is very different among MMPs, being often associated to their cellular compartmentalization and/or cellular type where they are expressed. An extensive review of the different MMPs structural and functional features is integrated with their pathological role in several types of diseases, spanning from cancer to cardiovascular diseases and to neurodegeneration. It emerges a very complex and crucial role played by these enzymes in many physiological and pathological processes.

Gene expression-based classification of non-small cell lung carcinomas and survival prediction

Background

Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy.

Methodology and Principal Findings

A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts.

Conclusions

The gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome.

Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status: a microarray study

BACKGROUND

Several different gene expression signatures have been proposed to predict response to therapy and clinical outcome in lung adenocarcinoma. Herein, we investigate if elements of published gene sets can be reproduced in a small dataset, and how gene expression profiles based on limited sample size relate to clinical parameters including histopathological grade and EGFR protein expression.

METHODS

Affymetrix Human Genome U133A platform was used to obtain gene expression profiles of 28 pathologically and clinically annotated adenocarcinomas of the lung. EGFR status was determined by fluorescent in situ hybridization and immunohistochemistry.

RESULTS

Using unsupervised clustering algorithms, the predominant gene expression signatures correlated with the histopathological grade but not with EGFR protein expression as detected by immunohistochemistry. In a supervised analysis, the signature of high grade tumors but not of EGFR overexpressing cases showed significant enrichment of gene sets reflecting MAPK activation and other potential signaling cascades downstream of EGFR. Out of four different previously published gene sets that had been linked to prognosis, three showed enrichment in the gene expression signature associated with favorable prognosis.

CONCLUSIONS

In this dataset, histopathological tumor grades but not EGFR status were associated with dominant gene expression signatures and gene set enrichment reflecting oncogenic pathway activation, suggesting that high immunohistochemistry EGFR scores may not necessarily be linked to downstream effects that cause major changes in gene expression patterns. Published gene sets showed association with patient survival; however, the small sample size of this study limited the options for a comprehensive validation of previously reported prognostic gene expression signatures.

Smoking-Related Gene Expression in Laser Capture-Microdissected Human Lung

PURPOSE: Interindividual differences in quantitative expression could underlie a propensity for lung cancer. To determine precise individual gene expression signatures on a lung compartment-specific basis, we investigated the expression of carcinogen metabolism genes encoding cytochromes P450 (CYP) 1B1, 2A13, GSTP1, and a tumor suppressor gene p16 in laser capture-microdissected samples of human alveolar compartment (AC) and bronchial epithelial compartment (BEC) lung tissue from 62 smokers and nonsmokers. EXPERIMENTAL DESIGN: Tobacco exposure was determined by plasma nicotine, cotinine, and smoking history. Precise mRNA expression was determined using our RNA-specific qRT-PCR strategy, and correlated with detailed demographic and clinical characteristics. RESULTS: Several correlations of mRNA expression included (a) CYP1B1 in AC (positively with plasma nicotine level, P = 0.008; plasma cotinine level, P = 0.001), (b) GSTP1 in AC (positively with plasma cotinine level, P = 0.003), and (c) GSTP1 in BEC (negatively with smoke dose, P = 0.043; occupational risk, P = 0.019). CYP2A13 was rarely expressed in AC and not expressed in BEC. p16 expression was not correlated with any measured factor. For each gene, subjects showed expression that was individually concordant between these compartments. No clear association of mRNA expression with lung cancer risk was observed in this pilot analysis. CONCLUSIONS: The association between lung mRNA expression and tobacco exposure implies that gene-tobacco interaction is a measurable quantitative trait, albeit with wide interindividual variation. Gene expression tends to be concordant for alveolar and bronchial compartments for these genes in an individual, controlling for proximate tobacco exposure. (Clin Cancer Res 2009;15(24):7562-70).

