The biology of ovarian cancer: new opportunities for translation.

Inheritance of DNA repair defects contributes to as many as 10–15% of ovarian cancers 31 , 32 . The lifetime risk of developing ovarian cancer in mutation carriers varies with the genetic defect (for BRCA1 30–60%, for BRCA2 15–30% and for hereditary non-polyposis colon cancer 7%). In contrast to sporadic disease, BRCA-related familial ovarian cancers are more frequently multifocal, with genetically distinct clones involving multiple sites 33 , and progress faster, but are more sensitive to platinum-based chemotherapy 34 . BRCA1 and BRCA2 are required for reliable DNA double strand break repair by homologous recombination 35 , 36 . As in familial breast cancers, an inactivated allele is inherited by all cells, and loss of BRCA1 or BRCA2 function occurs in ovarian cancer cells through LOH of the normal allele. Cells lacking BRCA1 or BRCA2 repair DNA by error-prone mechanisms such as non-homologous end joining, leading to chromosomal rearrangements and genomic instability. Ovarian cancer cells with truncating mutations of BRCA1 or BRCA2 or with lower expression of these genes are less able to repair DNA damage induced by platinum compounds. Indeed, platinum chemoresistance can arise from mutations that restore the BRCA2 open reading frame and thus the cellular capacity for homologous recombination 37 , 38 . Similar to platinum drugs, poly(ADP-ribose) polymerase (PARP) inhibitors are particularly effective in the presence of defects in homologous recombination repair, and clinical trials with these agents are underway in ovarian cancer patients with inherited BRCA1 and BRCA2 mutations 39 , 40 . Although the BRCA1 and BRCA2 genes have been thought to be mutated only rarely in sporadic ovarian cancers, somatic mutations have recently been documented in approximately 10% of non-familial cases 41 , and expression of BRCA1 and BRCA2 can also be silenced by methylation in additional cancers 42 . Remarkably, the gene expression profiles in sporadic cases have been reported to fall into two categories that resemble the expression in cancers from patients carrying either BRCA1 or BRCA2 mutations, although this observation requires confirmation 43 . High-grade sporadic serous epithelial ovarian cancer might show dysfunction of the BRCA1 or BRCA2 pathway, contributing to sensitivity to platinum-containingtherapies. PARP inhibitors might also find broader clinical application in sporadic cancers in which these pathways are also defective.

Several growth inhibitory genes are silenced by methylation or imprinting in ovarian cancer including RASSF1 , deleted in lung and esophageal cancer 1 ( DLEC1 ) and opioid binding protein/cell adhesion molecule-like ( OPCML ) ( Table 2 ). Additional growth-inhibitory genes such as DLEC1 are directly or indirectly downregulated by histone deacetylation. A recently published abstract showed that the histone deacetylase inhibitor belinostat has clinical activity against borderline ovarian cancers that are generally refractory to chemotherapy 28 . Platinum resistance has been associated with CpG methylation of the MLH1 mismatch repair gene in relapsed invasive ovarian cancers and can be reversed with demethylating agents in preclinical models 29 . An initial report on a Phase II trial at M. D. Anderson Cancer Center showed that the combination of the demethylating agent azacytidine and carboplatin had clinical activity in 22% of 18 patients with platinum-resistant ovarian cancer 30 .

The fraction of cycling cells in different ovarian cancers varies over a wide range from 1% to 79% (Ref. 72 ). Upregulation of cyclin D1 or E1, E2F1 or cyclin-dependent kinases (CDK2), and downregulation of CDK inhibitors (p16, p21 and p27) have been observed in a fraction of ovarian cancers, and the levels of cyclins and CDKs correlate with prognosis 73 , 74 . In addition to intrinsic deregulation of checkpoints in the cell cycle, a range of autocrine and paracrine growth factors stimulate ovarian cancer proliferation, including EGF, transforming growth factor-α(TGFα), amphiregulin, heregulin, VEGFA, insulin-like growth factor 1 (IGF1), IL-6 and LPA. In normal ovarian surface epithelial cells, autocrine growth inhibition is maintained by TGFβ 75 . In approximately 40% of ovarian cancers, expression of or responsiveness to TGFβ is lost. Although mutation of SMAD4 is sometimes observed, TGF βRI and TGF βRII receptors are generally intact, as is Smad signalling downstream of the receptors. Loss of growth inhibition and increased invasiveness might relate to ecotropic viral integration site 1 ( EVI1 ) overexpression in 43% of ovarian cancers 76 . EVI1 inhibits transcription of TGFβ-responsive genes. Ski-like protein (SKIL) and runt-related transcription factor 1 (RUNX1), which bind to and regulate Smads, are also deregulated in ovarian cancer. Mullerian inhibition substance (MIS) is a homologue of TGFβ and binds to a TGFβ-like receptor, leading to regression of gynaecological