Gene expression profile of normal lungs predicts genetic predisposition to lung cancer in mice
Manuela Gariboldi1,2,
Monica Spinola1,
Silvano Milani3,
Carmen Pignatiello1,
Koji Kadota2,4,
Hidemasa Bono2,
Yoshihide Hayashizaki2,
Tommaso A. Dragani1,5 and
Yasushi Okazaki2,5
1 Department of Experimental Oncology, Istituto Nazionale Tumori, Milan, Italy, 2 Laboratory for Genome Exploration Research Group, RIKEN, Yokohama, Japan, 3 Institute of Medical Statistics and Biometry, University of Milan, Milan, Italy and 4 University of Tokyo, Tokyo, Japan
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Abstract
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Genetic susceptibility to lung tumorigenesis shows large variations among mouse strains. To test whether genetic predisposition to lung tumorigenesis is associated with a specific gene expression profile in normal lungs, we analyzed gene expression in 16 inbred strains of known susceptibility/resistance to lung tumorigenesis, using the RIKEN mouse full-length cDNA 19K microarray set. The strain-specific expression profile of 91 cDNA clones correlated with strain lung tumor susceptibility/resistance and predicted, by principal component analysis, the genetic predisposition to lung tumorigenesis in mice.
Abbreviations: Pas1, pulmonary adenoma susceptibility 1
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Introduction
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Lung cancer is a major cause of cancer death in Western countries. The disease has a poor prognosis, and few early diagnostic and therapeutic tools are available. Complex genetic factors, together with exposure to environmental carcinogens (e.g. tobacco smoke, radon, asbestos) may confer a high risk of developing lung cancer (1). Epidemiological studies of lung cancer families supported the involvement of a major gene interacting with tobacco smoking in the risk and early onset of lung cancer (1,2). The difficulties in dissecting the genetic risk factors directly in humans make the use of experimental models attractive.
Inbred strains of mice differ in their susceptibility to spontaneous and chemically induced lung tumors. Some strains show high or intermediate propensity to these tumors, while others are almost completely resistant. Genetic analysis of different crosses allowed the mapping of the major locus responsible for inherited predisposition to lung cancer in mice, the pulmonary adenoma susceptibility 1 (Pas1) locus (3). Linkage disequilibrium analysis in 21 inbred strains of known susceptibility/resistance to lung cancer indicated that the Pas1 susceptibility allele (Pas1s) derives from an ancestral mouse and maps in a 1.5-Mb region (4). Mice carrying the susceptibility allele at this locus may display a high or intermediate susceptibility to lung tumorigenesis, depending on the presence of additional lung cancer modifier loci (5), whereas mice carrying the resistance allele at the Pas1 locus (Pas1r) do not or rarely develop lung cancer (4,6). In humans, population-based association studies have implicated the homologous Pas1 locus region as a potential cancer modifier (79).
The Pas1s allele may confer a high genetic predisposition to lung cancer by regulating in normal lung tissue the expression levels of genes involved in downstream pathways leading to lung tumor development. Microarray-based technology now provides the possibility to analyze the transcriptional profile of tissues under different conditions and to obtain a new understanding of gene functions.
To identify transcriptional alterations in normal lungs associated with lung cancer risk, we analyzed the gene expression profile of mouse-inbred strains characterized for their susceptibility/resistance to lung tumorigenesis and Pas1 allele status. From the 19K RIKEN array, 91 cDNA clones showed a correlation between strain-specific expression profile and lung tumor susceptibility of the strain.
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Materials and methods
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Mice and RNA extraction
Male mice from the strains 129Sv/J, A/J, AKR/J, BALB/cJ, C3H/HeJ, C57BL/6 J, C57L/J, CBA/J, DBA/2 J, LP/J, Mus. spretus SPAIN (SPRET/Ei), PL/J, RF/J, SJL/J, SM/J and SWR/J were obtained from The Jackson Laboratories (Bar Harbor, ME). Whole body mRNA from E17.5 C57BL/6 J mouse embryos was used as a reference probe for microarray and real-time RTPCR. Three mice of each strain were killed at 8 weeks of age and lungs were collected and pooled for microarray analysis. Separate pools were prepared from additional mice for real-time quantitative RTPCR analysis. Total RNA was obtained according to the guanidine thiocyanate protocol (10). Poly A+ RNA was obtained using the Micromax mRNA Isolation kit (Miltenyl Biotec, Auburn, CA).
