Down-Regulation of 14-3-3 Isoforms and Annexin A5 Proteins in Lung Adenocarcinoma – Induced by the Tobacco-Specific Nitrosamine NNK in the A/J Mouse Revealed by Proteomic Analysis

Abstract

The tobacco-specific nitrosamine 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a potent lung carcinogen in the A/J mouse model. Here we identified and validated, using two-dimensional difference gel electrophoresis (2D-DIGE) coupled with mass spectrometry and immunoblotting, proteins that are differentially expressed in the lungs of mice treated with NNK versus vehicle control treatment. We also determined whether protein levels in the lungs of NNK-treated mice could be further modulated by the chemopreventive agent 1,4-phenylenebis(methylene)selenocyanate (p-XSC). The proteins identified in this study are SEC14-like 3, dihydropyrimidinase-like 2, proteasome subunit α type 5, annexin A5, 14-3-3 protein isoforms (θ, ε, σ, and ζ), Rho GDP dissociation inhibitor α, myosin light polypeptide 6, tubulin-α-1, vimentin, Atp5b protein, α-1-antitrypsin, and Clara cell 10 kDa protein (CC10). Among those proteins, we demonstrated for the first time that 14-3-3 isoforms (θ, ε, and σ) and annexin A5 were significantly down-regulated in mouse lung adenocarcinoma induced by NNK and were recovered by p-XSC. These proteins are involved in a variety of biological functions that are critical in lung carcinogenesis. Identification of these proteins in surrogate tissue in future studies would be highly useful in early detection of lung adenocarcinoma and clinical chemoprevention trials.

Introduction

Lung cancer claims the lives of over one million people worldwide each year and is one of the most common cancers of men and women in North America, Europe, and East Asia.¹ Current strategies in the treatment of lung cancer including surgery, radiation therapy, chemotherapy, and targeted biological therapies have generated minimally significant results allowing for the 5-year survival rate for all stages combined to rest at 15%.² The inability of current treatment strategies to increase survival stems from the late diagnosis of the disease, histologic heterogeneity, and the high recurrence rate after curative treatment has been administered.^3,4

Ironically, lung cancer is the single most preventable cancer because it is strongly linked to tobacco use.⁵ Cigarette smoke contains a variety of toxic and carcinogenic agents, including the tobacco- and organ-specific N-nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK).⁶ NNK induces adenocarcinomas in various rodent models, independent of the route of administration;⁷ it has been classified as a human lung carcinogen by the International Agency for Research on Cancer working group.⁸ Therefore, initiatives prompted toward the prevention of smoking initiation and smoking cessation must be continually reinforced. In the United States, there are about 91 million current and former smokers composing about 40% of the adult population.⁹ Although former smokers have taken one of the greatest leaps towards health awareness by quitting smoking, they are unfortunately still at a high risk for lung cancer development for several years following cessation.¹⁰ As a result of dismal treatment strategies and the high number of individuals at risk for lung cancer development, there is clearly an urgent need to develop alternative approaches for early detection and management of lung cancer.

The development of sensitive, specific, and reliable biomarkers for early detection of lung cancer and the discovery of novel chemopreventive agents are two strategies with promising clinical implications. Although early attempts to identify novel biomarkers characteristic of lung cancer development have been reported (P16, K-ras, retinoblastoma, fragile histidine triad),¹¹ no single marker has so far met sufficient specificity and sensitivity to be recognized for clinical significance, suggesting that a global approach should be pursued.

Previous clinical chemoprevention trials of lung cancer using several agents have also been unsuccessful; however, selenium (Se) – depending on the form – appears to provide some protection.¹² Based on epidemiological, preclinical, and some, but not all, clinical studies, Se has been shown to have a preventive effect against a variety of cancers, including lung cancer.^13–16 Our laboratory has consistently shown that the organoselenium compound 1,4-phenylenebis(methylene)selenocyanate (p-XSC) is the most potent inhibitor, as compared to other forms of Se, against lung tumorigenesis in A/J mice treated with NNK.¹⁷

The emerging field of proteomics has developed a variety of techniques that analyze the global protein profile of disease states.¹⁸ Two-dimensional difference gel electrophoresis (2D-DIGE) has been used extensively in a variety of applications for quantitative proteomic analysis of diseases, including cancer.^19–21 An improvement from traditional two-dimensional electrophoresis, 2D-DIGE utilizes three spectrally distinct, charge and mass-matched fluorescent dyes known as CyDyes to implement the loading of more than one sample per gel, including a pooled standard containing an equal amount of protein from each sample in the study for quantitative purposes.²² In this study we used 2D-DIGE to compare changes in protein expression in normal lung tissue (vehicle-treated) versus lungs from mice treated with NNK,¹⁷; we also determined whether protein levels in the lungs of mice treated with NNK could be further modulated following dietary administration of the chemopreventive agent p-XSC. In this report, using 2D-DIGE and immunoblot analysis, we identified and verified for the first time that 14-3-3 protein isoforms (θ, ε, and σ) and annexin A5 proteins were significantly down-regulated in lung adenocarcinomas induced by NNK; we also showed that these proteins were recovered by p-XSC.

Materials and Methods

Chemicals and Reagents

All reagents for performing 2D-DIGE were purchased from GE Healthcare (Piscataway, NJ). Reagents for Western assays were purchased from Bio-Rad Laboratories (Hercules, CA) and primary and secondary antibodies were purchased from Abcam (Cambridge, MA), Cell Signaling (Danvers, MA), and Santa Cruz Biotechnology (Santa Cruz, CA). Chemiluminescent immunodetection reagents and autoradiography films were purchased from GE Healthcare and Imaging Resources, Inc. (Seattle, WA), respectively.