Dopamine depletion induces distinct compensatory gene expression changes in DARPP-32 signal transduction cascades of striatonigral and striatopallidal neurons

Functional alterations in striatal projection neurons play a critical role in the development of motor symptoms in Parkinson's disease (PD), but their molecular adaptation to dopamine depletion remains poorly understood. In particular, type and extent of regulation in postsynaptic signal transduction pathways that determine the responsiveness of striatal projection neurons to incoming stimuli, are currently unknown. Using cell-type-specific transcriptome analyses in a rodent model of chronic dopamine depletion, we identified large-scale gene expression changes, including neurotransmitter receptors, signal transduction cascades, and target proteins of dopamine signaling in striatonigral and striatopallidal neurons. Within the dopamine- and cAMP-regulated phosphoprotein of 32 kDa (DARPP-32) cascade of enzymes that plays a central role in signal integration of dopaminoceptive neurons multiple catalytic and regulatory subunits change their mRNA expression levels. In addition to the number of genes the fact that the alterations occur at multiple levels stresses the biological relevance of transcriptional regulation for adaptations of postsynaptic signaling pathways. The overall pattern of changes in both striatonigral and striatopallidal neurons is compatible with homeostatic mechanisms. In accordance with the distinct biological effects of dopamine D(1) and D(2) receptor stimulation, the alterations of the transcriptional profiles most likely result in prodopaminergic phosphorylation patterns. Our data provide insight into the disease-related plasticity of functional genomic networks in vivo that might contribute to the protracted preclinical phase of PD. In addition, the data have potential implications for the symptomatic treatment of the disease.

Cross talk between hedgehog and epithelial-mesenchymal transition pathways in gastric pit cells and in diffuse-type gastric cancers

We previously reported hedgehog (Hh) signal activation in the mucus-secreting pit cell of the stomach and in diffuse-type gastric cancer (GC). Epithelial–mesenchymal transition (EMT) is known to be involved in tumour malignancy. However, little is known about whether and how both signallings cooperatively act in diffuse-type GC. By microarray and reverse transcription–PCR, we investigated the expression of those Hh and EMT signalling molecules in pit cells and in diffuse-type GCs. How both signallings act cooperatively in those cells was also investigated by the treatment of an Hh-signal inhibitor and siRNAs of Hh and EMT transcriptional key regulator genes on a mouse primary culture and on human GC cell lines. Pit cells and diffuse-type GCs co-expressed many Hh and EMT signalling genes. Mesenchymal-related genes (WNT5A, CDH2, PDGFRB, EDNRA, ROBO1, ROR2, and MEF2C) were found to be activated by an EMT regulator, SIP1/ZFHX1B/ZEB2, which was a target of a primary transcriptional regulator GLI1 in Hh signal. Furthermore, we identified two cancer-specific Hh targets, ELK1 and MSX2, which have an essential role in GC cell growth. These findings suggest that the gastric pit cell exhibits mesenchymal-like gene expression, and that diffuse-type GC maintains expression through the Hh–EMT pathway. Our proposed extensive Hh–EMT signal pathway has the potential to an understanding of diffuse-type GC and to the development of new drugs.

Extreme value theory in analysis of differential expression in microarrays where either only up- or down-regulated genes are relevant or expected

We propose an empirical Bayes method based on the extreme value theory (EVT) (BE) for the analysis of data from spotted microarrays where the interest of the investigator (e.g. to identify up-regulated gene markers of a disease) or the design of the experiment (e.g. in certain 'wild-type versus mutant' experiments) limits identification of differentially expressed genes to those regulated in a single direction (either up or down). In such experiments, unlike in genome-wide microarrays, analysis is restricted to the tail of the distribution (extremes) of all the genes in the genome. The EVT provides a platform to account for this extreme behaviour, and is therefore a natural candidate for inference about differential expression. We compared the performance of the developed BE method with two other empirical Bayes methods on two real 'wild-type versus mutant' datasets where a single direction of regulation was expected due to experimental design, and in a simulation study. The BE method appears to have a better fit to the real data. In the analysis of simulated data, the BE method showed better accuracy and precision while being robust to different characteristics of microarray experiments. The BE method, therefore, seems promising and useful for inference about differential expression in microarrays where either only up- or down-regulated genes are relevant or expected.

