The purpose of cancer staging is to classify cancers into prognostic groups and to allow for comparison of treatment results and survival between patients and institutions. Staging for gynecologic cancers is based on extent of disease and metastasis, which was historically determined by physical examination and is now based on surgical and histologic examination of tumor specimens. Although the extent of disease is currently considered the most important predictor of recurrence and survival, current staging does not include molecular features that are associated with tumor aggressiveness, response to therapy, and prognosis. This review focuses on genomic and proteomic features of gynecologic cancers and the future of biomarkers in staging classification.
Highlights
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There is no universally accepted molecular staging system for gynecologic cancers.
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Different genetic alterations give rise to heterogeneity of gynecologic cancers.
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Biomarkers are associated with response to therapy and clinical outcomes.
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Clinical trials are evaluating novel drug therapies that target molecular pathways.
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Molecular classification is feasible and desirable for comprehensive cancer staging.
Introduction
Historically, gynecologic cancers were clinically staged and the extent of disease was predicted based on physical examination and radiographic findings. Given that clinical examination was inaccurate in determining lymph node involvement, distant metastasis, histologic grade, and other prognostic pathologic features, surgical staging was adopted for all but cervical cancer (CC). The late 1980s International Federation of Gynecology and Obstetrics (FIGO) staging nomenclature for carcinoma of the ovary, endometrium, and vulva became dependent on surgical and pathologic findings.
Current cancer research focuses on understanding the molecular and mutational events that occur in early carcinogenesis and eventually lead to metastasis. Sequencing, microarray, and proteomic methods allow analysis of all genes of a tumor at the DNA, RNA, and protein levels, but we must determine which alterations are clinically significant. In the last decade, researchers have begun performing molecular subclassification of several cancers , although there is no clear consensus of which prognostic markers to include in staging. None of the gynecologic cancers are staged with molecular markers, but it is imperative that we consider the use of newly available technologies to identify markers that are truly prognostic and predictive of survival, recurrence, and treatment response.
Uterine carcinoma
In addition to FIGO stage, assessments of tumor grade, lymphovascular space invasion (LVSI), and histologic subtype are important in the prognosis and management of endometrial cancer (EC) . In 1983, Bokhman described two subtypes of EC based on different clinical observations, but now type I includes grade 1 and 2 endometrioid endometrial carcinomas (EEC) and type II includes grade 3 EEC and non-EEC (serous, clear cell, and undifferentiated) . Grade and cell type are distinguished by microscopy based on morphologic features, but this method often lacks reproducibility and differences in grade and histology are better reflected in their genetic and molecular profiles . The progression from normal endometrium to EEC or non-EEC may not always follow a linear pathway and non-EEC may develop from high-grade EEC after further molecular alterations and tumor progression . Tumors with mixed features may represent this progression and histology diagnosis by microscopy may be difficult. Thus, improved classification systems are needed for EC.
Uterine carcinoma
In addition to FIGO stage, assessments of tumor grade, lymphovascular space invasion (LVSI), and histologic subtype are important in the prognosis and management of endometrial cancer (EC) . In 1983, Bokhman described two subtypes of EC based on different clinical observations, but now type I includes grade 1 and 2 endometrioid endometrial carcinomas (EEC) and type II includes grade 3 EEC and non-EEC (serous, clear cell, and undifferentiated) . Grade and cell type are distinguished by microscopy based on morphologic features, but this method often lacks reproducibility and differences in grade and histology are better reflected in their genetic and molecular profiles . The progression from normal endometrium to EEC or non-EEC may not always follow a linear pathway and non-EEC may develop from high-grade EEC after further molecular alterations and tumor progression . Tumors with mixed features may represent this progression and histology diagnosis by microscopy may be difficult. Thus, improved classification systems are needed for EC.