Animals and Treatments

Lung tissue (normal and tumor) stored at −80°C were obtained from a previously conducted efficacy study with p-XSC.¹⁷ Briefly, five-week old female A/J mice in groups 1 and 2 were fed a control diet (AIN-76A) and mice in group 3 were fed an experimental diet containing p-XSC (10 ppm as selenium). At 7 weeks of age, mice in groups 2 and 3 received NNK (3 μmol) in 0.1 ml cottonseed oil by intra gastric administration, once weekly, for 8 weeks (total dose: 24 μmol/mouse). Twenty-six weeks after the first administration of NNK, mice were fasted overnight, anaesthetized with a solution of ketamine-xylazine, and then killed by cervical dislocation and necropsied. Lungs were excised and tumors were counted. The lungs were then frozen in liquid nitrogen and stored at −80°C.

Minimal Labeling of Total Lung Protein with CyDye DIGE Fluors for 2D-DIGE

Frozen mouse lungs from groups 1, 2, and 3 (4 lungs/group) were individually processed. Lungs were placed in liquid nitrogen and pulverized using a mortar and pestle (Bessman Tissue Pulverizers, Spectrum Laboratories, Inc., Rancho Dominquez, CA). The pulverized tissue from each mouse was weighed and resuspended in 1 mL of cell lysis buffer [30 mM TrisCl, 2 M thiourea, 7 M urea, 4% (w/v) CHAPS, adjusted to pH 8.5 with dilute HCl] for every 100 mg of tissue, gently vortexed, briefly sonicated on ice for 10 sec, and centrifuged at 150 g for 10 min at 4°C. Recovered supernatants were aliquoted and frozen at −80°C. Protein concentration was determined using the Bio-Rad Protein Assay Dye Reagent Concentrate (Bio-Rad Laboratories). Fifty micrograms of total protein from each lung were collected and labeled separately by incubation for 30 min on ice with 400 pmol CyDye DIGE fluor minimal dyes Cy3 or Cy5 (diluted 400 pmol/μl with dimethylformamide). Samples were randomized to Cy3 and Cy5 to ensure no dye-based artifacts in quantitation.²³ An additional aliquot (29.2 μg) from each sample was used for an internal standard pool and labeled with Cy2 (400 pmol). The labeling reaction was stopped by the addition of 1 μl of 10 mM L-lysine for 10 min on ice.

2D-DIGE

Information about the 2D-DIGE study is provided in a form that is in concordance with the Minimum Information About a Proteomics Experiment – Gel Electrophoresis (MIAPE-GE) standards²⁴ currently under development by the Human Proteome Organization Proteomics Standards Initiative (see Supplementary Information File 1). Different group samples were combined randomly in pairs and diluted with an equal volume of 2X sample buffer [2 M thiourea, 7 M urea, 4% (w/v) CHAPS, 1.2% (v/v) DeStreak Reagent (GE Healthcare), IPG (Immobilized pH Gradient) Buffer 4–7 (GE Healthcare)] and the final volume brought up to 450 μl of Destreak Rehydration Solution (GE Healthcare). Immobiline DryStrips (24 cm, IPG 4–7; GE Healthcare) were rehydrated for 15 hrs with 450 μl DeStreak Rehydration solution (GE Healthcare) containing 0.5% pH 4–7 IPG buffer. Isoelectric focusing (IEF) in the first dimension, followed by second dimension separation by molecular weight was performed as previously described.²⁵ Second dimension separation was performed in 12.5% homogeneous SDS-PAGE gels.

Gel Scanning and Image Analysis

Information about the acquisition and processing of data from the 2D-DIGE studies are provided in the form recommended for Minimum Information About a Proteomics Experiment – Gel Informatics (MIAPE-GI) currently under development by the Human Proteome Organization Proteomics Standards Initiative (http://www.psidev.info/index.php?q=node/83) (see Supplementary Information File 2). Gels were imaged using the Typhoon 9410 Variable Mode Imager (GE Healthcare) for appropriate wavelengths (Cy2, 520 nm; Cy3, 580 nm; Cy5, 670 nm) at a resolution of 100 μm and were cropped and imported into Progenesis SameSpots v2.0 (Nonlinear Dynamics USA, Inc., Durham, NC) for spot matching and differential expression analysis as previously described.²⁵ Statistical analysis comparing spots between experimental groups was performed using Student’s t-test. A filter was set to select for spots that show statistically significant difference (p<0.05, average ratio or fold change >1.5 or <-1.5) and can be used to distinguish one group from the other. Using the expression data for the 191 proteins altered in a statistically significant manner, the relationship of the groups to each other was assessed by Principal Components Analysis (PCA). PCA by group was performed using GeneSpring GX 7.3 (Agilent Technologies, Santa Clara, CA) and mean centered and scaled. Each axis was scaled according to the variance incorporated in that component. The expression heat map was generated from the group mean expression values for the 191 proteins altered in a statistically significant manner. The groups were clustered by an average linkage algorithm with distance used as the similarity measure using GeneSpring GX 7.3 (Agilent Technologies). The proteins were clustered in the same manner.

Protein Identification by MS

Candidate protein spots were picked from a preparative gel loaded with a representative lung protein homogenate from each group (166 μg/group). The preparative/picking gel plate was stained for 2 hrs with Deep Purple Total Protein Stain (GE Healthcare), imaged with the Typhoon 9410 Variable Mode Imager (GE Healthcare) using the Deep Purple filter (610 nm) at a resolution of 100 μm, and imported into Progenesis SameSpots v2.0 (Nonlinear Dynamics) for alignment and spot picking coordinate assignment as previously described.²⁵ Spots of interest were picked from the gel using a spot-picking robot (Ettan Spot Picker, GE Healthcare).

