Elsevier

Gynecologic Oncology

Volume 141, Issue 1, April 2016, Pages 95-100
Gynecologic Oncology

Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures

https://doi.org/10.1016/j.ygyno.2016.02.023Get rights and content

Highlights

  • TCGA gene signatures are present in high grade case of rare histology.

  • Early stage high grade cases of rare histology cluster separately from advanced stages.

  • TCGA signatures may help to stratify patients with rare high grade ovarian cancer.

Abstract

Background

It is unclear whether the transcriptional subtypes of high grade serous ovarian cancer (HGSOC) apply to high grade clear cell (HGCCOC) or high grade endometrioid ovarian cancer (HGEOC). We aim to delineate transcriptional profiles of HGCCOCs and HGEOCs.

Methods

We used Agilent microarrays to determine gene expression profiles of 276 well annotated ovarian cancers (OCs) including 37 HGCCOCs and 66 HGEOCs. We excluded low grade OCs as these are known to be distinct molecular entities. We applied the prespecified TCGA and CLOVAR gene signatures using consensus non-negative matrix factorization (NMF).

Results

We confirm the presence of four TCGA transcriptional subtypes and their significant prognostic relevance (p < 0.001) across all three histological subtypes (HGSOC, HGCCOC and HGEOCs). However, we also demonstrate that 22/37 (59%) HGCCOCs and 30/67 (45%) HGEOCs form 2 additional separate clusters with distinct gene signatures. Importantly, of the HGCCOC and HGEOCs that clustered separately 62% and 65% were early stage (FIGO I/II), respectively. These finding were confirmed using the reduced CLOVAR gene set for classification where most early stage HGCCOCs and HGEOCs formed a distinct cluster of their own. When restricting the analysis to the four TCGA signatures (ssGSEA or NMF with CLOVAR genes) most early stage HGCCOCs and HGEOC were assigned to the differentiated subtype.

Conclusions

Using transcriptional profiling the current study suggests that HGCCOCs and HGEOCs of advanced stage group together with HGSOCs. However, HGCCOCs and HGEOCs of early disease stages may have distinct transcriptional signatures similar to those seen in their low grade counterparts.

Introduction

Microarray-based gene expression studies demonstrate that ovarian cancer (OC) is both a clinically diverse and molecularly heterogeneous disease, comprising subtypes with distinct gene expression patterns that are each associated with statistically significant different clinical outcomes. A gene expression analysis of high-grade serous and endometrioid OCs as part of the Australian Ovarian Cancer Study identified distinct molecular subtypes that have been designated with neutral descriptors (C1, C2, C4, and C5) [1]. The four molecular subtypes were validated in 489 high grade serous ovarian cancer (HGSOC) cases using 1500 intrinsically variable genes for consensus non-negative matrix factorization (NMF) clustering and were termed immunoreactive, differentiated, proliferative and mesenchymal on the basis of gene expression in the clusters [2]. These four molecular subtypes have been independently validated and have been shown to be of independent prognostic relevance [3]. Using the TCGA ovarian cancer data set, Verhaak et al. recently confirmed the four molecular subtypes of high grade serous ovarian cancer (HGSOC) using a reduced subtype gene expression signature, named “Classification of Ovarian Cancer” (CLOVAR) [4]. This reduced CLOVAR gene signature is composed of a 100 genes capable of predicting the ovarian cancer subtypes [4]. Validation studies in independent data sets demonstrated that the CLOVAR signature classifies HGSOC with small error rates, making implementation using medium-throughput expression profiling platforms feasible [4].