Markers associated with histology
Molecular profiling can distinguish EEC from non-EEC. EECs have a higher frequency of PTEN , PIK3CA , CTNNB4 , KRAS , FGFR-2 , and ARID1A mutations, estrogen and progesterone receptor (ER/PR) expression, and microsatellite instability (MSI). High-grade EECs have higher frequencies of PIK3CA and p53 mutations than low-grade EECs. Uterine serous carcinomas (USCs) exhibit a high frequency of mutations in p53 , HER2, PIK3CA , and PPP2R1A , loss of function in p16 and E-cadherin, overexpression of Stathmin and Cyclin D1/E, and chromosome instability. Clear-cell carcinomas show mutations in PIK3CA , PTEN , and ARID1A , loss of function of BAF250a (ARID1A protein), and positive immunoreaction for HNF1β . There are no clear guidelines for the use of immunohistochemistry (IHC) and molecular genetic profiling in cell type classification, but they often represent an improvement over the current histopathologic assessment. For example, McConechy et al. were able to accurately reclassify diagnostically difficult cases into correct histologic subtype based on exome-sequencing of nine genes . Similarly, molecular characterization of 373 ECs by the Cancer Genome Atlas (TCGA) Research Network helped reclassify 25% of high-grade EECs into USCs . These findings demonstrate that systematic immunoprofile and mutation analysis for certain biomarkers can improve tumor classification and prognostication.
Prognostic markers and targeted therapies
Numerous mutations and biomarkers are reported to have prognostic roles in large EC studies , but it is neither practical nor cost-effective to incorporate them all into molecular staging. When interpreting biomarker studies, special attention should be given to the techniques used in detecting alterations and the statistical analysis performed to show prognostic capabilities. Ideal biomarkers will be easy and economical to evaluate and will have prognostic value after adjusting for known clinical and pathologic prognostic factors .
PI3K–AKT–mTOR pathway
PTEN: This tumor suppressor gene encodes a phosphatase that enables cell-cycle arrest and apoptosis by antagonizing the PI3K-AKT pathway . PTEN mutations are present in 56–80% of low-grade EEC, 40% of mixed carcinomas, and are nearly absent in non-EEC . They are associated with a more favorable histology and outcome. However, the independent prognostic value of PTEN needs further evaluation. Early studies showed that PTEN mutations are associated with early FIGO stage and prolonged survival , but this favorable outcome may be limited to mutations not involving exons five through seven . In a population-based study, loss of PTEN expression as a result of promoter methylation was associated with advanced stage . While PTEN mutations are associated with EEC, these mutations may represent a high-risk group within EECs and adjuvant therapy could be considered in these patients.
PIK3CA: Activating mutations in the oncogene PIK3CA leads to upregulation of the anti-apoptotic PI3K-AKT pathway. Such mutations are present in 44% of mixed histotype ECs, 28% of EECs, and 21% of non-EECs . Catasus et al. suggested that mutations in exon 20 are important in the progression of low-grade to high-grade EEC and in the pathogenesis of non-EEC . With this biomarker, the specific sequence alteration carries prognostic significance and should be reported with mutation results.
Targeted therapies: Drugs targeting the PI3K/AKT/mTOR pathway are currently in preclinical and clinical trials . Results of phase II trials evaluating mTOR inhibitors in the treatment of recurrent or metastatic EC have been modest. Temsirolimus was evaluated in a phase II trial of chemotherapy-naïve patients and patients who received one prior chemotherapy regimen . Primary treatment with temsirolimus produced a 14% radiographically confirmed partial response rate (PRR) and a 69% stable disease rate (SDR) after median follow-up times of 5.1 and 9.7 months, respectively. Temsirolimus produced a 2% PRR, 48% SDR, and 48% progressive disease (PD) rate in recurrent EC. Half the patients required a dose reduction. Response was not associated with PTEN mutations, loss of PTEN expression or immuno-response for downstream targets of AKT, mTOR, and S6. Currently, a randomized phase II trial is evaluating temsirolimus with carboplatin and paclitaxel after promising results from a phase I trial (NCT00977574).
