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. 2015 Aug 7;7(1):87.
doi: 10.1186/s13073-015-0210-y. eCollection 2015.

Mutational landscape of mucinous ovarian carcinoma and its neoplastic precursors

Georgina L Ryland  1 , Sally M Hunter  1 , Maria A Doyle  2 , Franco Caramia  2 , Jason Li  2 , Simone M Rowley  1 , Michael Christie  3 , Prue E Allan  4 , Andrew N Stephens  5 , David D L Bowtell  6 ; Australian Ovarian Cancer Study Group; Ian G Campbell  7 , Kylie L Gorringe  7
Affiliations

Mutational landscape of mucinous ovarian carcinoma and its neoplastic precursors

Georgina L Ryland et al. Genome Med. .

Erratum in

Abstract

Background: Mucinous ovarian tumors are an unusual group of rare neoplasms with an apparently clear progression from benign to borderline to carcinoma, yet with a controversial cell of origin in the ovarian surface epithelium. They are thought to be molecularly distinct from other ovarian tumors but there have been no exome-level sequencing studies performed to date.

Methods: To understand the genetic etiology of mucinous ovarian tumors and assess the presence of novel therapeutic targets or pathways, we undertook exome sequencing of 24 tumors encompassing benign (5), borderline (8) and carcinoma (11) histologies and also assessed a validation cohort of 58 tumors for specific gene regions including exons 4-9 of TP53.

Results: The predominant mutational signature was of C>T transitions in a NpCpG context, indicative of deamination of methyl-cytosines. As well as mutations in known drivers (KRAS, BRAF and CDKN2A), we identified a high percentage of carcinomas with TP53 mutations (52 %), and recurrent mutations in RNF43, ELF3, GNAS, ERBB3 and KLF5.

Conclusions: The diversity of mutational targets suggests multiple routes to tumorigenesis in this heterogeneous group of tumors that is generally distinct from other ovarian subtypes.

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Figures

Fig. 1
Fig. 1
Mutational landscape of MOTs identified by exome sequencing. Samples are grouped according to pathological classification and ordered from lowest to highest mutation frequency. a Somatic mutation frequency (left Y-axis) and number of coding mutations by consequence (right Y-axis). b Relative frequency of somatic mutations according to base substitution type. Substitutions were categorized by the six possible base-pair changes
Fig. 2
Fig. 2
Candidate driver genes in MOTs. Significantly mutated genes identified by OncodriveFM and MuSiC analyses are arranged vertically by their frequency of mutated samples in the whole exome sequencing data. Color indicates mutation consequence. Selected genes were also investigated in a validation cohort of mucinous tumors. Each column denotes an individual tumor (ordered as listed in Additional file 1: Table S1), which have been arranged to emphasize mutational groups. Genomic aberrations in other MAPK pathway genes were also screened for mutations. LOH loss of heterozygosity
Fig. 3
Fig. 3
Distribution of somatic mutations identified in novel significantly mutated genes. ELF3, KLF5, GNAS and ERBB3 are shown in the context of protein domains as predicted by UniProt, with somatic mutations identified in the exome (closed circle) and validation (open circle) cohorts mapped to each gene. I-IV extracellular domains I, II, III and IV, AT hook & NLS AT-hook domain and nuclear localization signal, C2H2 zinc-finger C2H2 domain, ETS DNA binding domain, GTP GTP nucleotide binding region, PNT pointed domain, SAR serine-rich and aspartic acid-rich domain, TAD transactivation domain, TKD tyrosine kinase domain
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References

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