Molecular profiling and molecular classification of endometrioid ovarian carcinomas

Abstract

Objective: Endometrioid ovarian carcinomas (EOCs) comprise 5-10% of all ovarian cancers and commonly co-occur with synchronous endometrioid endometrial cancer (EEC). We sought to examine the molecular characteristics of pure EOCs in patients without concomitant EEC.

Methods: EOCs and matched normal samples were subjected to massively parallel sequencing targeting 341-468 cancer-related genes (n = 8) or whole-genome sequencing (n = 28). Mutational frequencies of EOCs were compared to those of high-grade serous ovarian cancers (HGSOCs; n = 224) and EECs (n = 186) from The Cancer Genome Atlas, and synchronous EOCs (n = 23).

Results: EOCs were heterogeneous, frequently harboring KRAS, PIK3CA, PTEN, CTNNB1, ARID1A and TP53 mutations. EOCs were distinct from HGSOCs at the mutational level, less frequently harboring TP53 but more frequently displaying KRAS, PIK3CA, PIK3R1, PTEN and CTNNB1 mutations. Compared to synchronous EOCs and pure EECs, pure EOCs less frequently harbored PTEN, PIK3R1 and ARID1A mutations. Akin to EECs, EOCs could be stratified into the four molecular subtypes: 3% POLE (ultramutated), 19% MSI (hypermutated), 17% copy-number high (serous-like) and 61% copy-number low (endometrioid). In addition to microsatellite instability, a subset of EOCs harbored potentially targetable mutations, including AKT1 and ERBB2 hotspot mutations. EOCs of MSI (hypermutated) subtype uniformly displayed a good outcome.

Conclusions: EOCs are heterogeneous at the genomic level and harbor targetable genetic alterations. Despite the similarities in the repertoire of somatic mutations between pure EOCs, synchronous EOCs and EECs, the frequencies of mutations affecting known driver genes differ. Further studies are required to define the impact of the molecular subtypes on the outcome and treatment of EOC patients.

Keywords: Endometrioid ovarian cancer; Heterogeneity; Massively parallel sequencing; Molecular subtypes; Somatic mutations.

Conflict of interest statement

CONFLICT OF INTEREST

M.M. Leitao Jr is an ad hoc speaker for Intuitive Surgical, Inc. C. Aghajanian reports personal fees from Tesaro, Immunogen, Clovis, Mateon Therapeutics, Cerulean Pharma, and grants from Clovis, Genentech, AbbVie and Astra Zeneca, outside the submitted work. N.R. Abu-Rustum reports grants from Stryker/Novadaq, Olympus and GRAIL paid to the institution, outside the submitted work. S.P. Shah is founder, shareholder and consultant of Contextual Genomics Inc., outside the submitted work. The remaining authors have no conflicts of interest to declare.

Copyright © 2019 Elsevier Inc. All rights reserved.

Figures

Figure 1.. Histologic features of endometrioid adenocarcinomas of the ovary.

(A) Well-differentiated endometrioid adenocarcinoma of the ovary arising in a background of endometriosis. (B) Higher power micrograph of a well-differentiated endometrioid ovarian carcinoma. (C) Well-differentiated endometrioid adenocarcinoma of the ovary with mucinous differentiation. (D) Well-differentiated endometrioid ovarian carcinoma with squamous differentiation. Scale bars, 500 μm.

Figure 2.. Non-synonymous somatic mutations identified in endometrioid ovarian carcinomas using targeted massively parallel sequencing.

Recurrent (n≥2) non-synonymous somatic mutations identified in 36 endometrioid epithelial ovarian cancers by massively parallel sequencing targeting 341 cancer-related genes. Mutation types are color-coded according to the legend. The phenobar provides information on FIGO stage, microsatellite instability (MSI) status and sequencing modality. Indel, small insertion/ deletion; SNV, single nucleotide variant.

Figure 3.. Comparison of the mutational profiles of pure endometrioid ovarian cancers with high-grade serous ovarian cancers, endometrioid endometrial cancers and synchronous endometrioid ovarian cancers.

The repertoire of somatic mutations affecting the 341 genes included in the MSK-IMPACT assay (smallest gene panel) in (A) pure microsatellite-stable/ POLE wild-type endometrioid epithelial ovarian cancers (EOCs) (n=28) and in high-grade serous ovarian cancers from The Cancer Genome Atlas (TCGA; n=224)[9] (B) all pure EOCs (n=36) and endometrioid endometrial cancers (EECs; TCGA; n=186)[8], and (C) all pure EOCs (n=36) and EOCs synchronously diagnosed with EECs (n=23)[14]. (D) Mutation frequencies of KRAS, PIK3CA, PTEN, CTNNB1, ARID1A and PIK3R1 in the pure EOCs studied here (n=36), in EECs (n=186, TCGA)[8] and EOCs synchronously diagnosed with EECs (synchronous EOCs; n=23)[14]. Comparisons were performed using Fisher’s exact test. (A and B) Benjamini-Hochberg adjusted statistically significant p-values (adjusted p<0.05) are shown in red bold font, (C) unadjusted statistically significant p-values (p<0.05) are shown in blue bold font.

Figure 4.. Molecular subtyping of endometrioid ovarian cancers.

(A) Surrogate classifier employed for the molecular subtyping of endometrioid epithelial ovarian cancers (EOCs), based on the molecular subtypes described for endometrial cancers by The Cancer Genome Atlas [8,26]. (B), Molecular subtype distribution in EOCs from this study (left) and in endometrioid ovarian cancers from TCGA (right) [8]. (C) Kaplan-Meier progression-free survival curve for EOC patients stratified according to the endometrial cancer molecular subtypes defined with a surrogate model. Two cases (one of POLE subtype and one of CN-high (serous-like) subtype) were excluded due to limited/ lack of follow-up information. P-values of the log-rank test are shown. CN, copy-number.