Literature DB >> 32698852

Molecular comparison of pure ovarian fibroma with serous benign ovarian tumours.

Sally M Hunter1, Genevieve V Dall1, Maria A Doyle2, Richard Lupat2, Jason Li2, Prue Allan3, Simone M Rowley1, David Bowtell1,4,5, Ian G Campbell1,4,5, Kylie L Gorringe6,7,8,9.   

Abstract

OBJECTIVE: Ovarian fibromas and adenofibromas are rare ovarian tumours. They are benign tumours composed of spindle-like stromal cells (pure fibroma) or a mixture of fibroblast and epithelial components (adenofibroma). We have previously shown that 40% of benign serous ovarian tumours are likely primary fibromas due to the neoplastic alterations being restricted to the stromal compartment of these tumours. We further explore this finding by comparing benign serous tumours to pure fibromas.
RESULTS: Performing copy number aberration (CNA) analysis on the stromal component of 45 benign serous tumours and 8 pure fibromas, we have again shown that trisomy of chromosome 12 is the most common aberration in ovarian fibromas. CNAs were more frequent in the pure fibromas than the benign serous tumours (88% vs 33%), however pure fibromas more frequently harboured more than one CNA event compared with benign serous tumours. As these extra CNA events observed in the pure fibromas were unique to this subset our data indicates a unique tumour evolution. Gene expression analysis on the two cohorts was unable to show gene expression changes that differed based on tumour subtype. Exome analysis did not reveal any recurrently mutated genes.

Entities:  

Keywords:  Adenofibroma; Copy number aberrations; Cystadenofibroma; Cystadenomas; Exome sequencing; Gene expression; Microarrays; Ovarian fibroma

Mesh:

Year:  2020        PMID: 32698852      PMCID: PMC7376903          DOI: 10.1186/s13104-020-05194-z

Source DB:  PubMed          Journal:  BMC Res Notes        ISSN: 1756-0500


Introduction

Ovarian fibromas and adenofibromas form part of the sex-cord stromal family of tumours and are relatively uncommon, accounting for approximately 8% of all diagnosed ovarian tumours [1]. These tumours are benign entities composed in significant part of fibroblasts (pure fibromas), or as compound tumours composed of a mix of fibroblast and epithelial (adenofibroma) or sex-cord (granulosa-stromal tumours) components. Tumours with a cystic epithelial component are termed cystadenomas or cystadenofibromas. Due to their relative rarity and benign nature these tumours have not been well molecularly characterised, with the majority of studies focussing on immunohistochemistry and cytogenetics. Ovarian fibromas differ from fibromas arising in other organs in that they frequently express hormone receptors (e.g. ER-β, PR, AR) and are typically negative for the characteristic markers of other cells derived from a fibroblast/myofibroblastic origin (e.g. SMA, CD34, CD117, S-100) [1, 2]. Genomic aberrations involving trisomy and tetrasomy of chromosome 12 appear to be particularly prevalent in tumours arising in the female genitourinary tract, including uterine leiomyomas [3, 4], thecomas [5-7], fibromas [7-10] and granulosa cell tumours [11, 12]. The underlying biological driver for this recurrent event has yet to be established. Other genomic aberrations that arise less frequently may be more cell type-specific. Imbalances involving chromosomes 4 and 9 are also common in the fibroma-thecoma subgroup, with chromosome 9 aberrations potentially being associated with cellular fibromas [13]. We previously reported that around 40% of benign serous cystadenomas and cystadenofibromas show copy number aberrations (CNA) exclusively in the stroma [14] and are thus likely misdiagnosed primary fibromas with epithelial inclusion. To investigate this further we undertook molecular characterisation of these epithelial-stromal tumours in comparison to pure fibromas.

Main text

Materials and methods

Tissue samples

Fresh frozen tissue samples were used for copy number, exome and expression analyses. All samples were collected with the patient’s informed consent and the study was approved by the Human Research Ethics Committees at the Peter MacCallum Cancer Centre. Patients with ovarian tumors were identified through hospitals in the Wessex Region, UK (n = 25) [15] and the Australian Ovarian Cancer Study (AOCS) (n = 31) [16, 17]. Pathology review was conducted on cryosections adjacent to the tissue from which DNA was extracted (PA). Microdissections and DNA/RNA extractions were performed as previously described [18]. Samples were selected for inclusion based on availability of tissue for DNA and RNA extraction.