Array hybridization and real-time quantitative RTPCR
Poly A+ RNA (1 mg) from normal lung of each strain and poly A+ RNA (1 mg) from embryos (whole body) of C57BL/6 J mice at 17.5 days were reverse-transcribed using random nonamers and Superscript reverse transcriptase (Gibco BRL, Gaithersburg, MD). Samples were labeled with the fluorescent dyes Cy-3 and Cy-5 (Amersham Bioscience, Uppsala, Sweden) and used as probes on a mouse full-length cDNA 19K microarray set as described (11). Hybridizations were repeated by inverting the fluorescent dye labeling (dye swap).
Arrays were subjected to laser-scanning using ScanArray 5000 (GSI Lumonics) with separate images obtained for each fluor. Data were analyzed using the program ScanAlyze (available at http://genome-www.stanford.edu/mbp), followed by a filtering procedure (12), which first eliminates signals whose intensity is lower than the average background of the entire chip and then removes spots located outside the best-fit line (correlation line) obtained plotting the mean of Cy3 and Cy5 values of the two experiments. For all strains, the correlation coefficient between the two experiments was >0.7.
For kinetically monitored, reverse transcriptase-initiated PCR (kRTPCR), total RNAs from E17.5 pooled mouse embryos and a pool of three normal lungs of 129/SvJ, A/J, BALB/cJ, C3H/HeJ, C57BL/6 J, C57L/J, CBA/J, DBA/2 J, LP/J, PL/J, SJL/J, SM/J and SWR/J strains were reverse-transcribed using the Thermoscript RTPCR system (Gibco BRL). Gene-specific PCR primers were designed on the sequences of the RIKEN full-length clones or Unigene mRNAs to amplify fragments 100150 bp in length (Table II). PCR products were checked on ethidium bromide-stained agarose gel. kRTPCR amplification mixtures contained 1 µl template cDNA, 12.5 µl 2x QuantiTect SYBRGreen PCR Master Mix (Qiagen, Valencia, CA), and 0.3 µM specific PCR primers. Final volume was adjusted to 25 µl. Reactions were run in triplicate on an ABI GeneAmp 5700 sequence detection system (Applied Biosystems, Foster City, CA). The cycling conditions comprised an initial activation step at 95°C for 15 min and 40 cycles at 94°C for 15 s/5562°C for 30 s/72°C for 30 s. The ribosomal protein 18S gene (180-bp PCR fragment) (GenBank acc. no. X00686) was used as a control to correct for differences in the amount of cDNA used.
Tissue expression profile
Analysis of tissue gene expression pattern has been performed in 18 tissues using RIKEN mouse cDNA microarray. As a reference cDNA probe, a mixture of male and female mouse embryos (whole body) at 17.5 days (E17.5) was used. The in silico expression profiles of the 91 genes were also searched against the 107 library source tissues used for RIKEN mouse Encyclopedia Project (http://read.gsc.riken.go.jp/fantom2/).
Statistical analysis
The Pearson correlation coefficients between gene expression profile and known strain lung tumor multiplicity (N) (5,6), normalized by transformation in log(N + 1) units, were calculated for each gene of the 19K RIKEN microarray set. Genes whose correlation coefficients with strain lung tumor multiplicity resulted |r|
0.6 were selected and used to construct a matrix of pairwise strain correlation for their expression levels. Principal component analysis on the correlation matrix of the gene expression levels (expressed as standard deviation score within each gene) in normal lungs of mouse inbred strains was carried out by means of SAS procedure PRINCOMP (SAS Institute, SAS Users Guide: Statistics, Cary, NC). The Pearson correlation coefficients were calculated between kRTPCR results and log(N + 1)-normalized strain lung tumor multiplicity, and also between decimal logarithms of microarray and kRTPCR results.
