Functional Genomics Unit (FGU) Microarray Data Site |
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Zuo F*, Kaminski N*, Eugui E, Allard J, Yakhini Z, Ben-Dor A, Lollini L, Morris D, Kim Y, DeLustro B, Sheppard D, Pardo A, Selman M,. Heller RA. Abstract, Introduction, Methods, Results, Discussion, References, Acknowledgements Figures: Figure 1, Figure 2, Figure 3, Figure 4, Figure 5, Figure 6 Tables: Table 1, All Genes with TNOM = 0, All data for download: Excel Sheet (4.5MB) Compressed (750kb) All reprints and correspondences should be addressed to Naftali Kaminski at: Functional Genomics, Institute of Respiratory
Medicine, Sheba Medical Center, Tel Hashomer, 52621, Israel Phone: 972-3-5305351, Fax: 972-3-5302377, E-mail: kamins@sheba.health.gov.il * Both authors contributed equally to the paper.
Pulmonary fibrosis is a progressive and largely untreatable group of
disorders that affects up to 100,000 people in the United States. To elucidate
the molecular mechanisms that lead to end-stage human pulmonary fibrosis we
analyzed samples from patients with histologically proven pulmonary fibrosis
(Usual Interstitial Pneumonia) using oligonucleotide 0microarrays. Gene
expression patterns clearly distinguished normal from fibrotic lungs.
Many of the genes that were significantly increased in fibrotic lungs
encoded proteins associated with extracellular matrix formation and degradation,
and proteins expressed in smooth muscle. Using a combined set of scoring systems
we determined that matrilysin (matrix metalloproteinase 7, MMP-7), a
metalloprotease not previously associated with pulmonary fibrosis, was the most
informative increased gene in our dataset. Immunohistochemisry demonstrated increased expression of
matrilysin protein in fibrotic lungs. Furthermore,
matrilysin knockout mice were dramatically protected from pulmonary fibrosis in
response to intratracheal bleomycin. Our
results identify matrilysin as a mediator of pulmonary fibrosis and a potential
novel therapeutic target. They also illustrate the power of global gene
expression analysis of human tissue samples to identify novel molecular pathways
involved in clinical disease.
The
molecular mechanisms that lead to end-stage pulmonary fibrosis are poorly
understood. Although a multitude of conditions - including granulomatous
disorders, exposure to environmental dusts and toxins, autoimmune diseases, and
drugs - have been associated with pulmonary fibrosis, in many cases the
causative agent remains unknown. The
most lethal and refractory form of pulmonary fibrosis is Idiopathic Pulmonary
Fibrosis. Idiopathic Pulmonary
Fibrosis (IPF) is defined histologically by the findings of Usual Interstitial
Pneumonia (UIP), characterized by the interposition of patchy foci of active
fibroblast proliferation associated with minimal inflammation, areas of advanced
scarring and fibrosis (honeycombing), and normal appearing lung (1, 2)
. The etiology of this
IPF/UIP has remained elusive, and the mean survival from the time of diagnosis
is only 3 years regardless of treatment (3)
.
Much of our understanding of the mechanisms of pulmonary fibrosis comes
from studies of bleomycin-induced lung fibrosis in mice. The common paradigm
postulates an initial alveolar injury, which triggers an inflammatory response
and, subsequently, fibrosis (4)
. The mainstay of the current therapeutic approach to UIP is suppression
of inflammation. However, this approach is ineffective in most patients (3)
. Recently, evidence has emerged that UIP may be the result of disordered
fibroblast regulation. Under this
paradigm, the pathological process of fibrosis is the result of persistent
remodeling of the lung interstitium by fibroblasts and smooth muscle cells
rather than the result of persistent inflammation (5)
.