A phase II trial of ridaforolimus produced an 11% PR rate and 18% SDR after 4 months of therapy in 45 patients with advanced EC . Everolimus treatment in recurrent or metastatic EC patients showed no RR, and half the patients with SD at first follow-up discontinued the drug due to toxicities while the other half developed PD . Preclinical trials of AZD8055 (a dual mTOR 1/2 inhibitor) and GDC-0980 (a dual P13K and mTOR 1/2 inhibitor) show promise in USC cell lines and clinical trials are anticipated .
KRAS–MAPK pathway
KRAS: This oncogene encodes a guanosine triphosphatase (GTPase) that transduces signals from growth receptors on the cell surface to the nucleus leading to transcription and translation via the mitogen-activated protein kinase (MAPK) pathway . KRAS also binds to PIK3CA and activates the PI3K–AKT–mTOR pathway. KRAS mutations are found in 10–30% of ECs and are more common in low-grade EECs. In a study with 466 EECs, KRAS mutations were identified in 19% of samples and were associated with longer progression-free survival (PFS) on univariate and multivariate analysis . However, preclinical studies show that KRAS mutations predicted resistance to single-agent therapy targeting the PI3K–AKT–mTOR pathway and cell lines without KRAS alterations had improved sensitivity to NVP-BEZ235 (a dual PI3K/mTOR inhibitor) and everolimus .
Targeted therapies: MEK inhibitors inhibit key enzymes in the MAPK pathway and have been studied in combination with PI3K–AKT–mTOR inhibitors in preclinical trials. Addition of MEK inhibitor PD98059 improved the sensitivity of KRAS mutant EC cell lines to NVP-BEZ235 and everolimus . Single-agent GDC-0941 (PI3K inhibitor) controlled tumor growth in xenografted mice, but combination with MEK inhibitor PD0325901 led to significant reduction in tumor size . A randomized phase II trial is evaluating MEK inhibitor trametinib with and without AKT inhibitor GSK2141795 in patients with persistent or recurrent EC (NCT01935973).
WNT/β-catenin signaling pathway
CTNNB1: This Wnt family member encodes the β-catenin protein that acts as a transcription factor . Phosphorylation of amino acids encoded by exon 3 of CTNNB1 leads to degradation of β-catenin. Mutations in this region prohibit β-catenin degradation and eventually lead to cell proliferation and progression to pre-cancerous and cancerous phenotypes due to unchecked transcription activation. CTNNB1 mutations are present in 14–44% of EECs but are absent in non-EEC and mixed tumors . Thus, the prognostic value of mutation status should be studied in large cohorts of EECs. Mutation and expression analysis of 192 EECs showed that tumors with CTNNB1 exon 3 mutations led to Wnt/β-catenin pathway activation and were associated with low-grade cancers, early-stage disease, younger patients, and shorter survival even after adjusting for age, grade, and stage of disease . CTNNB1 mutations that did cause activation of the Wnt/β-catenin pathway were not associated with poor survival. Therefore, the presence of CTNNB1 exon 3 mutations in young patients with early-stage and low-grade EEC may be a poor prognostic feature and should prompt closer follow-up and strong considerations for treatment and possibly adjuvant therapy.
P53 alterations
The tumor suppressor p53 encodes a transcription factor that inhibits cell growth and promotes cell-cycle arrest and apoptosis in response to DNA damage. P53 loss leads to chromosomal instability, aneuploidy, and inhibition of apoptosis . P53 mutations occur in 60–85% of non-EEC and are associated with aggressive histology, advanced stage, and poor clinical outcome . In 131 surgically staged EC patients, 30% had p53 mutations and an 11-fold increased risk of death compared to patients without p53 mutations, after adjusting for histology, grade, FIGO stage, and lymph node metastasis . A multivariate analysis for p53 mutations after stratifying for adjuvant radiotherapy found lower survival rates in patients with mutations . Adjuvant radiotherapy improved overall survival (OS) of p53 mutation carriers to match that of patients without p53 mutations, but did not improve OS in patients without mutations.
