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. 2021 Jan 11;76:e2324. doi: 10.6061/clinics/2021/e2324

The mutational repertoire of uterine sarcomas and carcinosarcomas in a Brazilian cohort: A preliminary study

Leonardo Tomiatti da Costa I, Laura Gonzalez dos Anjos I, Luciane Tsukamoto Kagohara II, Giovana Tardin Torrezan III, Claudia A Andrade De Paula III, Edmund Chada Baracat I, Dirce Maria Carraro III, Katia Candido Carvalho I,*
PMCID: PMC7798418  PMID: 33503190

Abstract

OBJECTIVES:

The present study aimed to contribute to the catalog of genetic mutations involved in the carcinogenic processes of uterine sarcomas (USs) and carcinosarcomas (UCSs), which may assist in the accurate diagnosis of, and selection of treatment regimens for, these conditions.

METHODS:

We performed gene-targeted next-generation sequencing (NGS) of 409 cancer-related genes in 15 US (7 uterine leiomyosarcoma [ULMS], 7 endometrial stromal sarcoma [ESS], 1 adenosarcoma [ADS]), 5 UCS, and 3 uterine leiomyoma (ULM) samples. Quality, frequency, and functional filters were applied to select putative somatic variants.

RESULTS:

Among the 23 samples evaluated in this study, 42 loss-of-function (LOF) mutations and 111 missense mutations were detected, with a total of 153 mutations. Among them, 66 mutations were observed in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. TP53 (48%), ATM (22%), and PIK3CA (17%) were the most frequently mutated genes. With respect to specific tumor subtypes, ESS showed mutations in the PDE4DIP, IGTA10, and DST genes, UCS exhibited mutations in ERBB4, and ULMS showed exclusive alterations in NOTCH2 and HER2. Mutations in the KMT2A gene were observed exclusively in ULM and ULMS. In silico pathway analyses demonstrated that many genes mutated in ULMS and ESS have functions associated with the cellular response to hypoxia and cellular response to peptide hormone stimulus. In UCS and ADS, genes with most alterations have functions associated with phosphatidylinositol kinase activity and glycerophospholipid metabolic process.

CONCLUSION:

This preliminary study observed pathogenic mutations in US and UCS samples. Further studies with a larger cohort and functional analyses will foster the development of a precision medicine-based approach for the treatment of US and UCS.

Keywords: Sarcoma, Carcinosarcoma, Mutation, DNA Sequence Analysis

INTRODUCTION

Sarcomas are rare heterogeneous tumors that affect the female genital tract and originate from tissues such as muscle, fat, bones, and fibrous tissue. Uterine sarcomas (USs) are the most commonly occurring gynecological sarcomas, representing 90% of the total cases (1). Based on their histological composition, uterine tumors with mesenchymal elements can be divided into 1) pure sarcomas (uterine leiomyosarcomas - ULMSs, endometrial stromal sarcomas - ESSs); 2) mixed epithelial and mesenchymal tumors (adenosarcomas - ADSs), and 3) carcinosarcomas - UCSs, a biphasic tumor composed of high-grade carcinomatous and sarcomatous components derived from transdifferentiation of carcinoma (2). Many studies have characterized UCS tumors as mixed USs; however, since 2014, they have been reclassified as endometrial carcinomas (ECs) that demonstrate metaplastic features (3,4). Despite their low prevalence, USs are associated with high rates of local recurrence, distant metastases, and poor prognosis, with two-year survival rates below 50% (1).

Several genetic alterations have been associated with USs and UCSs, with few alterations being associated with specific histological subtypes. For instance, ESSs can be divided into two types: low-grade ESS (LG-ESS) and high-grade ESS (HG-ESS), both characterized by recurrent chromosomal translocations. In LG-ESS, the most common translocation, t [7; 17] (p15; q21), is observed in almost 50% of the cases and results in the JAZF1-SUZ12 gene fusion (5). Ma et al. (6), revealed that the JAZF1-SUZ12 fusion protein destabilizes polycomb repressive complex 2 (PRC2), abolishes histone methyltransferase (HMT) activity, and subsequently activates genes normally repressed by PRC2. JAZF1-PHF1, EPC1-PHF1, PHF1-MEAF6, MBTD1-CXorf67, and JAZF1-BCORL1 are other less frequent fusion proteins observed in the patients with these tumors. HG-ESS exhibits a YWHAE-NUTM2 gene rearrangement (previously termed YWHAE-FAM22). Recently, molecular alterations in ZC3H7B-BCOR, BCOR-ITD, EPC1-BCOR, JAZF1-BCORL1, and BRD8-PHF1 have been identified. This histological subtype demonstrates more aggressive clinical behavior and worse prognosis (5,2). Many previous studies have investigated the ESS genome with a focus on genetic fusions (7-10). However, Choi et al. (11) demonstrated that fusions are not the only genetic alterations that occur during the development of ESS. Using whole-exome sequencing methods, the aforementioned study described mutations in PTEN, RB1, TP53, and CDH1. Despite the use of a very small number of ESS samples in this study (3 LG-ESS), it is a valuable contribution to the understanding of the pathogenesis of such tumors.

ULMSs are not characterized by specific chromosome translocations; however, they are associated with a complex karyotype with chromosomal gains and losses, such as deletion in chromosome 1. Most ULMSs express PDGFR-α, WT1, CYP19, and GNRH-R (12,13). Owing to gene alterations, the loss of function in the tumor suppressor genes, BRCA1 and MED12 as well as the loss of expression of the proteasome β1i subunit LMP2 have been associated with ULMS development (14). Additionally, The Cancer Genome Atlas (TCGA) Research Network (15) examined the molecular characterization of adult soft tissue sarcomas (STSs) and observed that ULMSs shared more similarities with extrauterine LMSs than that with other sarcomas. Although both tumors exhibit the same pattern of cell differentiation, their tumor environments are extremely diverse. This study included 53 cases of soft-tissue LMS (extrauterine) and 27 ULMS cases that were evaluated by whole-exome sequencing, demonstrating frequent alterations in TP53, RB1, ATRX, and MED12 (16).

Somatic mutations have also been described occurring at low frequency in the majority of the tyrosine kinase growth factor gene family and their targets, namely, v-raf murine sarcoma viral oncogene homolog B1 (BRAF), CDKN2A, epidermal growth factor receptor (EGFR), HER2, v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog (KIT), v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS), platelet-derived growth factor receptor (PDGFR), and phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit α (PI3KCA) during the development of UCS. In addition, mutations in TP53, PTEN, protein phosphatase 2 scaffold subunit alpha (PPP2R1A), F-box, and WD repeat domain containing 7 (FBXW7) have already been identified, which may contribute to the development of therapeutic alternatives including the use of the inhibitors of PARP, EZH2, cell-cycle, and PI3K pathway (14,17). Little information is available on how mutations contribute to ADS etiology; however, one study observed that DICER1 mutations are associated with the tumorigenic process in a small subset of such tumors (18).

Since these are rare tumors, only a few studies focusing on the definition of the mutational repertoire of the different histological types of rare sarcomas have been conducted thus far. Therefore, studies focusing on the mutational characterization of these tumors are of paramount importance and will contribute to the discovery of new biomarkers for precision medicine-based approaches in the treatment of such neoplasms. Herein, we investigated the mutational profile of the samples obtained from patients with ULMSs, UCSs, ESSs, and ADSs, using a commercial panel containing 409 cancer-associated genes involved in apoptosis, signaling, transcription regulation, inflammation response, and growth factors-associated pathway.