Differential gene expression in human conducting airway surface epithelia and submucosal glands

Human conducting airways contain two anatomically distinct epithelial cell compartments: surface epithelium and submucosal glands (SMG). Surface epithelial cells interface directly with the environment and function in pathogen detection, fluid and electrolyte transport, and mucus elevation. SMG secrete antimicrobial molecules and most of the airway surface fluid. Despite the unique functional roles of surface epithelia and SMG, little is known about the differences in gene expression and cellular metabolism that orchestrate the specialized functions of these epithelial compartments. To approach this problem, we performed large-scale transcript profiling using epithelial cell samples obtained by laser capture microdissection (LCM) of human bronchus specimens. We found that SMG expressed high levels of many transcripts encoding known or putative innate immune factors, including lactoferrin, zinc alpha-2 glycoprotein, and proline-rich protein 4. By contrast, surface epithelial cells expressed high levels of genes involved in basic nutrient catabolism, xenobiotic clearance, and ciliated structure assembly. Selected confirmation of differentially expressed genes in surface and SMG epithelia demonstrated the predictive power of this approach in identifying genes with localized tissue expression. To characterize metabolic differences between surface epithelial cells and SMG, immunostaining for a mitochondrial marker (isocitrate dehydrogenase) was performed. Because greater staining was observed in the surface compartment, we predict that these cells use significantly more energy than SMG cells. This study illustrates the power of LCM in defining the roles of specific anatomic features in airway biology and may be useful in examining how disease states alter transcriptional programs in the conducting airways.

Membrane type matrix metalloproteinases (MMPs) show differential expression in non-small cell lung cancer (NSCLC) compared to normal lung: correlation of MMP-14 mRNA expression and proteolytic activity

Improved understanding of the involvement of matrix metalloproteinases (MMPs), including membrane-type MMPs (MT-MMPs), in human tumours has potential diagnostic, prognostic and therapeutic implications. We assessed the relationship between MT-MMP expression and clinicopathological parameters in human non-small cell lung cancer (NSCLC) and histologically normal lung tissue by quantitative Real Time PCR (qRT-PCR). All MT-MMPs (MMPs 14-17, 24 and 25) were detected by qRT-PCR with significantly higher MMP-14, -15 and -17 expression observed in tumour relative to normal lung specimens. MMP-16 was undetectable in normal lung but expressed in 8% tumours. MMP-15 demonstrated significant overexpression in adenocarcinomas relative to squamous cell carcinomas and normal lung tissue. MMP-14 mRNA expression strongly correlated to MMP-14 proteolytic activity in preclinical tumour models, indicating that qRT-PCR may predict MMP-14 activity levels in NSCLC. These data suggest that MMP-14, -15 and -17 may be good markers of disease, or therapeutic targets for treatment of human NSCLC.

Respiratory immunotoxicity: An in vitro assessment

As yet, in vitro assessment of the immunotoxic potency of respiratory agents is not possible. The complexity of the endpoint and the respiratory tract, and the limited availability of well-documented respiratory agents are the main reasons. The evidence that epithelial cells (ECs) are triggered by compounds to express in vitro surface proteins and soluble mediators, has stimulated their use for developing tests for respiratory immunotoxicity. A variety of airway ECs and EC-lines have been assessed, but the available information seems to point at human alveolar cells (e.g., A549) as the most convenient cell type. EC-based test formats with various degrees of complexity have been assessed. Sofar, promising results were obtained using a 3D model using the human A549 lung cell line. Dendritic cells (DCs) have been subjected to intensive research. However, currently available tests are not well suited to discern among the potency of sensitizers. Potential explanations include the lack of standardised protocols for the generation of DCs, no good standards for estimating the quality of in vitro derived DC-cultures, and limited dynamics of the currently used end-points. Alveolar macrophages (AMs) have so far received less attention. This may proof unjustified as macrophages may link innate responses to adaptive immunity. The observation that ECs, DCs and AMs affect each other, suggests that test formats are required combining at least two of these cell types if ranking of compounds according to their sensitising potency is the aim. In addition, the capacity of compounds to cross a cellular membrane is an important property of an immunotoxic compound, which can be assessed only in 3D reconstituted human tissue models. While promising data have been reported for the skin, immunocompetent 3D reconstituted human lung remains to be evaluated for respiratory immunotoxicity. Obviously, the success of any of these simplified test (as compared to the complexity of the immune response) is highly dependent on the availability of early stage biomarkers (expressed at mucosal barrier level) that are predictive for relevant immunotoxicity mechanisms occurring down-stream of the immune response. As yet, such biomarkers are not yet available.