P53 mutations are also seen in 2% of low-grade EECs, 20% of high-grade EECs, 54% of mixed carcinomas, 75% of endometrial intraepithelial carcinomas, and up to 90% of USCs . Simultaneous loss of p53 and activating PIK3CA mutations in high-grade and mixed EECs promotes aggressive malignant transformation and leads to poorer survival than in patients with p53 mutations alone . These studies suggest that p53 mutations may influence early events in serous carcinogenesis and induce progression of EECs to non-EECs. Therefore, detecting p53 mutations and PI3K–AKT–mTOR pathway activations is critical in identifying women at high risk of poor outcomes and treating them appropriately.
Receptor tyrosine kinases
EGFR (Erb-B1): Epidermal growth factor receptor (EGFR) is a transmembrane glycoprotein belonging to the ErbB family of receptor tyrosine kinases (RTKs). Receptor activation initiates a complex set of pathways including PI3K–AKT–mTOR and KRAS–MAPK causing cell growth and proliferation . EGFR overexpression is reported in 46% of EECs and 34% of non-EECs . The prognostic value of EGFR overexpression is debatable: some studies show an association with poor survival, but others demonstrate no significant prediction of outcome .
Targeted therapies: EGFR inhibitors gefitinib and erlotinib have not shown a clinically significant RR or benefit in PFS and OS in phase II trials of advanced and recurrent EC . Furthermore, neither trial showed an association between response and EGFR overexpression.
HER2 (Erb-B2): This oncogene encodes human EGFR-2. HER2 protein overexpression seen in 20–40% of ECs, with highest frequency in non-EECs (43%), then high-grade EECs (29%), and then low-grade EEC (10%), is an independent predictor of poor OS in EC . HER2 overexpression negatively affects PFS and OS in ECs and HER2 expression may predict sensitivity to paclitaxel and therapies targeting the PI3K–AKT pathway . For example, high HER2 expression in USCs was associated with increased sensitivity to AZD8055 and GDC-0980 . HER2 amplification and overexpression are capable of predicting survival outcomes and response to targeted therapies; therefore, genetic and IHC analysis should be performed for comprehensive counseling and individualized targeted therapy recommendations.
Targeted therapies: Monoclonal antibodies targeting the extracellular domain of HER2 receptors such as trastuzumab and pertuzumab are approved for use in HER2-positive breast cancer. A phase II trial of 33 patients with HER2 overexpressing advanced or recurrent EC treated with trastuzumab did not lead to a tumor response, but 36% had SD and 55% had PD . A randomized phase II trial is evaluating trastuzumab in combination with carboplatin and paclitaxel in HER overexpressing USCs (NCT01367002).
Treatment of persistent or recurrent EC with lapatinib, a dual EGFR/HER2 inhibitor, showed a 3% PR, 23% SD, and 70% PD rate with median PFS of 1.8 months in all groups. Mutation analysis in this study identified three new EGFR mutations, one of which (E690K, in exon 18) was associated with partial response . Detecting this mutation in patients with EGFR overexpressing ECs may predict benefit with lapatinib.
FGFR2: Activating mutations or amplifications in oncogene Fibroblast growth factor receptor-2 ( FGFR2) are present in 10–16% of EECs . Mutations in FGFR2 were almost mutually exclusive of KRAS mutations, but they individually occurred in tumors with MSI. FGFR2 mutations were more common in low-grade tumors and were associated with shorter OS and disease-free survival in stage I and II disease .
Targeted therapies: FGFR2 mutations are associated with chemoresistance and therefore FGFR2 inhibition may improve response to chemotherapy. Preclinical studies of EC cell lines with FGFR2 mutations showed that knockdown or inhibition of FGFR2 with PD173074 resulted in cell-cycle arrest and apoptosis . A combination of PD173074 and cytotoxic chemotherapy showed synergistic activity with doxorubicin or paclitaxel . Brivanib and nintedanib are RTK inhibitors that block FGFR and vascular endothelial growth factor receptor (VEGFR). Phase II trials of these drugs in recurrent or persistent EC showed 19% RR with 30% 6-month PFS for brivanib and 9% PRR with 22% 6-month PFS for nintedanib .