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Results
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Gene expression profile in normal lungs
We analyzed mRNA from normal lung samples of 16 inbred strains characterized for their susceptibility or resistance to lung cancer (5,6). cDNA microarrays containing 19K full-length mouse cDNAs from the RIKEN full-length collection (13) were used to identify differences in gene expression among these mouse strains. As a reference cDNA probe, a mix of male and female mouse embryos (whole body) at 17.5 days (E17.5) was used, since it has a complex expression pattern at this time in a variety of cells and tissues (11).
The gene expression profile of 91 out of 14,827 (0.61%) cDNA clones showed a correlation coefficient |r|
0.6 with the reported quantitative scores of genetic susceptibility or resistance to lung tumorigenesis of mouse inbred strains (5,6) (Table I). Statistical significance P values associated to the |r| values ranged from P < 0.001 (gene-1) to P = 0.007 (gene-91).
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Table I. List of 91 cDNA clones whose mRNA expression in normal lungs is correlated (r 0.6) with strain lung tumor susceptibility
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Following full-length sequence analysis, gene-4, gene-7 and gene-64 represented different ESTs of the same gene (i.e. Mcl1, myeloid cell leukemia sequence 1), confirming association of Mcl1 expression levels with lung tumor susceptibility phenotype, although the strain expression patterns of the three cDNA clones were not exactly overlapping (Table I, Figure 1).

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Fig. 1. Hierarchical clusterings dendrogram of 91 genes whose mRNA expression pattern in normal lungs correlates (|r| > 0.60) with lung tumor susceptibility in mice. The normalized expression index for each transcript sequence (rows) in each strain (columns) is indicated by a pseudocolor representation shown according to the scale below (see EXPRESSION INDEX bar). Gene clustering analysis was performed using J-Express Pro software (http://www.molmine.com); the Pearson method and complete linkage method were used, and data were normalized using variance normalization. Red indicates higher than median expression and green indicates lower than median expression. Gene identification is provided in Table I.
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To confirm that the strain-specific expression patterns observed by cDNA hybridization on microarrays represent real differences correlated with lung tumor susceptibility, we performed kRTPCR for 28 genes in 13 (of 16) strains for which lung tissue and mRNA were available. Data were collected in blind and correlations with strain susceptibility were performed without knowledge of the previous microarray correlations. kRTPCR demonstrated a correlation of |r| > 0.6 with lung tumor susceptibility phenotype for 24/28 (86%) genes (Table I), thus independently confirming the microarray results. Overall correlation between microarray and kRTPCR was r = 0.378, P < 0.0001 (Figure 2).

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Fig. 2. Comparison of the range of mouse lung transcript levels determined by kRTPCR assay and hybridization-based cDNA array analysis. Data for 28 transcripts in 13 strains are expressed in terms of the decimal logarithm of normal lung levels with respect to the embryo levels (reference sample).
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Gene discovery
The in silico analyses of tissue expression profile for these genes were performed by searching against the one pass sequence information derived from the RIKEN mouse encyclopedia project (http://read.gsc.riken.go.jp/fantom2/). The microarray expression profiling data showed that most of the 91 genes do not display lung tissue restricted expression (not shown). Gene-7, gene-47 and gene-68 were specifically highly expressed in the lung compared with the other tissues, as analyzed by (14).