precursors during the development of normal male embryos 77 . MIS also inhibits the growth of epithelial ovarian cancer cells by binding to MISII G protein-coupled receptors and upregulating p16, leading to cell cycle arrest in G1. MISII receptors have been detected in 56% of human ovarian cancers, and clonogenic growth can be inhibited with MIS in more than 80% of the cancers that express MISII receptors 78 . Recombinant MIS also increases the activity of cisplatin against ovarian cancer cell lines 79 . As sufficient quantities of MIS become available, clinical trials could be undertaken. Decreased sensitivity to apoptotic stimuli occurs in epithelial ovarian cancer. The pro-apoptotic receptor CD95 was detected in 85% of inclusion cysts, 94% of cystadenomas, 35% of borderline tumours and 4% of invasive cancers 80 . Thus, invasive ovarian cancers are likely to resist the apoptosis that is induced by exposure to CD95 ligand or agonistic anti-CD95 antibodies. When compared with normal ovaries, overexpression (4–10-fold) of the anti-apoptotic proteins BCL-2, BCL-X L (also known as BCL2L1) and survivin (also known as BIRC5) was observed in >70% of invasiveepithelial ovarian cancers 81 . The altered expression of apoptosis-regulating proteins has also been associated with poor outcomes (decreased BAX), platinum resistance (XIAP upregulation) and taxane resistance (BCL-2 and survivin overexpression) 82 , 83 , 84 . During autophagy, cellular organelles are enclosed and digested in double-walled autophagosomes, recycling amino acids and fatty acids and providing substrates for the generation of ATP. Autophagy can serve as a short-term survival mechanism that sustains cancer cells in an environment that is poor in nutrients, but prolonged autophagy can induce nonapoptotic cancer cell death. The development of breast cancers in beclin +/− mice with impaired autophagy supports the notion that autophagy can suppress cancer progression 85 . However, recent studies suggest that autophagy might be crucial for the maintenance of tumour dormancy. Expression of the imprinted tumour suppressor gene ARHI is decreased or lost in 60% of ovarian cancers. Re-expression of ARHI at physiological levels blocks growth, motility and angiogenesis, and also induces autophagy by inhibiting PI3K and downregulating mTOR activity 86 . In addition to triggering autophagy, ARHI participates directly in autophagosome formation by upregulating the ATG4 enzyme that processes the microtubule-associated protein LC3I to LC3II. Although ARHI re-expression caused autophagic death of ovarian cancer cells in culture within days, induction of ARHI in xenografts does not kill ovarian cancer cells, but instead induces tumour dormancy for a period of weeks 86 . Ovarian cancer xenografts rapidly resume growth when ARHI is downregulated. Treatment with chloroquine, an inhibitor of autophagy, substantially delays the outgrowth of xenografts, which is consistent with the possibility that autophagy is required for tumour cell survival. Cytokines (IGF1, IL-8 and VEGFA) and matrix proteins (fibronectin and collagen) that are found in the microenvironment of xenografts can rescue ovarian cancer cells from autophagic death in culture and reverse ARHI-induced inhibition of PI3K signalling. If autophagy is required for tumour dormancy and if this model is relevant to human ovarian cancer, strategies could be devised using siRNAs (to target beclin and ATG5) and small molecules (class III PI3K inhibitors) to prevent autophagy in dormant cancer cells. Alternatively, crucial growth factors (IL-8 and VEGFA) that sustain autophagic cancer cells or their receptors (IGF1R and VEGFR) could be targeted using antibodies or protein tyrosine kinase inhibitors. To metastasize, ovarian cancer cells must not only detach from neighbouring epithelial cells and adopt a mesenchymal phenotype, but they must also acquire the ability to move and invade stroma, vessels and the walls of the cysts in which they arise. Signals regulating motility and invasion are transduced through the Ras–Mapk, PI3K–Akt–p70S6K and STAT3 signalling pathways. A range of ligands activate these pathways, including VEGFA, EGF, heregulin, hepatocyte growth factor, macrophage colony-stimulating factor, TGFβ, bone morphogenetic protein 4, TNFα and LPA 87 , 88 . LPA is frequently detectable in serum and ascites, and also induces the secretion of VEGFA, IL-6, IL-8 and GRO1 by ovarian cancer cells 89 . Interestingly, stress hormones, including adrenaline, noradrenaline and cortisol, have also recently been shown to upregulate matrix metalloproteinase 2 (MMP2) and MMP9 in ovarian cancer cells, thereby increasing invasion 90 . These experiments have provided one of the first physiological mechanisms by which psychological stress might influence tumour progression. Directed motion of cancer cells and invasion can also be stimulated by the binding of cancer-associated integrins to the extracellular matrix. Clustering of collagen-binding integrins during the adhesion