Spots were identified by Matrix-Assisted Laser Desorption Ionization Time-of-Flight/Time-of-Flight Mass Spectrometry (MALDI-ToF/ToF MS) as described previously.²⁵ Briefly, gel plugs were digested with 20 μg/mL trypsin (Sigma-Aldrich, St. Louis, MO) and peptides were spotted onto an Opti-TOF^™ 384 Well Insert MALDI plate (Applied Biosystems, Foster City, CA). Each sample was spotted three times. Peptides were analyzed using a 4800 Proteomics Analyzer (Applied Biosystems). For each sample, an initial mass spectrum was collected. Based on the initial mass spectrum, up to 15 precursors were selected for tandem mass spectrometry (MS/MS) analysis. Using GPS Explorer 3.6 software (Applied Biosystems), the MS and MS/MS data were submitted to a MASCOT search engine for identification. The National Center for Biotechnology Information (NCBI) nonredundant database and the Mus musculus taxonomy were used for sequence comparison searches. If the MASCOT confidence interval was greater than 95% for at least two MS/MS data sets along with a protein score >180, the spot was confidently identified as the corresponding protein.

We also used Nanoflow capillary Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS) to sequence and identify those spots on the preparative/picking gel that appeared to be in too low abundance based on spot intensity. Each spot was in-gel digested using an automated spot handling workstation (Ettan ProSpot, GE Healthcare) as previously described.²⁰ Nanoflow capillary LC/MS/MS was performed with Nanobore electrospray columns on digested peptides. Tandem mass spectra were acquired on a Thermo LTQ ion trap mass spectrometer (Thermo Corp., San Jose, CA).²⁰ A spot identified with >3 unique peptides was considered to be a positive identification for that corresponding protein (peptide probability >95%).

Immunoblot Analysis

Tumors in the NNK-treated group were carefully removed under a dissecting microscope and were classified by a board certified veterinarian pathologist as adenocarcinomas. Proteins from dissected adenocarcinomas and from whole lung of mice treated with the vehicle control or (NNK + p-XSC) (40 μg/lane) were denatured and resolved on a 12% or 15% SDS-PAGE gel and probed with the following antibodies: anti-14-3-3 σ (Abcam), anti-14-3-3 ε (Cell Signaling), anti-14-3-3 θ (Cell Signaling), anti-annexin V (Santa Cruz), anti-CC10 (Santa Cruz), anti-β-actin (Santa Cruz). Bands were detected using enhanced chemiluminescence reagents (ECL, GE Healthcare) and developed with autoradiography film (Imaging Resources, Inc). For densitometric analysis, films were scanned using Bio-Rad’s GS800 Calibrated Densitometer. Quantitation of protein levels was carried out using the Quantity One v4.5.0 1-D Analysis Software (Bio-Rad Laboratories) and normalized to actin levels. Statistical significance (p<0.05) was determined using Student’s t-test.

Network and Gene Product Ontology Analysis

Differentially expressed proteins identified in this study were imported into the Ingenuity Pathway Analysis (IPA) Software v7.1 (Ingenuity Systems, Mountain View, CA) for pathway analysis. HUGO or Swiss-Prot accession numbers and official gene symbols were inserted into the software along with corresponding comparison ratios between groups. The software identified various groupings for the gene products with respect to cellular location and components, and reported or suggested biochemical, biologic, and molecular functions. The identified proteins were mapped to associated network functions that were generated from existing literature from the Ingenuity Systems Knowledge Base. These networks are scored for degree of relevance with values >3 having a 99.9% confidence level of not being generated by random chance alone. The genetic networks that were created describe functional relationships between gene products based on known associations in the literature.

Results

2D-DIGE Identified Differences in Proteomic Profiles Observed in Normal Mouse Lungs from Vehicle-Treated Control Versus Lungs from Mice Treated with NNK

We demonstrated previously¹⁷ that dietary p-XSC significantly inhibited both lung tumor multiplicity (from 10.4 ± 6.0 tumors per mouse in the NNK-treated group to 1.8 ± 2.0 in mice in the (NNK + p-XSC) group) and incidence (from 96% in the NNK-treated group to 68% in the (NNK + p-XSC) group). Figure 1 shows representative images of a 2D-DIGE gel containing two samples, one labeled with Cy3 (total protein from the whole lung of mice treated with the vehicle control, Figure 1A) and the other with Cy5 (total protein from whole lung of mice treated with NNK, Figure 1B), and an internal standard pool labeled with Cy2 (total protein combined together from all of the lungs obtained from the three experimental groups, Figure 1C). These images were analyzed by the image analysis system Progenesis SameSpots v2.0 to compare the differential expression of proteins between groups. Spot matching (100%) between all of the gels (6 gels including 12 images) led to the identification of 796 protein spots (Figure 1D).

Figure 1.

Proteomic profiling of the A/J mouse lung using the 2D-DIGE approach to identify differentially regulated proteins in NNK-treated and (NNK + p-XSC)-treated mice. Representative images of a 2D-DIGE gel scanned for different CyDye fluorophores illustrating fractionated lung proteins from different groups. (A) The vehicle-treated control sample was labeled with Cy5 (red). (B) The NNK-treated sample was labeled with Cy3 (green). (C) An internal pool standard, consisting of all samples in the study, was labeled with Cy2 (blue). (D) Automatic and manual spot detection led to the identification of 796 protein spots outlined in red.

Quantitative analysis of individual spots was performed using the average normalized expression volume calculated from four lung samples for each group. The data was filtered according to the criteria described in the Materials and Methods section, and therefore 191 protein spots were included for subsequent analysis. With these 191 protein spots, an unsupervised, multivariate data analysis method known as PCA was used to analyze the union of all potential protein expression changes from the statistical analyses and establish a cluster for each group (Figure 2A). The location of each of the three treatment group markers represents the weighted average of the values of the two principal components for all samples within each group (4/treatment group). The first component represented the greatest variance between the groups (x-axis, 92%). The second component (y-axis), encompassing about 8% of the variance between the groups, had little effect in separating the three experimental groups. The PCA plot demonstrates that the proteomic shifts for the vehicle-treated control and (NNK + p-XSC) samples were similar to each other. On the other hand, the NNK-treated group exhibited its own unique proteomic shift that was considerably separate from the other two treatment groups. Further analysis of the 191 protein spots was performed by expression heat map and hierarchical clustering analysis (Figure 2B). This further demonstrated that each group had its own unique protein profile expression pattern for this particular set of proteins and that the vehicle-treated control and (NNK + p-XSC)-treated groups were related to each other, separate from the NNK-treated group.

