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Molecular staging of gynecological cancer: What is the future?

https://doi.org/10.1016/j.bpobgyn.2015.01.008Get rights and content

Highlights

  • There is no universally accepted molecular staging system for gynecologic cancers.

  • Different genetic alterations give rise to heterogeneity of gynecologic cancers.

  • Biomarkers are associated with response to therapy and clinical outcomes.

  • Clinical trials are evaluating novel drug therapies that target molecular pathways.

  • Molecular classification is feasible and desirable for comprehensive cancer staging.

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.

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 [1], [2], [3], 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.

Section snippets

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) [4]. 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) [5]. Grade and cell type are distinguished by

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

Prognostic markers and targeted therapies

Numerous mutations and biomarkers are reported to have prognostic roles in large EC studies [9], 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

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

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 [45]. 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 [46]. Type I OCs are slow-growing, arise from precancerous lesions, and are associated with KRAS and

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 [47]. 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 [47]. High nuclear Ki-67

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 [49]. Markers for CSCs in breast, hematopoietic, and brain cancers including CD44, CD117, and CD133 are being studied in OC.

CD44 is a

BRCA1 and BRCA2

These tumor suppressor genes encode proteins involved in homologous recombination repair of damaged DNA. Germline mutations in these genes lead to a hereditary breast and OC syndrome with a 30–70% lifetime risk of developing OC, mostly HGSOC type [57]. Somatic mutations in BRCA1-2 and hypermethylation of the BRCA1 promoter also cause aberrations in the BRCA pathway. Up to 50% of HGSOCs have molecular alterations in the BRCA pathway [58]. BRCA1 mutations are associated with longer median

Conclusions

Several meta-analyses evaluating biomarkers and their prognostic roles in OCs have been published over the last few years [9]. By using high-throughput genomic and proteomic analyses, studies are reporting unsupervised clustering of a large number of OCs into molecularly distinct subtypes that are associated with treatment response and clinical outcomes.

Cervical carcinoma

Current research efforts aim to discover molecular markers that will enhance or replace papanicolaou and human-papilloma virus (HPV) testing in screening and prevention of invasive disease. Diagnosis of pre-invasive disease has obvious benefits but here we focus on molecular prognostic markers of invasive disease. Recurrence and benefit from adjuvant radiation in stage IB patients depend on pathological findings of LVSI, cervical stromal involvement, and tumor size [74]. Other postsurgical

Angiogenesis markers

VEGF: High intra-tumor VEGF expression was related to poor PFS and OS in a series of 135 women with stage IB and IIA CC [77]. Another study including 173 CC patients treated with postsurgical radiotherapy because of lymph node or parametria or vaginal disease did not show a significant association between VEGF immunostaining and survival [78]. Thus, VEGF may be a predictor of lymph node involvement, and evaluation of this biomarker may be important in deciding treatment options when lymph node

Vulvar carcinoma

Investigating the prognostic potential of biomarkers in vulvar cancer (VC) is problematic because most case series are small. For example, strong VEGF expression is associated with poor OS in a univariate analysis of 25 patients [83]. As in CC, p16, p21, VEGF, CD44, EGFR, and HER2 correlate to clinical outcomes in small studies [84]. By contrast, studies report conflicting evidence about the association between HPV and prognosis. Studies with larger cohorts and adjustment for known pathologic

Summary

Although no gynecologic cancers are universally classified with molecular markers, this may be a staging strategy in the near future. With current genomic and proteomic platforms, we can generate high-throughput data leading to classification and analysis of cancer subtypes. Years of research have revealed that all gynecologic cancers have several subtypes and that genetic and molecular aberrations are responsible for heterogeneity in these diseases. Therefore, determining which genes and

Conflict of interest

The authors have no conflict of interest, financial or others.

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  • This manuscript has not been previously published and is not under consideration in the same or substantially similar form in any other peer-reviewed media. All authors listed have contributed sufficiently to the project to be included as authors, and all those who are qualified to be authors are listed in the author byline.

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