Global detection of molecular changes reveals concurrent alteration of several biological pathways in nonsmall cell lung cancer cells

Porphyromonas gingivalis gingipains potentially affect MUC5AC gene expression and protein levels in respiratory epithelial cells

Porphyromonas gingivalis (Pg) is a periodontopathic pathogen that may affect MUC5AC‐related mucus hypersecretion along airway epithelial cells. Here, we attempted to establish whether Pg virulence factors (lipopolysaccharide, FimA fimbriae, gingipains) affect MUC5AC in immortalized and primary bronchial cells. We report that MUC5AC gene expression and protein levels are affected by Pg culture supernatant, but not by lipopolysaccharide or FimA fimbriae. Cells treated with either Pg single (Kgp or Rgp) or double (Kgp/Rgp) mutants had altered levels of MUC5AC gene expression and protein levels, and MUC5AC staining of double mutant‐treated mouse lung cells showed that MUC5AC protein levels were unaffected. Taken together, we propose that Pg gingipains may be the primary virulence factor that influences both MUC5AC gene expression and protein levels.

Long noncoding RNA LINC00673-v4 promotes aggressiveness of lung adenocarcinoma via activating WNT/β-catenin signaling

This study uncovers a long noncoding RNA (lncRNA)-mediated mechanism underlying lung adenocarcinoma (LAD) metastasis. We here report that lncRNA LINC00673-v4 expression is up-regulated in LAD and is associated with disease progression. At the molecular level, LINC00673-v4 acts as a scaffold molecule that promotes the interaction between DDX3 and CK1ε and thus the phosphorylation of dishevelled, which subsequently activates WNT/β-catenin signaling and consequently causes aggressiveness of LAD. Treatment with antisense oligonucleotides against LINC00673-v4 strongly suppresses LAD metastasis in vivo.

It is well recognized that metastasis can occur early in the course of lung adenocarcinoma (LAD) development, and yet the molecular mechanisms driving this capability of rapid metastasis remain incompletely understood. Here we reported that a long noncoding RNA, LINC00673, was up-regulated in LAD cells. Of note, we first found that LINC00673-v4 was the most abundant transcript of LINC00673 in LAD cells and its expression was associated with adverse clinical outcome of LAD. In vitro and in vivo experiments demonstrated that LINC00673-v4 enhanced invasiveness, migration, and metastasis of LAD cells. Mechanistically, LINC00673-v4 augmented the interaction between DDX3 and CK1ε and thus the phosphorylation of dishevelled, which subsequently activated WNT/β-catenin signaling and consequently caused aggressiveness of LAD. Antagonizing LINC00673-v4 suppressed LAD metastasis in vivo. Together, our data suggest that LINC00673-v4 is a driver molecule for metastasis via constitutively activating WNT/β-catenin signaling in LAD and may represent a potential therapeutic target against the metastasis of LAD.

Reconstruction of an integrated genome-scale co-expression network reveals key modules involved in lung adenocarcinoma

Our goal of this study was to reconstruct a “genome-scale co-expression network” and find important modules in lung adenocarcinoma so that we could identify the genes involved in lung adenocarcinoma. We integrated gene mutation, GWAS, CGH, array-CGH and SNP array data in order to identify important genes and loci in genome-scale. Afterwards, on the basis of the identified genes a co-expression network was reconstructed from the co-expression data. The reconstructed network was named “genome-scale co-expression network”. As the next step, 23 key modules were disclosed through clustering. In this study a number of genes have been identified for the first time to be implicated in lung adenocarcinoma by analyzing the modules. The genes EGFR, PIK3CA, TAF15, XIAP, VAPB, Appl1, Rab5a, ARF4, CLPTM1L, SP4, ZNF124, LPP, FOXP1, SOX18, MSX2, NFE2L2, SMARCC1, TRA2B, CBX3, PRPF6, ATP6V1C1, MYBBP1A, MACF1, GRM2, TBXA2R, PRKAR2A, PTK2, PGF and MYO10 are among the genes that belong to modules 1 and 22. All these genes, being implicated in at least one of the phenomena, namely cell survival, proliferation and metastasis, have an over-expression pattern similar to that of EGFR. In few modules, the genes such as CCNA2 (Cyclin A2), CCNB2 (Cyclin B2), CDK1, CDK5, CDC27, CDCA5, CDCA8, ASPM, BUB1, KIF15, KIF2C, NEK2, NUSAP1, PRC1, SMC4, SYCE2, TFDP1, CDC42 and ARHGEF9 are present that play a crucial role in cell cycle progression. In addition to the mentioned genes, there are some other genes (i.e. DLGAP5, BIRC5, PSMD2, Src, TTK, SENP2, PSMD2, DOK2, FUS and etc.) in the modules.