Copy number data

The Affymetrix SNP6.0 Human Mapping (1.8 M probe set) array was utilised for ultra-high resolution allele-specific copy number analysis. Arrays were performed as recommended by the manufacturer with the exception that the input was reduced from the recommended 500 ng to 250 ng by reducing reaction volumes by half for all processes prior to the SNP6.0 PCR step. Reduction in DNA input does not result in any loss in the quality of the data. Copy number analysis was performed as previously described [18], using Partek Genomics Suite v 6.5. Copy number and allele-specific copy number was generated paired (when matching normal available) or unpaired and circular binary segmentation was performed to identify regions of copy number and loss of heterozygosity. Thresholds were > 2.3 for gains, < 1.7 for losses and < 0.75 for homozygous deletions. All SNP data has been made publicly available through Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/ - GSE67189).

Exome sequencing

For each case 500 ng–1 µg of microdissected tumour DNA and matched lymphocyte DNA when available was sheared to < 1000 bp using a Covaris® ultra-sonicator (Covaris®), libraries prepared using the Illumina TruSeq DNA Sample Preparation procedure (Illumina), and enriched for exome sequencing using the SeqCap EZ Human Exome Library v2.0 (Roche NimbleGen). Exomes were sequenced with 100 bp PE reads in pools of three per lane on a HiSeq 2000 (Illumina). Sequence reads were aligned to the human genome (GRCh37/hg19) using BWA-MEM (v0.7.7-r441) [19, 20]; duplicates marked using Picard (v1.77); local indel realignment and base quality recalibration performed using GATK (v2.7-2-g6bda569) [21, 22]; indel detection performed using GATK Unified Genotyper (v2.7-2-g6bda569), Indel Genotyper, Pindel (v0.2.5a3) [23], and VarScan2 (v2.2.4) [24]; SNV prediction performed using GATK Unified Genotyper, MuTect (v2.7-1-g42d771f) [25], SomaticSniper [26], JointSNVMix2 (v0.8-b2) [27], and VarScan2 (v2.2.4); and variants annotated using Ensembl variant effect predictor v73. Exome bam files are available from the Sequence Read Archive Accession number PRJNA631561 (https://www.ncbi.nlm.nih.gov/sra/PRJNA631561). Variants were enriched for genuine somatic events by filtering for those called by >=2 variant callers, with the exception of MuTect, which is capable of detecting variants at lower frequencies and therefore all MuTect variants were included; germline allele frequency <=0.01 and tumour allele frequency >=0.05, with >=0.1 difference in allele frequency between tumour and germline; variant observed in <=3 of 250 in-house germ-line exomes. All variants with a tumour allele frequency >=0.1 were taken forward for Sanger sequencing validation.

Expression data

Expression data was generated using the Affymetrix Human Gene 1.0 ST array according to the manufacturer’s recommendations. An input of 300 ng of total RNA was used, as quantified by Nanodrop spectrophotometer. RIN values were determined using the Agilent Bioanalyzer RNA 6000 Nano assay, the average RIN value for the 25 samples was 4.7 (range 1–7.9). Analysis of the data was performed using the Partek Gene Expression workflow. CEL files were processed using RMA normalisation and batch correction. All Gene 1.0 ST data has been made publicly available through Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/-GSE67223).

