t
d
e
bring nutrients and oxygen, evade immune detection, and ulti-
mately metastasize to distal organs (Hanahan and Weinberg,
2000). Many of these phenotypic traits can be brought about
by genetic alterations that involve the gain-of-function muta-
tion, amplification, and/or overexpression of key oncogenes
together with the loss-of-function mutation, deletion, and/
or epigenetic silencing of key tumor suppressors (Hahn and
Weinberg, 2002).
Cancer cells achieve these phenotypes in large part by reac-
tivating and modifying many existing cellular programs nor-
mally used during development. These programs control coor-
dinated processes such as cell proliferation, migration, polarity,
apoptosis, and differentiation during embryogenesis and tis-
sue homeostasis. Consistent with Darwinian principles, cancer
evolves through random mutations and epigenetic changes
that alter these pathways followed by the clonal selection of
cells that can survive and proliferate under circumstances that
would normally be deleterious.
Although a number of oncogenes and tumor suppressors,
such as PI3K, Ras, p53, PTEN, Rb, and p16INK4a, are frequently
mutated in cancer cells, there also appears to be a large num-
ber of low-frequency changes that can contribute to onco-
genesis. Indeed, data from tumor sequencing projects reveal
somatic mutations in different cancer types such as breast and
colon cancers appear to be different. Although there is much
debate with regard to the statistical requirements needed to
distinguish likely driver from noncontributing passenger muta-
tions among the large collection of mutations in tumors, it is
clear that there is tremendous complexity and heterogeneity in
the patterns of mutations in tumors of different origins.
The complexity of alterations in cancer presents a daunting
problem with respect to treatment: how can we effectively treat
cancers arising from such varied perturbations? Cancer cells
have extensively rewired pathways for growth and survival that
underlie the malignant phenotype. Thus, a key to successful
therapy is the identification of critical, functional nodes in the
oncogenic network whose inhibition will result in system fail-
ure, that is, the cessation of the tumorigenic state by apop-
tosis, necrosis, senescence, or differentiation. Furthermore,
therapeutic agents attacking these nodes must display a suf-
ficiently large therapeutic window with which to kill tumor cells
while sparing normal cells. To borrow a term from yeast and
fly genetic analyses, the therapeutic agents must constitute
“synthetic lethality” with the cancer genotype/phenotype (Kae-
lin, 2005). In some cases, particular agents can display geno-
type-dependent lethality similar to synthetic lethality without
Leading Edge
Review
The Current State of Cancer Research
The past two decades have witnessed tremendous advances
in our understanding of the pathogenesis of cancer. It is now
clear that cancer arises through a multistep, mutagenic pro-
cess whereby cancer cells acquire a common set of properties
including unlimited proliferation potential, self-sufficiency in
growth signals, and resistance to antiproliferative and apop-
totic cues. Furthermore, tumors evolve to garner support
from surrounding stromal cells, attract new blood vessels to
Principles of Cancer Th
Oncogene and Non-on
Ji Luo,1 Nicole L. Solimini,1 and Stephen J. Elledge1,*
1Howard Hughes Medical Institute, Department of Genetics, Harvard
Brigham and Women’s Hospital, Boston, MA 02115, USA
*Correspondence: selledge@genetics.med.harvard.edu
DOI 10.1016/j.cell.2009.02.024
Cancer is a complex collection of distinct gene
we expand upon the classic hallmarks to inclu
describe a conceptual framework of how oncog
these hallmarks and how they can be exploited th
selectively kill cancer cells. In particular, we pres
that are essential for cancer cell survival and pr
the path ahead to therapeutic discovery and p
orthogonal cancer therapies.
an astounding diversity of mutations in tumors. In one study,
Stratton and colleagues estimate that individual mutations in
as many as 20% of all kinases can play an active role in tumori-
genesis (Greenman et al., 2007), although it remains to be seen
whether mutations in 20% of other gene classes will also drive
tumorigenesis. Large-scale sequencing of multiple cancers
has so far failed to identify new, high-frequency mutation tar-
gets in addition to those previously identified (Cancer Genome
Atlas Research Network, 2008; Ding et al., 2008; Jones et al.,
2008; Parsons et al., 2008; Sjoblom et al., 2006; Wood et al.,
2007). Rather, these studies found that every tumor harbors a
complex combination of low-frequency mutations thought to
drive the cancer phenotype. Furthermore, the repertoires of
erapy:
cogene Addiction
Medical School, Department of Medicine, Division of Genetics,
ic diseases united by common hallmarks. Here,
e the stress phenotypes of tumorigenesis. We
ene and non-oncogene addictions contribute to
rough stress sensitization and stress overload to
ent evidence for a large class of non-oncogenes
sent attractive drug targets. Finally, we discuss
rovide theoretical considerations for combining
Cell 136, March 6, 2009 ©2009 Elsevier Inc. 823
directly inhibiting a particular protein. The two mainstay treat-
ment options for cancer today—chemotherapy and radiation—
are examples of agents that exploit the enhanced sensitivity
of cancer cells to DNA damage. Despite all of our knowledge,
however, we still do not have a clear molecular understanding
of why these agents work to selectively kill tumor cells and,
conversely, why they eventually fail. The advent of “targeted”
therapies, which aim to attack the underlying oncogenic con-
text of tumors, provides more sophisticated examples of syn-
thetic lethality. When properly deployed, these therapies tend
to be more effective relative to chemotherapy and radiation.