of ovarian cancer cells to collagen activates the Src family kinases to induce expression of early growth response 1 ( EGR1 ), resulting in transcriptional activation of the MMP14 promoter and subsequent collagen invasion catalysed by MMP14 (Ref. 91 ). Laminin, collagen and fibronectin can all increase chemotactic activity, whereas increased invasion is observed only with laminin and collagen. α3, α6 and β1 integrin-mediated signalling through Ras–Mapk, Erk and Akt regulate both processes. Effector proteases, which are crucial for invasion, have been detected in ovarian cancer cells and in stromal components. MMP2, MMP7, MMP9, urokinase plasminogen activator and the kallikreins are found in ovarian cancer cells in culture and in surgical specimens 92 . Twelve of the fifteen human kallikreins are transcriptionally upregulated in ovarian cancer. Kallikreins degrade matrix components, including fibronectin, vitronectin, laminin and collagens I, II, III and IV, thereby increasing ovarian cancer cell invasiveness 93 . They are therefore being evaluated as biomarkers for early detection or prognosis in ovarian cancer 94 . Metastasis to the peritoneal surface requires the adhesion of ovarian cancer cells to the mesothelial cells that line the cavity and to the underlying stroma. Adhesion is mediated by β integrins, CD44 and CA125 (Ref. 95 ) on the surface of ovarian cancer cells that bind to mesothelin and hyaluronic acid on mesothelial cells, or to fibronectin, laminin and type IV collagen in the underlying matrix. CA125 is a high molecular mass (1 MDa) glycosylated transmembrane mucin that is expressed by 80% of ovarian cancers 95 . The N-glycans of CA125 bind to mesothelin and might be the initial point of contact between ovarian cancer cells and the peritoneal surface 96 . Mesothelin-specific antibodies block the adhesion of ovarian cancer cells to mesothelial cells 97 . In addition, knockdown of CA125 decreases the invasion of ovarian cancers, consistent with active signalling by the intracellular domain of the mucin. Both CA125 and mesothelin are shed into body fluids and are being evaluated as serum biomarkers for the monitoring and early diagnosis of ovarian cancer ( Box 1 ). CD44–hyaluronic acid and β1 integrin–fibronectin, laminin and type IV collagen interactions might also contribute to peritoneal metastases. More than 70% of ovarian cancers show a diverse mixture of CD44 splice variants that can bind to hyaluronic acid 98 . CD44-specific antibodies can partially block adhesion of ovarian cancer cells to peritoneal mesothelial cells 99 . Thus, motility, adhesion and invasion might be inhibited using antibodies (LPA-, CA125-, CD44- and mesothelin-specific) and small molecule inhibitors (adrenergic receptors and proteases). Even after diagnosis and primary treatment, continued metastasis in the peritoneal cavity occurs during the progression of drug-resistant disease, ultimately producing intestinal obstruction. However, given dramatic differences in the rate of intra-abdominal progression from patient to patient, as well as the availability of multiple conventional drugs to treat recurrent disease, the design of appropriate clinical trials to test these strategies is problematic. As is the case in other cancers, tumour vessels must be recruited if ovarian cancers and their metastases are to grow to more than 2 mm 3 . Microvessel density correlates with the propensity of ovarian cancers to metastasize and with disease-free survival 100 . VEGFA, LPA, IL-6, IL-8, fibroblast growth factor 2 (FGF2) and FGF1 all contribute to angiogenesis in ovarian cancer 100 , 101 . Treatment with bevacizumab, a VEGFA-specific antibody, induced an objective response rate in 16% of patients with recurrent ovarian cancer and stabilized disease for 5.5 months in 50% of patients 102 . In general, anti-angiogenic therapy has been well tolerated, although hypertension has been observed in approximately one-third of the women treated and bowel perforation has occurred in approximately 5% of cases. In combination with cytotoxic chemotherapy, improved response rates have been reported in platinum-resistant disease. Daily metronomic chemotherapy with agents such as cyclophosphamide can take advantage of the differences in the proliferative rates of tumour-associated and normal endothelial cells 103 . New methods for inhibiting VEGFA activity are also being explored; for example, VEGF Trap 104 . Overexpression of the ephrin type A receptor 2 (EPHA2) in tumour cells or endothelial cells has been observed in >75% of ovarian cancers and is associated with increased microvascular density and increased expression of MMP2, MMP9 and MMP14 (Ref. 105 ). Xenograft growth can be inhibited by agonistic antibodies against EPHA2 (Ref. 106 ) or by the delivery of EPHA2 siRNA in neutral liposomes 107 . Pericytes contribute to the maintenance of endothelial cells 108 and secrete VEGFA to promote endothelial survival. Their survival, in turn, depends on platelet-derived growth factor (PDGF) produced by endothelial cells. Both endothelial cells and pericytes could thus be targeted by the simultaneous inhibition of VEGFA and PDGF 101 . Trials are planned at the M. D. Anderson Cancer Center to exploit this mechanism for the treatment of ovarian cancer. In addition to tumour vessels, ovarian cancers recruit a stroma that contains fibroblasts, lymphocytes and inflammatory cells. Haematopoietic mesenchymal stem cells have been shown to home to ovarian cancer xenografts and differentiate into fibroblasts, contributing to microvascularization, stromal networks and production of tumour-stimulating cytokines (for example, IL-6) 134 . Once recruited, fibroblasts can also be affected by the tumour microenvironment. Ovarian surface epithelial cells that have been immortalized by Ras produce GRO1, which induces the senescence of stromal fibroblasts that produce factors that increase ovarian cancer growth 109 . Lymphocytes and macrophages infiltrate ovarian tumours and are found in ascites in addition to a wide range of cytokines and chemokines 110 . T cells are most prevalent in solid tumour nodules, and their presence is associated with a 5-year survival rate of 38% compared with 4.5% for patients who have tumours that lack T cell infiltrates 111 , 112 . A high ratio of CD8 + to regulatory T cells is also associated with an improved prognosis 112 . Interferons produced by activated T cells can inhibit tumour growth and IL-8 secretion, block angiogenesis and upregulate major histocompatibility complex expression, which increases immune recognition. Macrophage colony-stimulating factor and macrophage chemotactic protein 1 secreted by ovarian cancer cells and by T cells are potent chemoattractants for macrophages. Activated macrophages can produce proteins that stimulate (IL-1, IL-6 and TNFα) or inhibit (nitric oxide and TNFα) tumour growth. However, tumour-associated macrophages have impaired phagocytic activity and decreased effector function for antibody-dependent cell-mediated cytotoxicity. The C–X–C chemokine receptor CXCR4 is expressed in 59% of ovarian cancers and is associated with decreased disease-free and overall survival duration; its ligand CXCL12 is found in 91% of ovarian cancers 113 , 114 , 115 . Inhibition of CXCR4 inhibits intraperitoneal dissemination of ovarian cancer xenografts 116 . Clinical trials should become feasible with the development of potent orally available CXCR4 inhibitors. Approximately 80% of ovarian cancers express TNFα (which is regulated both translationally and transcriptionally through NF-κB), in addition to TNFRI and TNFRII receptors that allow both autocrine and paracrine stimulation 117 . TNFα can stimulate clonal growth, and TNFα knockdown inhibits growth and dissemination in ovarian cancer xenografts 118 . Clinical trials have therefore been undertaken with a TNFα-specific antibody for ovarian cancer 119 .

The function of imprinted tumour suppressor genes can also be lost in a single step. Approximately 70 human genes are known to be imprinted: only one allele is expressed in each cell of the embryo and adult and silencing of the maternal or paternal allele is inherited despite a normal nucleotide sequence. Of the 16 candidate tumour suppressor genes identified to date in ovarian cancer, 3 are known to be imprinted: ARHI (also known as DIRAS3 ), pleiomorphic adenoma gene-like 1 ( PLAGL1 , also known as LOT1 ) and paternally expressed 3 ( PEG3 ). All three genes are downregulated in a substantial fraction of ovarian cancers. ARHI encodes a 26 kDa GTPase that shares homologywith Ras, but has a distinctive 34 amino acid amino-terminal extension that mediates its tumour-suppressive effect. The functional allele of ARHI is downregulated in >60% of ovarian cancers owing to LOH (30%), promoter hypermethylation (10%), transcriptional regulation (>20%) or decreased mRNA half-life 24 . Expression of ARHI is associated with prolonged progression-free survival. Re-expression of ARHI inhibits proliferation, motility and angiogenesis, and induces autophagy (see below). PLAGL1 encodes a 55 kDa zinc-finger protein that is downregulated in 39% of ovarian cancers through LOH and transcriptional regulation 25 . Re-expression of PLAGL1 inhibits proliferation in culture and tumour formation in xenografts. PEG3 encodes a 140 kDa Krüppel-type zinc-finger protein that is downregulated in 75% of ovarian cancers by LOH (20%), promoter methylation (26%) and, in all probability, transcriptional regulation 26 . Re-expression of PEG3 inhibits growth and induces apoptosis through translocation of BAX downstream of p53. However, the persistence of PEG3 expression does not improve prognosis. Treatment with demethylating agents and histone deacetylase inhibitors has induced expression of ARHI and PEG3 in ovarian cancer cell lines after treatment, correlating with growth inhibition 27 . Consequently, increased expression of imprinted and silenced genes might prove useful as a biomarker for monitoring epigenetic therapy.

