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癌治疗原理,癌基因与非癌基因

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癌治疗原理,癌基因与非癌基因 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, ampl...
癌治疗原理,癌基因与非癌基因
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
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