Additional Hallmarks: The Stress Phenotypes of Cancer
Although there is no simple way to predict a priori which pro-
teins will act as nodal points to generate cancer drug targets,
solutions are likely to emerge from multiple sources, includ-
ing recent initiatives to understand cancer at the systems level.
From a genetic point of view, it is important to appreciate that
the plethora of mutations observed in the cancer genome must
ultimately result in a common set of hallmarks in order to bring
about the malignant phenotype. The goal of cancer therapy is,
therefore, to either reverse these properties or target them as
tumor-specific liabilities, preferably through the combinatorial
application of a relatively small number of drugs. Thus we need
a thorough understanding of the nature of these hallmarks.
In addition to the six hallmarks outlined in the seminal review
by Hanahan and Weinberg (Hanahan and Weinberg, 2000) that
collectively promote survival and proliferation in foreign envi-
ronments (Figure 1, top), as well as the hallmark of “evading
immune surveillance” proposed by Kroemer and colleagues
(Kroemer and Pouyssegur, 2008) (Figure 1, left), we propose
a number of additional, equally prevalent hallmarks of can-
cer cells based on recent analyses of cellular phenotypes.
Although these cancer phenotypes are not responsible for
We collectively refer to this subset as
the stress phenotypes of cancers. There
are often intricate functional interplays
among these shared hallmarks of tumor
cells, which are illustrated in Figure 1 and
discussed below. Although some of these stress phenotypes
are not unique to cancer cells and can be observed in other
conditions such as chronic inflammation, we propose that they
represent a common set of oncogenesis-associated cellular
stresses that cancer cells must tolerate through stress support
pathways. How these phenotypes arise is not well understood,
but targeting these hallmarks and their associated vulnerabili-
ties in a wide variety of cancers has shown promise for thera-
peutic intervention.
DNA Damage and DNA Replication Stress
Based on karyotypic and mutational analyses, it is clear
that tumors, especially solid tumors, pass through stages of
extreme genomic instability that result in the accumulation of
point mutations, deletions, complex chromosomal rearrange-
ments, and extensive aneuploidy (Hartwell and Kastan, 1994).
This level of instability is due in part to a constitutive level of
endogenous DNA damage, which results in activation of the
DNA damage stress response (DDR) pathway (Bartkova et al.,
2005; Gorgoulis et al., 2005). Elevated levels of DNA damage
observed in early stage tumors are thought to be due to sev-
eral factors. First, the shortening of telomeres due to replica-
tion in the absence of sufficient telomerase activity leads to
the appearance of double-strand breaks (DSBs) at telomeric
ends. The subsequent fusions of these deprotected ends initi-
ate breakage-fusion-bridge cycles that result in translocations
and gene amplification events (Maser and DePinho, 2002).
DSBs resulting from replication stress can also lead to break-
age-fusion-bridge cycles (Windle et al., 1991). Additionally,
oncogene activation in precancerous lesions has been shown
to increase DSBs and genomic instability (Halazonetis et al.,
Figure 1. The Hallmarks of Cancer
In addition to the six hallmarks originally proposed
by Hanahan and Weinberg (top half, white sym-
bols) and evasion of immune surveillance pro-
posed by Kroemer and Pouyssegur, we propose
a set of additional hallmarks that depict the stress
phenotypes of cancer cells (lower half, colored
symbols). These include metabolic stress, proteo-
toxic stress, mitotic stress, oxidative stress, and
DNA damage stress. Functional interplays among
these hallmarks promote the tumorigenic state and
suppress oncogenic stress. For example, the utili-
zation of glycolysis allows tumor cells to adapt to
hypoxia and acidify its microenvironment to evade
immune surveillance. Increased mitotic stress
promotes aneuploidy, which leads to proteotoxic
stress that requires compensation from the heat
shock response pathway. Elevated levels of reac-
tive oxygen species result in increased levels of
DNA damage that normally elicits senescence or
apoptosis but is overcome by tumor cells.