At least 15 oncogenes have been implicated in ovarian cancers ( Table 3 ) 11 , and 11 of these oncogenes show genomic amplification 11 , 44 . DNA copy number abnormalities have also been found in 37% of 283 loci that are known to contain non-coding microRNAs 45 . In contrast to copy number anomalies, activating mutations in oncogenes are uncommon in the most frequently occurringhistotypes. KRAS is mutated in >20% of the less common low-grade (type I) cancers, but KRAS mutations are rare in the more numerous high-grade (type II) lesions 132 ( Box 3 ). PI3K catalytic subunit-α ( PIK3CA ) mutations occur commonly only in the small subset of endometrioid and clear-cell ovarian cancers. Thus, ovarian cancer can be split into two groups: low-grade tumours with mutations in KRAS , BRAF and PIK3CA , LOH on Xq, microsatellite instability 46 and expression of amphiregulin; and high-grade tumours with aberrations in TP53 and potential aberrations in BRCA1 and BRCA2 , as well as LOH on 7q and 9p 47 , 48 . Type I ovarian cancers constitute a minority of epithelial lesions and include low-grade and borderline serous cancers, endometrioid, mucinous and clear-cell cancers 132 . This group has more frequent PTEN , PI3K catalytic subunit-α ( PIK3CA ), KRAS, BRAF and b-catenin ( CTNNB1 ) mutations, along with genomic stability and TP53 mutations in only a small fraction of cases. Type II ovarian cancers constitute most epithelial ovarian cancers and include high-grade serous cancers, mixed malignant mesodermal tumours, carcinosarcomas and undifferentiated cancers 132 . These tumours have TP53 mutations in up to 80% of cases, along with marked genomic instability. Type II cancers arise more frequently from the fallopian tubes and the peritoneum. Ovarian cancers that arise in women with inherited BRCA1 and BRCA2 mutations are usually type II tumours. Type Histology Precursor Molecular features I Low-grade serous carcinoma Cystadenoma–borderline tumour–carcinoma sequence Mutations in KRAS and/or BRAF (≥ 60%) I Low-grade endometrioid carcinoma Endometriosis and endometrial cell-like hyperplasia * Mutations in CTNNB1 , PTEN and PIK3CA with microsatellite instability I Mucinous carcinoma Cystadenoma–borderline tumour–carcinoma sequence; metastases from bowel Mutations in KRAS; TP53 mutation associated with transition from borderline tumour to carcinoma I Clear cell carcinoma Endometriosis PTEN mutation or loss of heterozygosity; PIK3CA mutation ‡ II High-grade serous carcinoma De novo in epithelial inclusion cysts; fallopian tube TP53 mutation (up to 80%) and BRCA1 dysfunction II High-grade endometrioid carcinoma Epithelial inclusion glands or cysts TP53 mutation and BRCA1 dysfunction; PIK3CA mutation * Endometriosis and adjacent low-grade endometrioid carcinoma share common genetic events such as loss of heterozygosity at the same loci involving the same allele (for example, PTEN ). By contrast, high-grade and poorly differentiated endometrioid carcinomas are similar to high-grade serous carcinomas. ‡ PIK3CA at 3q26 encodes the p110α catalytic subunit of PI3K 19 . Endometriosis and adjacent low-grade endometrioid carcinoma share common genetic events such as loss of heterozygosity at the same loci involving the same allele (for example, PTEN ). By contrast, high-grade and poorly differentiated endometrioid carcinomas are similar to high-grade serous carcinomas. PIK3CA at 3q26 encodes the p110α catalytic subunit of PI3K 19 . Well-differentiated tumours with a low histological grade are associated with a better prognosis than are high-grade neoplasms, despite the resistance of low histological grade tumours to chemotherapy. At least a fraction of low-grade serous cancers seem to arise from LMP tumours. Karyotypically, LMP tumours are generally diploid 49 and have few DNA copy number changes. Expression of the oestrogen receptor is found more frequently in LMP and low-grade ovarian cancers, suggesting that hormonal manipulation might be effective for controlling the growth of these neoplasms 50 . Ovarian surface epithelial cells immortalized with human telomerase reverse transcriptase and SV40 t antigen have been transformed with mutant HRAS or KRAS , and lead to cells that grow slowly but progressively as xenografts with serous papillary histology in the peritoneal cavity of nude mice 51 . Gene expression profile analysis of the transformed cells showed the increased expression of several cytokines, including interleukin 1 (IL-1), IL-6 and IL-8, which are upregulated by the NF-κB pathway 51 . Each of these molecules might provide targets for therapeutic intervention in type I cancers with Ras mutations. The small G-protein RAB25 is amplified and upregulated in most ovarian cancers and regulates motility, aggressiveness, apoptosis and autophagy 52 . RAB25 also mediates survival in response to stress, such as that induced by chemotherapy, ultraviolet radiation, serum depletion and glucose starvation. Delivery of specific small-interfering RNAs (siRNAs) could allow targeting of RAB25. Several other amplified oncogenes are potential targets for ovarian cancer therapy. Small molecule inhibitors of Aurora kinases are currently being evaluated in several cancers 53 . Antibodies that inhibit NOTCH3 or its ligands are being developed 54 . New gold compounds have been shown to target the N-terminal PHOX-BEM1 domain of PKC ι that is required for PKC ι-driven transformation.