The advent of microarray technology allows the simultaneous monitoring of
the transcriptional behavior of thousands of genes. This technology has been
repeatedly shown to be useful in the analysis of the response of a variety of
cellular systems to stimuli, in the classification of human cancer and in the
analysis of animal models of human disease (6-8)
. To characterize the transcriptional profile of UIP, we analyzed gene
expression patterns in lung tissue from patients with UIP using oligonucleotide
microarrays, and compared them with gene expression patterns in normal lung
tissue. Our results demonstrate a clear distinction between gene expression
patterns in the lungs of patients with UIP and control lungs. In addition to the
expected increase in extracellular matrix proteins, we found a coordinated
induction of genes that encode metalloproteases. One of them, matrilysin
(MMP-7), was the gene that was most distinctive between fibrotic and normal
lungs. To analyze the role of matrilysin in pulmonary fibrosis we injected
bleomycin into the tracheas of matrilysin knockout mice, and found that
matrilysin knockout mice are protected from bleomycin induced pulmonary
fibrosis. Our data suggest that matrilysin is a key regulator of pulmonary
fibrosis in mice and humans. Blocking matrilysin activity may thus serve as a
novel therapeutic intervention in this devastating disease. Lung specimens Microarray analysis - Lung specimens from patients
with pulmonary fibrosis were either obtained from lungs removed for lung
transplantation (patients 4,5) or by diagnostic thoracoscopy (patients 6,7,8).
Only one of the patients had been treated with corticosteroids at the time of
biopsy (patient 8, prednisone 15mg/day). Control specimens were obtained from
the normal parts of lungs removed for lung cancer (patients 1,2,3). An
additional control was a purchased pool of total RNA from 5 lungs obtained from
Clontech (sample 0). Patients with pulmonary fibrosis (2 smokers, 3 nonsmokers)
showed a restrictive physiology with decreased diffusion capacity (DLCO), ground
glass attenuation and honeycombing on HRCT, and a typical pattern of UIP on lung
histology. Two suffered from an autoimmune disease (patient 7: Rheumatoid
arthritis, patient 8: Sjogren’s Syndrome). The other 3 patients were diagnosed
as having IPF/UIP. The experimental
protocol was approved by the Institutional Internal review Board. All surgical
specimens for gene expression analysis were snap frozen in liquid nitrogen. For immunohistochemistry, lung samples were obtained from 7 other
patients with IPF/UIP (5
male and 2 female; 5 nonsmokers, 2 ex-smokers), aged 59 + 6 years by open lung
biopsy. None of the patients had been treated with corticosteroids or
immunosuppressive drugs. The diagnosis of IPF was based on clinical,
radiological and functional findings, and was corroborated by the characteristic
morphology of Usual Interstitial Pneumonia. Control lung tissue samples were
obtained from autopsies of patients who died from non-lung related causes (2 men
and 1 women, mean age 48 + 11 years). Preparation of labeled cRNA Probe preparation was performed as recommended by
the manufacturer of the microarrays (9)
. Briefly, total RNA was isolated by homogenization of lung specimens in
ice-cold Trizol. Twice purified
poly-A mRNA was isolated (Oligotex, Qiagen) and used as template for double
stranded cDNA synthesis with an oligo(dT)24 primer containing a T7
RNA polymerase promoter site added to the 3’ end (Genset). The cDNA was
extracted with phenol/chloroform, ethanol precipitated and used as a template
for in vitro transcription (Ambion T7 Megascript system) with biotin labeled
nucleotides (Enzo Diagnostics). Labeled cRNA was fragmented and a hybridization
mix was generated as recommended (9)
Hybridization of microarrays Aliquots of each sample (10mg
cRNA in 200 ml hybridization mix) were hybridized to a Genechip Hugene FLâ
array. After hybridization, each array was washed,
stained with streptavidin phycoerythrin (Molecular probes), washed again,
hybridized with biotin labeled anti streptavidin phycoerythrin antibodies,
restained with streptavidin phycoerythrin (Molecular probes) and scanned
(Hewlett Packard, GeneArrayTM scanner G2500A). Analysis of Genechip data Scanned output files were visually inspected for hybridization artifacts.
Arrays lacking significant artifacts were analyzed using Genechipâ 3.3 software (Affymetrix). Arrays were scaled to an
average intensity of 150 per gene and analyzed independently. The expression
value for each gene was determined by calculating the average of differences
(perfect match intensity minus mismatch intensity) of the probe pairs in use for
this gene. The expression analysis files created by Genechipâ 3.3 software were then transferred to a database
(Microsoft Access) linked to Internet genome databases (e.g. NHLBI, Swiss Prot,
and GeneCards) to update gene definitions.