VEGFR: Ligand binding and activation of VEGFR leads to endothelial proliferation, angiogenesis, and increased tumor growth .
Targeted therapies: The monoclonal antibody bevacizumab binds and inactivates VEGF, thereby inhibiting endothelial and possibly tumor proliferation. A phase II trial evaluating its efficacy in recurrent or persistent EC showed an RR of 14%, median PFS of 4.2 months, and OS of 10.5 months . Patients treated with a combination of bevacizumab and temsirolimus had a 25% RR and median OS of 16.9 months, but the combination was significantly more toxic than bevacizumab alone . The safety and efficacy of adding bevacizumab to carboplatin and paclitaxel in advanced EC patients are being evaluated in a phase II open-label clinical trial (NCT00513786).
Hormone receptors
ER/PR: Estrogen and progesterone receptor positivity are associated with endometrioid histology and significantly improved PFS .
Targeted therapies: Median PFS after medroxyprogesterone, anastrozole, or arzoxifene use in recurrent or advanced EC ranges from 1 to 3.7 months . The ER antagonist fulvestrant produced a 17% RR and 10-month median PFS in patients with ER-positive recurrent or metastatic EC . For stage I EC, a systematic review reported no benefit of adjuvant hormone therapy in seven of nine randomized controlled trials . Nevertheless, IHC of ER/PR is a good and inexpensive biomarker and may predict response to nontoxic hormone therapy.
DNA polymerase E ( POLE ) mutations
Based on genomic and proteomic characterization of 373 ECs, The Cancer Genome Atlas (TCGA) research network identified the POLE ultra-mutated group in which no recurrences occurred. Although these results seem like a breakthrough in association between molecular profiles and clinical prognosis, the data should be interpreted keeping established histopathologic prognostic factors in mind. POLE mutations were present in 10% of EEC and absent in non-EECs. Given the association of POLE mutations with low-grade EECs, we would expect a better clinical outcome compared to serous and high-grade EEC tumors. Billingsley et al. identified POLE mutations in 5.6% of 535 EECs. There was no association between POLE mutation and PFS (univariate analysis) or OS (multivariate analysis), but only one patient with POLE mutation recurred . Another study looking specifically at grade 3 EEC showed an improved PFS, and no recurrence for patients with POLE mutant tumors . POLE shows promise as a reliable marker but needs better characterization in the context of EEC.
Conclusions
Characterization of ECs based on high-throughput data from molecular profiles is already underway. The four categories described by TCGA have significant overlap with current histologic subtypes. Pronounced differences in mutation profiles of low-grade EEC, high-grade EEC, and non-EECs strengthen the hypothesis that these histologic subtypes are probably more heterogeneous than originally thought. Correct classification is essential to predict tumor behavior, risk of recurrence, and response to adjuvant and targeted therapies. Reliable and valid classification of EC based on molecular profiling may result in improved patient counseling, choice of adjuvant therapy, and clinical outcomes.
Ovarian carcinoma
The two most important prognostic factors for ovarian cancer (OC) are FIGO stage and the presence of macroscopic residual tumor after primary surgical debulking . For decades, all OCs were treated the same way with aggressive surgical resection followed by platinum chemotherapy. Based on morphologic and genetic characteristics, two distinct pathways for ovarian carcinogenesis were proposed . Type I OCs are slow-growing, arise from precancerous lesions, and are associated with KRAS and BRAF mutations. Type II OCs are aggressive, arise de novo, present with metastases, and are associated with p53 mutations. Similar to EC, research shows this classification may be too simplistic as tumors within each subtype differ in carcinogenesis events, patterns of spread, precursor lesions, response to chemotherapy, and clinical outcomes. Now, OC is classified into five subtypes including high-grade serous (HGSOC), low-grade serous (LGSOC), endometrioid (EOC), clear-cell (CCC), and mucinous (MC) carcinomas . In a study of 575 optimally resected OC patients, histology was associated with outcome . Specifically, patients with serous histology had a shorter OS than patients with EOC and MC. Historically, diagnosis was based on morphological features, but IHC to detect biomarkers is more useful in distinguishing tumor behavior.
