The epidermal growth factor receptor is overexpressed in up to 60% of ovarian epithelial malignancies. EGFR regulates complex cellular events due to the large number of ligands, dimerization partners, and diverse signaling pathways engaged. In ovarian cancer, EGFR activation is associated with increased malignant tumor phenotype and poorer patient outcome. However, unlike some other EGFR-positive solid tumors, treatment of ovarian tumors with anti-EGFR agents has induced minimal response. While the amount of information regarding EGFR-mediated signaling is considerable, current data provides little insight for the lack of efficacy of anti-EGFR agents in ovarian cancer. More comprehensive, systematic, and well-defined approaches are needed to dissect the roles that EGFR plays in the complex signaling processes in ovarian cancer as well as to identify biomarkers that can accurately predict sensitivity toward EGFR-targeted therapeutic agents. This new knowledge could facilitate the development of rational combinatorial therapies to sensitize tumor cells toward EGFR-targeted therapies.
Epithelial ovarian cancer, defined as cancers arising either from the mesothelial lining of the ovaries (either from the epithelial surface lining or cortical ovarian cysts formed by invaginations of the surface epithelium) or from the fallopian tube epithelium [
The EGFR family (also known as the HER or ERBB family) consists of 4 members: EGFR, HER2, HER3, and HER4 (alternately known as ERBB1–4). Structurally, the EGFR family consists of an extracellular ligand binding domain, a single transmembrane-spanning region, and an intracellular region containing the kinase domain (Figure
Structure of EGFR. EGFR consists of extracellular, transmembrane, and intracellular domains. The extracellular domain is the least conserved domain among the EGFR family members and consists of 4 subdomains—two ligand-binding domains and two receptor dimerization domains, which are cysteine-rich (reviewed in [
EGFR is activated upon ligand binding, which results in a conformational change in the extracellular domain, leading to homo- or heterodimerization with another EGFR family member. The EGFR binding partner appears to depend on several properties, including the proportion of EGFR family members in the membrane, type and proportion of ligand (reviewed in [
Activation of the EGFR family members results in transduction of EGFR signals, via intracellular cascades, such as mitogen-activated protein kinases (MAPKs), and AKT (also known as protein kinase B), resulting in perturbation of multiple cellular responses including proliferation, differentiation, cell motility, and survival (reviewed in [
Selected representation of canonical EGFR family signaling pathways. The EGFR family consists of 4 members: EGFR, HER2, HER3, and HER4 (indicated by numbers 1–4 in the diagram). EGFR family ligands include EGF-and EGF-like ligands, transforming growth factor (TGF)-
The EGFR family members can also be activated by other signaling proteins independent of addition of exogenous EGFR ligands. These include other receptor tyrosine kinases (RTKs) such as insulin-like growth factor-1 receptor (IGF-1R) (reviewed in [
The
One of the first studies implicating the EGFR pathway in ovarian cancer was the detection of TGF-
While initial studies suggested that EGF, due to the inability to detect transcripts in Northern blotting, might not play a significant role in ovarian cancer [
While earlier studies focused on EGFR ligands in ovarian cancer, emerging studies examined the mechanism of EGFR activation itself. For example, Campiglio et al. detailed the activation characteristics of the EGFR family members upon addition of EGF or HRG in human ovarian cancer cell lines containing different levels of EGFR family proteins [
Further elucidation of the effects of EGFR signaling in ovarian cancer comes from inhibition of EGFR in cultured human ovarian cancer cells. For example, treatment of the human ovarian serous epithelial cancer cell line OVCA420 with the anti-EGFR murine monoclonal antibody (mAb) C225 resulted in decreased levels of cell cycle progression-associated proteins Cyclin-dependent kinase (CDK) 2, CDK4, and CDK6 and increased expression of the cell cycle-inhibiting protein P