A value of 20 was assigned to all measurements lower than 20. For cluster
analysis we used Cluster and Treeview programs described by Michael Eisen (10)
. We did not include in the analysis genes that did not have at least one
average difference intensity value ³ 100 or one present call by Affymetrix criteria. Fold ratios were
calculated for each sample against the median of the controls. Average fold
ratios are the averages of the fold ratios of the UIP samples. To
determine the most informative genes we used scoring methods previously
described by Ben-Dor et al (10)
and applied to the analysis of breast cancer and melanoma using cDNA
arrays (12)
. For detailed descriptions see reference (13)
. In brief, a gene is
designated as informative based on the degree to which its tissue expression
level is predictive of an independent classification of the tissue sample as
“diseased” or “not diseased” (11)
. The scores used in this study were: TNoM (Total number of misclassifications) - a count of the number
of classification errors committed when using the best simple threshold to
distinguish between two classes (diseased or not diseased) based on the
expression levels of a specific gene. Info – an estimate of the uncertainty remaining about the sample
classification (diseased or not diseased) after the incorporation of predictions
based on expression of an individual gene is given (a lower “Info” score
indicates a higher predictive value for a given gene). Gaussian
–
The overlap between distributions of expression levels for genes in two classes.
The score is based on normality assumptions.
Immunohistochemistry Immunohistochemistry
was performed as previously described (14)
. Briefly, after deparaffinization and re-hydration tissue sections were
blocked with 3% H2O2 in methanol, followed by antigen
retrieval in citrate buffer (10 mM pH 6.0). Lung sections were incubated with
normal serum for 30 minutes, followed by overnight incubation at
4oC with primary monoclonal anti-MMP-1 (20 mg/ml), anti-MMP-9 (5
mg/ml) (Fuji Chemical Ind., Ltd., Toyama, Japan), or anti-MMP-7 (20 mg/ml)
(Chemicon International, Inc. Temecula, CA). A secondary biotinylated
anti-immunoglobulin was applied followed by horseradish peroxidase-conjugated
streptavidin (BioGenex, San Ramon CA) according to manufacturer.
3-amino-9-ethyl-carbazole (AEC, BioGenex) in acetate buffer containing
0.05% H2O2 was used as substrate. The sections were counterstained
with hematoxylin. The primary antibody was replaced by non-immune serum for
negative control slides. Bleomycin
Treatment Age
and sex matched 8 -16 weeks old 129/Sv MMP-7+/+ (Jackson) and MMP-7-/-mice
(a gift from LM Matrisian), and 14-23 weeks old C57Bl/6 MMP-7+/+
(Charles River) and MMP-7-/- (LM Matrisian) mice were
maintained in a specific pathogen-free environment. Mice were anesthetized by
methoxyflurane and a 24-gauge needle was inserted into the trachea via the oral
cavity. 50 ml
of bleomycin (0.05-0.08 units in 0.9% saline, Sigma) or saline was slowly
injected. Mice were sacrificed 14 or 21 days after bleomycin or saline
injection, and lungs were collected for either hydroxyproline determination or
histology. Hydroxyproline
assay To estimate the total amount of collagen in the
lungs, hydroxyproline was measured as described (15)
. In brief, both lungs were removed and submitted to acid hydrolysis in 5
ml 6N HCl for 21 hr at 110 oC. Precipitates were removed by
centrifugation. Supernatants were dried overnight and dissolved in 100 ml of distilled water at room temperature. Each sample was tested in
duplicate. 50 ml of chloramine T (Sigma) in acetate-citrate buffer, pH 6.0, 50 ml
of perchloric acid, and 50 ml of Erlich’s reagent were added sequentially to
each sample as previously described (15)
. Absorbance was measured at 570 nm and the amount of hydroxyproline was
calculated. Histology
and Morphometry
Murine lungs were fixed in 10% formalin by perfusion followed by
submersion and processed by routine histologic methods through paraffin into
H&E stained sections for evaluation by light microscopy. A single
longitudinal section of each lung lobe was examined from each mouse.