The genes whose expression pattern correlated with lung tumor susceptibility belong to different gene families. No apparent clustering of biochemical pathways is currently established. By literature search, a large percentage of clones, i.e. 26 out of 89 different genes (30%) (Mcl1 is redundant) showed some involvement in cancer (Table I). The percentage may be even higher, considering that most of the remaining clones have not been studied in depth for their possible involvement in tumorigenesis. At least 10 genes play an established functional role in cancer growth, differentiation or progression (gene-4, myeloid cell leukemia sequence 1; gene-8, stromal interaction molecule 1; gene-13, S100 calcium binding protein A4; gene-26, Retinoid X receptor gamma; gene-27, endothelial monocyte activating polypeptide 2; gene-35, trypsin 4; gene-40, BCL2/adenovirus E1B 19 kDa interacting protein 3-like; gene-66, macrophage migration inhibitory factor; gene-69, Friedreich ataxia; gene-85, Arhc ras homolog gene family, member C) (Table I). The remaining genes show deregulation or other types of involvement in cancer. In particular, immunohistochemical studies of protein encoded by gene-4 (Mcl1), gene-41 (Mvp, major vault protein), gene-56 (Amacr, alpha-methylacyl-CoA racemase), gene-61 (plastin), gene-85 (Arhc) showed that these proteins are tumor markers whose altered expression in tumors is associated with clinical findings (1519).
Gene expression profile of normal lung predicts lung tumor susceptibility
To further characterize the relationship between gene expression profile and strain susceptibility/resistance to lung tumorigenesis, gene expression data were subjected to principal component analysis. Results of such analysis can be expressed as 16 axes, reflecting the 16 mouse strains analyzed, and if no significant component distinguishes the strains, each axis is expected to explain 1/16 (i.e.
6%) of the variance. However, the first axis (horizontal) explained a significantly high percentage (32%, i.e. >5-fold the expected value) of the variance of the inter-strain gene expression profile and contrasted strains highly susceptible (Figure 2, left group, circled in green), intermediate-susceptible (Figure 2, middle group, circled in blue) and resistant (Figure 2, right group, circled in red) to lung tumorigenesis. The second axis (vertical) of the principal component analysis also explained a significant fraction (12%) of the gene expression profile variance. Strain relatedness (close distance on this axis) may result from strain correlation in gene expression patterns unrelated to predisposition to lung tumorigenesis.
Chromosomal mapping
To test the hypothesis that a subset of the 91 genes may represent lung cancer susceptibility genes whose alleles result in differential expression, we have compared the chromosomal localizations of these genes with the mapping of lung cancer modifier loci. By SSAHA analysis of the mouse genome (http://www.ensembl.org/Mus_musculus/) we have identified the precise location of the 91 genes on the mouse genome. Chromosomal position of lung cancer modifier loci was based on the Ensembl mapping of genetic markers located in the loci peak regions (http://www.informatics.jax.org/). Fifteen genes showed multiple chromosomal localizations, indicating that they belong to multi-gene families, and were excluded. Chromosomes 3 and 5 were not included because they do not contain known lung cancer modifier loci. Figure 4 shows that the 91 genes are scattered along the whole mouse genome. Among the 91 genes, the genes mapping closer to lung cancer modifier loci were: gene-12 at the Pas1 locus, gene-41 and -55 at the Sluc19 locus, gene-33, -63 and -73 at the Par1 locus (Figure 4).

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Fig. 4. Comparison of the chromosomal mapping of the 91 genes (on the right of each chromosome) with the mapping of lung tumor modifier loci (on the left). Chromosomal positions of the 91 genes are based on Ensembl mouse genome sequence. Positions of lung cancer modifier loci are based on the Ensembl position of genetic markers mapping in the peak regions; for each locus, the real position of candidate genes is expected to be included within ±5 Mb of the peak position. Chromosomal number is indicated below each chromosome.
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Discussion
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Our study was aimed at supporting with experimental evidence the hypothesis that the differences in lung tumor susceptibility among strains are associated with differences in the expression profile of specific genes in the normal lungs. We found that 91 cDNA clones show a transcript level profile significantly associated with genetic predisposition to lung tumorigenesis. Microarray data were reproducible, as hybridizations were performed in duplicate and resulted highly correlated (r > 0.7); additionally, kRTPCR confirmed in 24/28 (86%) genes the correlation between transcript levels and strain lung tumor susceptibility, in independent mRNA samples. Sensitivity of kRTPCR is higher than that of hybridization-based array technologies, which underestimate the magnitude of transcript level changes (20). Accordingly, we found a range of variation of
2 and
6 orders of magnitude for microarray and kRTPCR, respectively (Figure 2). The difference in sensitivity and the variability in both technologies may in part account for the better correlation of kRTPCR gene expression patterns with phenotype rather than with microarray results.