Transcriptosome and serum cytokine profiling of an atypical case of myelodysplastic syndrome with progression to acute myelogenous leukemia

A Native American-Indian female presenting with anemia and thrombocytosis was diagnosed with myelodysplastic syndrome (MDS, refractory anemia). Over the course of 5 years she developed cytopenias and periods of leukocytosis with normal bone marrow (BM) blast counts, features of an unclassifiable MDS/MPS syndrome. The patient ultimately progressed to acute myelogenous leukemia (AML, FAB M2) and had a normal karyotype throughout her course. The episodes of leukocytosis were associated with infectious complications. Transformation to AML was characterized by a BM blast percentage of 49%. Peripheral blood and BM samples were obtained for serum protein analysis and gene expression profiling (GEP) to elucidate her disease process. An ELISA assay of the serum analyzed approximately 80 cytokines, which demonstrated that hepatocyte growth factor/scatter factor and insulin-like growth factor binding protein 1 were markedly elevated compared to normal. GEP demonstrated a unique "tumor molecular profile," which included overexpression of oncogenes (HOXA9, N-MYC, KOC1), proliferative genes (PAWR, DLG5, AKR1C3), invasion/metastatic genes (FN1, N-CAM-1, ITGB5), pro-angiogenesis genes (c-Kit), and down regulation of tumor suppressor genes (SUI1, BARD1) and anti-apoptotic genes (PGLYRP, SERPINB2, MPO). Hence, a biomics approach has provided insight into elucidating disease mechanisms, molecular prognostic factors, and discovery of novel targets for therapeutic intervention.

Identification of tumor markers and differentiation markers for molecular diagnosis of lung adenocarcinoma

To identify tumor markers and differentiation markers for lung adenocarcinoma (AdC), we analysed expression profiles of 14,500 genes against three cases of type II alveolar epithelial cells, bronchiolar epithelial cells, and bronchial epithelial cells, respectively, and 10 cases of AdC cells isolated by laser capture microdissection. Hierarchical clustering analysis indicated that AdC cells and noncancerous lung epithelial cells are significantly different in their expression profiles, and that different sets of differentiation markers are expressed among alveolar, bronchiolar and bronchial epithelial cells. Nine genes were identified as being highly expressed in AdC cells, but not expressed in noncancerous lung epithelial cells. Sixteen genes were identified as differentiation markers for lung epithelial cells. Real-time RT-PCR analysis of 45 lung AdC cases further revealed that expression of four tumor markers in AdC cells was significantly higher than that in noncancerous lung cells and that expression of ten differentiation markers was retained in a considerable fraction of lung AdC cases. Five tumor markers and seven differentiation markers were not expressed in peripheral blood cells. Similarities and differences in expression profiles between normal epithelial cells from different lung respiratory compartments and AdC cells demonstrated in this study will be informative for the molecular diagnosis of lung AdC.