Scores were assigned for pulmonary fibrosis, increased numbers of
pulmonary alveolar macrophages, the presence leukocytes other than macrophages
within alveoli, and interstitial leukocytic infiltrates.
Each parameter was marked as being essentially normal or given a severity
score from 1, minimal severity, to 5, most severe.
A score of 1 indicated a threshold level. A score of 2 indicated slight
changes that did not involve a significant amount of tissue. A score of 3
indicated the effect was easily discernable in multiple sites and/or was present
in larger foci in from one to a few sites. A score of 4 indicated a relatively
severe change that was widespread within multiple lobes or which completely
filled a single lobe. A score of 5 indicated that a change was severe and
involved all lobes. Gene expression patterns are distinct in fibrotic and non-fibrotic lungs - Global gene expression patterns clearly distinguished between fibrotic
and normal histology lungs (Fig 1a). Furthermore, when only the genes that
received the most significant score (TNoM = 0) are presented, the differences in
gene expression patterns are even clearer (Fig 1b). This distinction was also
evident when we applied hierarchical clustering to the samples (data not shown).
A known issue in analysis of microarray data is the small numbers of
samples compared to the large number of parameters measured – a situation that
can lead to spurious statistical associations. To address this issue we
subjected TNoM to rigorous statistical benchmarking. We calculated the number
(out of 7129) of genes expected for every score (TNOM 0,1,2 etc), when a
classification of the tissues is uniformly drawn at random. In this case we
expected 111 genes to have the best score (TNoM = 0).
We actually observed 164 such highly
informative genes. Such an overabundance of highly informative genes has a p
value < 10-6 when genes are independently drawn and their TNoM is
calculated with respect to a random partition. In performing the calculations we
treated the pool of 5 normal lungs as a single sample, thus the figures
presented here may even underestimate the information content of this study. The
complete dataset is provided on our website (http://FGUSheba.cs.huji.ac.il/)
Smooth muscle markers are increased in fibrotic lungs
- One of the most intriguing phenomena that occurs
during the development of UIP is the formation of small aggregates of actively
proliferating myofibroblasts and fibroblasts called myofibroblast/fibroblast
foci (5)
. In addition, abnormal collections of smooth muscle cells have been
identified in UIP lungs (16)
. Interestingly, we observed a marked increase in the expression of genes
that encode for muscle proteins. These included markers of smooth muscle
differentiation such as vascular a smooth muscle actin, g
smooth muscle actin, calponin and integrin a7b1. Genes that encode for
proteins associated with cell contraction and actin filament organization, such
as myosin, SM22, tropomyosin and S100 A9 protein are also increased. The
complete list is provided in table 1. Genes that encode immunoglobulins, complement and some chemokines were
upregulated in fibrotic lungs
– Surprisingly, gene expression patterns in patients with pulmonary fibrosis
did not suggest increased acute inflammatory activity. We did not observe any
activation of an IL-1 or TNFa
related pathway, nor did we observe any increase in apoptosis related genes.
However, we did observe an increase in genes that encode for immunoglobulins,
potentially reflecting chronic B cell infiltration, and an increase in some
complement factors. The genes that encode the chemokines MCP 4, GRO 1 and
eotaxin were increased (Table 1). Genes
that encode proteins that are involved in extracellular matrix formation,
degradation and signaling are increased in fibrotic lungs - As expected expression of the genes that encode for collagens I, and
III were increased in fibrotic lungs, as was expression of the genes that encode
for collagen VI, tenascin C, osteopontin and fibronectin (Table 1). Several
other genes that encode for proteins involved in extracellular matrix formation
such as BIGH3, filamin and fibrillin were increased, as were genes associated
with ECM related signaling such as cell adhesion kinase b and the collagen receptor tyrosine kinase DDR (Table
1). Another interesting subset
was of genes that encoded proteases.