At least seven signalling pathways are activated in >50% of ovarian cancers ( Box 4 ). New screening small-interfering (siRNA) libraries have been used to identify targets such as Src and Akt that increase the cytotoxicity of paclitaxel in ovarian cancer cells. Phase II clinical trials of the Src inhibitor dasatinib have been initiated. Although small molecule inhibitors can be developed for intracellular targets and antibodies can be developed for the inhibition of cell surface receptors, growth factors and cytokines, the therapeutic use of siRNA promises to provide more rapid translation of this approach to the clinical setting. Recent studies have shown that the intravenous injection of siRNA in neutral liposomes can deliver adequate amounts of siRNA to inhibit the growth of intraperitoneal xenografts 104 . New technologies are being introduced that allow the simultaneous measurement of multiple signalling pathways. Gene expression analysis has identified ovarian cancer signatures that predict optimal cytoreductive surgery, poor overall survival and chemoresistance, although the predictive values of these signatures have not been sufficient to affect patient management. Recently, gene expression profiles have also been reported that identify the activation of particular signalling pathways (see the table) and responsiveness to targeted therapies. New reverse-phase protein lysate arrays can measure the simultaneous activation of multiple signalling pathways, thus allowing a more accurate definition of signalling heterogeneity and prediction of responsiveness to targeted therapies. Signalling pathway Percentage of cancers in which activation is observed PI3K 70% Src >50% IL-6–IL-6R; Jak–STAT3 70% LPA 90% MEKK3–IKK–NK-κB >50% Mullerian inhibitory substance receptor >50% PKCι 78% Ras–Mek–Mapk * <50% (activated in most low-grade type I cancers) * As Ras mutations are only common in low-grade ovarian cancers, Ras and Mek inhibitors are likely to be most efficacious in low-grade tumours, IKK, inhibitor of nuclear factor-κB kinase; IL-6, interleukin 6; IL-6R, IL-6 receptor; Jak, Janus kinase; LPA, lysophosphatidic acid; NK-κB, nuclear factor-κB; PKCι, protein kinase Cι; STAT3, signal transducer and activator of transcription 3. As Ras mutations are only common in low-grade ovarian cancers, Ras and Mek inhibitors are likely to be most efficacious in low-grade tumours, IKK, inhibitor of nuclear factor-κB kinase; IL-6, interleukin 6; IL-6R, IL-6 receptor; Jak, Janus kinase; LPA, lysophosphatidic acid; NK-κB, nuclear factor-κB; PKCι, protein kinase Cι; STAT3, signal transducer and activator of transcription 3. Epidermal growth factor receptor (EGFR) mutations are rare in ovarian cancer, and the receptor is not markedly overexpressed. Gefitinib and erlotinib, which are inhibitors of EGFR, stabilized disease in 11–44% of patients with ovarian cancer but produced objective regression in only 4–6% of cases 55 , 56 . As shown in colorectal cancers, activation of the Ras–Mapk signalling pathway might also minimize the effect of EGFR inhibitors 57 . ERBB2 (also known as HER2 ) is not frequently amplified and is overexpressed in only 11% of ovarian cancers 58 . Objective responses were observed in only 7% of 41 patients with ovarian cancer that overexpressed ERBB2 who were treated with trastuzumab, and only 1 complete response and 2 partial responses were observed 58 . The PI3K pathway is activated in approximately 70% of ovarian cancers, and activation of this pathway is associated with resistance to cytotoxic chemotherapy. Activation of the PI3K pathway can be driven by gene amplification ( PIK3CA and AKT2 ), activating mutations ( PIK3CA ) or inactivating mutations ( PTEN ), but in many cancers the pathway is activated by autocrine or paracrine signalling through protein tyrosine kinase growth factor receptors. Inhibitors of PI3K and Akt prevent the growth of ovarian cancer xenografts and potentiate the cytotoxic effects of paclitaxel and cisplatin 59 . Perifosine inhibits Akt, and an ovarian cancer clinical trial is currently underway at M. D. Anderson Cancer Center combining perifosine with docetaxel. More specific Akt inhibitors are being developed and PI3K inhibitors are entering Phase I–II trials 60 . IL-6 is overexpressed in most ovarian cancers, providing autocrine stimulation of the IL-6 receptor, which activates Janus kinase 2 (JAK2), facilitating phosphorylation and nuclear translocation of the signal transducer and activator of transcription 3 (STAT3), which upregulates genes that stimulate proliferation, inhibit apoptosis and induce angiogenesis. Nuclear localization of activated phosphorylated STAT3 occurs in more than 70% of ovarian cancers and is associated with decreased overall survival 61 . Activated STAT3 also translocates to focal adhesion complexes and stimulates motility in combination with SRC. In addition to antibodies against IL-6 and inhibitors