As transactivation pathways in various cell systems have been delineated, so have the pathways associated with EGFR family activation in ovarian cancer. For example, Vacca et al. have provided evidence that the GPCR ligand, endothelin (ET)-1, can activate EGFR in the human ovarian cancer cell line OVCA 433 [
More recent studies have found additional signaling molecules or pathways that contribute to EGFR-mediated malignant phenotype in human ovarian cancer cell lines, including EGFR-interleukin-6 crosstalk through Janus kinase 2/Signal transducer and activator of transcription 3 signaling to mediate epithelial-mesenchymal transition [
In addition to the studies alluded to above in determining the effects of molecular modulations of EGFR and its biochemical and biological effects, several other approaches for studying EGFR have been used; these are summarized in Table
EGFR assay method | Assay output | Performed in ovarian cancer? | Platform for ovarian cancer | References for ovarian cancer |
---|---|---|---|---|
cDNA Array | Detection of mRNA levels of various genes | Ye | Patient tissue, Human cell lines | [ |
Comparative Genomic Hybridization | Detection of copy number changes in chromosomes | Ye | Patient tissue, Human cell lines | [ |
Chromatin Immunoprecipitation | Detection of stable protein-DNA associations | No | ||
Coimmunoprecipitation + Western blotting | Detection of stable protein-protein associations | No | ||
Crystallography | Determination of entire structure or portions of molecule; interacting molecules | No | ||
Enzyme-linked Immunosorbent Assay | Determination of amount of protein in sample | Yes | Patient tissue | [ |
Fluorescence/ Chromogenic in situ Hybridization | Determination of gene copy number | Yes | Patient tissue | [ |
Flow Cytometry/ Fluorescence-Activated Cell Sorting | Determination of protein levels at cell surface | Yes | Patient tissue, Human cell lines | [ |
Immuno-histochemistry/ Immunocyto-chemistry/ Immunofluorescence (includes Tissue Microarrays) | Determination of presence, location, or amount of protein in tissue/cell | Yes | Patient tissue, Patient effusions, Human cell lines | [ |
In vitro Kinase Assay | Measurement of intrinsic kinase activity | No | ||
Mass Spectrometry after Protein Enrichment /Purification (e.g., Immunoprecipitation, Chromatographic Separation, Baculovirus Expression) | Detection of protein modification sites (e.g., phosphorylation, glycosylation); changes in protein levels or proteomic profiles, protein-protein complexes | No | ||
Microscopic Techniques (e.g., Confocal) | Determination of presence, location, or amount of protein in cell | No | ||
Mulitplex Antibody Arrays (Solid Phase or Bead Based) | Detection of multiple molecules (usually proteins) of interest | Ye | Patient serum, Human cell lines | [ |
Northern Blotting | Determination of steady-state RNA levels | Yes | Patient tissue, Human cell lines | [ |
PCR + DNA analysis (e.g., Sequencing, Restriction Fragment Length Polymorphisms, Denaturing Gradient Gel Electrophoresis) | Detection of known mutations/ polymorphisms | Yes | Patient tissue, Human cell lines | [ |
Quantitative PCR | Measurement of RNA levels of interest | Yes | Human cell lines | [ |
Radioligand Binding/ Radioimmunoassay | Estimation of number of receptors; determination of ligand or agonist/ antagonist binding kinetics | Yes | Patient tissue, Patient effusions, Human cell lines | [ |
Reverse Phase Protein Array | Determination of levels of several proteins and protein modifications of interest | Yes | Patient tissue, Patient effusions | [ |
Reverse Transcription-PCR + Southern Blotting | Determination of mRNA levels | Yes | Human cell lines, Rat cell lines | [ |
Southern Blotting | Detection of gene of interest | Yes | Rat cell lines | [ |
Tryptic Digests + Peptide Resolution (e.g., Reverse Phase High Performance Liquid Chromatography) | Determination of phosphorylation sites of protein | No | ||
Western Blotting | Determination of protein abundance, protein-associated modifications (e.g., phosphorylation, cleavage, ubiquitination) | Yes | Patient tissue, Human cell lines | [ |
Xenograft Tumors | Determination of effect of gene/cell perturbation on tumor growth | Yes | Human and mouse cell lines | [ |