The expression levels of Matrix metalloproteinase 1 (MMP-1), Matrix
metalloproteinase 2 (MMP-2), MMP-7, Matrix metalloproteinase 9 (MMP9) (table 1)
and cathepsin E were all relatively increased in fibrotic lungs. MMP7
(matrilysin) was the gene that scored as the most informative (TNoM = 0, Info =
0, Gaussian = 0.00625, complete dataset, http://FGUSheba.cs.huji.ac.il/) among
the genes that were upregulated (Figure 2A).
Increased expression of MMP-7 is confirmed by
immunohistochemistry
- To verify the gene expression data at the level of protein expression, and to
identify the cellular source of MMP-7 we performed immunohistochemiistry on lung
tissue from patients with UIP. Immunoreactive MMP-7 was abundantly localized in
the epithelium including in alveolar and bronchiolar epithelial cells, (Figures
2B and C, and Supplemental figure 4A-C at http://www.pnas.org/). MMP-7 was also detected in the extracellular
space as shown by staining in thickened alveolar septa and in the extracellular
matrix (Figure 2B). MMP-7 was
minimally detected in normal lung parenchyma (Figure 2D). We also stained for
MMP-1 and MMP-9. MMP-1 was primarily present on hyperplastic type 2 pneumocytes
and bronchiolar cells lining honeycomb cysts, as well as in reactive
alveolar epithelial cells. (Supplemental Figure 5A and B, http://www.pnas.org/). Alveolar macrophages also intensely stained for
MMP-1 in tissue sections from patients with fibrotic lung disease (1A,
Supplemental figure 5 insert A, http://www.pnas.org/). MMP-9 was detected in neutrophils, both inside
vessels and in the interstitium (Supplemental Figure 6A and insert, http://www.pnas.org/). MMP-9 was also localized in the
extracellular matrix and in some areas of dense scars (Figure 3B, supplemental
data). Control lungs showed scattered staining for MMP-1 in (Supplemental figure
5C, http://www.pnas.org/), and minimal MMP-9 staining in neutrophils
(Supplemental figure 6D, http://www.pnas.org/). Control samples incubated with non-immune sera
were negative as shown in Figure 4D supplemental data (http://www.pnas.org/). Matrylisin knockout mice do not develop lung
fibrosis following treatment with bleomycin - To determine whether MMP-7 was actually involved
in the fibrotic process, we administered bleomycin to lungs of MMP-7-/-mice,
and to age and sex matched wild type controls from two different backgrounds:
129Sv and C57Bl/6. Two to three weeks after intratracheal bleomycin,
hydroxyproline level increased by 96 - 119% in wild type 129 Sv mice compared to
55 - 59% in matrilysin knockout mice, in three separate experiments using 5 - 9
mice/group (Figure 3A). The differences were statistically significant with p
values from 0.0002 to 0.02 in all three experiments. This finding was not
dependent on the genetic background of the mice, since comparable results were
obtained in three separate experiments with mice of the C57Bl/6 background (Fig
3A). These results were supported by histologic evaluation that revealed milder
changes in the lungs of matrilysin knockout mice (Fig 3D). The mean severity for
all histopathologic parameters assessed was significantly less in the
bleomycin-challenged MMP-7-/- mice than in the corresponding WT
controls (Fig 3B). The results of this
study support the view of UIP as a disease of persistent matrix deposition and
destruction that is associated with relatively modest, chronic inflammation.