MATERIALS AND METHODS

Sample selection

In order to analyze differences in genetic mutations between different histological types of US, we initially selected 43 formalin-fixed and paraffin-embedded (FFPE) human samples including 14 ULMS, 12 ESS, 2 ADS, 12 UCS, and 3 ULM-non-cancerous tumor (as reference samples). All samples were obtained via surgical procedures performed between 2000 and 2012 at the Institute of Cancer of Sao Paulo (ICESP) and Clinics Hospital of the Faculty of Medicine, University of Sao Paulo (HCFMUSP). Tissues were stored at the molecular and structural gynecology laboratory (LIM-58) of the University of Sao Paulo Medical School (FMUSP).

This study was performed in accordance with the Declaration of Helsinki and was approved by the Research Ethics Committee of the FMUSP with protocol number 477/15. Patients' medical records were revised and the following data were recorded: age at diagnosis, postmenopausal bleeding, adjuvant treatment, presence of metastasis or recurrence, and status.

DNA Isolation

Genomic DNA was extracted using the QIAamp DNA FFPE Tissue Kit obtained from QIAGEN® according to the manufacturer’s instructions. DNA concentration, purity, and integrity were assessed by spectrophotometry (Nanodrop 2000, Thermo Fisher Scientific) and fluorometry (Qubit - Thermo Fisher Scientific), respectively.

Preparation of sequencing libraries and Next-Generation Sequencing (NGS)

Sequencing libraries were prepared using the Ion Torrent Ampliseq Comprehensive Cancer Panel - Catalog number: 4477685 (Thermo Fisher Scientific), which contains ∼16,000 primer pairs multiplexed into 4 pools. This commercial panel was designed to assess the mutational profile of 409 cancer driver genes and drug targets along with signaling cascades, apoptosis genes, DNA repair genes, transcription regulators, inflammatory response genes, and growth factor genes (Table S1). Prior to amplification, DNA was treated with the uracil-DNA glycosylase enzyme (Thermo Fisher Scientific) by adding 1 unit of enzyme per 50 ng of DNA and incubating for 15 min at 37 °C. This procedure was performed to remove DNA molecules containing uracil and decrease the number of artifactual variants in the sequencing (19). Libraries were then prepared using Ion AmpliSeqTM Library kit 2.0 protocols, with 10 ng of input DNA per pool, totaling 40 ng of DNA from each sample. The FuPa reagent was used to partially digest primer sequences and phosphorylate the amplicons. Next, sequencing adaptors and barcodes were ligated to the amplicon by the enzyme Ligase using the Ion Xpress™ Barcode Adapters kit (Thermo Fisher Scientific), which were then purified using magnetic beads (Agencourt® AMPure® XP Reagents, Beckman Coulter). Subsequently, emulsion PCR was performed using the Ion PI™ Hi-Q™ OT2 200 Kit (Thermo Fisher Scientific), followed by sequencing with Ion PITM Hi-QTM sequencing 200 and Ion PITM Chip.

Data Analysis

The results were analyzed using the Torrent Suite v5.0.5 software (Thermo Fisher Scientific). Sequence variants (SNVs and indels) were identified using the Torrent Variant Caller (Ion Torrent - Thermo Fisher Scientific) and compared to the GRCh37 / hg19 genome version. VCF files were analyzed using VarSeq v1.8 software (GoldenHelix) for variant annotation and prioritization. The variants were filtered based on the quality and frequency criteria: coverage (>100), genotype quality score cutoff (GQS>50), variant base in at least 5% of reads, variant base present in at least 2 reads in each direction, homopolymer-length error<5, absence of genetic variants in population databases (ExAC; NHLBI-ESP; 1000 Genomes Project) or minor allele frequency (MAF)≤0.01%.

Subsequently, variants were selected based on their effect on protein expression, with the following being considered: 1) variants described in the COSMIC database; 2) loss-of-function variants - Frameshift variants-nucleotide insertions/deletions, gain/loss of stop codons, splice site alterations); or 3) missense variants (in-frame insertions/deletions, amino acid exchange) predicted as possibly pathogenic in at least three of six prediction programs used (SIFT, PolyPhen, MutationTaster, MutationAssessor, FATHMM, FATHMM-MKL) and occurring in oncogenes or tumor suppressor genes in OncoMD database. Variants not previously described in the COSMIC database were visually inspected using the integrative genomics viewer (IGV) program to exclude sequencing artifacts.

Construction of genetic interaction networks was performed using Cytoscape platform version 3.7.0, which uses data from protein and genetic interactions, pathways, co-expression, co-localization, and protein domain similarity.

RESULTS

Initially, 40 US and UCS (14 ULMS, 12 ESS, 2 ADS, and 12 UCS) and 3 ULM samples were selected from the pathology department files; however, only 23 (7 ULMS, 7 ESS, 1 ADS, 5 UCS, and 3 ULM) remained until the end of NGS analyses. Some losses occurred while performing multiplex PCR reactions (AmpliSeq™), during which we observed a high degree of fragmented DNA and many genetic artifacts in several samples. These issues are expected since tissue processing for paraffin inclusion and long storage time causes damage to the DNA structure (integrity). The clinical and pathological features of 40 patients with US and UCS who were enrolled in this study are summarized in Table 1.

Table 1. Clinical and pathological features of US and UCS patients (n=40).

Variables Categories US/UCS n (%)
Age >50 years 33 (82)
≤50 years 7 (18)
N.A. 0 (0)
Postmenopausal Bleeding Yes 22 (55)
No 13 (33)
N.A. 5 (12)
Adjuvant Treatment No 8 (20)
RT 19 (47)
CT 8 (20)
RT+CT 5 (13)
N.A. 0 (0)
Metastasis or Recurrence Yes 22 (55)
No 14 (35)
N.A. 4 (10)
Status Alive 11 (27)
Death 23 (58)
Loss of follow-up 6 (15)
N.A. 0 (0)

radiotherapy (RT); chemotherapy (CT); not available (NA); uterine sarcomas (US).

*ULM samples were not included owing to their benign characterization.

Among the 23 samples deemed suitable for the evaluation of sequencing data, homogeneity average was 73.2%, median base coverage was 1257X, and horizontal coverage was 84.3% corresponding to 100X. Based on the NGS data, we selected point mutations with possible impacts on the function of the protein encoded by the altered gene (missense, nonsense, splice-site mutations, loss of stop codons) and small insertions and deletions (indels). Total variants detected in each sample and filtered variants for the selection of somatic alterations of interest are presented in Table 2.

Table 2. Total variants obtained after filtering performed to increase the specificity of NGS results (higher stringency).

General (pre-filters) Selected Variants
Samples Total SNV Insertions Deletions LOFs Missense Cosmic
ESS 2 2347 2257 40 50 1 6 5
ESS 3 1551 1473 31 47 2 6 4
ESS 4 1249 1162 36 51 1 1 1
ESS 5 1416 1324 36 56 0 4 3
ESS 7 1494 1397 40 57 2 2 1
ESS 9 1421 1343 35 43 1 6 5
ESS 10 1440 1329 35 76 4 6 6
UCS 2 1332 1223 47 62 3 4 4
UCS 5 1362 1271 42 49 7 13 7
UCS 9 1972 1884 42 46 1 6 4
UCS 13 1234 1150 36 48 1 6 4
UCS 19 1604 1516 33 55 1 3 3
ULMS 38 746 678 43 25 0 7 4
ULMS 39 1768 1688 34 46 1 2 2
ULMS 40 1296 1193 42 61 2 3 1
ULMS 45 2004 1921 36 47 2 3 1
ULMS 52 2806 2746 23 37 0 11 6
ULMS 50 2842 2651 77 114 0 1 0
ULMS 59 2132 1968 76 88 4 6 2
ADS 2 3521 3406 41 74 6 10 0
ULM 119 1298 1201 37 60 1 1 0
ULM 143 981 919 33 29 1 2 2
ULM 152 1297 1237 25 35 1 2 1

*Endometrial stromal sarcoma (ESS); Uterine carcinosarcoma (UCS); Uterine leiomyosarcoma (ULMS); Adenocarcinoma (ADS); Uterine leiomyoma (ULM).Single nucleotide variant (SNV); Loss of function (LOFs); Catalogue of Somatic Mutations in Cancer (COSMIC).