To determine the effects of EGFR activation or inhibition in tumor formation, human ovarian tumor cells are most frequently implanted heterotopically (subcutaneously) in immunocompromised mice (Table
In addition to implantation of human tissues or cells via xenografts, animal models utilizing other methods of tumor formation have been used to study ovarian cancer. (For comprehensive reviews on animal tumor models, see [
In one study where signaling proteins downstream of EGFR induced ovarian cancer, transgenic mice harboring exogenously controllable (“floxed”) expression of phosphatase and tensin homolog (
While several strategies have been attempted to block EGFR activity, two types of inhibitors are currently used in the clinic: (1) monoclonal antibodies (mAbs), and (2) small molecule tyrosine kinase inhibitors (see [
Monoclonal Antibodies
Study and Year | CT no. | Phase | # Pts | Therapy | Selection criteria | Outcome | Comments |
---|---|---|---|---|---|---|---|
Secord et al. 2008 [ | NCT 00086892 | II | 28 | Cetuximab + Carboplatin | Recurrent, platinum-sensitive disease | CR: 3 pts | Response rate criteria not met for next stage of accrual. 26 pts were EGFR positive by IHC. |
PR: 6 pts | |||||||
SD: 8 pts | |||||||
Konner et al. 2008 [ | NCT 00063401 | II | 40 | Cetuximab + Paclitaxel + Carboplatin | Grade III-IV debulked tumor, EGFR positive by IHC | Median PFS: 14.4 months | Combination was adequately tolerated. No increase in PFS when compared to historical data. |
PFS at 18 months: 39% | |||||||
Schilder et al. 2009 [ | II | 25 | Cetuximab | Persistent or recurrent ovarian or primary peritoneal disease, EGFR positive tumors by IHC | 12 serologic markers examined before and during treatment. No correlation between PFS and marker changes, but high baseline of markers associated with earlier disease progression. | ||
PR: 1 pt | |||||||
SD: 9 pts | |||||||
Seiden et al. 2007 [ | NCT 00073541 | II | 37 | Matuzumab | Recurrent platinum-refractory disease, EGFR positivity by IHC | No objective response | Primary objective was pharmacodynamic; signal transduction evaluation. 75 pts were screened for EGFR status. |
SD: 16%–22% | |||||||
Bookman et al. 2003 [ | GOG-160 | II | 41 | Trastuzumab | Persistent and/or refractory disease with 2-3+ HER2 by IHC | CR: 1 pt | Serum HER2 levels not associated with clinical outcome. |
PR: 2 pts |
Small Molecule Inhibitors
Study and Year | CT no. | Phase | # Pts | Therapy | Selection criteria | Outcome | Comments |
---|---|---|---|---|---|---|---|
Posadas et al. 2007 [ | NCT 00049556 | II | 24 | Gefitinib | Platinum-refractory disease | No objective response | Protein correlates done with RPPA. No significant correlation between EGFR phosphorylation and tumor response |
SD: 37% for >2 months | |||||||
Schilder et al. 2005 [ | NCT 00023699 | II | 27 | Gefitinib | Persistent or recurrent disease | PR: 1 pt | Analyses suggest trend towards responsiveness in EGFR positive (by IHC) pts. Activating mutations documented in the PR pt. |
Wagner et al. 2007 [ | NCT 00189358 | II | 56 | Gefitinib + Tamoxifen | Disease refractory or resistant to platinum-taxane-based therapy | No objective response | EGFR positivity not a prerequisite; EGFR status not determined |
SD: 16 pts | |||||||
Gordon et al. 2005 [ | II | 34 | Erlotinib | Relapsed or progressive disease, EGFR positivity by IHC | PR: 2 pts | Primary goal was to estimate the objective tumor response rate to erlotinib as a single agent. | |
SD: 15 pts | |||||||
Vasey et al. 2008 [ | Ib | 45 | Erlotinib + Docetaxel + Carboplatin | Chemonaïve pts | CR: 5 pts | Phase Ib dose finding study. Addition of erlotinib to other agents did not increase response rate. | |
PR: 7 pts | |||||||
(23 evaluable) | |||||||
Nimeiri et al. 2008 [ | NCT 00126542 | II | 13 | Erlotinib + Bevacizumab | Recurrent or refractory disease, ≤2 prior cytotoxic chemotherapies; no previous anti-EGFR or VEGFR therapies | No indication of improvement over bevacizumab treatment only. No | |
CR: 1 pt | |||||||
PR: 1 pt | |||||||
Kimball et al. 2008 [ | NCT 00317434 | I | 11 | Lapatinib + Carboplatin | Recurrent, platinum-sensitive disease | PR: 3 pts | No screening or measurement of EGFR or HER2 performed. |