Figure 2.

(A) Principal Components Analysis (PCA) of 191 significant differentially expressed protein spots with either carcinogenesis or chemoprevention-based relationships. The two greatest study variances between the three groups are represented on the x- and y- axes (x-axis, 1^st principal component, 92%; y-axis, 2^nd principal component, 8%). Each spot represents the compressed weighted average of the principal components of the 191 proteins for each sample in each treatment group; the vehicle-treated control group (shaded circle), the NNK-treated group (open circle), and the (NNK + p-XSC)-treated group (closed circle). (B) Protein expression heat map for 191 protein spots that were differentially regulated between the three treatment groups (Vehicle-treated Control, NNK-treated, and (NNK + p-XSC)-treated). Up-regulated proteins are in red and down-regulated proteins are in green. Hierarchial clustering of protein expression was performed in two dimensions. The first dimension (top dendrogram) shows the similarity in protein expression profiles of the groups and the second dimension (left hand side dendrogram) shows individual protein expression profiles.

After comparing the vehicle-treated control and NNK-treated groups, 138 protein spots were found to be differentially regulated. Of these, 10 protein spots were significantly up-regulated and 128 were significantly down-regulated in the lungs of mice treated with NNK. However, after comparing the vehicle-treated control and (NNK + p-XSC) groups, only 22 protein spots were differentially regulated. Of these, 13 protein spots were significantly up-regulated and 9 were significantly down-regulated in the (NNK + p-XSC) group. After comparing the NNK and (NNK + p-XSC)-treated groups, 136 proteins spots were differentially regulated. Of these, 126 protein spots were significantly up-regulated and 10 were significantly down-regulated in the (NNK + p-XSC) group. Interestingly, expression levels of 83 proteins negatively regulated by NNK were recovered to levels that were equal to or greater than those observed in the lungs of vehicle-treated control mice.

Identification of Protein Spots Modulated by NNK Individually and in Combination with p-XSC

After statistical analysis was completed using the Progenesis SameSpots v2.0 software, a select group of significant, differentially expressed protein spots were excised and identified using MALDI-ToF/ToF MS. Figure 3 shows the location of 16 candidate protein spots that were selected for MS analysis, of which 10 proteins were identified by MALDI-ToF/ToF MS (Table 1). Figure 4A shows a representative peptide mass fingerprint match spectrum and MS/MS spectrum of the corresponding amino acid sequence YLAEFATGNDRK used in the identification of 14-3-3 ε protein. Of particular interest concerning these proteins is that they were down-regulated in the lungs of mice treated with NNK compared to vehicle-treated control mouse lungs, but were significantly up-regulated in the group receiving (NNK + p-XSC); this is clearly shown in Figure 4B. The proteins identified in this study are known to be involved in a variety of biological processes, as noted using the PANTHER ontology database (www.pantherdb.org), including cholesterol, nucleic acid, protein, and fatty acid metabolism (SEC14-like 3, dihydropyrimidinase-like 2, proteasome subunit α type 5, and annexin A5, respectively), signal transduction (the 14-3-3 protein isoforms consisting of ε, ζ, and θ, and Rho GDP dissociation inhibitor α), muscle contraction (myosin light polypeptide 6), and intracellular protein trafficking (tubulin-α-1).

Figure 3.

2D-DIGE reference gel image. A selected group of protein spots (indicated by arrows, total number 16) that were differentially regulated were excised and identified using mass spectrometry methods.

Table 1.

Proteins that are differentially expressed in NNK and (NNK + P-XSC) groups as identified by 2D-DIGE and MALDI-ToF/ToF MS

			Vehicle-treated Control vs NNK		Vehicle-treated Control vs (NNK+ p-XSC)		NNK vs (NNK + p-XSC)
Spot No.	Identified Protein	Accession No.*	Average Ratio	p- value	Average Ratio	p-value	Average Ratio	p- value	Protein Score/C.I.%†	Total Ion Score/C.I.%‡	Protein MW/pI§	Protein Coverage(%)¶	Biological Function||
198	SEC14-like 3	gi|71480138	−2.79	0.009	1	0.977	2.78	0.040	569/100	422/100	46.5/5.6	32.7	Cholesterol Metablolism
337	dihydropyrimidinase-like 2	gi|40254595	−1.84	0.021	1.24	0.412	2.29	0.033	533/100	400/100	62.6/6.0	26.6	Nucleoside, Nucleotide, Nucleic Acid Metabolism
455	proteasome subunit α type 5	gi|7106387	−1.61	0.045	1.21	0.145	1.95	0.010	348/100	298/100	26.6/4.7	24.9	Protein Metabolism and Modification
587	annexin A5	gi|6753060	−1.23	0.105	1.09	0.178	1.34	0.030	1260/100	1041/100	35.8/4.8	51.7	Lipid, Fatty Acid and Steroid Metabolism
391	14-3-3 ε	gi|5803225	−1.98	0.002	1.09	0.666	2.15	0.025	419/100	302/100	29.3/4.6	23.1	Signal Tranduction, Protein Targeting, Cell Cycle
420	14-3-3 ζ	gi|1841387	−1.85	0.027	1.12	0.326	2.07	0.017	525/100	393/100	27.9/4.7	30.2	Signal Tranduction, Protein Targeting, Cell Cycle
426	14-3-3 θ	gi|51593617	−1.84	0.037	1.12	0.427	2.06	0.016	483/100	343/100	30.2/4.9	35.1	Signal Tranduction, Protein Targeting, Cell Cycle
471	Rho GDP dissociation inhibitor (GDI) α	gi|13435747	−1.52	0.019	1.24	0.073	1.88	0.008	363/100	290/100	23.4/5.1	33.3	Rho Protein Signal Transduction, Negative Regulation of Cell Adhesion
425	myosin light polypeptide 6	gi|17986258	−1.99	0.055	1.03	0.748	2.06	0.028	325/100	245/100	17/4.6	25.8	Muscle Contraction
462	tubulin-α-1	gi|6755901	−1.14	0.576	1.69	0.005	1.92	0.014	481/100	388/100	50.8/4.9	18.8	Intracellular Protein Traffic, Cell Cycle, Cell Structure and Motility