An average of 1700 alterations were identified per sample (ranging from 746 to 3521), with an average of 1606 single nucleotide variants (SNVs) (ranging from 678 to 3406), 40 insertions (ranging from 23 to 77), and 55 deletions (ranging from 25 to 114). To select relevant somatic variants, a first filter was applied focusing on the quality and frequencies of these alterations. A second filter, focusing on variant functions and effects, was used to select the alterations that would be most relevant in alterations of gene functions. Collectively, in 23 samples that were evaluated, 42 LOF mutations and 111 missense mutations were detected, with a total of 153 filtered mutations, among which 66 were found in the COSMIC database (Table 2).

Among the 409 genes included in the panel, mutations were detected in 94 distinct genes, with 30 genes demonstrating mutations in more than one sample and 64 genes showing mutations in a single sample. Table 3 presents the list of genes that were mutated in more than one sample of the cohort, along with the number of mutated samples and the histological types. TP53 (11/23 - 48%), ATM (5/23 - 22%), and PIK3CA (4/23 - 17%) were the most frequently mutated genes.

Table 3. Gene mutations observed in more than one sample and histological subtypes.

Gene Mutated samples n (%) Histological Types (ULMS/ESS/UCS/ADS/ULM)
TP53 11 (48%) 4 ULMS, 3 ESS, 4 UCS
ATM 5 (22%) 2 ULMS, 2 ESS, 1 UCS
PIK3CA 4 (17%) 1 ESS, 3 UCS
KMT2D 3 (13%) 1 ULMS, 1 ESS, 1 UCS
MTOR 3 (13%) 1 ESS, 1 UCS, 1 ULM
JAK3 3 (13%) 1 ULMS, 1 ESS, 1 ULM
APC 3 (13%) 1 ULMS, 2 ESS
DICER1 3 (13%) 1 ESS, 2 UCS
TRRAP 3 (13%) 2 UCS, 1 ADS
TSC2 3 (13%) 2 ULMS, 1 ADS
PDE4DIP 3 (13%) 3 ESS
AR 2 (9%) 1 ESS, 1 UCS
ATRX 2 (9%) 1 ULMS, 1 ESS
CREBBP 2 (9%) 1 ULMS, 1 ESS
DNMT3A 2 (9%) 1 UCS, 1 ADS
EPHA7 2 (9%) 1 UCS, 1 ADS
KAT6B 2 (9%) 1 UCS, 1 ADS
KMT2A 2 (9%) 1 ULMS, 1 ULM
MET 2 (9%) 1 UCS, 1 ULM
MYB 2 (9%) 1 ULMS, 1 ESS
NOTCH1 2 (9%) 1 ULMS, 1 UCS
PRKDC 2 (9%) 1 UCS, 1 ADS
SYNE1 2 (9%) 1 ULMS, 1 ESS
NF1 2 (9%) 1 ESS, 1 UCS
NOTCH2 2 (9%) 2 ULMS
HER2 2 (9%) 2 ULMS
ERBB4 2 (9%) 2 UCS
DAXX 2 (9%) 1 ESS, 1 ADS
ITGA10 2 (9%) 2 ESS
DST 2 (9%) 2 ESS

The Venn diagram (Figure 1) shows the shared and individual (specific) mutations of each malignant histological subtype evaluated (ULMS, ESS, UCS, and ADS). Three shared genes were observed (ATM, TP53, and KMT2D) among the ULMS, ESS, and UCS samples. Nineteen genes were shared between 2 types of tumors, and 68 genes were mutated in a single type. Among them, 6 genes were mutated in more than one sample of the same histological subtype, namely, PDE4DIP (3 ESS samples), ITGA10, and DST (2 ESS samples), NOTCH2, and HER2 (2 ULMS samples), and ERBB4 (2 UCS samples). Quantitatively, this analysis shows similarities in the mutational profiles of ULMS and ESS, with 6 mutated genes in common (6.7%) between both subtypes. In the genes JAK3, APC, ATRX, CREBBP, MYB, and SYNE1, most of the mutations were characterized as missense mutations; however, in the SYNE1 gene, the two mutations observed in ULMS and ESS samples were determined as LOF mutations (c.352C>T and c.8565G>A, respectively). In addition, mutations in the TRRAP, DNMT3A, EPHA7, KAT6B, and PRKDC genes indicate that UCS and ADS may exhibit molecular similarities.

Figure 1. Venn diagram (Oliveros J.C, 2015) constructed using the genetic sequencing data obtained from all samples. The numbers represent shared and individual mutations for each assessed histological type.

Figure 1

Table 4 summarizes the genes with the most frequent alterations (mutations in 2 or more samples, or with 2 mutations in the same sample), the types of mutations, and their position. Alterations in the respective proteins are also indicated, along with the combined effect of these alterations (Missense or LOF) and DNA (c.), and protein (p.) nomenclatures. Their nomenclature can be used for database searches. The descriptions of the 153 potentially somatic variants are listed in Table S2. UCS5, ULMS52, ESS58107, and ADS2 samples demonstrated the highest number of mutations (UCS5 with 20 mutations in 19 genes; ULMS52 with 11 mutations in 10 genes; ESS58107 with 10 mutations in 10 genes, and ADS2 with 16 mutations in 16 genes). Samples with the lowest number of mutations were ULMS50b with 1 mutation in ALK, ESS4 with 2 mutations (ATM and CREBBP), and ULM119 (benign tissue) with 2 mutations (MET and PDGFB).

Table 4. Most common mutations observed in the study, their chromosomal positions, effects, and nomenclature.

