Oncogene (2003) 22, 5907–5914
& 2003 Nature Publishing Group All rights reserved 0950-9232/03 $25.00
www.nature.com/onc
Investigating hypoxic tumor physiology through gene expression patterns
Nicholas C Denko*,1, Lucrezia A Fontana1, Karen M Hudson1, Patrick D Sutphin1, Soumya
Raychaudhuri2, Russ Altman2 and Amato J Giaccia1
1
Division of Radiation and Cancer Biology, Department of Radiation Oncology, Stanford University School of Medicine, Stanford,
CA 94305, USA; 2Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
Clinical evidence shows that tumor hypoxia is an
independent prognostic indicator of poor patient outcome.
Hypoxic tumors have altered physiologic processes,
including increased regions of angiogenesis, increased
local invasion, increased distant metastasis and altered
apoptotic programs. Since hypoxia is a potent controller
of gene expression, identifying hypoxia-regulated genes is
a means to investigate the molecular response to hypoxic
stress. Traditional experimental approaches have identified physiologic changes in hypoxic cells. Recent studies
have identified hypoxia-responsive genes that may define
the mechanism(s) underlying these physiologic changes.
For example, the regulation of glycolytic genes by
hypoxia can explain some characteristics of the Warburg
effect. The converse of this logic is also true. By
identifying new classes of hypoxia-regulated gene(s), we
can infer the physiologic pressures that require the
induction of these genes and their protein products.
Furthermore, these physiologically driven hypoxic gene
expression changes give us insight as to the poor outcome
of patients with hypoxic tumors. Approximately 1–1.5%
of the genome is transcriptionally responsive to hypoxia.
However, there is significant heterogeneity in the transcriptional response to hypoxia between different cell
types. Moreover, the coordinated change in the expression
of families of genes supports the model of physiologic
pressure leading to expression changes. Understanding the
evolutionary pressure to develop a ‘hypoxic response’
provides a framework to investigate the biology of the
hypoxic tumor microenvironment.
Oncogene (2003) 22, 5907–5914. doi:10.1038/sj.onc.1206703
rely upon oxygen-dependent energy production suffer
when oxygen falls below a certain threshold level.
However, too much oxygen can also result in the
generation of toxic, damaging radical byproducts. The
net effect of these opposing pressures necessitates
the evolution of molecular mechanisms to regulate the
cellular availability and usage of oxygen.
The response to low-oxygen conditions has been
identified in both procaryotes and eucaryotes. Although
the mechanisms for gene regulation in response to lowoxygen conditions are diverse, parallel systems have
evolved in different organisms that are transcriptionally
responsive to low-oxygen. This convergent evolution
suggests that the ability to respond to low-oxygen
conditions offers a competitive Darwinian advantage.
Although the magnitude of the ‘hypoxic’ response may
differ between unicellular and multicellular organisms,
they both share the principal goal of maintaining the
critical energy levels required for homeostasis, while
extracellular oxygen concentrations decrease. While this
review is focused on the transcriptional changes in the
pathophysiologic environment of hypoxic tumor cells,
the reason why hypoxic gene regulation evolved is
obviously in response to a more physiologic condition of
hypoxia such as occurs during embryonic development
(Chen et al., 1999a) or during wound healing (Warren
et al., 2001).
Keywords: hypoxic gene induction; HIF-1; VHL
Hypoxia/anoxia-responsive gene expression has been
well characterized in procaryotic organisms such as
bacteria as well as in lower and higher eucaryotes such
as yeast and mammals, respectively. Unicellular organisms have less control over environmental oxygen, so
their hypoxia response is designed to utilize efficiently
the decreased levels of oxygen. The facultative anaerobic
bacterium Escherichia coli utilizes the fumarate, nitrate
reduction (FNR) protein, which is a bifunctional protein
that acts both as a hypoxic sensor and a hypoxiaresponsive transcription factor. Under aerobic conditions, FNR exists as an inactive apoprotein, but under
hypoxia, it forms an active homodimer that is dependent
on a redox-sensitive 4Fe–4S cluster (Green et al., 2001).