Interestingly, despite the prevailing view of “honeycomb” lung as an
irreversibly scarred and quiescent tissue, our gene expression data show a
tissue that is quite actively remodeling with a high level of gene expression of
both matrix degrading proteins and proteins involved in matrix deposition. One of the most
impressive features of our results is the clear distinction in gene expression
patterns, and therefore the fundamental tissue biology, of UIP lungs compared to
non-fibrotic lungs. A usual concern with microarray analysis of diseases, in
which tissue availability is a challenge, is the difficulty in obtaining data
that is both biologically meaningful and statistically significant. The use of
traditional statistics is complicated in microarray experiments because of the
troubling asymmetry between the numbers of samples and the number of parameters
measured, which may result in spurious statistical associations. One of the
advantages of the analytic methods that we used here is their amenability to
rigorous statistical benchmarking (11)
. We can calculate the number of informative genes per score expected in a
random classification and then compare this estimated number of high scoring (or
informative) genes to the actual number of informative genes (per score)
measured in our dataset (13)
. In our study, despite the small sample size and the genetic
heterogeneity of our patients we observed overabundance of informative genes
suggesting that the differences in gene expression that we observed between the
two groups were biologically meaningful. Indeed, gene expression patterns were
highly robust and also evident when we applied other statistical tools (t test,
Wilcoxon), clustering methods and self-organizing maps (data not shown). The
results of our analysis are an example of overcoming some of the limitations of
a small sample size using computational tools specifically designed for
microarray experiments. Close inspection of the
informative genes in our data set sheds light on several important aspects of
fibrotic lung disease. One
impressive feature is the coordinated upregulation of matrix metalloproteinases,
predominantly MMP-1 and MMP-7, in the lungs of patients with UIP.
It has been suggested that the tissue phenotype of fibrosis
(primarily the exaggerated extracellular matrix deposition) results from
dysregulation of the synthesis and degradation of extracellular matrix proteins
- a process that could involve several members of the MMP family. Thus, MMP-1 (collagenase-1 that degrades fibrillar
collagens) as well as MMP-2 and MMP-9 (gelatinases A and B which have a broad
range of substrates including type IV collagens from basement membranes) have
previously been reported to be upregulated in human pulmonary fibrosis and in
animal models of pulmonary fibrosis (17-19)
. In our dataset, MMP-1, 2,
and 9 were significantly higher in UIP lungs. These observations were
verified at the protein expression level for MMP-1 and 9 (Supplemental figures
5,6). We did not observe any significant increase in gene expression levels of
tissue inhibitors of metalloproteinases in UIP lungs. Surprisingly we detected a
decrease in TIMP3 gene expression (Complete data set table,
http://FGUSheba.cs.huji.ac.il/), an observation that has been seen in other
microarray experiments (Pardo A. Unpublished observation). MMP-7, a metalloproteinase not previously associated with pulmonary
fibrosis, was the most informative gene among the increased genes in UIP lungs.
This was confirmed by immunohistochemical staining on lung tissue from a
separate group of patients with UIP. The intense staining confirmed increased
MMP-7 protein expression by epithelial cells as well as an increase in MMP-7
bound to the extracellular matrix. The protection of MMP-7-/-
knockouts from bleomycin-induced fibrosis shows that this metalloproteinase
plays an important role in the development of pulmonary fibrosis. MMP-7 is
expressed in epithelial tissues that are in contact with the environment.
Although it is not expressed by mice living in germ free environment (20)
, its expression is rapidly induced by infection and air pollution (21,
22)
. MMP-7 is required for activation of defensins in the small bowel and
MMP-7-/- mice cannot kill enteric pathogens (23)
. Recently, MMP-7 has been shown to play a role in two pathways that are
considered important in the development of bleomycin-induced pulmonary fibrosis,
the TNFa,
and Fas pathways (24, 25)
. Like MMP-1, MMP-7 was primarily expressed by alveolar epithelial cells,
and both may have a role in cell migration as has been proposed for
keratinocytes in skin wound healing (26, 27)
. Similarly, MMP-1 and MMP-7 may participate in alveolar and bronchiolar
cell migration over different matrices during UIP lung remodeling (28)
. In addition, MMP-7 may enhance a procoagulant microenvironment in the
alveolar spaces since it is able to rapidly cleave tissue factor pathway
inhibitor, an inhibitor of tissue factor-induced coagulation (29)
. Increased local procoagulant activity has been found in fibrotic lung
disorders, including idiopathic pulmonary fibrosis, and alveolar epithelial