Sample Chr:Pos Gene HGVS c. HGVS p. Effect
UCS2 3:178921549 PIK3CA c.1031T>C p.Val344Ala Missense
6:94120318 EPHA7 c.733G>A p.Ala245Thr Missense
7:116339356 MET c.218T>A p.Leu73Ter LOF: stop - gained
8:48776121 PRKDC c.5586delT p.Phe1862Leufs LOF: frameshift
17:7577547 TP53 c.734G>T p.Gly245Val Missense
UCS5 1:11227575 MTOR c.4254-1G>A r.spl? LOF: splice - acceptor
3:178952085 PIK3CA c.3140A>G p.His1047Arg Missense
10:76735809 KAT6B c.1714C>T p.Arg572Cys Missense
11:108114777 ATM c.594C>A p.Cys198Ter LOF: stop - gained
14:95572101 DICER1 c.3007C>T p.Arg1003Ter LOF: stop - gained
17:29588751 NF1 c.4600C>T p.Arg1534Ter LOF: stop - gained
17:29665110 NF1 c.6772C>T p.Arg2258Ter LOF: stop - gained
2:25469168 DNMT3A c.1290T>G p.Asn430Lys Missense
2:212587219 ERBB4 c.782A>C p.Gln261Pro Missense
7:98513427 TRRAP c.2281C>T p.Arg761Trp Missense
X:66766207 AR c.1219C>T p.Arg407Cys Missense
UCS9 9:139391355 NOTCH1 c.6836C>T p.Ala2279Val Missense
12:49444719 KMT2D c.2747C>T p.Pro916Leu Missense
17:7578442 TP53 c.488A>G p.Tyr163Cys Missense
UCS13 3:178916854 PIK3CA c.241G>A p.Glu81Lys Missense
14:95574253 DICER1 c.2614G>A p.Ala872Thr Missense
17:7577534 TP53 c.747G>T p.Arg249Ser Missense
7:98609947 TRRAP c.11549G>A p.Arg3850His Missense
UCS19 2:212295800 ERBB4 c.2513G>A p.Arg838Gln Missense
17:7577580 TP53 c.701A>G p.Tyr234Cys Missense
ULMS38 1:120458122 NOTCH2 c.7223T>A p.Leu2408His Missense
17:37864584 HER2 c.236A>C p.Glu79Ala Missense
19:17937659 JAK3 c.3268G>A p.Ala1090Thr Missense
ULMS39 17:7577545 TP53 c.736A>G p.Met246Val Missense
ULMS40 11:108139268 ATM c.2770C>T p.Arg924Trp Missense
17:7577120 TP53 c.818G>A p.Arg273His Missense
17:37881117 HER2 c.2446C>T p.Arg816Cys Missense
X:76891445 ATRX c.4660A>T p.Arg1554Ter LOF: stop - gained
ULMS45 11:108160506 ATM c.4414T>G p.Leu1472Val Missense
17:7578290 TP53 c.560-1G>C r.spl? LOF: splice - acceptor
16:2135281 TSC2 c.4620C>A p.Tyr1540Ter LOF: stop - gained
ULMS52 1:120459251 NOTCH2 c.6094C>A p.His2032Asn Missense
9:139400980 NOTCH1 c.4013C>T p.Ala1338Val Missense
11:118377142 KMT2A c.10535C>T p.Pro3512Leu Missense
12:49416396 KMT2D c.16315C>T p.Arg5439Trp Missense
16:2130319 TSC2 c.3551C>T p.Ala1184Val Missense
16:3779521 CREBBP c.5527T>C p.Cys1843Arg Missense
16:3790470 CREBBP c.4063G>A p.Gly1355Arg Missense
17:7574017 TP53 c.1010G>A p.Arg337His Missense
ULMS59 5:112173857 APC c.2566C>T p.Arg856Cys Missense
6:135511289 MYB c.331G>A p.Gly111Ser Missense
ULMS59 6:135539101 MYB c.2269C>T p.Arg757Trp Missense
6:152832196 SYNE1 c.352C>T p.Arg118Ter LOF: stop - gained
ULMS59 20:57429026 GNAS c.706G>A p.Asp236Asn Missense
20:57480457 GNAS c.2381A>C p.Lys794Thr Missense
ESS2 (LG-ESS) 6:152706896 SYNE1 c.8565G>A p.Trp2855Ter LOF: stop - gained
11:108175463 ATM c.5558A>T p.Asp1853Val Missense
17:7577121 TP53 c.817C>T p.Arg273Cys Missense
ESS2 17:7577139 TP53 c.799C>T p.Arg267Trp Missense
ESS3 1:145015874 PDE4DIP c.214C>T p.Arg72Ter LOF: stop - gained
5:112154777 APC c.1048T>C p.Ser350Pro Missense
5:112162855 APC c.1459G>A p.Gly487Arg Missense
6:56328464 DST c.16429C>T p.Arg5477Trp Missense
12:49418436 KMT2D c.15977T>C p.Leu5326Pro Missense
17:7578176 TP53 c.672+1G>A r.spl? LOF: splice - donor
17:29556250 NF1 c.2617C>T p.Arg873Cys Missense
17:29677234 NF1 c.7355G>T p.Arg2452Leu Missense
ESS4 11:108141990 ATM c.2934delT p.Leu979Cysfs LOF: frameshift
16:3820773 CREBBP c.2678C>T p.Ser893Leu Missense
ESS5 1:11217330 MTOR c.4348T>G p.Tyr1450Asp Missense
19:17937659 JAK3 c.3268G>A p.Ala1090Thr Missense
ESS7 6:33287248 DAXX c.1885G>A p.Val629Ile Missense
14:95590677 DICER1 c.1232C>A p.Ser411Ter LOF: stop - gained
ESS7 X:76939115 ATRX c.1633C>G p.Gln545Glu Missense
ESS9 1:144906139 PDE4DIP c.2494delC p.Gln832Argfs LOF - frameshift
1:145536012 ITGA10 c.2104G>A p.Ala702Thr Missense
3:178936091 PIK3CA c.1633G>A p.Glu545Lys Missense
5:112175711 APC c.4420G>A p.Ala1474Thr Missense
ESS58107 1:145015874 PDE4DIP c.214C>T p.Arg72Ter LOF: stop - gained
1:145536012 ITGA10 c.2104G>A p.Ala702Thr Missense
6:56328464 DST c.16429C>T p.Arg5477Trp Missense
6:135516944 MYB c.1007C>T p.Thr336Ile Missense
17:7578176 TP53 c.672+1G>A r.spl? LOF: splice - donor
X:66863156 AR c.1675A>T p.Thr559Ser Missense
ADS2 2:25467477 DNMT3A c.1599C>A p.Tyr533Ter LOF: stop - gained
6:33288629 DAXX c.959A>G p.Gln320Arg Missense
6:93979315 EPHA7 c.1513C>A p.Leu505Met Missense
7:98501128 TRRAP c.1024G>T p.Glu342Ter LOF: stop - gained
8:48711786 PRKDC c.10279G>T p.Glu3427Ter LOF: stop - gained
10:76781925 KAT6B c.3308_3310delAAG p.Glu1104del LOF: inframe/del
16:2138078 TSC2 c.5098G>T p.Ala1700Ser Missense
ULM119 7:116403114 MET c.2429A>C p.His810Pro Missense
ULM143 1:11307996 MTOR c.995_996dupGG p.Leu333Glyfs LOF: frameshift
19:17945696 JAK3 c.2164G>A p.Val722Ile Missense
ULM152 11:118344893 KMT2A c.3019G>T p.Gly1007Cys Missense

Based on the data described in Table 4, we selected genes with more than three mutations in our cohort to submit to the OncoPrinter visualization tool (cBioPortal - http://www.cbioportal.org/). Figure 2 shows the percentage of patients demonstrating mutations in each gene, distribution, and the types of mutations observed in each sample. The highest frequency of gene mutations was observed in TP53 (48%) with the highest frequency of missense-type mutations (3 ULMS, 1 ESS, and 4 UCS samples). ATM mutations were observed in 22% of the samples, with 3 missense-type mutations (2 ULMS and 1 ESS) and 2 LOF-type mutations (1 ESS and 1 UCS). PIK3CA appeared to be the third most mutated gene (17%) present in 3 UCS samples, with most of the mutations determined as the missense-type. APC, MTOR, DICER1, TRRAP, KMT2D, TSC2, PDE4DIP, and JAK3 showed a 13% mutational frequency. LOF mutations in PDE4DIP was found exclusively/specificaly in the ESS samples. NF1, CREBBP, and MYB demonstrated a 9% mutational frequency. Missense mutations in CREBBP and MYB were associated with ULMS and ESS (4 mutations in ULMS and 2 in ESS).