Results

The clinical features of the ovarian cohort are presented in Table 1. Women with ovarian fibromas compared to benign serous ovarian tumours had very similar median ages and ranges (64, range 35–80 and 61, range 27–80 respectively). Interestingly, there appeared to be a strong preponderance for both fibromas and benign serous tumours to be bilateral or detected on the right ovary (Binomial test for left vs right P = 0.02).
Table 1

Clinical features of cohort

Sample IDAgeLateralityCNGene expressionExome
Pure Fibromas
 IC3380Bilateral (same)YY
 IC4n/aBilateral (same)YY
 IC26959RightYY
 IC42549LeftYY
 IC45835RightYY
 IC49453Bilateral (same)YY
 IC18165RightYY
 IC13764Bilateral (other)YY
Cystadenofibroma
 IC14966Bilateral (same)YY
 IC1059RightYY
 IC16472LeftYaYY
 IC15882Bilateral (same)YaYY
 IC581LeftYaYY
 IC10356Bilateral (same)YaYY
 IC46752RightYaYY
 IC12074RightYY
 A474RightYaY
 A361Bilateral (same)YaY
 A263Bilateral (same)YaY
 A566RightYaY
 A675Bilateral (same)Ya
 A848Bilateral (same)Y
 A966LeftYa
 A1054Bilateral (same)Ya
 A2561RightYa
 A1172Bilateral (same)Ya
 A1276Bilateral (same)Ya
 A6168RightY
 A2957Bilateral (same)Ya
 A2251Bilateral (same)Ya
 A1350RightYa
 A1462Bilateral (same)Ya
 A1545LeftYa
 A769RightYa
Adenofibroma
 IC45027Right (other)YaYY
Cystadenoma
 IC14867Bilateral (other)YaYY
 IC2477Bilateral (same)YY
 IC19646unilateral (unspecified)YY
 IC779RightYaY
 IC59148RightYY
 A1735Bilateral (same)YaY
 A1650RightYa
 A1873Bilateral (same)Ya
 A1946RightYa
 A2065RightYa
 A2358Bilateral (same)Ya
 A2164Bilateral (same)Ya
 A2655Bilateral (same)Ya
 A2759LeftYa
 A6268Bilateral (same)Y
 A6343RightY
 A6455Bilateral (same)Y
 A2458Bilateral (same)Ya
Normal
 IC7960n/aY
 IC236n/an/aY
 IC36940n/aY

Same = same diagnosis both ovaries. Other = different diagnosis in contralateral ovary. n/a, information not available. Y, included in this manuscript

ain Hunter et al. 2011

Clinical features of cohort Same = same diagnosis both ovaries. Other = different diagnosis in contralateral ovary. n/a, information not available. Y, included in this manuscript ain Hunter et al. 2011

Copy number aberrations

Genome-wide copy number analysis was performed for eight unselected pure fibromas, and compared to copy number data from the stroma of 27 serous cystadenofibromas and 18 serous cystadenomas (collectively referred to as benign serous tumours). CNAs were detectable in 7/8 (88%) of the pure fibromas, with gain of chromosome 12 being the most recurrently observed aberration in five of eight (63%) cases (Additional file 1: Table S1). Other recurrent CNAs in the fibromas were gain of chromosomes 9 or 9q (50% cases), 18 and 21 (20% cases each). CNAs were detected in the stroma of 33% of benign serous tumours. Recurrent gain of chromosome 12 was also observed in 31% of serous cystadenofibromas (8/27) and 17% of serous cystadenomas (3/18), gain of 9q was only observed in single serous cystadenofibroma case, while loss of chromosome 22 was detected in 11% of cystadenofibromas (3/27). No CNAs were detected in the stroma of the normal ovaries.

Expression analysis

Gene expression arrays were used to compare the stromal RNA of three normal ovaries against eight pure fibromas (seven with CNAs), seven cystadenomas (two with CNAs), and seven cystadenofibromas (four with CNAs). Comparing normal ovary to benign serous tumours or fibromas did not identify any differentially expressed genes following multiple testing correction. Comparison of benign serous tumours to fibromas also did not identify any differentially expressed genes. Comparison of samples based on the presence or absence of CNA, or the presence of specific CNA compared to an absence of genomic aberrations (with and without tumour subtyping), did not identify differentially expressed genes that remained significant following multiple testing correction. As these samples are difficult to enrich for neoplastic cells due to a mixture of cell types in the stroma the expression signal from the tumour cells will be diluted, therefore a less stringent approach was taken to identify candidate genes by taking the most significantly altered genes p <=0.001 with a fold change >=2. Through this approach 17 genes were found to be differentially expressed based on the presence of specific CNA (gain 9q and 12, loss of 16q) compared to samples with no genomic CNAs (Table 2).
Table 2