The strain differences in the expression of the 91 genes may be related to lung cancer susceptibility of these strains or, alternatively, may represent unconnected strain differences. At the moment, we cannot exclude either explanations and further studies are required before firm conclusions are reached. The first explanation seems more probable since it is strengthened by the findings that at least 26/89 (30%) genes are somehow cancer-related. Indeed, the likelihood that 30% of a random set of mammalian genes (i.e. >4000 genes of the 19K set) have some implication in cancer (i.e. altered expression, functional role in cancer growth or apoptosis, etc.) is low. For example, gene-13 (S100a4) belongs to the S100 calcium-binding protein family, whose members have been detected to be over-expressed in several types of human cancer, including lung cancer (21). S100A4 protein expression strongly correlates with reduced survival in human breast and bladder cancer and it induces the metastatic phenotype in rodent cancer models (22). Gene-85 (Arhc) plays an essential role in metastasis (23) and gene-4 (Mcl1) expression correlates with clinical outcome in colorectal cancer patients (15).
Comparison of chromosomal mapping of the 91 genes with mapping of known lung cancer modifier loci pointed out to gene-12 (homolog to human NM_018318 transcript with unknown functions) as an obvious Pas1 candidate gene. In contrast, the genes mapping near Sluc loci (Figure 4) cannot be considered as good candidates for Sluc loci, as these loci have been mapped in recombinant congenic mice originated from a cross between two strains (O20 and C57BL/10) (24) not included in our analysis.
Principal component analysis showed that lung tumor susceptible, intermediate-susceptible, and resistant strains can be grouped separately, with very few overlaps among groups (Figure 3). Noticeably, the highly susceptible A/J and SWR/J strains, despite their different geographical origin and phylogenetical unrelatedness (25), are very close to each other (Figure 3, on the left in green) and clearly separated by all genetic resistant mice (Figure 3, on the right in red).

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Fig. 3. Principal component analysis of the correlation matrix of gene expression levels in normal lungs of mouse inbred strains. Analysis included 91 genes whose expression levels showed a correlation coefficient |r| 0.6 with strain lung tumor susceptibility [expressed as log(N + 1) units]. The first factorial axis, which accounts for 32% of the total gene expression phenotype variance, contrasts strains with gene expression correlated to high lung tumor susceptibility (left) to resistant strains (right). The second factorial axis (12% of the variance) contrasts strains whose different gene expression is not correlated with lung tumor susceptibility. Ellipses include inbred strains that display a related gene expression pattern; proximity between strains indicates relative relatedness in gene expression pattern.
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These results indicate that mouse inbred strains can be grouped accordingly to lung tumor susceptibility phenotype based on their gene expression profile in normal lungs.
In conclusion, our results suggest that the gene expression profile of normal lung tissue is predictive of the genetic predisposition to lung tumorigenesis in mice. The present results may lead to a better understanding of the mechanisms underlying predisposition to cancer in an experimental model and provide a tool to test whether the same gene expression profile is predictive of genetic risk of lung tumor development in humans. If so, the gene expression profile might provide new diagnostic markers for lung cancer and these genes might provide targets for new strategies designed to prevent or treat lung cancer.
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Notes
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5 To whom correspondence should be addressed Email: dragani{at}istitutotumori.mi.it or Email: okazaki{at}saitama-med.ac.jp 
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Acknowledgments
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This study was partially funded by grants from Special Coordination Funds for Promoting Science and Technology from the Ministry of Education, Culture, Sports, Science, Japan to Y.O., the RIKEN Genome Exploration Research Project from the Ministry of Education, Culture, Sports, Science, Japan to Y.H., the Japan Science and Technology Corporation to Y.H., Associazione and Fondazione Italiana Ricerca Cancro (AIRC and FIRC, Italy) to T.A.D.
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Received April 9, 2003;
revised June 25, 2003;
accepted July 25, 2003.