824 Cell 136, March 6, 2009 ©2009 Elsevier Inc.
initiating tumorigenesis, they are common characteristics of
many tumor types (Figure 1, bottom). Among these additional
hallmarks are DNA damage/replication stress, proteotoxic
stress, mitotic stress, metabolic stress, and oxidative stress.
2008), possibly through DNA hyper-replication (Bartkova et al.,
2006; Di Micco et al., 2006). Finally, mutation of genes involved
in either DNA repair programs (such as excision, crosslink, or
mismatch repair) or the DDR pathways (such as ATM and p53
signaling) can lead to increased DNA damage, inappropriate
cell-cycle progression, and genomic instability (Harper and
Elledge, 2007). In normal cells, DNA damage signals to halt
proliferation, induce cellular senescence, or elicit apoptosis.
Cancer cells have evolved to overcome the antiproliferative
effects of DNA damage, continuing to replicate in the presence
of damage (Figure 1).
Proteotoxic Stress
Tumors exhibit proteotoxic stress evidenced by their frequent
constitutive activation of the heat shock response. We think
this is due, in part, to the striking degree of aneuploidy (altered
chromosome number) often found in solid tumors (Figure 1)
(Ganem et al., 2007; Torres et al., 2008; Williams et al., 2008).
Aneuploidy and gene copy-number changes can alter the rela-
tive balance of growth and survival signals, thereby promot-
ing tumorigenesis. However, they also result in correspond-
ing increases and decreases in transcript levels (Pollack et
al., 2002; Torres et al., 2007; Tsafrir et al., 2006) that produce
imbalances in the stoichiometry of protein complex subunits
(Papp et al., 2003). These imbalances increase the amount of
toxic, unfolded protein aggregates in the cell and place addi-
tional burdens on the protein folding and degradation machin-
eries (Denoyelle et al., 2006). This proteotoxic stress is coun-
teracted, in part, by the heat shock response pathway, which
promotes the proper folding and/or proteolytic degradation of
proteins (Whitesell and Lindquist, 2005).
Mitotic Stress
A subset of tumors display increased rates of chromosome
mis-segregation, which is referred to as the CIN (chromosome
instability) phenotype (Komarova et al., 2002). This instability
results in a shifting chromosome distribution, thus allowing
tumor cells to rapidly evolve. In principle, CIN phenotypes can
result from defects in a variety of pathways involved in mitosis,
including defects in mitotic proteins that execute chromosome
segregation and defects in the spindle assembly checkpoint,
which coordinates anaphase entry with proper alignment of
chromosomes on the mitotic spindle (Cahill et al., 1998). In
addition, the CIN phenotype could result from the presence of
extra centrosomes in tumor cells or from stresses placed on
the mitotic apparatus due to the need to segregate supernu-
merary chromosomes (Ganem et al., 2007). Furthermore, CIN
and mitotic stress might arise indirectly as a result of DSBs
and genomic instability following oncogene activation, even in
lesions where the mitotic machinery is intact (Halazonetis et
al., 2008). Mutations in certain oncogenes, such as Ras, and
tumor suppressors, such as p53, have been suggested to con-
tribute to the CIN phenotype (Denko et al., 1994). However, the
precise cause of mitotic stress is not known for the vast major-
ity of tumors.
Metabolic Stress
Normal cells derive the bulk of their ATP through mitochondrial
oxidative phosphorylation. In what has been referred to as the
Warburg effect, most cancer cells are found to predominantly
produce energy by the less efficient method of glycolysis and
secrete a large amount of lactic acid, even under high oxygen
conditions (Warburg, 1956). Tumor cells exhibit dramatically
increased glucose uptake and highly elevated rates of glycoly-
sis (DeBerardinis et al., 2007). This provides the basis for tumor
imaging by positron emission tomography (PET) using the glu-
cose analog 18F-2-deoxyglucose. This transition to glycoly-
sis for energy production provides several advantages to the
tumor including adaptation to a low oxygen environment and
the acidification of the surrounding microenvironment, which
promotes tumor invasion and suppresses immune surveillance
(Figure 1).
Oxidative Stress
The defining characteristic of oxidative stress is the presence
of reactive oxygen species (ROS), and cancer cells typically
generate more ROS than normal cells (Szatrowski and Nathan,
1991). Both oncogenic signaling (Lee et al., 1999) and the
downregulation of mitochondrial function (Gogvadze et al.,
2008) in tumors can contribute to ROS generation. ROS are
highly reactive and likely to contribute to the increased levels
of endogenous DNA damage observed in cancer cells (Figure
1). In addition, ROS are important signaling mediators, and
their presence may contribute to transformation. For example,
ROS promote the activation of the transcription factor HIF-1
by hypoxia (Dewhirst et al., 2008), and HIF-1 can promote the
glycolytic switch and angiogenesis observed in tumors.