A pathway-based approach to identify molecular biomarkers in cancer

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Comparison of lung cancer cell lines representing four histopathological subtypes with gene expression profiling using quantitative real-time PCR

BACKGROUND

Lung cancers are the most common type of human malignancy and are intractable. Lung cancers are generally classified into four histopathological subtypes: adenocarcinoma (AD), squamous cell carcinoma (SQ), large cell carcinoma (LC), and small cell carcinoma (SC). Molecular biological characterization of these subtypes has been performed mainly using DNA microarrays. In this study, we compared the gene expression profiles of these four subtypes using twelve human lung cancer cell lines and the more reliable quantitative real-time PCR (qPCR).

RESULTS

We selected 100 genes from public DNA microarray data and examined them by DNA microarray analysis in eight test cell lines (A549, ABC-1, EBC-1, LK-2, LU65, LU99, STC 1, RERF-LC-MA) and a normal control lung cell line (MRC-9). From this, we extracted 19 candidate genes. We quantified the expression of the 19 genes and a housekeeping gene, GAPDH, with qPCR, using the same eight cell lines plus four additional validation lung cancer cell lines (RERF-LC-MS, LC-1/sq, 86-2, and MS-1-L). Finally, we characterized the four subtypes of lung cancer cell lines using principal component analysis (PCA) of gene expression profiling for 12 of the 19 genes (AMY2A, CDH1, FOXG1, IGSF3, ISL1, MALL, PLAU, RAB25, S100P, SLCO4A1, STMN1, and TGM2). The combined PCA and gene pathway analyses suggested that these genes were related to cell adhesion, growth, and invasion. S100P in AD cells and CDH1 in AD and SQ cells were identified as candidate markers of these lung cancer subtypes based on their upregulation and the results of PCA analysis. Immunohistochemistry for S100P and RAB25 was closely correlated to gene expression.

CONCLUSIONS

These results show that the four subtypes, represented by 12 lung cancer cell lines, were well characterized using qPCR and PCA for the 12 genes examined. Certain genes, in particular S100P and CDH1, may be especially important for distinguishing the different subtypes. Our results confirm that qPCR and PCA analysis provide a useful tool for characterizing cancer cell subtypes, and we discuss the possible clinical applications of this approach.

Cancer genomics identifies regulatory gene networks associated with the transition from dysplasia to advanced lung adenocarcinomas induced by c-Raf-1

BACKGROUND

Lung cancer is a leading cause of cancer morbidity. To improve an understanding of molecular causes of disease a transgenic mouse model was investigated where targeted expression of the serine threonine kinase c-Raf to respiratory epithelium induced initially dysplasia and subsequently adenocarcinomas. This enables dissection of genetic events associated with precancerous and cancerous lesions.

METHODOLOGY/PRINCIPAL FINDINGS

By laser microdissection cancer cell populations were harvested and subjected to whole genome expression analyses. Overall 473 and 541 genes were significantly regulated, when cancer versus transgenic and non-transgenic cells were compared, giving rise to three distinct and one common regulatory gene network. At advanced stages of tumor growth predominately repression of gene expression was observed, but genes previously shown to be up-regulated in dysplasia were also up-regulated in solid tumors. Regulation of developmental programs as well as epithelial mesenchymal and mesenchymal endothelial transition was a hall mark of adenocarcinomas. Additionally, genes coding for cell adhesion, i.e. the integrins and the tight and gap junction proteins were repressed, whereas ligands for receptor tyrosine kinase such as epi- and amphiregulin were up-regulated. Notably, Vegfr- 2 and its ligand Vegfd, as well as Notch and Wnt signalling cascades were regulated as were glycosylases that influence cellular recognition. Other regulated signalling molecules included guanine exchange factors that play a role in an activation of the MAP kinases while several tumor suppressors i.e. Mcc, Hey1, Fat3, Armcx1 and Reck were significantly repressed. Finally, probable molecular switches forcing dysplastic cells into malignantly transformed cells could be identified.

CONCLUSIONS/SIGNIFICANCE

This study provides insight into molecular pertubations allowing dysplasia to progress further to adenocarcinoma induced by exaggerted c-Raf kinase activity.

