Integrated Molecular Analysis of Undifferentiated Uterine ... · Integrated Molecular Analysis of Undifferentiated Uterine Sarcomas Reveals Clinically Relevant Molecular Subtypes

Precision Medicine and Imaging

Integrated Molecular Analysis of UndifferentiatedUterine Sarcomas Reveals Clinically RelevantMolecular SubtypesAmrei Binzer-Panchal1, Elin Hardell2, Bj€orn Viklund1, Mehran Ghaderi2, Tjalling Bosse3,Marisa R. Nucci4, Cheng-Han Lee5, Nina Hollfelder1, P�adraic Corcoran1,JordiGonzalez-Molina2,6, LidiaMoyano-Galceran6,DebraA.Bell7, JohnK.Schoolmeester7,Anna Ma

�sb€ack8, Gunnar B. Kristensen9, Ben Davidson10, Kaisa Lehti6,11, Anders Isaksson1,

and Joseph W. Carlson2

Abstract

Purpose: Undifferentiated uterine sarcomas (UUS) arerare, extremely deadly, sarcomas with no effective treatment.The goal of this study was to identify novel intrinsic molec-ular UUS subtypes using integrated clinical, histopatholog-ic, and molecular evaluation of a large, fully annotated,patient cohort.

Experimental Design: Fifty cases of UUS with full clinico-pathologic annotation were analyzed for gene expression(n ¼ 50), copy-number variation (CNV, n ¼ 40), cellmorphometry (n ¼ 39), and protein expression (n ¼ 22).Gene ontology and network enrichment analysis were used torelate over- and underexpressed genes to pathways and furtherto clinicopathologic and phenotypic findings.

Results: Gene expression identified four distinct groups oftumors, which varied in their clinicopathologic parameters.Gene ontology analysis revealed differential activation ofpathways related to genital tract development, extracellular

matrix (ECM), muscle function, and proliferation. A multi-variable, adjusted Cox proportional hazard model demon-strated that RNA group, mitotic index, and hormone receptorexpression influence patient overall survival (OS). CNV arraysrevealed characteristic chromosomal changes for each group.Morphometry demonstrated that the ECM group, the mostaggressive, exhibited a decreased cell density and increasednuclear area. A cell density cutoff of 4,300 tumor cells permm2

could separate ECM tumors from the remaining cases with asensitivity of 83% and a specificity of 94%. IHC staining ofMMP-14, Collagens 1 and6, and Fibronectin proteins revealeddifferential expression of these ECM-related proteins, identi-fying potential new biomarkers for this aggressive sarcomasubgroup.

Conclusions:Molecular evaluation of UUS provides novelinsights into the biology, prognosis, phenotype, and possibletreatment of these tumors.

IntroductionUndifferentiated uterine sarcomas (UUS) are high-grademalig-

nant mesenchymal tumors (1). These tumors are extremely rare,so knowledge of their biology, prognosis, and therapy has beenlimited to small case serieswith often patchy or limited follow-up.They are diagnosed after exclusion of other, more common,mesenchymal tumors of the uterus and soft tissue, particularly

leiomyosarcoma, low-grade and high-grade endometrial stromalsarcoma, and carcinosarcoma (2).

Recent large-scale genomic studies of sarcomas have revealedseveral important conclusions (3–5) First, they can be generallydivided into translocation sarcomas, which show a diploid ornear-diploid genome, and karyotypically complex sarcomas,which often show large and complex chromosomal gains andlosses of genetic material (6). Second, within traditionally

1Science for Life Laboratory, Department of Medical Sciences, Uppsala Univer-sity, Uppsala, Sweden. 2Department of Oncology-Pathology, KarolinskaInstitutet, and Department of Pathology and Cytology, Karolinska UniversityHospital, Stockholm, Sweden. 3Department of Pathology, Leiden UniversityMedical Center, Leiden, the Netherlands. 4Department of Pathology, Brighamand Women's Hospital, Boston, Massachusetts. 5Department of Pathology andLaboratory Medicine, BC Cancer, Vancouver, BC, Canada. 6Department ofMicrobiology, Tumor and Cell Biology, Biomedicum, Karolinska Institutet, Stock-holm, Sweden. 7Department of LaboratoryMedicine and Pathology,MayoClinic,Rochester, Minnesota. 8Department of Pathology, Ska

