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. 2016 Aug;48(8):848-55.
doi: 10.1038/ng.3602. Epub 2016 Jun 27.

The Genomic Landscape and Evolution of Endometrial Carcinoma Progression and Abdominopelvic Metastasis

Free PMC article

The Genomic Landscape and Evolution of Endometrial Carcinoma Progression and Abdominopelvic Metastasis

William J Gibson et al. Nat Genet. .
Free PMC article


Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.

Conflict of interest statement

Competing Financial Interests

The authors declare no competing financial interests.


Figure 1
Figure 1. Samples assessed
(a) Anatomic sites from which samples were obtained. (b) Histologic subtypes (EN: endometrioid, CC: clear cell, S: serous and U: undifferentiated carcinomas, and CS: carcinosarcoma), grade, FIGO 2009 stage at primary diagnosis, time of metastatic lesion sampling, and treatment after primary diagnosis. Asterisks indicate four cases that were clinically difficult to distinguish as metastatic or independent synchronous primary cancers at time of resection.
Figure 2
Figure 2. Somatic genetic alterations in complex atypical hyperplasias and primary and metastatic endometrial carcinomas
(a) Number of exonic mutations (top) and SCNAs (middle) detected in each tumor biopsy. PTEN, TP53, and 1q amplification status, histologic subtype, TCGA annotation, and tissue type are indicated on the bottom. (b) Number of mutations (y-axis) against fraction of the genome affected by SCNAs (x-axis) across complex atypical hyperplasias (green), primary lesions from endometrioid endometrial carcinoma (red) and non-endometrioid endometrial carcinoma (blue); primaries from our dataset (squares) and TCGA (dots). (c) Number of mutations detected in the primary tumor compared to their metastatic counterpart. (d) Fraction of the genome affected by SCNAs in metastases (y-axis) relative to paired primaries (x-axis). Circles indicate metastases that exhibit whole-genome doubling not observed in the primary biopsy. (e) Stick plot depicting detected mutations in NRIP1, a cofactor of the estrogen receptor. (f) Impact of indel rescue on the percentage of patients harboring mutations in known driver genes.
Figure 3
Figure 3. Heterogeneity among somatic mutations
Fractions of (a) all mutations and (b) driver mutations detected in metastases that were truncal. Lines indicate the mean. (c) The number truncal and branch mutations involving the indicated driver genes. (d) Percentage of mutations that were detected in all paired biopsies in our dataset for frequently mutated driver genes. ARID1A is frequently mutated in the branches of phylogenies. (e) Distribution of cancer cell fraction (CCF) values for each detected mutation in TCGA endometrial samples for the indicated genes. Bars indicate 95% confidence intervals. (f) Distribution of the probability that each mutation detected in TCGA endometrial biopsies is clonal for the indicated genes. Hypermutated samples (> 1,000 mutations) were excluded from (e) and (f)
Figure 4
Figure 4. Phylogenetic trees for tumors with more than one metastasis
(a) The labeled alterations constitute a subset of the alterations that distinguish between the indicated branches. Hash symbols indicate trees that were derived from SNP6.0 array data. (b) 2D phylogenetic illustration comparing subclonal structures between biopsies in patient EC-007. Cancer cell fraction (CCF) probability densities for the mutations supporting the metastasizing subclone (purple) are presented in Supplementary Figure 16. (c) Phylogenetic tree of patient EC-007. A subclone in the biopsy of the primary tumor shared a common ancestor with the two metastases, not detected in the dominant clone of the primary biopsy. Subclone 2 from (b) could be placed in three different phylogenetic locations as indicated by the dotted purple lines.

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