Candidate genes for differential expression

GeneCytobandFold-changeP valueFunction
9q genes gain vs no gain
 HAPLN15q14.3+5.20.000008ECM protein and ERK signalling; overexpressed in metastatic melanoma and mesotheliomas
 PRAME22q11.22+3.60.000342Repressor of retinoic acid receptor. Overexpressed in multiple neoplasms (including melanoma)
 SLC17A36p22.2+3.30.000081Voltage-driven transporter. Affects serum uric acid levels
 CKS29q22.2+3.30.000232CDC28 protein kinase regulatory subunit 2. Overexpressed in numerous neoplasms, overrides the intra-S-phase DNA damage checkpoint
 ANOS1Xp22.31+2.80.000297ECM protein. Putative cell adhesion molecule, upregulated in some tumour types
 RNF1826p23+2.50.000110E3 ubiquitin ligase. Overexpressed in Alzheimers
 SLC17A16p22.2+2.30.000711Sodium-dependent phosphate transporter. Affects uric acid levels
 CRB11q31.3+2.10.000466Photoreceptor protein
 SYT141q32.2+2.10.000601Family of proteins involved in synaptic transmission
 C6orf1156q24.1+20.000848Uncharacterised protein
 APOD3q29−2.60.000762Putative lipoprotein metabolism. Inverse correlation between expression and colorectal tumour progression. Associated with neurodegeneration
 CLU8p21.1−2.40.000751Secreted anti-apoptotic chaperone protein. Overexpressed in many tumour types and associated with neurodegeneration
 SLFN1117q12−2.30.000237Putative DNA/RNA helicase. Expression of other family members inhibits growth of fibroblasts and thymoctyes. Sensitises cancer cells to DNA damaging agents
chr12 genes gain vs no gain
 NDST34q26+2.90.000814N-deacetylase/N-sulfotransferase 3. Golgi apparatus protein, associated with schizophrenia and bipolar disorder
 PRELP1q32.1−2.20.000646Connective tissue ECM protein. Abnormally expressed in chronic lymphocytic leukaemia cells
16q genes loss vs no loss
 PRAME22q11.22+6.40.000347Repressor of retinoic acid receptor. Overexpressed in multiple neoplasms (including melanoma).
 GLRA2Xp22.2+2.70.000412Glycine receptor alpha 2, neutrophil and p38 MAPK associated
 GABRA515q12+2.50.000136GABA receptor alpha 5, associated with schizophrenia and bipolar I disorder
 SLFN1117q12−3.60.000336Putative DNA/RNA helicase. Expression of other family members inhibits growth of fibroblasts and thymoctyes. Sensitises cancer cells to DNA damaging agents
Candidate genes for differential expression

Exome data

Exome sequencing was performed on the stromal DNA of seven cystadenofibromas, one adenofibroma and one cystadenoma (all with CNAs), and two cystadenofibromas and one cystadenoma with no CNAs. Exome sequencing identified 83 putative somatic variants, with an average of 7 mutations per case (range 2–20). It is difficult to enrich for the subpopulation of neoplastic fibroblasts in the stroma, as indicated by the low variant allele frequency of the majority of the variants (Additional file 2: Table S2), and subsequently difficult to validate findings by Sanger sequencing. We undertook Sanger validation of a subset of variants for each case. No recurrent mutations or recurrently mutated genes were identified that went on to validate. In total, 20 somatic variants were able to be validated by Sanger sequencing (Table 3). Of the validated variants, a single nonsense mutation was identified in the DMD gene. The remaining 19 validated variants were all missense variants, the functional impacts of which were assessed using transFIC (Transformed Functional Impact for Cancer) (Table 3). No variants from the three tumours with no CNAs validated by Sanger sequencing.
Table 3