�nes University Hospital,

Lund, Sweden. 9Department Gynecologic Oncology and Institute for CancerGenetics and Informatics, Norwegian Radium Hospital, Oslo University Hospital,Oslo, Norway. 10Department of Pathology, Norwegian Radium Hospital, OsloUniversity Hospital, Oslo; Institute for Clinical Medicine, The Medical Faculty,

University of Oslo, Oslo, Norway. 11Genome-Scale Biology, Research ProgramsUnit, University of Helsinki, Helsinki, Finland.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

A. Binzer-Panchal and E. Hardell contributed equally to this article.

A. Isaksson and J.W. Carlson contributed equally to this article.

Corresponding Author: JosephW. Carlson, Karolinska Institutet and KarolinskaUniversity Hospital, Cancer Center Karolinska, R8:3, 17176 Stockholm, Sweden.Phone: 46761130912; E-mail: [email protected]

doi: 10.1158/1078-0432.CCR-18-2792

�2019 American Association for Cancer Research.

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defined sarcoma subtypes are subtype-specific molecular char-acteristics that can govern biology, therapy, and prognosis(3, 4). Thus, although general conclusions regarding sarcomabiology can be made with these studies, further work isrequired to understand the subtype and location-specificchanges that might govern biology, prognosis, and, ultimately,therapy.

Uterine sarcomas have a distinct biology from other soft-tissue sarcomas. They demonstrate unique translocations, suchas JJAZ-JAZF1 and YWHAE-FAM22, that are not seen at othertissue sites (7–9). Benign tissues of the female genital tractexpress hormone receptors, and this is retained in a subset ofsarcomas (10, 11). This expression has been demonstrated toconfer a better prognosis in leiomyosarcomas (10). Indeed,smooth-muscle tumors have a distinct biology depending uponwhether they arise in the gynecologic tract or not (3, 5).Previously, our group has demonstrated that division intomitotic index groups has prognostic significance for overallsurvival (12, 13). Other studies have attempted to use atypiato subdivide UUS into "uniform" and "pleomorphic" types(14, 15). To date, no large-scale molecular characterization hasbeen performed on UUSs.

Research into therapies for gynecologic sarcomas has beenlimited by the difficulty of assembling a sufficient number ofcases for clinical trials. Despite limited evidence, primary therapyis complete surgical resection, if possible. There are no conclusivedata regarding the use of adjuvant therapy inUUS, and the currentsuggestion is to use therapies indicated for soft-tissue sarcomas atother sites (16). One study evaluated the use of pazopanib, amultitargeted receptor tyrosine kinase inhibitor, in pretreated,metastatic uterine sarcomas (17). This study demonstrated clin-ically relevant efficacy and tolerability.

The goal of this study was to comprehensively examine thebiology of a large, well-annotated cohort of UUS, in order toidentify tumor-intrinsic molecular subgroups with biological,clinical, and potential therapeutic significance.

Materials and MethodsPatient cohort and central review

This retrospective patient cohort was assembled via interna-tional collaboration from seven collaborating centers. Ethicalapproval was obtained from the relevant local authorities. Themajority of cases were submitted to three levels of review. First,they were reviewed by the original diagnosing pathologist. Sec-ond, a central review was performed by the participating expertgynecologic pathologist. Based on this review, a single represen-tative hematoxylin and eosin (H&E)-stained tumor slide wasselected for the third, central, review. Finally, the selected slideswere reviewed again at the KarolinskaUniversityHospital.Mitoticrate and grade of nuclear atypia was determined as describedpreviously (12, 13). IHC for estrogen receptor and progesteronereceptor was performed locally in clinical labs accredited for thisanalysis. Representative FFPE tumor material containing a min-imum of 70% tumor cells was submitted to the KarolinskaUniversity Hospital for isolation of DNA and RNA. One repre-sentative tumor slide was digitally scanned (Hamamatsu Nano-Zoomer, 40� scan) for image analysis. Exceptions to the aboveprotocolwere Ska