SD: 3 pts | |||||||
Campos et al. 2005 [ | II | 105 | CI-1033 | Relapsed or refractory disease | No objective response | Baseline HER1-2 levels determined by IHC. No association between HER levels and SD. | |
SD: 26–34% |
Anti-EGFR mAbs that are used in the clinic typically bind to the extracellular domain of EGFR (e.g., [
Cetuximab (Erbitux) was the first anti-EGFR mAb tested in the clinic. Cetuximab inhibits growth of a variety of cultured cancer cells including breast, prostate, lung, colon, kidney, head and neck (reviewed in [
Reports for cetuximab in ovarian cancers have appeared recently (Table
Among other anti-EGFR antibodies, a single multi-institution open-label phase II trial was reported in patients with ovarian cancer using matuzumab (EMD 72000) [
Due to potential EGFR transactivation by other EGFR family members, mAbs targeting other EGFR family members have also been tested or used clinically against various cancer types such as breast and urothelial malignancies (reviewed in [
Among antibodies targeted toward other signaling molecules known to activate EGFR are monoclonals for IGF-1R, including 19D12 and EM164. These antibodies have been demonstrated to inhibit proliferation of human ovarian cancer cells [
Small molecule inhibitors, based on modeling by structure-based drug design [
Gefitinib (Iressa or ZD1839), which inhibits a variety of cancer cell lines and xenograft tumors (reviewed in [
Gefitinib was also used in combination with tamoxifen in a phase II study in Germany involving patients refractory or resistant to platinum-taxane-based treatment but not prescreened for estrogen receptor or EGFR expression [
Another small molecule inhibitor, erlotinib (Tarceva), demonstrated limited activity for ovarian cancer patients in a multicenter phase II trial, with only 2 chemorefractory patients in 34 demonstrating a partial response to treatment [
Lapatinib (Tykerb, Tyverb), a dual EGFR-HER2 inhibitor [
The irreversible pan-EGFR family inhibitor CI-1033 (Canertinib) was administered in a multicenter open-label phase II trial for ovarian cancer patients who had failed prior platinum-based therapy [
Due to the relatively unremarkable results of anti-EGFR small molecules in earlier clinical trials, more recent trials have focused on small molecules that bind irreversibly or have a broader target range. For instance, BIBW2992 (Tovok) binds irreversibly to EGFR and HER2 and can inhibit both wild type EGFR and activated mutants of EGFR and HER2 [
In lung cancers, sensitivity to EGFR inhibition by small molecules such as gefitinib and erlotinib is associated with
As detailed by the list of clinical trials, the use of EGFR inhibitors as single agents or in early combination studies in ovarian cancer has met with limited success. The regimens have included EGFR-selective or less selective inhibitors and administration as single agents or in combination with other non-EGFR antineoplastic agents. One not yet widely explored possibility is whether using a combination of an externally targeting EGFR drug (i.e., mAb) with an internally targeting drug (i.e., small molecule kinase inhibitor) would produce better results. So far, there is one complete report of a phase I study that has determined optimal doses of combined cetuximab and gefitinib therapy in patients with advanced or metastatic NSCLC previously treated with platinum therapy [
While later studies selected patients based on EGFR positivity or overexpression via IHC, many of these trials still demonstrated low efficacy, suggesting that other methods of EGFR detection might be better suited for pre-drug screening. Quantitative approaches to assess protein level, RNA levels, gene amplification, and mutations might prove less subjective and more robust than IHC and could be included as one of the predictors of patient response. In lung cancer, gene copy number assessed by fluorescence in situ hybridization (FISH) has been reported to indicate sensitivity to EGFR inhibition (reviewed in [
An understanding of the mechanisms leading to resistance of EGFR inhibitors could help enrich for patients likely to respond to therapy and more importantly identify rational combinatorial therapy. Resistance of tumors to anti-EGFR therapies has been discussed in a number of reviews (e.g., [