Validated exome variants

SampleCHRPOSREFALTConsequenceGeneAmino acidsCondelPolyPhenSIFTSiftTransficLabelValidation
A4211821679TGMSPNPLA2F/CDeleterious (0.702)Prob_damaging (0.984)Tolerated (0.11)Low_impactSomatic
A4219897480GAMSR3HDM4P/LDeleterious (0.481)Prob_damaging (0.996)Tolerated (0.37)Low_impactSomatic
A42197090514TCMSHECW2Y/CDeleterious (0.935)Prob_damaging (0.999)Deleterious (0)High_impactSomatic
A4535068332CAMSPRLRA/SNeutral (0.019)Benign (0.026)Tolerated (0.38)Medium_impactSomatic
A4169943623CTMSGRIN2AV/INeutral (0.000)Benign (0.002)Tolerated (1)Low_impactSomatic
A4194448308CGSRVUBXN6.....Somatic
A41938692604GCMSSIPA1L3G/ANeutral (0.001)Benign (0.002)Tolerated (0.82)Low_impactSomatic
A17X31222107CANSDMDE/*....Somatic
IC158347127761TCMSSETD2H/RDeleterious (0.808)Prob_damaging (0.96)Deleterious (0.01)Medium_impactSomatic
IC158144156598CTMSKDM4AP/LDeleterious (0.881)Prob_damaging (0.987)Deleterious (0)High_impactSomatic
IC158796639132CTMSDLX6R/CDeleterious (0.877)Prob_damaging (0.985)Deleterious (0)High_impactSomatic
IC1587100484701GAMSSRRTV/MDeleterious 0.892)Prob_damaging (0.992)Deleterious (0)Medium_impactSomatic
IC15814102504858GTMSDYNC1H1G/VDeleterious (0.886)Prob_damaging (0.99)Deleterious (0)High_impactSomatic
IC1581621726339GAMSOTOAA/TNeutral (0.021)Benign (0.042)Tolerated (0.37)Low_impactSomatic
IC4671249422612TCMSKMT2DK/RDeleterious (0.543)Prob_damaging (0.994)Deleterious (0)NASomatic
IC4671711603150AGMSDNAH9K/EDeleterious (0.832)Prob_damaging (0.942)Deleterious (0)Medium_impactSomatic
IC4671951582924CAMSKLK14R/MNeutral (0.346)Benign (0.231)Tolerated (0.06)Medium_impactSomatic
IC4671954313656CAMSNLRP12E/DNeutral (0.028)Benign (0.113)Tolerated (0.37)Low_impactSomatic
IC467X5811262CTMSNLGN4XA/TNeutral (0.199)Poss_damaging (0.47)Tolerated (0.21)Low_impactSomatic
IC467X77112855TCMSMAGT1N/SNeutra (0.002)Benign (0.014)Tolerated (0.76)Low_impactSomatic

MS missense, NS nonsense, SRV splice receptor variant

Validated exome variants MS missense, NS nonsense, SRV splice receptor variant The ability to detect variants may be confounded by normal DNA contamination. There was a positive correlation between the number of variants detected (before validation) and the average allele frequency (Spearman’s r = 0.76, P = 0.01, Additional file 3: Figure S1). The mean sequencing depth was 121.3 reads (88.6–186.8) for germline samples and 122.7 reads (72.8–163.6) for somatic samples, therefore the detection of low frequency variants is not substantially compromised by limited depth of coverage.