In contrast, one mechanism that yeast Saccharomyces
cerevisiae uses for hypoxic gene expression is a heme-
Introduction
Evolution of the transcriptional ‘hypoxic response’
Molecular oxygen is beneficial to many organisms due
to its role in efficient energy production. Organisms that
*Correspondence: NC Denko; E-mail: [email protected]
Supplemental data is available at: http://cbrl.stanford.edu/hypoxia/
welcome.htm
Mechanisms of gene regulation in response to hypoxia
Functions of hypoxia responsive genes
NC Denko et al
5908
regulated repressive system based on the ROX1
(repressed in oxygen) molecule. Under aerobic conditions, abundant heme activates the HAP1 complex that
in turn transactivates the ROX1 gene. ROX1 protein
blocks expression of a large set of hypoxia-responsive
genes (Becerra et al., 2002). Under hypoxic conditions,
heme-deficient HAP1 represses ROX1 transcription,
and the hypoxia-responsive genes are derepressed
(Zitomer et al., 1997). These are two examples of the
diverse mechanisms that have evolved in single-cell
procaryotes and lower eucaryotes to respond to lowoxygen concentrations.
The mammalian transcriptional response to hypoxia
is considerably more complicated, relying on multiprotein complexes to regulate several transcription
factors, the most well studied being (hypoxia-inducible
factor 1 (HIF-1)). General stress-responsive transcription factors such as AP-1, NF-kB and Egr1 have also
been reported to be regulated by hypoxia and/or
reoxygenation (Faller, 1999; Ten and Pinsky, 2002).
However, the sensitivity of these factors to mild
hypoxia, and the duration of their transcriptional
response is much less than that of HIF-1. The ‘general
stress responsive’ transcription factors are therefore not
well suited to regulating gene expression in the
chronically hypoxic tumor microenvironment. Furthermore, the number of genes that are upregulated by nonHIF mechanisms in response to chronic hypoxia seems
to be small compared to the HIF-responsive genes.
In contrast to gene induction by hypoxia, several
mechanisms of gene repression by hypoxia have also
been reported. Repression can contribute to the hypoxic
response by downregulating such genes as the antiangiogenic thrombospondin (TSP) genes (Tenan et al.,
2000). The TSP genes function to block new blood vessel
formation, so they are presumably downregulated by
hypoxia in order to stimulate angiogenesis (Laderoute
et al., 2000). Recent in vitro data have suggested that
hypoxic downregulation of gene expression can be
through the induction of the (negative cofactor 2
(NC2)) transcriptional repressor (Denko et al., 2003).
NC2 has been shown to block gene expression by
regulating core promoter action through binding to the
TATA-associated factor TBP (Kamada et al., 2001). In
addition, the P53 tumor suppressor gene has been found
to associate with the transcriptional corepressor mSin3A
under hypoxia, and may also be involved in repressing a
subset of genes in these conditions (Koumenis et al.,
2001). Further study is needed to define all the genes
that are repressed in response to hypoxia, and that are
regulated through the activity of either P53, NC2, or
other mechanisms (Yun et al., 2002).
HIF-1 regulation in mammalian cells
HIF1 was identified through the investigation of the
hypoxia-responsive gene erythropoetin (EPO) (Goldberg et al., 1988). EPO is the growth factor responsible
for stimulating the bone marrow to produce new red
Oncogene
blood cells, especially in times of systemic hypoxia, such
as during travel to high altitudes (Caro, 2001). The
enhancer element responsible for EPO induction under
hypoxia was identified (Imagawa et al., 1991), and the
protein that bound to this hypoxia-responsive element
was purified, cloned, and found to be a heterodimer
(Wang and Semenza, 1993). One subunit of the dimer
was constitutively expressed in cells (HIF-1b or ARNT),
and the other component was oxygen labile and
stabilized in cells exposed to low oxygen (HIF-1a)
(Jiang et al., 1996). The molecular mechanism of HIF
activation has been recently elucidated, largely because
of the functional interaction between HIF-1a and the
tumor suppressor protein von Hippel–Lindau (VHL).