^*National Center for Biotechnology Information (NCBI)

^†Sum of the scores of the peptide mass fingerprint match and MS/MS peptide fragment ion matches; scores >95 are considered significant

^‡Scores of the quality of the MS/MS fragment ion matches only; scores >20 are considered significant

^§Theoretical values from MASCOT

^¶The percent of the residues in each protein sequence that have been identified

^||PANTHER ontology database

Figure 4.

Identification of spot #391 (14-3-3 ε). (A) Representative MALDI-ToF/ToF MS and tandem MS spectra used in the identification of the 14-3-3 ε proteins. The peptide sequence YLAEFATGNDR was unique to the 14-3-3 ε protein. (B) 2D-DIGE gel images of 14-3-3 ε expression for all three experimental groups. The three dimensional and graphical presentations of the normalized spot volume for the 14-3-3 ε protein illustrates the expression differences between the vehicle-treated control, NNK, and (NNK + p-XSC)-treated groups. *p<0.05; **p<0.005 (Student’s t-test)

In addition to MALDI-ToF/ToF MS described above, LC/MS/MS analysis was employed for the identification of low abundant proteins on the preparative/picking gel and four additional protein spots were identified as vimentin, Atp5b protein, serine (or cysteine) peptidase inhibitor clade A member 1c (commonly known as α-1-antitrypsin, AAT) and Clara cell 10 kDa protein (CC10) (Table 2). Three isoforms of CC10 were also identified and verified by immunoblot analysis. Interestingly, vimentin expression was 1.64-fold and 2-fold greater in the (NNK + p-XSC) group compared to both vehicle-treated control and NNK-treated groups, respectively. Atp5b protein and AAT were only 1.2-fold higher in expression in the (NNK + p-XSC) group compared to the vehicle-treated control group. Atp5b, which is involved in ATP biosynthesis, was up-regulated in the NNK-treated group 2.36-fold and 1.92-fold compared to both the vehicle-treated control and (NNK + p-XSC) groups, respectively, but this was found to be non-significant. All three isoforms of CC10 were down-regulated in the NNK group compared to vehicle-treated control and remained at comparable levels in the (NNK + p-XSC) group.

Table 2.

Proteins that are differentially expressed in NNK and (NNK + P-XSC) groups as identified by 2D-DIGE and LC/MS/MS

			Vehicle-treated Control vs NNK		Vehicle-treated Control vs (NNK + p-XSC)		NNK vs (NNK + p-XSC)
Spot No.	Identified Protein	Accession No.*	Average Ratio	p- value	Average Ratio	p- value	Average Ratio	p- value	No. of Peptides†	Protein MW	Biological Function‡
730	vimentin	gi|2078001	−1.22	0.441	1.64	0.011	2.00	0.016	15	51.6	Intermediate Filament-based Process
645	Atp5b protein	gi|23272966	2.36	0.225	1.2	0.006	−1.92	0.295	11	56.7	ATP Biosynthetic Process
1553	Serine (or cysteine) peptidase inhibitor, clade A member 1c (AAT)	gi|15012149	1.03	0.922	1.2	0.046	1.16	0.577	5	52	Serine Protease Inhibitor
865	Clara cell 10kDa protein (CC10)	gi|627855	−1.72	0.067	−1.64	0.007	1.05	0.874	1	12.5	Ligand Mediated Signaling, Anti-inflammatory
661	Clara cell 10kDa protein (CC10)	gi|627855	−2.27	0.028	−2.09	0.006	1.08	0.839	1	12.5	Ligand Mediated Signaling, Anti-inflammatory
627	Clara cell 10kDa protein (CC10)	gi|627855	−2.54	0.031	−2.64	0.024	−1.04	0.929	1	12.5	Ligand Mediated Signaling, Anti-inflammatory

^*National Center for Biotechnology Information (NCBI)

^†No. of peptides that match the theoretical digest of the primary protein identified

^‡PANTHER ontology database

Immunoblotting Verified Modulation of Protein Levels Found in 2D-DIGE

To verify the identity of proteins described above, we performed an immunoblot analysis on select proteins that have been suggested to be involved in various cancers. To determine if these changes are specifically occurring in tumor tissue as compared to normal tissue, dissected tumors from the NNK-treated group were compared to vehicle-treated control lung tissue. The tumors were classified histopathologically as adenocarcinomas, papillary type (Figure 5). Quantification of the protein bands determined that the 14-3-3 proteins (θ and ε) were expressed at lower levels, in the NNK-treated group compared to the vehicle-treated control group (Figure 6A and B). We also focused on the analysis of the 14-3-3 protein isoform σ, since it has been shown to be frequently modulated in human cancers, including lung cancer.^26,27 Although we did not identify this protein in our 2D-DIGE study, we were able to show that it was significantly down-regulated in the adenocarcinomas induced by NNK in our immunoblot analysis compared to the vehicle-treated control group (Figure 6A and B). Annexin A5 was also found to be significantly down-regulated in the NNK-induced adenocarcinomas compared to the vehicle-treated control group (Figure 6B). We also observed a significant decrease in CC10 expression in the adenocarcinomas compared to the vehicle-treated control group (Figure 6B). We observed that those proteins down-regulated in the NNK-induced tumors were restored to normal lung tissue expression levels, except for CC10, in the (NNK + p-XSC)-treated group (Figure 6C and D). Although it was not statistically significant, except for 14-3-3 σ, it should be mentioned that these expression levels exceeded those observed for the vehicle-treated control group (Figure 6D).