Comparative study of gene set enrichment methods

Background

The analysis of high-throughput gene expression data with respect to sets of genes rather than individual genes has many advantages. A variety of methods have been developed for assessing the enrichment of sets of genes with respect to differential expression. In this paper we provide a comparative study of four of these methods: Fisher's exact test, Gene Set Enrichment Analysis (GSEA), Random-Sets (RS), and Gene List Analysis with Prediction Accuracy (GLAPA). The first three methods use associative statistics, while the fourth uses predictive statistics. We first compare all four methods on simulated data sets to verify that Fisher's exact test is markedly worse than the other three approaches. We then validate the other three methods on seven real data sets with known genetic perturbations and then compare the methods on two cancer data sets where our a priori knowledge is limited.

Results

The simulation study highlights that none of the three method outperforms all others consistently. GSEA and RS are able to detect weak signals of deregulation and they perform differently when genes in a gene set are both differentially up and down regulated. GLAPA is more conservative and large differences between the two phenotypes are required to allow the method to detect differential deregulation in gene sets. This is due to the fact that the enrichment statistic in GLAPA is prediction error which is a stronger criteria than classical two sample statistic as used in RS and GSEA. This was reflected in the analysis on real data sets as GSEA and RS were seen to be significant for particular gene sets while GLAPA was not, suggesting a small effect size. We find that the rank of gene set enrichment induced by GLAPA is more similar to RS than GSEA. More importantly, the rankings of the three methods share significant overlap.

Conclusion

The three methods considered in our study recover relevant gene sets known to be deregulated in the experimental conditions and pathologies analyzed. There are differences between the three methods and GSEA seems to be more consistent in finding enriched gene sets, although no method uniformly dominates over all data sets. Our analysis highlights the deep difference existing between associative and predictive methods for detecting enrichment and the use of both to better interpret results of pathway analysis. We close with suggestions for users of gene set methods.

Adamantyl-substituted retinoid-derived molecules that interact with the orphan nuclear receptor small heterodimer partner: effects of replacing the 1-adamantyl or hydroxyl group on inhibition of cancer cell growth, induction of cancer cell apoptosis, and inhibition of SRC homology 2 domain-containing protein tyrosine phosphatase-2 activity

(E)-4-[3-(1-Adamantyl)-4'-hydroxyphenyl]-3-chlorocinnamic acid (3-Cl-AHPC) induces the cell-cycle arrest and apoptosis of leukemia and cancer cells. Studies demonstrated that 3-Cl-AHPC bound to the atypical orphan nuclear receptor small heterodimer partner (SHP). Although missing a DNA-binding domain, SHP heterodimerizes with the ligand-binding domains of other nuclear receptors to repress their abilities to induce or inhibit gene expression. 3-Cl-AHPC analogues having the 1-adamantyl and phenolic hydroxyl pharmacophoric elements replaced with isosteric groups were designed, synthesized, and evaluated for their inhibition of proliferation and induction of human cancer cell apoptosis. Structure-anticancer activity relationship studies indicated the importance of both groups to apoptotic activity. Docking of 3-Cl-AHPC and its analogues to an SHP computational model that was based on the crystal structure of ultraspiracle complexed with 1-stearoyl-2-palmitoylglycero-3-phosphoethanolamine suggested why these 3-Cl-AHPC groups could influence SHP activity. Inhibitory activity against Src homology 2 domain-containing protein tyrosine phosphatase 2 (Shp-2) was also assessed. The most active Shp-2 inhibitor was found to be the 3'-(3,3-dimethylbutynyl) analogue of 3-Cl-AHPC.

Epigenetic alteration of Wnt pathway antagonists in progressive glandular neoplasia of the lung

BACKGROUND

Atypical adenomatous hyperplasia (AAH) is now recognized as a precursor lesion from which lung adenocarcinomas arise and thus represents an ideal target for studying the early genetic and epigenetic alterations associated with lung tumorigenesis such as alterations of the Wnt pathway.

METHODS

We assessed the level of Wnt signaling activity in lung cancer cell lines by determining the level of active beta-catenin and determined the level of expression of Wnt antagonists APC, DKK1, DKK3, LKB1, SFRP1, 2, 4, 5, WIF1 and RUNX3 using reverse transcription-polymerase chain reaction. Using multiplex nested methylation-specific polymerase chain reaction, we analyzed promoter region methylation of these genes in resected lung tissue in the histopathologic sequence of glandular neoplasia (normal lung parenchyma, low-grade and high-grade AAH, adenocarcinoma).