Attacking the Hallmarks of Cancer
Any therapy with the stated goal to treat and possibly cure can-
cer must show differential toxicity toward tumor cells relative
to normal cells. Implicit in this statement is that some unique
properties of cancer cells not shared by normal cells, such as
those depicted in Figure 1, must be exploited to the specific
detriment of cancer cells, i.e., the concept of synthetic lethal-
ity. In principle, cancer can be treated by inducing cancer cells
to undergo apoptosis, necrosis, senescence, or differentia-
tion. These changes can be brought about by disrupting can-
cer cell-autonomous processes, by interfering with autocrine/
paracrine signaling within tumors, or by blocking heterotypic
signaling between tumor cells and the surrounding stromal tis-
sue or blood vessels. Enhancing immune surveillance against
cancer cells expressing novel antigens is also an attractive
approach that has shown efficacy in specifically killing cancer
cells (Muller and Scherle, 2006).
Experiments aimed at either suppressing oncogene activ-
ity or restoring tumor suppressor function have revealed that
such intervention is highly deleterious to the cancer cell. The
heightened state of dependency of cancer cells on oncogenes
and the loss of tumor suppressors led to the terms “oncogene
addiction” (OA) and “tumor suppressor gene hypersensitivity”
(Weinstein, 2002; Weinstein and Joe, 2008). These alterations
are necessary for both the establishment and maintenance
of the oncogenic state and therefore are logical drug targets.
Indeed, much effort has been extended to pharmacologically
inhibit oncoproteins. What is thought to underlie the phenom-
enon of oncogene addiction is the observation that oncogenes
elicit strong, opposing prosurvival and proapoptotic signals in
cancer cells that favor growth and survival, and the acute inhi-
bition of oncogene function tilts this balance toward cell death
Cell 136, March 6, 2009 ©2009 Elsevier Inc. 825
(Downward, 2003; Sharma and Settleman, 2007).
To bring about their phenotypic manifestations, oncogenes
rely on extensive adaptations in cellular processes that are
themselves not oncogenic. In addition, cancer cells may also
Table 1. Cancer Therapies Targeting Various Hallmarks of Cancer
Agent Target Addiction Hallmarks Potential mechanisms References
17AAG
(small molecule)
HSP90 NOA A geldanamycin analog that binds to the
ATP-binding pocket of HSP90 and inhibits its
catalytic activity
Whitesell and
Lindquist, 2005
1MT, MTH-Trp
(small molecule)
IDO NOA Inhibits tryptophan catabolism in tumor mi-
croenvironment to allow T cell proliferation
Muller and Scherle,
2006
5-fluorouracil
(small molecule)
DNA NOA Inhibits pyrimidine metabolism, incorporation in
to DNA and RNA causes cell-cycle arrest
Longley et al., 2003
ABT-737, ABT-263
(small molecule)
BCL-XL, BCL-2 OA Bind to the BH3 pocket of Bcl-XL and inhibit its
antiapoptotic function
Stauffer, 2007
Alvocidib, PD 0332991
(small molecule)
CDKs OA Inhibit CDKs and induce cell-cycle arrest Lee and Sicinski,
2006
AP 12009
(antisense oligo)
TGFβ 2 NOA
Inhibits tumor autocrine and paracrine signal-
ing, reverses immune suppression in the tumor
microenvironment
Muller and Scherle,
2006
AZD2281, AG014699
(small molecule)
PARP1 NOA Inhibit base excision repair in homologous
recombination repair-deficient cancer cells
Bryant et al., 2005;
Farmer et al., 2005
Bevacizumab
(antibody)
VEGF NOA Inhibits endothelial cell recruitment and tumor
vasculature
Folkman, 2007
BEZ235
(small molecule)
PI3K OA
Causes cell-cycle arrest in tumor cells and
inhibits tumor angiogenesis
Maira et al., 2008
Bortezomib
(small molecule)
Proteasome NOA Inhibits the catalytic activity of 26S proteasome
and induces apoptosis
Roccaro et al.,
2006
Celecoxib
(small molecule)
COX2 NOA
Reverses immune suppression in the tumor
microenvironment, inhibits tumor autocrine and
paracrine signaling
Muller and Scherle,
2006
Cisplatin and analogs
(small molecule)
DNA NOA Induces DNA crosslinks Siddik, 2003
Erlotinib, Gefitinib
(small molecule)
EGFR OA
Inhibit EGFR tyrosine kinase by competing with
ATP binding
Sharma et al., 2007
GRN163L
(modified oligo)
hTERT OA Mimics telomere sequence and inhibits the
hTERT active site
Dikmen et al.,
2005; Harley, 2008
GRNVAC1
(cell therapy)
hTERT OA
Autologous dend