cells seem to contribute to the increased procoagulant and antifibrinolytic
activities in this disorder (5,
30)
. Based on our data and its
known functions, matrilysin is an excellent candidate to be a key player in
sustained tissue injury and fibrosis. On one side it is induced by epithelial
injury, a common pathological process leading to pulmonary fibrosis, and
on the other hand it may be an activator of cell death, chronic inflammation,
and procoagulant activity. The focus on MMP-7 in our work is a good example of
large-scale gene expression experiments as hypothesis generating tools. Based on
previous knowledge we had little reason to suspect that MMP-7 played a role in
pulmonary fibrosis. However, no matter what type of analysis was used, MMP-7 was
the most significant gene that was induced in UIP samples, thus almost demanding
its analysis. Among the genes that
where significantly upregulated, we did not find many inflammatory related
genes. We observed evidence of a chronic inflammatory infiltration probably
associated with B-cell infiltration (immunoglobulins etc), but we did not
observe any evidence for T cell activation, or for any significant activation of
apoptotic pathways. Although in animal models of pulmonary fibrosis the fibrotic
response may be dependent on intact TNFa or Fas signaling pathways (31-35)
, activation of these pathways was not apparent in this study. One limitation of using
whole lung homogenates in our study is our relative inability to assess the
exact cells that are overexpressing genes that were higher in UIP lungs. For
some typical cellular markers it is very hard to even guess whether the changes
result from changes in cellular content or real gene expression patterns. For
instance we observed changes in three cytokeratins (5, 8, 15). This may
represent a change in epithelial gene expression, a change in epithelial
cellular subset (epithelial migration), or a phenotypic change in another cell
type. So far such analysis is cumbersome, but the creation of databases that
will contain gene expression signatures of specific cell types and analytic
approaches to dissect them out computationally could ameliorate this hardship.
Despite this limitation one of the impressive clusters of genes that that were
significantly increased in UIP lungs was that of muscle related genes.
An important feature in the histological description of UIP is the
presence of fibroblastic foci (5)
. Fibroblast foci possibly represent microscopic areas in which
fibroblasts migrate, proliferate, and maintain the abnormal architecture of the
lung. A major subpopulation of the fibroblasts in these foci expresses markers
of smooth muscle differentiation, such as a-smooth muscle actin (aSMA) (16,
17)
. In addition, clusters of
smooth-muscle cells are usually seen in UIP lungs, probably contributing to the
decreased lung compliance (16)
. We observed an
increase in muscle-related genes that ranged from 2.5 to 25 fold (table 1).
These coordinated increases in smooth muscle markers, and in cellular
contractile machinery, reflect our ability to detect a significant phenotypic
change in even in a relatively small cell population in the lung. In this study we used
oligonucelotide microarrays to analyze gene expression patterns in UIP. We
distinguished specific subsets of genes that differentiated UIP from
non-fibrotic lungs. These genes included genes that encoded proteins associated
with B cells and with chronic inflammation, muscle related genes and genes that
encoded proteins involved in extracellular matrix production, degradation and
signaling. Using advanced computational scoring methods we determined that
MMP-7, a multifunctional matrix metalloprotease not previously associated with
pulmonary fibrosis, was the most informative increased gene in our dataset.
The hypothesis that MMP-7 is indeed involved in the pathogenesis of
pulmonary fibrosis was supported by our observation that MMP-7 knockout mice
were protected from bleomycin induced fibrosis. Our results support the view of
UIP as a chronic destructive process, in which an increase in myofibroblasts and
cells with smooth muscle-like phenotype, active abnormal reepithelialization,
and aberrant repair are interwoven. The authors thank Gady Cojocaro and Dr Hal van Wart for their support and,
Dr. Tom Raffin and Ms. Susan Jacob for their support to obtain fresh human lung
tissue samples from Stanford Medical Center, Stanford University.
Dr. Isasshar Ben-Dov provided helpful comments on the manuscript.
Dr Kaminski's work was supported in part by a generous grant from the Tel-Aviv
chapter of the Israeli Lung Association.
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Pathol 190, 221-9. Author Affiliations
Roche Bioscience, Palo Alto, California,
Functional Genomics, and Institute of Respiratory Medicine, Sheba Medical center, Tel Hashomer, Israel.
Agilent technologies, Haifa, Israel,
Lung Biology Center, Cardiovascular Research Institute and the Department of Medicine University of California, San Francisco,
Facultad de Ciencias, Universidad Nacional Autonoma de Mexico,
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