of JAK2 (Refs 62 , 63 ), new inhibitors of STAT3 are being developed that might be used to target most ovarian cancers 64 . Lysophosphatidic acid (LPA) is produced by the phosphodiesterase autotoxin (ATX; also known as lysophospholipase D). The G protein-linked LPA receptors LPAR2 and LPAR3 are upregulated during the malignant transformation of ovarian surface epithelial cells. LPAR3 responds to LPAs with unsaturated fatty acyl chains that are produced by ovarian cancers. Interestingly, cyclic phosphatidic acid blocks ATX, reducing LPA levels and metastasis, but not the growth of primary cancers 65 . LPA-neutralizing antibodies have been developed, and LPA receptor inhibitors are being sought that might block the proliferation of ovarian cancer cells 66 . The NF-κB transcription factor is constitutively activated in more than half of ovarian cancers 67 , 68 through signalling initiated by several cytokines (IL-1 and TNFα) and growth factors (EGF). Inactive NF-κB is complexed with inhibitor of NF κB (IκB) and is generally activated by the IκB kinase (IKK) complex, which contains two kinase subunits (IKKα and IKKβ) and a regulatory subunit (IKKγ) 69 . MEKK3 is one of several kinases that can activate the IKK complex 70 , 71 and is overexpressed in >50% of ovarian cancers. The resultant activation of NF-κB upregulates anti-apoptotic genes (for example, CFLAR ), antioxidant proteins (superoxide dismutase or ferritin heavy chain), growth regulatory cytokines (IL-6 or growth regulated-α (GRO1)) and angiogenic factors (IL-8) 71 . Selective inhibition of NF-κB has been difficult to achieve, but gene therapy with adenoviral E1A reduces NF-κB signalling and increases sensitivity to paclitaxel in xenograft models, which has prompted a clinical trial at the University of Texas M. D. Anderson Cancer Center of liposomal E1A in combination with paclitaxel in patients with intra-abdominal recurrence of ovarian cancer.

Given the large number of potential targets in ovarian cancer, an immediate challenge is to identify promising candidates for which inhibition would provide synthetic lethality using conventional drugs or other targeted therapies ( Box 4 ). A crucial goal is to identify patients who would benefit from particular targeted therapies. Given the complexity of crosstalk between protein signalling pathways, predicting the impact and efficacy of any one signalling inhibitor is difficult. Individual inhibitors produce only modest xenograft growth inhibition. Thus, inhibition of multiple pathways will almost certainly be required to substantially affect ovarian cancer growth. With many new targets and more than 400 potential drugs in the pharmaceutical pipeline, the clinical evaluation of new agents individually, and particularly in combination, is likely to limit the rate of progress. Participation of more ovarian cancer patients, enrichment of Phase I–II trials with cancers that express relevant targets, more efficient Bayesian trial design, use of surrogate biomarkers such as CA125 for response 120 , and studying tissues and imaging to determine whether drugs are 'hitting the target' will contribute to accelerating progress in early clinical trials. As new agents become available, future trials should focus on inhibitors of the molecules (Src, MIS, RAB25 and PKCι) and signalling pathways (PI3K, IL-6–JAK2–STAT3, LPA and NF-κB) that are most frequently activated or overexpressed in ovarian cancers. Targeted therapy should be accelerated by the delivery of siRNAs, which have been shown to be effective in xenograft models of ovarian cancer and are moving towards clinical trials. Greater emphasis should be placed on targeting the interactions of cancer cells with stromal components. In addition to VEGFA, anti-angiogenic therapy could be directed towards other relevant factors (IL-8, PDGF, FGF1, FGF2 and LPA), receptors (EPHA2, PDGFR and FGFR) and cells (pericytes) in combination with metronomic dosing of cytotoxic drugs. If animal models prove to be relevant to the clinic, dormant ovarian cancer cells might be eliminated by targeting autophagy (chloroquine and siRNA) or survival factors (VEGFA, IGF and IL-8) that are required to prevent autophagic death in cancer cells that still express ARHI. Ultimately, we must improve our ability to predict response in the clinic and to identify patients who are most likely to benefit from particular combinations of drugs. Given the heterogeneity of ovarian cancer at a molecular level, if we are to match the abnormalities present in an ovarian cancer to appropriate therapy, extensive characterization of every cancer specimen must be carried out using DNA sequencing of all relevant genes, high-resolution comparative genomic hybridization, single nucleotide polymorphism analysis, expression arrays, reverse-phase protein arrays and immunohistochemistry of selected biomarkers. As a greater rate of response to targeted therapy might