Under normoxic conditions, HIF-1a is rapidly degraded, with a half-life of a few minutes. In contrast,
under hypoxic conditions, HIF-1a becomes stabilized
(Maxwell et al., 1999), associates with the HIF-1b
subunit, translocates to the nucleus, and binds in a
sequence-specific manner to a hypoxia-responsive element in target genes to activate transcription. The
regulation of HIF-1a stability has been shown to rely
heavily upon the VHL tumor suppressor protein
(Maxwell et al., 1999). Under normoxia, HIF-1a is
rapidly hydroxylated at proline 564 (Ivan et al., 2001;
Jaakkola et al., 2001) by a novel family of proline
hydroxylases (Bruick and McKnight, 2001; Epstein
et al., 2001). The hydroxylated form of HIF-1a binds
to the VHL protein that is part of the multiprotein
complex containing elongins B and C and CUL1 (Hon
et al., 2002; Min et al., 2002). This complex acts to
ubiquitinate HIF-1a and target it to the proteasome for
degradation (Maxwell et al., 1999). Under hypoxia,
HIF-1a is not hydroxylated (Chan et al., 2002), does not
bind to VHL, and becomes stabilized.
Studies of the VHL tumor suppressor have identified
a role for hypoxia-regulated genes in modifying
malignant transformation in human tumors (Kondo
et al., 2002). VHL has been identified as a classic tumor
suppressor gene that requires the loss of both alleles to
generate disease (Friedrich, 1999). The von Hippel–
Lindau syndrome is a result of the germline loss of one
VHL allele, with the loss of the second allele resulting in
high-frequency renal cell carcinoma, pheochromocytomas and hemangioblastomas (Friedrich, 1999). In the
absence of VHL, HIF-1a exhibits increased stability in
normoxic conditions and stimulates constitutive expression of HIF-responsive genes under normoxic conditions (Wykoff et al., 2000). Thus, it is thought that one
factor contributing to VHL’s role as a tumor suppressor
is its ability to downregulate the expression of hypoxiaresponsive genes under normoxic conditions (Kondo
et al., 2002).
The importance for HIF-1-regulated genes in driving
tumor development is supported by studies on murine
tumor cell lines that are deficient in either HIF-1a (Ryan
et al., 1998) or HIF-1b (Maxwell et al., 1997). Both
tumors that are derived from HIF-1a and HIF-1bdeficient cells exhibit reduced aggressiveness in allografted tumor formation in immune-deficient mice
(Maxwell et al., 1997; Ryan et al., 1998). The reduced
Functions of hypoxia responsive genes
NC Denko et al
5909
tumor formation of HIF-deficient tumor cells has been
attributed to several factors, including decreased levels
of vascular endothelial growth factor (VEGF) secretion
that leads to decreased levels of angiogenesis in vivo
(Grunstein et al., 1999).
Physiologic versus pathophysiologic hypoxia
Mice in which HIF-1a has been deleted fail to develop
beyond day 10 (Iyer et al., 1998; Ryan et al., 1998). This
observation suggests that HIF-1a or hypoxia-regulated
genes are necessary for normal embryonic development.
One target hypoxia-responsive gene that has been
hypothesized to be in large part responsible for these
effects is the vascular endothelial growth factor A
(VEGFA) gene. Embryos deficient in a single copy of
VEGFA do not develop (Carmeliet et al., 1996; Ferrara
et al., 1996). The direct link between hypoxia and VEGF
is found when the HRE of VEGF is specifically
mutated, and mice also show a partial embryonic
lethality at day 10 (Oosthuyse et al., 2001). These
animal studies reinforce an essential role for hypoxiaresponsive genes during embryonic development. Physiologic hypoxia occurs during development, wound
healing, exposure to increased elevation, or other
transient vascular alterations (Elson et al., 2000). These
examples are conditions in which the hypoxic state
elicits a response and that response in turn ‘cures’ the
hypoxic insult. Wounding causes vascular damage that
leads to the induction of VEGF, the reestablishment of
blood flow through new vessels and a return to a
normoxic state (Figure 1).