Mechanism of action of ferrocene derivatives on the catalytic activity of topoisomerase IIα and β—Distinct mode of action of two derivatives

Topoisomerase II is found to be present in two isoforms alpha and beta, and both the isoforms are regulated in cancerous tissue. Development of isoform-specific topoisomerase II poisons has been of great interest for cancer-specific drug targeting. In the present investigation using quantitative structure-activity analysis of ferrocene derivatives, we show that two derivatives of ferrocene, azalactone ferrocene and thiomorpholide amido methyl ferrocene, can preferentially inhibit topoisomerase IIbeta activity. Thiomorpholide amido methyl ferrocene shows higher inhibition of catalytic activity (IC(50) = 50 microM) against topoisomerase IIbeta compared to azalactone ferrocene (IC(50) = 100 microM). The analysis of protein DNA intermediates formed in the presence of these two compounds suggests that azalactone ferrocene readily induces formation of cleavable complex in a dose-dependent manner, in comparison with thiomorpholide amido methyl ferrocene. Both the compounds show significant inhibition of DNA-dependent ATPase activity of enzyme. These results suggest that azalactone ferrocene inhibits DNA passage activity of enzyme leading to the formation of cleavable complex, while thiomorpholide amido methyl ferrocene competes with ATP binding resulting in the inhibition of catalytic activity of enzyme. In summary, thiomorpholide amido methyl ferrocene and azalactone ferrocene show distinctly different mechanisms in inhibition of catalytic activity of topoisomerase IIbeta.

From signatures to models: understanding cancer using microarrays

Genomics has the potential to revolutionize the diagnosis and management of cancer by offering an unprecedented comprehensive view of the molecular underpinnings of pathology. Computational analysis is essential to transform the masses of generated data into a mechanistic understanding of disease. Here we review current research aimed at uncovering the modular organization and function of transcriptional networks and responses in cancer. We first describe how methods that analyze biological processes in terms of higher-level modules can identify robust signatures of disease mechanisms. We then discuss methods that aim to identify the regulatory mechanisms underlying these modules and processes. Finally, we show how comparative analysis, combining human data with model organisms, can lead to more robust findings. We conclude by discussing the challenges of generalizing these methods from cells to tissues and the opportunities they offer to improve cancer diagnosis and management.

Laser capture microdissection, microarrays and the precise definition of a cancer cell

Most expression profiling studies of solid tumors have used biopsy samples containing large numbers of contaminating stromal and other cell types, thereby complicating any precise delineation of gene expression in nontumor versus tumor cell types. Combining laser capture microdissection, RNA amplification protocols, microarray technologies and our knowledge of the human genome sequence, it is possible to isolate pure populations of cells or even a single cell and interrogate the expression of thousands of sequences for the purpose of more precisely defining the biology of the tumor cell. Although many of the studies that currently allow for characterization of small sample preparations and single cells were performed utilizing noncancer cell types, and in some cases isolation protocols other than laser capture microdissection, a list of protocols are described that could be used for the expression analysis of individual tumor cells. Application of these experimental approaches to cancer studies may permit a more accurate definition of the biology of the cancer cell, so that ultimately, more specific targeted therapies can be developed.

S100A2 is strongly expressed in airway basal cells, preneoplastic bronchial lesions and primary non-small cell lung carcinomas

S100A2 gene products were shown to be frequently and dramatically over-represented in non-small cell lung cancer (NSCLC) lesions over normal tissue by microarray analysis. We have now analysed an independent series of NSCLC tumours and multiple matched normal bronchial epithelial sites by RT–PCR and immunohistochemistry to investigate: whether this expression pattern can be confirmed and whether elevated expression is associated with tumour histology, clinical outcome or preneoplasia. In this second series, S100A2 was strongly expressed in 76% (35 out of 46) of tumours, more frequently in squamous cell than adenocarcinomas (P<0.002). This strong expression was not related to high-level gene amplification, but was associated in one of five informative cases with an allele-specific imbalance in transcript levels. Most tumours strongly expressed the ΔNp63 transcript, the product of which is a putative regulator of S100A2 transcription and while all but one of the tumours positive for ΔNp63 expressed S100A2, others negative for this regulator also expressed the gene. Contrary to the hypothesis that S100A2 is a tumour suppressor, no somatic mutations were identified in the coding sequence in 44 tumours. Furthermore, an examination of multiple tumour-free epithelial sites from 20 patients showed that strong expression was often associated with increasing levels of disorder in preinvasive bronchial lesions (P<0.0001).