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Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to emergence of treatment-resistant sub-clones. We sought to measure the degree of genomic diversity within primary, untreated HGSC to examine the natural state of tumor evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on thirty-one spatially and temporally separated HGSC tumor specimens (six patients) including ovarian masses, distant metastases, and fallopian tube lesions. We found widespread intra-tumoral variation in mutation, copy number, and gene expression profiles, with key driver alterations in genes present in only a subset of samples (e.g. PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range: 10.2% to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology with common etiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating diversity arises at early stages of tumorigenesis. Our results reveal that HGSC exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug resistance mechanisms.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001000669 Illumina Genome Analyzer 25
EGAD00001000974 Illumina HiSeq 2000 Illumina MiSeq 131
EGAD00001000978 Illumina HiSeq 2000 48
EGAD00010000500 Affymetrix_U133plus2- 35
EGAD00010000502 Affymetrix_U133plus2- 35
EGAD00010000504 Affymetrix_U133plus2- 35
Publications Citations
Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling.
J Pathol 231: 2013 21-34
TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data.
Genome Res 24: 2014 1881-1893
Inferring parsimonious migration histories for metastatic cancers.
Nat Genet 50: 2018 718-726
Phylogenetic Tree Inference: A Top-Down Approach to Track Tumor Evolution.
Front Genet 10: 2019 1371