In contrast to the physiologic hypoxia described
above, tumor hypoxia is an example of a chronic,
pathophysiologic condition. The difference lies in the
fact that the response is unable to resolve completely the
hypoxic insult (Dvorak, 1986) (Figure 1). Despite
hypoxia-induced VEGF production in the tumor, the
Figure 1 Model showing comparison of physiologic stress
response to pathophysiologic stress response
formation of new blood vessels is unable to keep pace
with growing tumor cells. The result is a constant
production of hypoxia-dependent changes that are never
able to establish a uniform normoxic environment. The
continuous subversion of the normal hypoxic response is
what gives the hypoxic tumor its unique phenotype
(Denko and Giaccia, 2001). Understanding the normal
hypoxic response can therefore give insight into how it
can lead to the pathophysiologic effects.
Tumor hypoxia and clinical correlates
Tumor oxygenation can be directly measured in vivo in
patients by microelectrodes or PET imaging through
hypoxic marker binding (Hockel and Vaupel, 2001).
Numerous clinical studies have demonstrated that the
pretreatment oxygenation status of solid tumors can be
used to stratify patients prospectively. These studies
indicate that mean oxygen status below 10 mmHg in the
tumor predicts for poor survival in patients with tumors
of the head and neck (Nordsmark et al., 1996), or cervix
(Hockel et al., 1996) or in soft tissue (Brizel et al., 1996).
The poor prognosis of hypoxic tumors is independent of
treatment modality, with patients treated surgically
suffering a similarly poor outcome as patients treated
with radiotherapy (Hockel et al., 1996). Most importantly, the clinical data suggest that hypoxic tumors
represent a biologically more aggressive tumor, in
addition to one that is more resistant to oxygendependent therapies such as radiation (or some chemotherapies) (Teicher, 1994).
Target genes regulated by hypoxia
What are the specific genes that are responsible for the
hypoxic tumor phenotype, and how do they give the
hypoxic tumor its increased predisposition to invade,
metastasize and apoptose? Several groups have used
genomic approaches to identify gene expression profile
changes in hypoxia (Denko et al., 2000a; Koong et al.,
2000; Wykoff et al., 2000; Scandurro et al., 2001). Thus
far, the different cell types examined in vitro, the relative
level and duration of hypoxia used, and the resultant
gene profiles have underscored the heterogeneity of the
induced genes. An analysis of these various studies
indicates that there is a core set of genes that are induced
consistently by hypoxia and a large number of genes
that exhibit cell-type-specific induction. The differential
response of various cell types emphasizes the specialized
roles for the different cellular components of the solid
tumor. Some of the more specific examples of cell-typedependent hypoxia-responsive genes include the production of tyrosine hydroxylase (TH) by cells of the carotid
body (Millhorn et al., 1996), or the production of EPO
by cells of the juxtaglomerular apparatus (Fandrey and
Bunn, 1993). However, some genes are induced by
hypoxia in a large number of diverse cell types, such as
VEGF or glucose transporter 3 (GLUT3). Members of
Oncogene
Functions of hypoxia responsive genes
NC Denko et al
5910
the family of glycolytic enzymes are also induced in
almost all cell types, even if the specific members may
not be induced in all (Seagroves et al., 2001). The
cellular need to generate energy seems to be an obvious
universal response to hypoxia, while production of TH
or EPO is required in a more specialized cellular context.
One example of expression profiling cells treated in
vitro with hypoxia is shown in Figure 2. The hypoxic
profile of six cell types, representing normal cervical and
dermal keratinocytes (NCK, NDK), normal stromal
fibroblasts (NCF) and transformed keratinocytes (Siha,
C33a, FaDu), is shown. In this cDNA array of 6800
genes, 110 genes were found to be hypoxia-responsive,
with 84 being induced, 24 being repressed and three
showing a mixed response of induction in some cells
with repression in others. Extrapolating from these data,
approximately 1.5% of the genome is transcriptionally
responsive to hypoxia. This frequency of hypoxiaresponsive genes agrees with previous findings using a
much smaller array (Koong et al., 2000).