Figure 2. Distribution of mutations in samples and their biological effects. The figure was constructed using the OncoPrinter from cBioPortal for Cancer Genomics database (http://www.cbioportal.org/). Each gray rectangle represents a sample according to the sequence indicated at the top. Genes with the highest frequency of alterations are shown. Captions for each type of alteration (Loss of function - Black Square; Missense - Green Square; Two alterations in the same gene - vertical line [modified by authors]; No alteration - gray rectangle) are indicated.

Figure 2

Since uterine sarcomas are histologically classified into two primary subtypes, we used the same classification to study the association of the mutated genes with pure sarcomas (ULMS - ESS) and mixed tumors (UCS - ADS). Figure 3 shows the association of the mutated genes in the group of tumors classified as pure (ULMS and ESS). According to the Cytoscape platform (20), many genes demonstrating mutations in these histological subtypes exhibit functions associated with the cellular response to hypoxia (MTOR, PDK1, MDM2, TP53, CREBBP, NOTCH1, and HIF1A) and peptide hormone stimulus (EIF4EBP1, RPTOR, TSC2, TSC1, MTOR, JAK3, ADCY6, PIK3CA, GNAS, and ATP6V1D).

Figure 3. Interaction network of mutated genes in the histological types of pure sarcomas (ULMS - ESS) prepared by the Cytoscape 3.7.0 platform. The network shows patterns of predicted interaction (orange); physical interactions (red); co-expression (violet); shared proteins domains (yellow); co-localization (blue), and genetic interaction (green). Red-labeled genes have a function associated with the cellular response to hypoxia and yellow-labeled genes have a function associated with the cellular response to the peptide hormone stimulus. The genes that were inserted to perform the analysis are shown with cross-hatched circles of a uniform size. The relevant genes are shown with solid circles whose size is proportional to the number of interactions. The reported link weights are indicated visually by line thickness.

Figure 3

Although UCS is no longer classified as uterine sarcoma but as metaplastic carcinoma, we included this tumor group in the analysis shown in Figure 4. Here, we associated UCS - ADS owing to their mixed histologies (epithelial and mesenchymal components) and also because many retrospective studies on the US still include UCS in their available samples. According to the Cytoscape platform (20), many mutated genes in these tumors have functions associated with phosphatidylinositol kinase activity (PI4K2A, PIK3CA, PIK3CB, ATM, PI4KB, PIK3CG, PIK3C2B, PI4KA, PIK3C2A, PIK3C3, PIK3C2G, and PIK3CD) and glycerophospholipid metabolic process (PI4K2A, PIK3CA, PIK3CB, ATM, PI4KB, PIK3CG, PIK3C2B, PI4KA, PIK3C2A, PIK3C3, PIK3C2G, PIK3CD, PI4K2B, and SMG1).

Figure 4. Interaction network of mutated genes in mixed tumors (UCS - ADS) prepared by the Cytoscape 3.7.0 platform. The network shows patterns of predicted interaction (orange); physical interactions (red); co-expression (violet); shared proteins domains (yellow); co-localization (blue) and genetic interaction (green). Red-labeled genes have a function associated with phosphatidylinositol kinase activity and blue-labeled genes have a function associated with the glycerophospholipid metabolic process. The genes that were inserted to perform the analysis are shown with cross-hatched circles of a uniform size. The relevant genes are shown with solid circles whose size is proportional to the number of interactions. The reported link weights are indicated visually by line thickness.

Figure 4

Collectively, our results indicate that despite the molecular heterogeneity demonstrated by USs and UCSs, they share similarities in their mutational profiles. In addition, genetic interaction networks indicate that alterations in functions associated with hypoxia, response to peptide hormone stimulus in ULMSs and ESSs, and phosphatidylinositol kinase activity and glycerophospholipid metabolic process in UCS and ADS can influence the carcinogenic process of these tumors. Considering that NGS technology can provide a reliable molecular portrait of neoplasms quickly and cost-effectively (21), these results open new avenues for research and consequently, may positively impact the clinical management of patients with such tumors.

DISCUSSION

In this study, we performed a mutational screening of the samples collected from patients with USs and UCSs. We employed a panel of 409 genes for the screening. Initially, we focused on the mutated genes shared among more than one histological subtype of US. We initiated our analyses with 40 samples, but owing to the quality of the FFPE material, certain losses reduced the number of samples to 23. Considering the published reports on sarcomas, the number of samples was sufficient for this type of population mutational screening. In UCS and ESS samples, we identified mutations in genes that demonstrated alterations in previous studies conducted for examining other tumors, such as PIK3CA, DICER1, AR, and NF (22). Although the role of these genes is known in different cancers, their role in the tumorigenesis of USs and USCs is not fully understood.

The PIK3CA gene encodes the p110α protein, the catalytic subunit of PI3K, which controls the growth, division, survival, movement, and structure of cells. Many studies have demonstrated the importance of PIK3CA mutation in mediating tumorigenesis via increased PI3K/AKT/mTOR signaling (23,24). While investigating druggable molecular targets in uterine sarcomas, Cuppens et. al (25) identified PI3K/MTOR as a potential target in 26% of cases, which were primarily ULMS, HG-ESS, and undifferentiated uterine sarcomas. Here, we included eight samples of ESS. Seven of these were characterized as HG-ESS, consistent with the molecular findings described in previous reports published for these tumors. DICER1 is critical for the regulation of expression of several miRNAs. The DICER1 gene is highly conserved among various species, indicating that mutations may compromise its function and might be involved in the onset of tumors (26). Previous reports published by our group (2,27) demonstrated the regulation of microRNAs associated with several oncogenic pathways, including DICER1. Mutations in NF1 have already been demonstrated in soft-tissue sarcomas (myxofibrosarcomas and pleomorphic liposarcomas) (28). The expression of the androgen receptor (AR) seems to be associated with a better prognosis in patients with ESS. AR expression is higher in pre-malignant lesions and low-grade tumors (LG-ESS) (29). These findings may explain why AR expression is low in ULMS, which is an extremely aggressive tumor (30). However, the effects of the mutations observed in this gene need to be further investigated for US.

It is important to note that NOTCH1 was the unique gene that shared mutations in the UCS and ULMS. Similarly, mutations in the DAXX gene have also been observed in the cases of ESS/ADS and ULMS/ADS, which share mutations in TSC2. Thus, our results suggest that besides exhibiting a similar tumor microenvironment, USs and UCSs also share genetic alterations. This observation is relevant to the understanding of the onset and evolution of these tumors. Furthermore, ULMS cases originating from ULMs have been reported; however, this hypothesis has not been proven yet (31,32). Our study showed that mutations in KMT2A were exclusively observed in ULMS and ULM. The c.3019G>T variant appears to be related to the Wiedemann-Steiner syndrome and Kabuki syndrome (33,34).

We attempted to identify specific genes for each type of tumor, establishing individual signatures. Despite the heterogeneity, we were able to identify six specific genes for three of the histological types evaluated in this study. In ESS samples, we observed variants in the PDE4DIP (c.214C>T and c.2494delC), ITGA10 (c.2104G>A), and DST (c.16429C>T) genes. The variant PDE4DIP c.214C>T is described in the COSMIC database (35) and was first observed in papillary thyroid carcinoma. Mutations in this gene are described in several tumors, such as breast cancer as well as the cancers of the endometrium, cervix, ovaries, and urinary tract. The protein encoded by the PDE4DIP gene is responsible for binding 4D phosphodiesterase to the Golgi complex. Alterations in this gene may cause a myeloproliferative disorder associated with eosinophilia (36). Despite the information available in databases and the literature, its typical role in tumor biology remains unknown.