Markers associated with histology
IHC for cytokeratin-7 and PAX-8 can be performed to distinguish mullerian from other primaries and IHC for WT-1 can distinguish between serous carcinomas of ovarian versus endometrial origin . Serous carcinomas are WT-1 and ER positive, EOC are ER positive and WT-1 negative, CCC are HNF1β positive and negative for WT-1 and ER, and MC are ER and CA-125 positive and can be negative or weakly positive for gastrointestinal markers such as CEA, CA 19-9, and CDX2 . High nuclear Ki-67 expression is seen in HGSOC but absent in LGSOC.
Like EC, histologic subtypes of OC have characteristic genetic profiles. HGSOCs are characterized by mutations in p53 , BRCA1-2, and aneuploidy, whereas LGSOCs have KRAS and BRAF mutations. EOCs have mutations in ARID1A , CTNNB1 , and PTEN along with MSI, whereas CCCs carry mutations in ARID1A , PIK3CA , PTEN , and KRAS . Screening for these biomarkers is not a part of OC classification.
Markers associated with cancer stem cells
Despite good response rates to cytotoxic chemotherapy, the recurrence rate for OC remains high and may be due to the presence of cancer stem cells (CSCs) in the original tumor. Although they represent a small proportion of the tumor, CSCs are believed to be resistant to chemotherapy and can grow rapidly, thereby repopulating chemotherapy-resistant recurrences . Markers for CSCs in breast, hematopoietic, and brain cancers including CD44, CD117, and CD133 are being studied in OC.
CD44 is a hyaluronate receptor seen in breast CSCs, and CD44+ cancer cells have been isolated from the primary tumor, metastatic sites, and ascites of OC patients. These cells were chemoresistant and able to generate new heterogeneous (CD44+/CD44−) tumors when transplanted into immune-compromised mice . More than 25% of CD44+ cells in ascites fluid was predictive of a higher recurrence rate and a shorter median PFS in 19 consecutive advanced-stage OC patients .
CD117 is a stem cell growth factor receptor encoded by proto-oncogene KIT . It is an RTK and may play a role in carcinogenesis and chemoresistance by activation of the WNT/β-catenin pathway . In a series of 25 OC patients, 40% of tumors were positive for CD117 expression by IHC and were associated with chemoresistance .
CD133 is a transmembrane glycoprotein expressed on CSCs in acute myeloid leukemia and brain cancers. CD133+ OC cells were chemoresistant and tumorigenic generating tumors with CD133+ and CD133− cells . In a study of 400 OC samples, 31% were positive for CD133 expression and these cancers were associated with high-grade serous histology, advanced stage, and nonresponse to chemotherapy . Multivariate analysis showed that CD133 expression was an independent predictor of shorter recurrence-free survival (RFS).
Targeted therapies
Trials of CD44 ligands conjugated to cisplatin and paclitaxel in intraperitoneal OC murine models have shown decreased growth and weights of tumor . Imatinib, a KIT tyrosine kinase, showed disappointing results in the treatment of recurrent platinum-resistant LGSOC with no responders, only one of 11 patients with SD for 7.3 months and the rest with PD .
A high percentage of CSCs in primary tumors is associated with resistance to chemotherapy and shorter RFS. Evaluating such patients more often may lead to early diagnosis of recurrence, but it is unclear whether early diagnosis and treatment would affect response or survival. Nonetheless, the presence and percentage of CSC markers may be an effective screening tool to diagnose recurrence.
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