The hypoxia-responsive genes identified in this
experiment are ordered in Figure 2 by both cell type
and induction pattern for display purposes. A red signal
represents induction, and green represents repression,
with maximal changes of approximately 10-fold. Using
this set of genes, cell types were ordered for the
similarity of hypoxic response by principle component
analysis (Raychaudhuri et al., 2000). PCA orders the cell
lines as depicted in Figure 2 in the order of similarity
and shows that the normal keratinocytes are most
closely related, the normal fibroblasts more distantly
related and the tumor lines even more distant from the
normal keratinocytes. These two axes, the similarity of
cell type in the x-dimension, and the level of induction in
the y-dimension describe the representation of the
‘hypoxiatome,’ as depicted in Figure 2. Figure 3 shows
a panel of selected genes used as probes for Northern
blot comparison of techniques.
Interestingly, the differences in hypoxia-responsive
profiles cannot be simply explained by the fact that the
cells were genetically unstable tumor cells. The normal
stromal and normal epithelial cells also show differences
in their hypoxic profiles. These data underscore the
importance of studying hypoxic gene expression in a
cell-type-dependent context. From this sample, we can
see that some genes are widely inducible, such as NIP3L,
IGFBP3 and Dec1, but many genes are inducible only in
certain cellular contexts, such as placental growth factor
or ephrin A1. Identifying the additional factors regulating hypoxic gene responsiveness will continue to be a
major point of investigation.
"
Figure 2 Expression profile changes in response to long-term
hypoxia. The subset of genes with robust expression changes was
selected as described in the text. Expression ratios were converted into
log base 2 values; these are plotted in matrix form, with cell lines listed
across the top and gene name and accession number on the side. Boxes
are colored to indicate relative expression levels. The red values
indicate induction, while green values indicate repression with maximal
changes of approximately 10-fold
Oncogene
Functions of hypoxia responsive genes
NC Denko et al
5911
Table 1 Categorization of selected hypoxia-regulated genes by
function
Metabolism
References
Glucose transporter 1, 3
Ebert et al. (1995), O’Rourke et al.
(1996)
Ebert et al. (1996)
Salceda et al. (1996)
Ebert et al. (1996), Semenza et al.
(1994)
Niitsu et al. (1999)
Semenza et al. (1994)
This work
This work
Ivanov et al. (2001)
6-Phosphofructo-2 kinase
Phosphoglycerate kinase
Aldolase A, C
Triose phosphate isomerase
Lactate dehydrogenase A, B
Glycogen branching enzyme
Solute carrier family 6, 16
Carbonic anhydrase IX
Angiogenesis
VEGF A, B C D
VEGF R1
Placental growth factor
Angiopoietin 2
Adrenomedullin
Endothelin 1, Endothelin 2
Ephrin A1
Nitric oxide synthase
COX1 COX2
Thrombospondin 1,
Thrombospondin 2
Tissue remodeling
Lysyl oxidase
PLOD2
Integrin 5alfa
Plasminogen activator
inhibitor 1
Urokinase plasminogen
activator receptor
LDLR related protein
Tissue factor
Mucin 1
Apoptosis
BNIP3 BNIP3L
IGFBP1, 3
Figure 3 Northern analysis of hypoxic induction in several test
genes. The same series of cells lines were treated with hypoxia in
vitro, and Northern blot was used to determine hypoxic gene
regulation. Representative genes are shown for several of the
functional classes (GAPDH, glyceraldehye 3-phosphate dehydrogenase; G6PI, glucose 6-phosphate isomerase; GBE, glycogen
branching enzyme; VEGF, vascular endothelial growth factor;
PGF, placental growth factor; EphA1, ephrin A1; PLOD2, lysyl
hydroxylase 2; PAI-1, plasminogen activator inhibitor 1; TF, tissue
factor; IGFBP3, insulin-like growth factor binding protein 3;
BNIP3, 19 K interacting protein; DEC1, differentiated in
embryonic chondrocytes; BTG1, B-cell translocation breakpoint
gene)
Coordinated regulation suggests functional categories of
response
Based on the published function(s) of the various
hypoxia-responsive genes, we grouped the most robustly
Enholm et al. (1997), Shweiki et al.
