In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 2417-2417
Abstract:
High-grade serous ovarian cancers (HGSOCs) are the most common subtype of epithelial ovarian cancer. Pathways driving HGSOC development are poorly understood, and the cellular origins are debated in the literature. Previously, ovarian surface epithelial cells (OSECs) were thought to be cellular precursors of HGSOC, but there is now strong evidence that at least half of all HGSOCs arise from fallopian tube secretory epithelial cells (FTSECs). We took a large-scale integrated transcriptomic-epigenomic profiling approach to defining the molecular hallmarks of HGSOC and to explore the disease cell-of-origin. RNA sequencing was performed on 121 OSEC cultures and 84 FTSEC cultures and integrated with 394 HGSOC transcriptomes profiled by TCGA. We identified around 100 genes that differentiate OSECs and FTSECs, and pathway analysis of this gene list identified ovarian cancer genes as highly enriched (p=2.2x10-8), with ZEB1 and estrogen the most significant predicted upstream regulators (P & lt;3.7x10-7). We integrated gene expression data with clinical metadata to identify associations between gene expression signatures and clinical variables and found that in patients diagnosed with ovarian cancer, OSEC and FTSEC profiles converged, suggestive of a field cancerization phenotype occurring in the normal OSECs on the unaffected ovary contralateral to a clinically diagnosed ovarian carcinoma. Transcriptomic signatures for OSECs, FTSECs and HGSOCs were then merged with superenhancers defined by performing chromatin immunoprecipitation data for acetylated H3K27 profiled in primary HGSOC tissue specimens. We detected many more superenhancer-target gene relationships in the normal cells than in the tumor cells, suggesting superenhancer fingerprints define the cell of origin rather than determining upregulation of oncogenes driving cancer. To explore this further we determined the similarities of HGSOCs to OSEC and FTSEC using a machine learning model. Using a pre-defined gene signature of OSECs and FTSECs, our model (high specificity and sensitivity; 95% CI = 0.77-1, p-value=6.1-5) was applied to HGSOCs and we observed that the majority of HGSOCs were classified as FTSEC-like. Interestingly, the mesenchymal subtypes were enriched as FTSEC-like. Moreover, a subset of HGSOCs were characterized as OSEC-like, and these tumors were associated with poorer outcomes. Our data describe molecular subgroups within HGSOC precursor tissues as well as defining the transcriptional networks that define HGSOC precursor tissues, drive HGSOC development; furthermore we describe the interplay between the epigenetic landscape and the transcriptome in these cell types. In closing, these large-scale integrative analyses support a predominantly FTSEC origin for HGSOCs, but reinforce conclusions that OSECs cannot be excluded as origins of HGSOC, and may represent a subset of tumors with a different biology. Citation Format: Kate Lawrenson, Marcos Abraao, Felipe Segato, Janet M. Lee, Simon Coetzee, Ji-Heui Seo, Matthew L. Freedman, Dennis Hazelett, Simon Gayther, Houtan Noushmehr. Large scale integrated transcriptomic and epigenetic profiling defines the molecular hallmarks of HGSOC and disease origins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2417. doi:10.1158/1538-7445.AM2017-2417
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2017-2417
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2017
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