The main objective of a molecular classification of OC into subtypes with distinct gene expression patterns is to develop robust biomarker signatures that will allow clinicians to identify women likely to benefit from a given therapy. These evolving subgroups are thought to have distinct biologic features that can translate into different therapeutic implications. Epithelial ovarian cancer is a heterogeneous disease consisting of tumors with different histology and grade. The most common OC types are the serous tumors followed by endometrioid and clear-cell cancers which represent 50%–60%, 25% and 4% of all ovarian tumors, respectively [5]. Importantly, however, the evolving molecular classification using the four main subtype signatures have almost exclusively been studied and applied to HGSOC [2], [3], [4]. Although some early gene expression studies have included endometrioid and clear cell ovarian cancers [6], [7], [8], [9], [10] these studies were limited by their small sample size and the use of early generation microarrays. Nevertheless these studies did suggest that clear cell and endometrioid ovarian cancers may be distinguished from serous ovarian cancers based on their gene expression profiles [6], [7], [8], [9], [10]. However, many of these early studies included well differentiated tumors (G1) known to be distinct molecular entities [11]. To date it is unclear if the evolving signatures which have been used to successfully classify HGSOC into four molecular subtypes could also be used to classify these less common epithelial ovarian cancer histologies. Although clear cell carcinomas and endometrioid carcinomas have been previously shown to be in part driven by pathways distinct from those driving progression of HGSOC we wanted to investigate whether high grade clear cell ovarian cancers (HGCCOCs) or high grade endometrioid ovarian cancers (HGEOCs) may nevertheless in part share gene signatures that have been described in HGSOCs. For instance, we thought it would be important to know if gene signatures characterizing an immunoreactive or mesenchymal subtype can also be found in HGEOCs or HGCCOCs because the evolving molecular signatures are becoming increasingly clinically relevant. In the present study we, therefore, examined the transcriptional profiles of 276 ovarian cancer cases including 37 HGCCOCs, 66 HGEOCs and 173 previously published HGSOCs using Agilent Whole Human Genome 4x44K Expression Arrays [3]. All low grade tumors were excluded from this study as they are known to represent distinct biologic entities [11]. We applied the pre-specified TCGA gene expression signatures and the reduced CLOVAR gene signatures to this cohort of 276 well annotated OCs from Mayo Clinic. Moreover, we also performed single sample gene set enrichment analysis (ssGSEA) which calculates separate enrichment scores for each sample and allows the assignment to the nearest TGCA subgroup.

Section snippets

Patient cohort

Fresh frozen tumors were collected from a series of 276 consecutive women with high grade serous, clear cell and endometrioid ovarian, primary peritoneal or fallopian tube cancer who underwent surgery by a gynecologic oncologist at Mayo Clinic between 1994 and 2005. All patients signed an Institutional Review Board approved consent for bio-banking, clinical data extraction, and molecular analysis. Clinical data were abstracted from medical records and tumor registry. Thirteen patients (7.5%)

Results

We used Agilent microarrays to determine gene expression profiles of 276 well annotated OCs including 37 HGCCOCs and 66 HGEOCs and 173 HGSOCs. Patient and disease characteristics for the entire cohort and the histologic subtypes are shown in Table 1. Median patient age was 63 years (range 24–89). In the overall cohort of 276 patients 56 (21%) of the patients had early stage (FIGO I or II) disease, while 220 (79%) were diagnosed with advanced stage disease (FIGO III or IV). In the cohort of

Discussion

We tested the hypothesis whether gene expression based molecular subtyping of epithelial ovarian cancer developed for high grade serous histology could be applied to high grade endometrioid and clear cell histologies. Using a gene set representing the1500 genes described by the TCGA that defined the immunoreactive, differentiated, proliferative and mesenchymal subtypes, consensus NMF revealed six distinct expression subtypes. In addition to the four TCGA subtypes we describe an

Conflict of interest

The authors declare that there are no conflicts of interest.

Acknowledgements

This work is supported by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Thelma L. Culverson Endowed Cancer Research Fund, and the Stranahan Foundation for Translational Cancer Research and Advanced Clinical Cancer Research. Funding was also provided by the Fred C. and Katherine B. Andersen Foundation, the US National Institute of Health (P50 163393, R01 CA122443) and Mayo Clinic Ovarian Cancer SPORE (P50 CA136393).

References (25)

  • K.K. Zorn et al.

    Gene expression profiles of serous, endometrioid, and clear cell subtypes of ovarian and endometrial cancer

    Clin. Cancer Res.

    (2005)
  • R.T. Marquez et al.

    Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon

    Clin. Cancer Res.

    (2005)
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