Anti-EGFR therapy resistance mechanisms include production of EGFR-activating ligands, receptor mutations, constitutive activation of downstream pathways, and activation of alternative signaling pathways (reviewed in [
Another potential mechanism of EGFR inhibitor resistance is inflammation, such as by release of the inflammatory cytokine prostaglandin E2, which in lung cancer cells induced phosphorylation of MAPK, indicating a bypass of EGFR activation (reviewed in [
Experimental results have also indicated the need to better understand the interaction of EGFR with other family members, signaling events, and the tumor environment in ovarian as well as in other cancers. As noted earlier, relative differences in levels of EGFR family members induced different dimerization partners upon stimulation by a given ligand in ovarian cancer cell lines [
As evident here and in numerous other reports on EGFR inhibitors in various cancer cell types, other signaling molecules affected by or effecting EGFR family members will have to be concomitantly examined in solid tumors. First, signaling of the EGFR family occurs primarily in
In addition to signaling across EGFR family members and proteins downstream, consideration of other transmembrane signaling molecules must be taken into account. Considerable data in various cell types including hepatoma [
Despite these challenges, reports utilizing adherent human epithelial cancer cell lines and tumor types suggest that mechanisms of resistance and methods to overcome resistance could be determined and incorporated into ovarian cancer therapies. For instance, MAPK phosphorylation was not inhibited in an EGFR-positive, gefitinib-resistant human bladder cancer cell line upon gefitinib treatment, while MAPK phosphorylation decreased in an EGFR-positive, gefitinib-sensitive cell line [
With the emergence of high-throughput technologies and their accompanying development and refinement of data analyses, reports contributing to further understanding of ovarian cancers have emerged. Among the first reports utilizing gene arrays was that of Wang et al., who identified genetic differences between human ovarian tumor specimens (comprising 5 different histopathologic types) and normal ovarian tissue [
Based on the current outcomes of EGFR targeted therapy in ovarian cancers, it is evident that patients should be screened for EGFR status including amplification and mutation; additionally, screening for other EGFR family members and key downstream effector proteins such as RAS and PTEN would be preferable. Also, while
Determination of other molecular markers for likely responders or nonresponders toward anti-EGFR therapies should also be performed; identification of such markers could be facilitated by high-throughput methods that can be correlated with patient response. High-throughput methods could also be used to aid in developing predictive models of drug combination in patients, such as by testing well-defined chemotherapeutic drugs in a large number of cancer cell lines and performing cell “population studies,” to better correlate drug response with precisely defined oncogene status (e.g., specific mutations, gene amplification), such as with EGFR [
EGFR and its family members play a variety of roles in oncogenesis and tumor progression in different cancer and cell types. To date, clinical studies using EGFR antagonists in ovarian cancer have shown limited efficacy. As we learn more about the complexities of specific signaling changes associated with EGFR mutation and overexpression, future studies using EGFR antagonists in ovarian cancer should focus on determining reliable predictors for patient responsiveness to anti-EGFR therapy such as by obtaining good biomarker profiles and utilizing assays most appropriate to determine EGFR status as well as developing rational combination therapies with EGFR inhibitors. These determinations should be facilitated by the use of high-throughput methods, as well as development of robust algorithms to help design experiments and analyze results. Continuing these studies in ovarian and other types of cancers will increase our likelihood of achieving success in targeting EGFR-dependent tumors.