In UCS, we observed two variants of ERBB4 (c.782A>C and c.2513G>A). The variant ERBB4 c.2513G>A is described in the COSMIC database (35) as pathogenic (score 0.99) and has already been observed in hormone receptor-positive breast cancer, large bowel adenocarcinoma, malignant melanoma, and gastroesophageal junction adenocarcinoma. The role of ERBB4 as a tumor progression factor is not fully elucidated. However, this gene is known to be overexpressed and/or mutated in several solid tumors (37). The monoclonal antibody ERBB4 therapy is effective in breast, lung, and prostate cancer cells in vitro and in vivo (38). Specific and detailed studies may demonstrate new opportunities for the development of therapies targeting these tumors.

Mutations in NOTCH2 and HER2 have also been observed exclusively in ULMS. All variants are described in the COSMIC database (35). c.6094C>A mutation of NOTCH2 is considered to be pathogenic (score 0.97) and is described in diffuse large B cell lymphoma and pancreatic ductal adenocarcinoma (PDAC). The NOTCH2 c.7223T>A variant is also pathogenic (score 0.85) and has already been described in meningioma, a primary non-malignant CNS tumor (39). HER2 also presented two pathogenic variants in ULMS: c.236A>C and c.2446C>T. The c.236A>C variant has already been described in meningothelial meningioma and is associated with IL-6 signaling pathways and DNA damage response. The c.2446C>T mutation has been observed in large bowel adenocarcinoma and transitional cell carcinoma of the urinary system. Persistent NOTCH2 signaling is largely associated with poor clinical prognosis. In addition, it increases resistance to chemotherapy and radiotherapy, making these cancers less sensitive to treatment (40). HER2 mutations have emerged as therapeutic targets for a variety of tumors. Anti- HER2 therapies are effective against breast, lung, and cervical cancers (41).

In this study, we were able to identify several mutations that contribute to a better understanding of the biology of USs and UCSs. Even with the limitations associated with rare tumors, we identified genetic alterations that might act as potential target markers for precision medicine-based approaches upon validation in larger cohorts. To date, there is no precise preoperative diagnostic test for these tumors. Although rare, such tumors are very aggressive and associated with a poor prognosis. Thus, even with small cohorts, the molecular profiling of USs and UCSs is extremely important to identify the changes driving the development of these tumors and provide powerful tools for diagnostic and prognostic tests as well as adequate treatment alternatives. Our study is the first DNA-sequencing study to investigate all histological types of USs and UCSs together and is an insightful contribution for defining the mutational repertoire of these rare tumors.

CONCLUSIONS

Using a platform to profile mutations in a panel of 409 genes, we identified that TP53, ATM, PIK3CA, APC, MTOR, DICER1, TRRAP, KMT2D, TSC2, PDE4DIP, and JAK3 are the most frequently mutated genes in USs and UCSs. Considering common mutations among the different tumor types being evaluated, the TP53 (4 UCS/4 ULMS/3 ESS), ATM (2 ULMS/2 ESS/1 UCS), and KMT2D (1 UCS/1 ULMS/1 ESS) genes could be indicators of similarities in neoplastic progression. As specific signature genes, ESS exhibited mutations in the PDE4DIP, IGTA10, and DST genes. UCS showed mutations in the ERBB4 gene, and ULMS demonstrated exclusive alterations in the NOTCH2 and HER2 genes. Mutations in the KMT2A gene were observed exclusively in ULM and ULMS samples, and therefore, are potentially involved in the malignant transformation process. According to the Cytoscape platform, many genes that were mutated in the ULMS and ESS samples exhibit functions associated with the cellular response to hypoxia and peptide hormone stimulus. In UCS and ADS, most altered genes exhibit functions associated with phosphatidylinositol kinase activity and glycerophospholipid metabolic process. More studies should be conducted with a larger number of samples and functional analyses. However, the current screening contributes to the characterization of the complex genetic profile of USs and USCs.

AUTHOR CONTRIBUTIONS

Da Costa LT and Dos Anjos LG were responsible for study conceptualization, literature organization and paper elaboration. Kagohara LT collaborated in analyses of data, manuscripts and reviews. Torrezan GT and De Paula CAA contributed to the study execution. Baracat EC and Carraro DM provided intellectual support. Carvalho KC analyzed the literature, critically reviewed the manuscript, supervised the research and developed the original idea.

ACKNOWLEDGMENTS

The research received financial support from Fundacão de Amparo è Pesquisa do Estado de São Paulo - FAPESP (process numbers: 2016/03163-6 and 2019/01109-2).

Table S1. Ion AmpliSeq Comprehensive Cancer Panel target gene list.

1 ABL1 CBL EP300 GATA2 LAMP1 MYD88 PKHD1 SMARCA4 WHSC1
2 ABL2 CCND1 EP400 GATA3 LCK MYH11 PLAG1 SMARCB1 WRN
3 ACVR2A CCND2 EPHA3 GDNF LIFR MYH9 PLCG1 SMO WT1
4 ADAMTS20 CCNE1 EPHA7 GNA11 LPHN3 NBN PLEKHG5 SMUG1 XPA
5 AFF1 CD79A EPHB1 GNAQ POT1 NCOA1 PML SOCS1 XPC
6 AFF3 CD79B EPHB4 GNAS LPP NCOA2 PMS1 SOX11 XPO1
7 AKAP9 CDC73 EPHB6 GPR124 LRP1B NCOA4 PMS2 SOX2 XRCC2
8 AKT1 CDH1 ERBB2 GRM8 LTF NF1 POU5F1 SRC ZNF384
9 AKT2 CDH11 ERBB3 GUCY1A2 LTK NF2 PPARG SSX1 ZNF521
10 AKT3 CDH2 ERBB4 HCAR1 MAF NFE2L2 PPP2R1A STK11
11 ALK CDH20 ERCC1 HIF1A MAFB NFKB1 PRDM1 STK36
12 APC CDH5 ERCC2 HLF MAGEA1 NFKB2 PRKAR1A SUFU
13 AR CDK12 ERCC3 HNF1A MAGI1 NIN PRKDC SYK
14 ARID1A CDK4 ERCC4 HOOK3 MALT1 NKX2-1 PSIP1 SYNE1
15 ARID2 CDK6 ERCC5 HRAS MAML2 NLRP1 PTCH1 TAF1
16 ARNT CDK8 ERG HSP90AA1 MAP2K1 NOTCH1 PTEN TAF1L
17 ASXL1 CDKN2A ESR1 HSP90AB1 MAP2K2 NOTCH2 PTGS2 TAL1
18 ATF1 CDKN2B ETS1 ICK MAP2K4 NOTCH4 PTPN11 TBX22
19 ATM CDKN2C ETV1 IDH1 MAP3K7 NPM1 PTPRD TCF12
20 ATR CEBPA ETV4 IDH2 MAPK1 NRAS PTPRT TCF3
21 ATRX CHEK1 EXT1 IGF1R MAPK8 NSD1 RAD50 TCF7L1
22 AURKA CHEK2 EXT2 IGF2 MARK1 NTRK1 RAF1 TCF7L2
23 AURKB CIC EZH2 IGF2R MARK4 NTRK3 RALGDS TCL1A
24 AURKC CKS1B FAM123B IKBKB MBD1 NUMA1 RARA TET1
25 AXL CMPK1 FANCA IKBKE MCL1 NUP214 RB1 TET2
26 BAI3 COL1A1 FANCC IKZF1 MDM2 NUP98 RECQL4 TFE3
27 BAP1 CRBN FANCD2 IL2 MDM4 PAK3 REL TGFBR2
28 BCL10 CREB1 FANCF IL21R MEN1 PALB2 RET TGM7
29 BCL11A CREBBP FANCG IL6ST MET PARP1 RHOH THBS1
30 BCL11B CRKL FAS IL7R MITF PAX3 RNASEL TIMP3
31 BCL2 CRTC1 FBXW7 ING4 MLH1 PAX5 RNF2 TLR4
32 BCL2L1 CSF1R FGFR1 IRF4 MLL PAX7 RNF213 TLX1
33 BCL2L2 CSMD3 FGFR2 IRS2 MLL2 PAX8 ROS1 TNFAIP3
34 BCL3 CTNNA1 FGFR3 ITGA10 MLL3 PBRM1 RPS6KA2 TNFRSF14
35 BCL6 CTNNB1 FGFR4 ITGA9 MLLT10 PBX1 RRM1 TNK2
36 BCL9 CYLD FH ITGB2 MMP2 PDE4DIP RUNX1 TOP1
37 BCR CYP2C19 FLCN ITGB3 MN1 PDGFB RUNX1T1 TP53
38 BIRC2 CYP2D6 FLI1 JAK1 MPL PDGFRA SAMD9 TPR
39 BIRC3 DAXX FLT1 JAK2 MRE11A PDGFRB SBDS TRIM24
40 BIRC5 DCC FLT3 JAK3 MSH2 PER1 SDHA TRIM33
41 BLM DDB2 FLT4 JUN MSH6 PGAP3 SDHB TRIP11
42 BLNK DDIT3 FN1 KAT6A MTOR PHOX2B SDHC TRRAP
43 BMPR1A DDR2 FOXL2 KAT6B MTR PIK3C2B SDHD TSC1
44 BRAF DEK FOXO1 KDM5C MTRR PIK3CA SEPT9 TSC2
45 BRD3 DICER1 FOXO3 KDM6A MUC1 PIK3CB SETD2 TSHR
46 BRIP1 DNMT3A FOXP1 KDR MUTYH PIK3CD SF3B1 UBR5
47 BTK DPYD FOXP4 KEAP1 MYB PIK3CG SGK1 UGT1A1
48 BUB1B DST FZR1 KIT MYC PIK3R1 SH2D1A USP9X
49 CARD11 EGFR G6PD KLF6 MYCL1 PIK3R2 SMAD2 VHL
50 CASC5 EML4 GATA1 KRAS MYCN PIM1 SMAD4 WAS