be seen when signalling pathways are activated by genetic events, integrating mutation data from the Cancer Genome Atlas Project and DNA copy number with other 'omics' data should be particularly relevant for defining subsets of patients for therapy. Biopsy samples of fresh ovarian cancer tissue will be required from all patients before Phase I and II trials. Logistically, this is a particular challenge in recurrent ovarian cancer in which much of the disease is often localized in the abdominal cavity. The reward of more effective, potentially less toxic, individualized targeted therapy provides a substantial incentive to design and execute such trials. Currently available biomarkers (p53 and KRAS) support the treatment of low-grade serous and non-serous type I and high-grade serous and endometrioid type II ovarian cancers with different agents. Reverse-phase protein array analysis suggests that distinct subsets of patients might benefit from either a combination of PI3K and MAPK inhibitors, a combination of KIT and cyclin E2 inhibitors, hormonal therapy or antiangiogenic approaches. A multi-arm trial is under development to determine the value of predictive tests for assigning patients to each of these treatment groups. As clinical trials mature with PI3K pathway inhibitors, the response in ovarian cancers with gene amplifications ( PIK3CA and AKT2 ) or mutation ( PIK3CA and PTEN ) of pathway components can be compared with cancers in which PI3K activation is driven by autocrine or paracrine stimulation. If mutations are important drivers for cancer cell proliferation and survival, we anticipate that type I ovarian cancers will show a higher response rate than type II cancers to inhibitors of the PI3K–Akt and Ras–Mapk pathways. In the long term, earlier detection of ovarian cancer is likely to have an important effect on the management of this disease. In the next 3 years, the results of a trial involving 200,000 subjects in the United Kingdom will establish whether measuring increasing CA125 levels followed by transvaginal ultrasound will detect sufficient numbers of patients with early-stage disease to affect survival 121 . Regardless of the outcome, it is likely that multiple marker panels will be required to detect >90% of patients with preclinical or early-stage disease. Understanding the heterogeneity of different ovarian cancers at a molecular level has facilitated the development of candidate panels of markers.

Multiple genetic and epigenetic abnormalities have been detected in ovarian cancers from different individuals 11 ( Table 1 ). Activation of genes occurs through amplification, mutation and hypomethylation, whereas genetic inactivation results from deletion of large chromosomal regions, more limited loss of heterozygosity (LOH) at particular loci and promoter methylation. Evidence for genetic instability is provided by the observation of multiple changes using comparative genomic hybridization, particularly in cancers that have a high histological grade and are of a late stage 12 Only 10–15% of ovarian cancers are associated with germline mutations of BRCA1, BRCA2 or the heritable non-polyposis colorectal cancer mismatch repair genes, loss of which predisposes to transformation and genetic instability 13 . The source of much genetic damage remains uncertain. Chemical carcinogens with mutagenic potential have generally not been linked to ovarian cancer risk, although exposure to the chronic inflammation produced by talc has been cited as a risk factor in some studies 14 , 15 . Consistent with an absence of strong exogenous chemical carcinogens, the pattern of TP53 mutations in sporadic ovarian cancers is most consistent with spontaneous mutations that occur during cell proliferation 16 . Epithelial cells covering the ovary are generally quiescent and have a low proliferative index. Following the rupture of mature follicles to release oocytes, epithelial cells proliferate to repair damage to the ovarian surface. Ovulation is also crucial to the development of epithelial cell-lined subsurface inclusion cysts from which a substantial fraction of ovarian cancers develop. Epidemiological factors that increase the number of ovulatory cycles — early onset of menses, late menopause and infertility — increase the risk of ovarian cancer, whereas factors that decrease ovulation — multiple pregnancies, prolonged lactation and use of oral contraceptives — decrease the risk of ovarian cancer in later life. After menopause, proliferation of ovarian epithelial cells could be driven by increased levels of follicle-stimulating hormone, luteinizing hormone, oestrone and androgen. Given the low rates of spontaneous mutation, it is not surprising that few oncogenes are activated by mutation and several of the most frequently affected tumour suppressor genes are either haploinsufficient or are imprinted genes and are therefore heterozygous and subject to LOH.