• 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2020-03
  • 2020-07
  • 2020-08
  • 2021-03
  • br In a recent study of gynecologic and


    In a recent study of gynecologic and breast cancers by TCGA, MSI-high ECs were found to often display DNA MMR mutational signatures [11], however a detailed systematic evaluation of the mutational signa-tures in ECs has not been performed to date. In addition, in other cancer types, there is evidence to suggest that the dominant mutational signa-tures present in the primary tumors may differ from those identified in the metastatic lesions from the same patients [12,13], a phenomenon that has yet to be investigated in EC. Hence, in this study, we sought to define the mutational signatures of i) endometrioid and serous ECs stratified into the four molecular subtypes, ii) uterine carcinosarcomas, a histologic EC subtype associated with poor outcome, and iii) primary ECs matched to their metastatic lesions.
    2. Material and methods
    2.1. Whole-exome sequencing (WES) data from TCGA
    The recently updated WES-derived somatic mutation MC3 data [14] of the 232 endometrioid and serous ECs with molecular subtype 
    2.2. Mutational signatures
    Mutational signatures were defined by deconstructSigs using all SNVs [17] at default parameters, as previously described [18], for sam-ples with ≥20 somatic SNVs [19].
    2.3. MSIsensor and MLH1 promoter methylation scores
    For the quantification of microsatellite instability (MSI), MSIsensor was employed, as described by Niu et al. [20], and samples with an MSIsensor score ≥ 3.5 were deemed MSI-high. Level 3 Illumina HumanMethylation450K methylation data for endometrioid and serous ECs with molecular subtype classification (n = 232) [3] and uterine car-cinosarcomas (n = 57) [5] were obtained from the TCGA GDC Legacy Archive. A beta-value threshold of b0.3 was used for unmethylated DNA/CpG locus, as described [21].
    2.4. Large-scale state transitions (LSTs), mutations affecting homologous recombination (HR) DNA repair genes and Aprotinin length
    LST scores, a genomic feature of HR deficiency (cut-off ≥15) [22], and information on bi-allelic somatic and germline pathogenic mutations in a curated list of 102 HR-related DNA repair genes in copy-number high (serous-like) ECs, HGSOCs and basal-like breast cancers were obtained from Riaz et al. [23]. In addition, the length of small deletions (indels) was assessed in these tumors, as HR-defective cancers have been shown to have an enrichment for deletions ≥5 bp [24].
    2.5. WES analysis of primary and matched metastatic ECs
    WES data in the form of Binary Sequence Alignment Map (BAM) files from primary ECs and matched metastatic lesions from 26 EC pa-tients described by Gibson et al. [6] were obtained from the database of Genotypes and Phenotypes (dbGaP; accession phs001127.v1.p1). Se-quencing data analysis was performed as previously described [18] (Supplementary Methods). Only somatic mutations with ≥20 reads in the respective normal samples were considered. Somatic copy number alterations and loss of heterozygosity (LOH) were defined using FACETS [25], as previously described [18]. The cancer cell fractions (CCFs) of all mutations were computed using ABSOLUTE (v1.0.6) [26], as previously described [18].
    2.6. Phylogenetic tree construction
    A given mutation was considered “shared” if it was present in both the primary and metastatic lesion. We defined mutations “private to the primary lesion” and “private to the metastatic lesion” as those pres-ent only in the primary tumor or only in the metastasis, respectively. Mutational signatures were defined for shared and private mutations separately using deconstructSigs [17] as described above, for cases with ≥20 shared and/or private SNVs. To reconstruct the phylogeny of the primary and matched metastatic ECs we used Treeomics [27] based on all synonymous and non-synonymous mutations identified, as previously described [18].
    2.7. Statistical analyses
    Comparisons of LST scores and indel length between different tumor types were performed using the Mann-Whitney U test.
    Associations between specific clinicopathologic features/molecular features/molecular signatures and molecular subtypes were tested using Fisher's exact tests. Progression-free survival curves were calcu-lated using the Kaplan–Meier method with the Aprotinin log-rank test. p-values of b0.05 were considered statistically significant. Statistical analyses were performed using IBM SPSS v24.0.0.0 and Prism 7.
    3. Results
    3.1. Mutational signatures of primary endometrioid and serous ECs strati-fied according to molecular subtypes
    We first defined whether primary treatment-naïve endometrioid and serous ECs from TCGA stratified according to the molecular sub-types would have distinct mutational signatures. This analysis revealed that 76% (13/17) of the ECs of POLE (ultramutated) subtype had a dom-inant signature 10 associated with POLE mutations [28]. The majority of ECs of MSI (hypermutated) subtype (85%; 55/65) had a dominant mu-tational signature associated with defective DNA MMR (53/65, signa-ture 6; 1/65, signature 15; 1/65, signature 26; Fig. 1a; Supplementary Figs. S1 and S2). Conversely, the majority of ECs of copy-number low (endometrioid) and copy-number high (serous-like) subtypes had the aging-related signature 1 as the most prevalent dominant mutational signature (88%, 79/90 and 70%, 42/60, respectively; Figs. 1 and 2, Sup-plementary Figs. S1 and S3).