Table S2. Description of 153 potential somatic variants selected in 23 samples of uterine tumors.

Sample Chr:Pos Gene HGVS c. HGVS p. Effect
UCS2 3:178921549 PIK3CA c.1031T>C p.Val344Ala Missense
6:94120318 EPHA7 c.733G>A p.Ala245Thr Missense
7:116339356 MET c.218T>A p.Leu73Ter LOF: stop - gained
8:48776121 PRKDC c.5586delT p.Phe1862Leufs LOF: frameshift
15:99500303 IGF1R c.3736C>T p.Arg1246Cys Missense
17:7577547 TP53 c.734G>T p.Gly245Val Missense
22:33253291 TIMP3 c.260delC p.Glu88Argfs LOF: frameshift
UCS5 1:11227575 MTOR c.4254-1G>A r.spl? LOF: splice - acceptor
1:27105553 ARID1A c.5164C>T p.Arg1722Ter LOF: stop - gained
1:65310574 JAK1 c.2116-2A>G r.spl? LOF: splice - acceptor
3:178952085 PIK3CA c.3140A>G p.His1047Arg Missense
10:76735809 KAT6B c.1714C>T p.Arg572Cys Missense
10:97969609 BLNK c.731C>T p.Pro244Leu Missense
11:108114777 ATM c.594C>A p.Cys198Ter LOF: stop - gained
14:95572101 DICER1 c.3007C>T p.Arg1003Ter LOF: stop - gained
17:29588751 NF1 c.4600C>T p.Arg1534Ter LOF: stop - gained
17:29665110 NF1 c.6772C>T p.Arg2258Ter LOF: stop - gained
19:45260400 BCL3 c.646C>T p.Arg216Cys Missense
1:47685756 TAL1 c.632G>A p.Arg211His Missense
2:25469168 DNMT3A c.1290T>G p.Asn430Lys Missense
2:212587219 ERBB4 c.782A>C p.Gln261Pro Missense
7:98513427 TRRAP c.2281C>T p.Arg761Trp Missense
9:37015073 PAX5 c.331G>A p.Ala111Thr Missense
19:11098401 SMARCA4 c.919C>T p.Pro307Ser Missense
20:36030940 SRC c.1219G>A p.Asp407Asn Missense
X:44942716 KDM6A c.3452A>G p.Gln1151Arg Missense
X:66766207 AR c.1219C>T p.Arg407Cys Missense
UCS9 9:139391355 NOTCH1 c.6836C>T p.Ala2279Val Missense
10:123298226 FGFR2 c.628C>T p.Arg210Ter LOF: stop - gained
12:49444719 KMT2D c.2747C>T p.Pro916Leu Missense
15:40916649 KNL1 c.4265G>A p.Arg1422Gln Missense
17:7578442 TP53 c.488A>G p.Tyr163Cys Missense
3:52440867 BAP1 c.637C>T p.Arg213Cys Missense
21:39755729 ERG c.1057G>A p.Glu353Lys Missense
UCS13 3:178916854 PIK3CA c.241G>A p.Glu81Lys Missense
11:71726283 NUMA1 c.2266G>T p.Glu756Ter LOF: stop - gained
13:29001422 FLT1 c.1310C>T p.Ser437Leu Missense
14:95574253 DICER1 c.2614G>A p.Ala872Thr Missense
17:7577534 TP53 c.747G>T p.Arg249Ser Missense
5:176636902 NSD1 c.1502A>G p.Lys501Arg Missense
7:98609947 TRRAP c.11549G>A p.Arg3850His Missense
UCS19 2:212295800 ERBB4 c.2513G>A p.Arg838Gln Missense
9:5126715 JAK2 c.3323A>G p.Asn1108Ser Missense
17:7577580 TP53 c.701A>G p.Tyr234Cys Missense
17:37829120 PGAP3 c.900-1G>A r.spl? LOF: splice - acceptor
ULMS38 1:120458122 NOTCH2 c.7223T>A p.Leu2408His Missense
6:51914991 PKHD1 c.2243C>T p.Ala748Val Missense
16:23646942 PALB2 c.925A>G p.Ile309Val Missense
17:5462805 NLRP1 c.1211G>A p.Arg404Gln Missense
17:37864584 ERBB2 c.236A>C p.Glu79Ala Missense
3:65425588 MAGI1 c.1234_1236delCAG p.Gln421del Inframe - deletion
19:17937659 JAK3 c.3268G>A p.Ala1090Thr Missense
ULMS39 3:188327501 LPP c.982C>T p.Arg328Trp Missense
7:142562071 EPHB6 c.513_515delCTC p.Ser176del LOF: disruptive - inframe - del
17:7577545 TP53 c.736A>G p.Met246Val Missense
ULMS40 2:100218031 AFF3 c.1310_1312delGCA p.Ser444del LOF: disruptive - inframe - del
ULMS40 11:108139268 ATM c.2770C>T p.Arg924Trp Missense
17:7577120 TP53 c.818G>A p.Arg273His Missense
17:37881117 ERBB2 c.2446C>T p.Arg816Cys Missense
X:76891445 ATRX c.4660A>T p.Arg1554Ter LOF: stop - gained
ULMS45 3:128204775 GATA2 c.666G>C p.Lys222Asn Missense
11:108160506 ATM c.4414T>G p.Leu1472Val Missense
12:121437187 HNF1A c.1618A>G p.Lys540Glu Missense
17:7578290 TP53 c.560-1G>C r.spl? LOF: splice - acceptor
16:2135281 TSC2 c.4620C>A p.Tyr1540Ter LOF: stop - gained
ULMS50b 2:29432740 ALK c.3748A>G p.Ile1250Val Missense
ULMS52 1:6528318 PLEKHG5 c.2815C>T p.Arg939Cys Missense
1:120459251 NOTCH2 c.6094C>A p.His2032Asn Missense
9:139400980 NOTCH1 c.4013C>T p.Ala1338Val Missense
11:118377142 KMT2A c.10535C>T p.Pro3512Leu Missense
12:49416396 KMT2D c.16315C>T p.Arg5439Trp Missense
13:26978093 CDK8 c.1270C>T p.Arg424Cys Missense
16:2130319 TSC2 c.3551C>T p.Ala1184Val Missense
16:3779521 CREBBP c.5527T>C p.Cys1843Arg Missense
16:3790470 CREBBP c.4063G>A p.Gly1355Arg Missense
17:7574017 TP53 c.1010G>A p.Arg337His Missense