RESULTS

The majority of non-small cell lung cancer cell lines (11 of 16, 69%) have evidence of active Wnt signaling and silencing of Wnt antagonists correlated with promoter hypermethylation. Promoter region methylation of Wnt antagonists was common in primary lung adenocarcinoma and there was a significant increase in the frequency of methylation for Wnt antagonist genes and the number of genes methylated with each stage of tumorigenesis (test for rend P <or= 0.01). Additionally, odds ratios for promoter hypermethylation of individual or multiple Wnt antagonist genes and adenocarcinomas were statistically significantly elevated and ranged between 3.64 and 48.17.

CONCLUSION

These results show that gene silencing of Wnt antagonists by promoter hypermethylation occurs during the earliest stages of glandular neoplasia of the lung and accumulates with progression toward malignancy.

Testicular germ cell tumor susceptibility genes from the consomic 129.MOLF-Chr19 mouse strain

Chromosome substitution strains (CSS or consomic strains) are useful for mapping phenotypes to chromosomes. However, huge efforts are needed to identify the gene(s) responsible for the phenotype in the complex context of the chromosome. Here we report the identification of candidate disease genes from a CSS by using a combination of genetic and genomic approaches and by using knowledge about the germ cell tumor disease etiology. We used the CSS 129.MOLF-Chr19 chromosome substitution strain, in which males develop germ cell tumors of the testes at an extremely high rate. We were able to identify three protein-coding genes and one microRNA on chromosome 19 that have previously not been implicated to be testicular tumor susceptibility genes. Our findings suggest that changes in gene expression levels in the gonadal tissues of multiple genes from Chr 19 likely contribute to the high testicular germ cell tumor (TGCT) incidence of the 129.MOLF-Chr19 strain. Our data advance the use of CSS to identify disease susceptibility genes and demonstrate that the 129.MOLF-Chr19 strain serves as a useful model to elucidate the genetics and biology of germ cell transformation and tumor development.

DNA microarray technology in toxicogenomics of aquatic models: methods and applications

Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.

A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer

BACKGROUND

Clinical trials have indicated a benefit of adjuvant chemotherapy for patients with stage IB, II, or IIIA--but not stage IA--non-small-cell lung cancer (NSCLC). This classification scheme is probably an imprecise predictor of the prognosis of an individual patient. Indeed, approximately 25 percent of patients with stage IA disease have a recurrence after surgery, suggesting the need to identify patients in this subgroup for more effective therapy.

METHODS

We identified gene-expression profiles that predicted the risk of recurrence in a cohort of 89 patients with early-stage NSCLC (the lung metagene model). We evaluated the predictor in two independent groups of 25 patients from the American College of Surgeons Oncology Group (ACOSOG) Z0030 study and 84 patients from the Cancer and Leukemia Group B (CALGB) 9761 study.

RESULTS

The lung metagene model predicted recurrence for individual patients significantly better than did clinical prognostic factors and was consistent across all early stages of NSCLC. Applied to the cohorts from the ACOSOG Z0030 trial and the CALGB 9761 trial, the lung metagene model had an overall predictive accuracy of 72 percent and 79 percent, respectively. The predictor also identified a subgroup of patients with stage IA disease who were at high risk for recurrence and who might be best treated by adjuvant chemotherapy.

CONCLUSIONS

The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

Human lung project: evaluating variance of gene expression in the human lung

Nondiseased tissue is an important reference for microarray studies of pulmonary disease. We obtained 23 single lungs from multiorgan donors at time of procurement. Donors varied in age, sex, smoking history, and ethnicity. Lungs were dissected into upper and lower lobe peripheral sections for RNA extraction. Microarray analysis was performed using Affymetrix Hu-133 Plus 2.0 arrays. We observed that the relative variability of gene expression increased rapidly from technical (lowest), to regional, to population (highest). In addition, age and sex have measurable effects on gene expression. Gene expression variability is heterogeneously distributed among biologic categories. We conclude that gene expression variability is greater between individuals than within individuals and that population variability is the most important factor in the study design of microarray experiments of the human lung. Classes of genes with high population variability are biologically important and provide a novel perspective into lung physiology and pathobiology. Our study represents the first comprehensive analysis of nondiseased lung tissue. The generation of this robust dataset has important implications for the design and implementation of future comparative expression analysis with pulmonary disease states.