(1992)
Plate et al. (1993)
Gleadle et al. (1995)
Mandriota and Pepper (1998)
Nakayama et al. (1998)
Kourembanas et al. (1993), Koong
et al. (2000)
This work
Melillo et al. (1995)
This work, Schmedtje et al. (1997)
Tenan et al. (2000), this work
This work
This work
Suzuma et al. (1998)
Pinsky et al. (1998)
Graham et al. (1998)
Koong et al. (2000)
Yan et al. (1998)
This work
Pim1, Pim-2
Bcl-w like
Bruick (2000)
Tazuke et al. (1998), Koong et al.
(2000)
This work
This work
Proliferation/differentiation
BTG1
Cyclin G2
DEC1/stra13
Adipophilin
p21 CDKI
This work
Wykoff et al. (2000)
Wykoff et al. (2000)
Saarikoski et al. (2002)
Denko et al. (2000b)
Gene expression
Early growth response 1
p35srj
ETS-1
Mxi-1
GRP78 GRP94 ORP150
Prolyl-4-hydroxylase
Yan et al. (1999)
Bhattacharya et al. (1999)
Oikawa et al. (2001)
This work
Ozawa et al. (2001), Roll et al.
(1991)
Epstein et al. (2001)
induced genes into functional categories. Table 1 is a
compilation of data from our lab as well as data from
the literature. The six largest functional groups are
shown and represent genes involved in metabolism/
Oncogene
Functions of hypoxia responsive genes
NC Denko et al
5912
transport, angiogenesis, tissue remodeling, apoptosis,
proliferation/differentitation and gene expression. In
addition to the five major categories, there are many
interesting genes that fall into smaller functional
categories such as mRNA processing (RNAse L,
CDC-like kinase 1, CCR4-associated protein), or genes
with unknown functions (HIG2, RTP, RAIG3,
TGFBind, VitDind68). Some genes, such as PAI-1,
can be placed in multiple categories of tissue remodeling
and angiogenesis.
Hypoxia and metastasis
The physiological demands of hypoxia and the response
to those demands in the various cell types result in
different gene expression patterns. For example, lysyl
hydroxylase (PLOD2, Figures 2 and 3) is normally
required for collagen maturation and is therefore
normally only expressed in fibroblasts (Wang et al.,
2000). However, under hypoxia, both primary and
transformed keratinocytes induce high levels of PLOD2
expression, while fibroblasts exhibit little change in their
PLOD2 mRNA levels. The same environmental signal
elicits two different responses in the two cell types.
While the reason for PLOD2 upregulation in hypoxic
epithelial cells is unclear, we hypothesize that it is related
to the wounding/re-epithelialization response of the
keratinocytes. The intimate interaction between stromal
and epithelial cells in the hypoxic solid tumor combines
to regulate PLOD2 expression and, presumably, collagen maturation. The alterations in the extracellular
matrix of hypoxic tumors could in turn contribute to
hypoxia-induced metastasis (Denko & Giaccia, 2001; De
Jaeger et al., 2001).
Furthermore, the hypoxic profiles of the untransformed cells are more closely related to each other than
to the tumor cells. For example, while tumor cells
exhibit a significant downregulation in the basal level of
PAI-1 expression (Figure 2), hypoxic upregulation is
found both in the untransformed cells and in the tumor
cells (Figures 2 and 3). Likewise, hypoxia can upregulate
another member of the plasmin pathway, urokinasetype plasminogen activator receptor, which has also
been implicated in metastasis (Postovit et al., 2002). The
induced response, irrespective of the transformed
phenotype, suggests that the physiological demands
upon the cells have a dominant effect on their expression
patterns. Thus, one can see how alteration of the
extracellular protease plasmin by PAI-1 by both
hypoxia and transformation could also combine to
contribute to hypoxia-induced metastasis (Denko and
Giaccia, 2001; De Jaeger et al., 2001).