22:36678790 MYH9 c.5807G>A p.Arg1936Gln Missense
ULMS59 5:112173857 APC c.2566C>T p.Arg856Cys Missense
6:135511289 MYB c.331G>A p.Gly111Ser Missense
6:135539101 MYB c.2269C>T p.Arg757Trp Missense
6:152832196 SYNE1 c.352C>T p.Arg118Ter LOF: stop - gained
7:2946463 CARD11 c.3274C>T p.Arg1092Ter LOF: stop - gained
18:22806393 ZNF521 c.1489C>T p.Arg497Ter LOF: stop - gained
18:47803035 MBD1 c.472C>T p.Arg158Ter LOF: stop - gained
20:57429026 GNAS c.706G>A p.Asp236Asn Missense
20:57480457 GNAS c.2381A>C p.Lys794Thr Missense
22:30069262 NF2 c.1127G>A p.Arg376Gln Missense
ESS2 (LG-ESS) 6:152706896 SYNE1 c.8565G>A p.Trp2855Ter LOF: stop - gained
11:108175463 ATM c.5558A>T p.Asp1853Val Missense
14:81610269 TSHR c.1867G>T p.Ala623Ser Missense
17:7577121 TP53 c.817C>T p.Arg273Cys Missense
17:7577139 TP53 c.799C>T p.Arg267Trp Missense
19:3119273 GNA11 c.805G>A p.Val269Ile Missense
22:41553308 EP300 c.3397C>T p.Arg1133Trp Missense
ESS3 1:145015874 PDE4DIP c.214C>T p.Arg72Ter LOF: stop - gained
5:112154777 APC c.1048T>C p.Ser350Pro Missense
5:112162855 APC c.1459G>A p.Gly487Arg Missense
6:56328464 DST c.16429C>T p.Arg5477Trp Missense
12:49418436 KMT2D c.15977T>C p.Leu5326Pro Missense
17:7578176 TP53 c.672+1G>A r.spl? LOF: splice - donor
17:29556250 NF1 c.2617C>T p.Arg873Cys Missense
17:29677234 NF1 c.7355G>T p.Arg2452Leu Missense
ESS4 11:108141990 ATM c.2934delT p.Leu979Cysfs LOF: frameshift
16:3820773 CREBBP c.2678C>T p.Ser893Leu Missense
ESS5 1:11217330 MTOR c.4348T>G p.Tyr1450Asp Missense
14:51227050 NIN c.1924G>A p.Glu642Lys Missense
19:17937659 JAK3 c.3268G>A p.Ala1090Thr Missense
20:41101170 PTPRT c.1186G>A p.Val396Ile Missense
ESS7 6:33287248 DAXX c.1885G>A p.Val629Ile Missense
6:117710646 ROS1 c.1626delT p.Phe542Leufs LOF: frameshift
14:95590677 DICER1 c.1232C>A p.Ser411Ter LOF: stop - gained
ESS7 X:76939115 ATRX c.1633C>G p.Gln545Glu Missense
ESS9 1:144906139 PDE4DIP c.2494delC p.Gln832Argfs LOF: frameshift
1:145536012 ITGA10 c.2104G>A p.Ala702Thr Missense
3:178936091 PIK3CA c.1633G>A p.Glu545Lys Missense
4:55564641 KIT c.529C>T p.Arg177Cys Missense
4:55976709 KDR c.1116G>C p.Glu372Asp Missense
5:112175711 APC c.4420G>A p.Ala1474Thr Missense
5:180048651 FLT4 c.1911C>G p.Ser637Arg Missense
ESS58107 1:145015874 PDE4DIP c.214C>T p.Arg72Ter LOF: stop - gained
1:145536012 ITGA10 c.2104G>A p.Ala702Thr Missense
2:142567932 LRP1B c.121G>A p.Asp41Asn Missense
4:153332477 FBXW7 c.479C>T p.Pro160Leu Missense
6:56328464 DST c.16429C>T p.Arg5477Trp Missense
6:135516944 MYB c.1007C>T p.Thr336Ile Missense
7:91570414 AKAP9 c.1A>G p.Met1? LOF: initiator - codon
17:7578176 TP53 c.672+1G>A r.spl? LOF: splice - donor
X:41056743 USP9X c.4360delG p.Gly1454Glufs LOF: frameshift
X:66863156 AR c.1675A>T p.Thr559Ser Missense
ADS2 1:162748436 DDR2 c.2350T>C p.Cys784Arg Missense
2:25467477 DNMT3A c.1599C>A p.Tyr533Ter LOF: stop - gained
2:209110123 IDH1 c.440C>A p.Pro147His Missense
3:38182306 MYD88 c.766T>C p.Phe256Leu Missense
5:131927073 RAD50 c.1610delA p.Met538Trpfs LOF: frameshift
6:33288629 DAXX c.959A>G p.Gln320Arg Missense
6:93979315 EPHA7 c.1513C>A p.Leu505Met Missense
7:98501128 TRRAP c.1024G>T p.Glu342Ter LOF: stop - gained
8:48711786 PRKDC c.10279G>T p.Glu3427Ter LOF: stop - gained
9:98209391 PTCH1 c.4147C>A p.Pro1383Thr Missense
10:76781925 KAT6B c.3308_3310delAAG p.Glu1104del LOF: disruptive - inframe - del
11:106558436 GUCY1A2 c.2131G>T p.Glu711Ter LOF: stop - gained
15:90630454 IDH2 c.857A>G p.Glu286Gly Missense
16:2138078 TSC2 c.5098G>T p.Ala1700Ser Missense
22:29121048 CHEK2 c.638T>C p.Val213Ala Missense
X:53223847 KDM5C c.3512A>G p.Lys1171Arg Missense
ULM119 7:116403114 MET c.2429A>C p.His810Pro Missense
22:39621795 PDGFB c.659dupA p.Lys222Glnfs LOF: frameshift
ULM143 1:11307996 MTOR c.995_996dupGG p.Leu333Glyfs LOF: frameshift
9:32634260 TAF1L c.1318A>G p.Ile440Val Missense
19:17945696 JAK3 c.2164G>A p.Val722Ile Missense
ULM152 8:41791030 KAT6A c.4708G>A p.Asp1570Asn Missense
11:118344893 KMT2A c.3019G>T p.Gly1007Cys Missense
19:1207176 STK11 c.263_264insC p.Asn90Glnfs LOF: frameshift

Footnotes

No potential conflict of interest was reported.

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