Figure 5.

Histopathological analysis of H&E stained NNK-induced lung tumors in the A/J mouse. (A) Tumor section surrounded by normal tissue; tumors were classified as adenocarcinomas, papillary type (magnification, X100). (B) Magnified region of box in (A) (magnification, X600); arrows, indicating multinucleate tumor cells; arrowheads, highlighting variation in nuclear size (anisokaryosis), a feature of dysplasia.

Figure 6.

Validation of 14-3-3 isoforms θ, ε, and σ, CC10, and annexin A5 under-expression by immunoblot analysis. (A) Representative immunoblot analysis, from three experiments, of expression of 14-3-3 θ, ε, and σ, CC10, and annexin A5 in dissected NNK-induced lung adenocarcinomas and vehicle-treated control lung tissue. Forty micrograms of total lung protein were loaded into each lane for each sample. (B) Fold-change in mean protein band expression from immunoblot for 14-3-3 θ, ε, and σ, CC10, and annexin A5 in lung tissue from mice treated with vehicle (solid bars) or tumors from mice treated with NNK (open bars). (C) Representative immunoblot analysis, from three experiments, of expression of 14-3-3 θ, ε, and σ, CC10, and annexin A5 in vehicle-treated lung tissue and (NNK + p-XSC)-treated lung tissue. Forty micrograms of total lung protein were loaded into each lane for each sample. (D) Fold-change in mean protein band expression from immunoblot for 14-3-3 θ, ε, and σ, CC10, and annexin A5 in lungs from mice treated with vehicle (solid bars) or (NNK + p-XSC) (gray bars). For comparison between protein expression levels between groups, the fold change was calculated relative to vehicle-treated control levels and normalized with respect to β-actin protein expression levels. ^* p<0.05 (Student’s t-test)

Network Analysis of Identified Proteins

In order to understand the biological association of the identified proteins within context to each other and potential pathways in which they may be involved, we used the Ingenuity Systems, Inc. software, Ingenuity Pathway Analysis (IPA). The proteins that were statistically different and had a 1.5-fold change in expression between the lungs of mice treated with the vehicle control and NNK, including annexin A5 and vimentin, were included in this analysis. IPA identified an associated cancer-related network regarding tumor morphology and cell morphology between 11 of these proteins with a score of 25. Figure 7 shows the cellular location of these proteins along with direct or indirect relationships exhibited by the proteins with each other within the network. In particular, the down-regulated 14-3-3 protein isoforms we identified in the lungs of NNK-treated mice compared to the vehicle-treated group bind to numerous proteins, including each other, to modulate the bound protein’s activity. Interestingly, the 14-3-3 θ isoform binds to the oncogenic MYC protein,²⁸ a transcriptional regulator known to play a enhancing role in cancer development.²⁹ MYC was also found to exhibit associations with annexin A5, 14-3-3 ε, and proteasome subunit α type 5.

Figure 7.

Network Analysis of differentially expressed proteins using the Ingenuity Pathways Analysis (IPA) software. Proteins that were found to be significantly different between lungs of mice treated with the vehicle control versus NNK were analyzed using IPA. The proteins were classified in a cancer, tumor morphology, and cell morphology associated network, along with corresponding protein-to-protein direct (solid lines) or indirect (dashed lines) interactions/regulations, based on information published in the literature. The proteins shown in green were down-regulated and those in red were up-regulated in the NNK-treated group compared to the vehicle-treated control group. Proteins were given shapes related to functionality and were also grouped with respect to cellular location: extracellular space, plasma membrane, cytoplasm, and nucleus.

Discussion

In the present study we have utilized the well-established NNK-induced lung tumorigenesis model in A/J mice to identify lung protein alterations in cancer development.⁷ To validate the relevance of these proteins as potential biomarkers, we have selected the chemopreventive agent p-XSC that has been shown previously to be a powerful inhibitor of both lung tumor incidence and multiplicity in the above mentioned A/J mouse model.¹⁷

Cancer development is a multi-step process characterized by abnormal protein expression ultimately leading to phenotypic changes. These changes are caused by a large number of proteins rather than a single protein change alone. Therefore, it is of paramount importance to understand the proteome as a whole. To globally analyze the plethora of proteins that may contribute to lung tumor development we used 2D-DIGE. Using this approach, we analyzed over 700 protein spots for differential protein expression among three experimental groups: vehicle-treated control, NNK-treated, and (NNK + p-XSC)-treated groups. After filtering for only those significant (p<0.05), differentially expressed protein spots (average ratio or fold change >1.5 or <−1.5), our results indicated that a large number of these 191 proteins (97%) were down-regulated in the lungs of mice treated with NNK compared to vehicle-treated controls. However, after the dietary administration of p-XSC in NNK-treated mice, a majority of these proteins (65%) were restored to similar or even higher expression levels compared to those observed in the vehicle-treated control group. Among the proteins identified (Table 1 and Table 2), a variety of biological functions were noted, including metabolic, signal transduction, cell cycle regulation, muscle contraction, protein trafficking, anti-inflammation, intermediate filament-based processes, ATP biosynthesis, and serine protease inhibition activities. Furthermore, pathway analysis indicated that 11 of these proteins are involved in a cancer-associated network based on current literature (Ingenuity Systems Knowledge Base).