Apoptotic response to hypoxia
P53 independent, hypoxia-induced apoptosis is thought
to rely upon the hypoxic upregulation of certain
proapoptotic genes, such as BH3-containing BNIP3
Oncogene
and BNIP3L (Bruick, 2000). While the kinetics of
BNIP3 induction correlate with apoptosis, there are
several characteristics of its expression pattern that still
need to be reconciled. For example, VHL-negative cells
are able to withstand constitutive expression of these
supposedly apoptogenic molecules (Sowter et al., 2001),
and normal fibroblasts can induce high levels of BNIP3
expression in the absence of apoptosis (Figures 2 and 3,
and data not shown). Normoxic expression of BNIP3/
BNIP3L in the VHL-negative tumor cells could lead to
the selection of cells with a second site mutation
somewhere downstream in the apoptotic signaling
pathway (Graeber et al., 1996).
Alternatively, it is possible that BNIP3/BNIP3L have
different functions under hypoxia from those reported in
transfection studies under normoxia (Chen et al.,
1999b). We could therefore gain new insight into the
function(s) of BNIP3/BNIP3L by this supposed discrepancy between hypoxic induction and apoptosis.
While BNIP3/BNIP3L induced by hypoxia could still be
targeted to the mitochondria just as the normoxic
experiments report (Chen et al., 1999b), their biochemical roles under hypoxia may be different. It is possible
that the mitochondrion has physiological pressures
under hypoxia that require BNIP3/BNIP3L expression,
and it is only under normoxic conditions that its
overexpression is apoptogenic.
Additional levels of regulation
Finally, there are genes that are induced by hypoxia in
some cell types, while they are repressed by hypoxia in
other cell types with unknown factors controlling this
regulation, such as ornithine decarboxylase (ODC) and
glucose-regulated protein 78 (GRP78). These examples
make it clear that the definition of a hypoxia-responsive
gene is cell-type dependent. There are also multiple
levels of gene regulation within the same family. For
example, lactate dehydrogenase isoform A (LDHA) is
strongly induced in all cell lines, while LDH B is
repressed in all the cell lines tested (Figure 2). Thus, we
have examples of added complexity to hypoxic gene
expression, multiple levels of control of hypoxic
response between cells of different origins and multiple
levels of control between members of a single gene
family.
Conclusions
We can infer that physiologic changes in the hypoxic
tumor drive gene expression changes, and these in turn
result in the different cellular effects within that tumor.
For example, low oxygen stimulates angiogenesis, and
the establishment of new vessels requires tissue remodeling. The genes involved in tissue remodeling may then be
part of the explanation as to why hypoxic tumors are
more likely to be locally invasive or distantly metastatic.
The expression changes in the lysine hydroxylase gene
Functions of hypoxia responsive genes
NC Denko et al
5913
PLOD2 in keratinocytes and tumor cells is an example
of how gene expression profiling can allow us to infer
new insights about tumor physiology in hypoxic tumors.
Keratinocytes are able to play an active role in collagen
maturation in the hypoxic solid tumor instead of the
fibroblast that is traditionally thought to serve this
function. The interaction between hypoxia, fibroblasts
and tumor cells in tissue remodeling represents a cellcontext-dependent regulation of gene expression to
result in a coordinated tissue response. Understanding
that tumor cells are an active participant in this process
may influence the development of targeted antimetastatic chemotherapeutics in the future.
Furthermore, we may learn how the biochemical
characterization of hypoxic gene products may also be
influenced by the cellular physiology. For example,
seeing that the potentially apoptogenic genes BNIP3
and BNIP3L are robustly induced in all hypoxic cells
regardless of their apoptotic potential makes one
question their role in hypoxia-induced apoptosis. The
targeting of BH3-only molecules to the mitochondria
may represent a survival response to impaired mitochondrial function under hypoxic conditions. The
function of the BH3 proteins may be very different in
this environmental context than under control conditions. We therefore need to design our functional assays
to take into account the conditions in which the gene
products are expressed.
Acknowledgements
This work was supported in part by Varian Biosynergy and
NIH Grant CA67166. LF was supported by a predoctoral
fellowship from Fondazione Italiana per la Ricerca sul
Cancero.
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