Discussion

The findings of this study are consistent with previous karyotyping and FISH studies that identified trisomy 12 as the most common chromosomal abnormality identifiable in ovarian fibromas [8-10]. Pure ovarian fibromas were found to harbour chromosomal abnormalities more frequently than benign serous ovarian tumours (88% vs. 33%), further supporting our hypothesis that a subset of benign serous tumours are actually fibromas that coincidentally have an associated epithelial cyst. However, benign serous tumours more frequently harboured trisomy 12 as the sole aberration (47% of tumours with aberrations) compared to fibromas (30% of tumours with aberrations). Fibromas also more frequently harboured CNA that were rarely detected in the benign serous tumours such as 9q gain (50% cases), potentially indicating unique underlying biological drivers. Expression analysis provided some interesting candidates that have previously been associated with neoplasms or fibroblast growth for further investigation. Genes with increased expression in tumours with CNAs compared to those without CNAs included the extracellular matrix (ECM) and signalling molecules HAPLN1 and ANOS1, the antigen and repressor of retinoic acid signalling molecule PRAME, and the cell cycle regulator CKS2. All of these genes have been previously associated with overexpression in other types of neoplasm [28-34], and PRAME and CKS2 expression have been proposed as markers of poor prognosis in high-grade serous ovarian carcinoma [33, 35]. Genes with decreased expression in tumours with CNAs compared to those without CNAs included the putative DNA/RNA helicase SLFN11, the ECM protein PRELP, the high density lipoprotein component APOD, and the secreted chaperone CLU. Although these have all been linked with altered expression in other neoplasms before, this has typically been upregulation and potentially linked to neoplastic progression [36-40], including in ovarian cancer for APOD and CLU [41, 42]. Data is inconsistent for CLU, as expression was also linked to improved prognosis in high-grade serous ovarian carcinoma [33]. Low expression of SLFN11 has been associated with resistance to chemotherapy in ovarian cancer other cancers due to its role in the DNA damage response [43]. No genes were found to be recurrently mutated, however, two tumours had mutations in histone methytransferases (SETD2 and KMT2D) and one also had a mutation in a demethylase (KDM4A), all previously associated with neoplasia and all mutations predicted to be deleterious. Other mutated genes have also been associated with neoplasia, such as HECW2, SRRT and KLK14, with predicted medium to high deleterious impact.

Limitations

Use of Affymetrix Human Gene 1.0 ST array is limited to the probes on the array at the time. Insufficient power to detect differentially expressed genes due to n = 3 normal ovaries. Limited ability to detect mutations due to normal contamination. Additional file 1: Table S1. Genomic copy number aberrations. Additional file 2: Table S2. Variants detected by exome sequencing. Additional file 3: Figure S1. Correlation between the number of mutations and average allele frequency, suggesting that normal contamination may limit the number of mutations detected.
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4.  Pre-invasive ovarian mucinous tumors are characterized by CDKN2A and RAS pathway aberrations.

Authors:  Sally M Hunter; Kylie L Gorringe; Michael Christie; Simone M Rowley; David D Bowtell; Ian G Campbell
Journal:  Clin Cancer Res       Date:  2012-08-13       Impact factor: 12.531

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6.  PRAME-induced inhibition of retinoic acid receptor signaling-mediated differentiation--a possible target for ATRA response in AML without t(15;17).

Authors:  Lars Bullinger; Richard F Schlenk; Marlies Götz; Ursula Botzenhardt; Susanne Hofmann; Annika C Russ; Anna Babiak; Lu Zhang; Vanessa Schneider; Konstanze Döhner; Michael Schmitt; Hartmut Döhner; Jochen Greiner
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Journal:  Tumori       Date:  1992-04-30

8.  Clusterin is a potential molecular predictor for ovarian cancer patient's survival: targeting clusterin improves response to paclitaxel.

Authors:  Mohamed K Hassan; Hidemichi Watari; Yimin Han; Takashi Mitamura; Masayoshi Hosaka; Lei Wang; Shinya Tanaka; Noriaki Sakuragi
Journal:  J Exp Clin Cancer Res       Date:  2011-12-20

9.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples.

Authors:  Kristian Cibulskis; Michael S Lawrence; Scott L Carter; Andrey Sivachenko; David Jaffe; Carrie Sougnez; Stacey Gabriel; Matthew Meyerson; Eric S Lander; Gad Getz
Journal:  Nat Biotechnol       Date:  2013-02-10       Impact factor: 54.908

10.  Report on the first SLFN11 monothematic workshop: from function to role as a biomarker in cancer.

Authors:  Alberto Ballestrero; Davide Bedognetti; Domenico Ferraioli; Paola Franceschelli; Sana Intidhar Labidi-Galy; Elisabetta Leo; Junko Murai; Yves Pommier; Petros Tsantoulis; Valerio Gaetano Vellone; Gabriele Zoppoli
Journal:  J Transl Med       Date:  2017-10-02       Impact factor: 5.531

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