A group of proteins consistently showing down-regulation in expression in the lung of mice treated with NNK were the 14-3-3 protein isoforms ε, ζ, and θ. Although we did not identify the 14-3-3 σ isoform in our 2D-DIGE study, we were able to detect its expression in our immunoblot study. We determined that 14-3-3 σ was significantly up-regulated in (NNK + p-XSC) treated lungs compared to both vehicle-treated control and NNK-treated groups. There are three other known 14-3-3 isoforms, including β, γ, and η,³⁰ but their expression levels were not examined in this study. The 14-3-3 proteins are ubiquitously expressed regulatory proteins that primarily function by binding to protein ligands and as a result, interfere with or enhance the ligand’s normal activities. Some of the proteins to which 14-3-3 proteins bind play various roles in apoptosis, mitogenic signal transduction, DNA replication, and cell-cycle control.³⁰ Interestingly, many of the ligands that 14-3-3 proteins bind to are proto-oncogene or oncogene products³⁰ suggesting a potential role in carcinogenesis. However, previous studies have provided inconsistent views as both tumor promotion and tumor suppression activities have been attributed to the 14-3-3 proteins.^31–33 It appears that the lack of consistency may be dependent on the specific 14-3-3 isoform, the type of tissue examined, and the experimental approach used.²⁶ In lung cancer, 14-3-3 protein isoforms have been found in all major histological types, but at different expression levels.^26,27,34 In our study, we identified 14-3-3 protein isoforms ε, ζ, θ, and σ in all lungs of the three experimental groups [vehicle-treated control, NNK, and (NNK + p-XSC)-treated groups]. Our 2D-DIGE results, also confirmed by our immunoblot analysis, indicated that these isoforms were down-regulated in lung adenocarcinomas of mice treated with NNK, but dietary p-XSC was capable of providing the necessary environment to restore expression to basal levels noted in the vehicle-treated (normal) control lungs. Of particular significance, the 14-3-3 proteins have been shown to play a role in inducing G2 arrest under DNA damaging scenarios through Cdc2 inactivation.^30,35 In our case, the NNK-induced tumor environment may be favorable with a reduced level of these particular isoforms to avoid cell cycle arrest. Reports have also shown that over-expression of 14-3-3 σ can lead to tumor growth suppression in breast cancer.^36–38 In the present study, lungs collected from A/J mice that had been treated with (NNK + p-XSC) exhibited a significant increase in the levels of the 14-3-3 σ protein. This suggests that over-expression of this protein may provide protection against the development of lung tumorigenesis. Overall, to fully validate the use of these proteins as potential biomarkers future pilot clinical investigations of the role of all of the 14-3-3 isoforms in lung cancer are urgently needed.

Annexin A5 (anxA5) is a phospholipid binding protein that efficiently binds to phosphatidylserine. During early events of apoptosis, phosphatidylserine, which normally resides on the inner leaflet of the plasma membrane, becomes externalized to the outer leaflet of the plasma membrane where anxA5 can bind to it. By binding to phosphatidylserine on the outer leaflet of the plasma membrane, anxA5 essentially marks the cell for safe removal from the system by macrophages.³⁹ Interestingly, the use of anxA5 as a clinical tool for visualization of cell death has been suggested to be important in monitoring pathologies such as atherosclerosis, myocardial infarction, and cancer.⁴⁰ In our study we observed a decrease in anxA5 expression in lung adenocarcinomas of mice treated with NNK compared to the vehicle-treated control group. In addition, we noted that p-XSC administration to mice treated simultaneously with NNK increased anxA5 expression in lungs. These results are in line with our previous report demonstrating that p-XSC is a powerful inducer of apoptosis.¹⁴

CC10 is a homodimeric protein predominantly secreted in the lungs and composes approximately 7% of the total protein in bronchoalveolar lavage fluid (BALF). CC10 has been assigned a multitude of protective roles in the lung, including anti-inflammatory, anti-oxidant, and immunomodulatory functions. Exposure to tobacco smoke and lung carcinogens have been associated with reduced levels of CC10 and numerous studies have indicated that decreased levels of CC10 exist in both BALF and serum in smokers and lung cancer patients compared to healthy nonsmokers.⁴¹ Chen et al ⁴² showed that the levels of CC10 in plasma and BALF could be restored following smoking cessation, suggesting that some of the damage caused by tobacco smoke could be repaired. Furthermore, it has been shown that high levels of CC10 are associated with improvement of bronchial dysplasia and sputum cytometric assessments in individuals at high risk for lung cancer.⁴³ In addition, CC10 has also been implicated as an inhibitor of lung carcinogenesis.^41,44 Our results are in line with other laboratories regarding CC10 down-regulation in rodent lungs following NNK treatment,⁴¹ as well as NNK in combination with another lung carcinogen, benzo[a]pyrene (B[a]P).⁴⁵ However, CC10 levels were not recovered by dietary p-XSC (this study) and other chemopreventive agents reported in the literature, such as N-acetyl-S-(N-2-phenethylthiocarbamoyl)-L-cysteine and the isothiocyanates, myo-inositol and indole-3-carbinol.⁴⁵ We also detected three isoforms of CC10 in the A/J mouse lung. Previous studies have indicated the presence of three to four isoforms for CC10 in mammals,^46,47 but the role of each isoform in carcinogenesis is not entirely understood. All three isoforms were down-regulated in the NNK-treated group compared to the vehicle-treated control group. Although p-XSC was unable to restore CC10 expression, CC10 still warrants further investigation as a potential biomarker because it is primarily a lung-specific protein and can be detected in surrogate tissue, such as BALF and serum.⁴⁸

The literature concerning AAT in lung cancer has had conflicting observations. Some groups have shown a positive correlation between high levels of AAT in plasma and lung cancer risk,⁴⁹ whereas others have shown that a genetic deficiency in AAT is associated with an increased risk for lung cancer development.⁵⁰ Our results showed that AAT was significantly increased in the lung in (NNK + p-XSC)-treated mice compared to vehicle-treated control group, but was not significant when compared to the NNK-treated groups. However, in a previous report,⁵¹ AAT was decreased in the A/J mouse lung following treatment with B[a]P in combination with NNK. The discrepancy between findings of Kassie et al.⁵¹ and the present studies could be due to the effect of B[a]P alone or in combination with NNK on AAT levels. AAT is a serine-type endopeptidase inhibitor responsible for neutralizing the effects of proteases in a number of organ systems, including the lung, protecting them from damage. Its primary protease counterpart in the lower respiratory tract is neutrophil elastase.⁵² The balance between these molecules has been suggested to be critical in facilitating the cancer causing effects of cigarette smoke.⁵² Therefore the increased expression of AAT in the presence of p-XSC might be critical in providing the necessary protection to the lung from carcinogens in cigarette smoke, such as NNK.

Vimentin and tubulin-α-1 are both components of the cytoskeleton and play various roles in intermediate filament based processes and intracellular protein trafficking, respectively. Previous reports have indicated that aberrant expression of vimentin is consistent with increased motility, invasive behavior, and poor prognosis in tumors and transformed cell lines.^53–55 Tubulin-α-1 was previously found to be informative in characterizing different histological types of lung cancer.⁵⁶ In our study, we found both vimentin and tubulin-α-1 to be increased in the lungs of mice treated with (NNK + p-XSC) compared to both the vehicle-treated group and the NNK-treated group lungs. The increased expression exhibited in the lungs of mice treated with (NNK + p-XSC), for both of these proteins, may further define the protective property elicited by this chemopreventive agent. In addition, regarding tubulin-α-1, since our model addresses adenocarcinoma, restoration of this protein may be inhibitory to the development of this histological type of lung cancer.

Dihydropyrimidinase-like 2 is involved in nucleoside, nucleotide, and nucleic acid metabolism by hydrolytic catalysis activity. It is typically studied in the brain as its decreased expression has been observed in Alzheimer’s disease, Down Syndrome and Schizophrenia.⁵⁷ Although its modulation in lung cancer has been identified in other proteomic studies,⁴⁵ the role of dihydropyrimidinase-like 2 in lung cancer remains questionable.

As is the case with many of the proteomic methodologies currently in use, there are certain limitations to this study. First, we identified roughly 796 protein spots under our experimental conditions, which represent a small fraction of the protein-encoding transcripts expected in the mouse genome (~20,000).⁵⁸ Each proteome method has its limitations, but DIGE allows for the simultaneous examination of a number of samples. While whole proteome analyses are not possible with current technology, the use of narrow range pH gradients (4–7) allows for high resolution of the proteins examined.⁵⁹ Secondly, some of the proteins we identified in this study are not lung-specific. Therefore, it will be necessary to further delineate which proteins are both primarily important to understanding the cellular state of lung tissue and provide a molecular profile to carcinogenesis-related changes. Nonetheless, these findings provide a pivotal step towards understanding the changes taking place at the proteomic level in the target tissue cellular environment that plays an important role in cancer development.⁶⁰ Some of the proteins identified in this study have been previously implicated in lung carcinogenesis and therefore, further support their usefulness in understanding the course of this disease and may serve as promising candidate biomarkers to monitor lung cancer progression. The chemopreventive agent, p-XSC, further validated the usefulness of these proteins as it was able to restore, and in many cases increase, the expression of NNK-induced negatively-regulated proteins to levels observed in the normal lung tissue. These biomarkers may also be used to evaluate the efficacy of chemopreventive agents other than selenium-containing compounds. Future studies in the NNK-A/J mouse model are aimed at analyzing these proteins in surrogate tissue such as BALF and plasma and at different stages of disease (hyperplasia, adenoma, adenocarcinoma). Identification of these proteins in surrogate tissue in future studies would be highly useful in early detection of lung adenocarcinoma and clinical chemoprevention trials.

Abbreviations

2D-DIGE

two-dimensional difference gel electrophoresis

NNK

4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone

p-XSC

1,4-phenylenebis(methylene)selenocyanate

Se

selenium

IPG

immobilized pH gradient

IEF

isoelectric focusing

DTT

dithiothreitol

MALDI-ToF/ToF MS

matrix-assisted laser desorption ionization time-of-flight/time-of-flight mass spectrometry

LC/MS/MS

liquid chromatography tandem mass spectrometry

NCBI

National Center for Biotechnology Information

PCA

Principal Components Analysis

CC10

Clara cell 10 kDa protein

BALF

bronchoalveolar lavage fluid

AAT

α-1-antitrypsin

anxA5

annexin A5

ERBB2

v-erb-b2 erythroblastic leukemia viral oncogene homolog 2

CDKN2A

cyclin-dependent kinase inhibitor 2A

ARHGDIA

Rho GDP dissociation inhibitor (GDI) α

DPYSL2

Dihydropyrimidinase-like 2

RRAD

Ras-related associated with diabetes

VIM

vimentin, PSMA5, proteasome (prosome, macropain) subunit, alpha type, 5

MYL6

myosin, light chain 6, alkali, smooth muscle and non-muscle

MYC

v-myc myelocytomatosis viral oncogene homolog (avian)

YWHAD

tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein, delta polypeptide

YWHAQ

tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein, theta polypeptide

YWHAZ

tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein, zeta polypeptide

YWHAE

tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein, epsilon polypeptide

ATP5B

ATP synthase, H⁺ transporting, mitochondrial F1 complex, beta polypeptide

SCGB1A1

secretoglobin, family 1A, member 1 (uteroglobin, CC10)

ITGB2

integrin, beta 2 (complement component 3 receptor 3 and 4 subunit)

REM1

RAS (RAD and GEM)-like GTP-binding 1

DENND4A

DENN/MADD domain containing 4A

EIF4A3

eukaryotic translation initiation factor 4A, isoform 3

ACSL4

acyl-CoA synthetase long-chain family member 4

PXN

paxillin