�nesUniversityHospital (n¼10patients), where

no second, local, review was performed; all slides were submittedfor the third, central review, and Vancouver General Hospital (n¼4 patients), where no central reviewwas performed;mitotic countand atypia review were assessed by the participating pathologist.

RNA expression arraysRNA quality was evaluated using the Agilent 2100 Bioanalyzer

system (Agilent Technologies Inc.). Total RNA (100 ng) from eachsample was used to generate amplified and biotinylated sense-strand cDNA from the entire expressed genome according to theSensation Plus FFPE Amplification and WT Labeling Kit (P/N703089, Rev.4 Thermo Fisher Scientific Inc., Life Technologies).GeneChip ST Arrays (GeneChip Human Gene 2.1 ST Array Plate)were hybridized, washed, stained, and finally scanned with theGeneTitan Multichannel (MC) Instrument, according to theGeneTitan Instrument User Guide for Expression Array Plates(PN 702933, Thermo Fisher, Scientific Inc., Life Technologies).

DNA copy-number arraysDNA quantity was measured using the Qubit Fluorometer.

Samples with low concentration of DNA were concentrated withthe use of MinElute Reaction Cleanup Kit (50) Cat no. 28204(QIAGEN). During this procedure, the DNA binds to a column, isrinsed with washing buffer, and finally eluted in nuclease-freewater.

DNA Array experiments were performed according to standardprotocols for Affymetrix OncoScan Arrays (Affymetrix OncoScanFFPE Assay Kit User Guide (P/N 703175 Rev. 2), Affymetrix Inc.).Total genomic DNA (80 ng) was incubated overnight to annealthe MIP probe. Each sample was then divided into two differentchannels, one for AT nucleotides and another for GC nucleotides.The gaps formed after the annealing process were filled usingdNTPs and relevant reagents. Exonuclease removed nonligatedMIP probes and a cleavage enzyme linearized the circular MIPprobes. Then the DNA was amplified via two cycles of PCR anddigested using the HaeIII enzyme. On the Oncoscan Arrays,hybridized probes were captured by streptavidin–phycoerythrinconjugates using the GeneChip Fluidics Station 450 and arrayswere scanned using GeneChip Scanner 3000 7G.

Translational Relevance

Undifferentiated uterine sarcomas (UUS) are among therarest and deadliest of the uterine sarcomas. This has hinderedthemolecular understanding of their biology and thus limitedthe introduction of new therapies. This study uses a well-annotated, large cohort of UUS, combined with RNA expres-sion, chromosomal copy number, computer-assisted histo-logic analyses and IHC, to identify and describe four intrinsicsubtypes of these tumors. These subtypes vary in their biology,clinicopathologic parameters, and survival. The most aggres-sive, ECM, subtype was characterized by a tumor cell pheno-type with distinct morphology and protein expression, whichwill provide means to identify these cases using current lab-oratory techniques. Unique chromosomal changes were sig-nificantly associated with each group. Finally, gene ontologyand network enrichment analysis identified target candidatesfor therapy. These results, from our hypothesis-generatingcomprehensive approach, will open new avenues to studyand stratify these tumors, with the long-term goal of devel-oping clinical interventions that will help improve patientsurvival.

Binzer-Panchal et al.

Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research2156




The OncoScan fluorescence intensity (CEL) files were normal-ized with Affymetrix OncoScan Console v.1.3 with default set-tings. Segmentation was done with Nexus Copy Number v.9.0from BioDiscovery with the TuScan algorithm. Allele specificcopy-number analyses were performed with the Tumor Aberra-tion Prediction Suite (TAPS) 2.0 (18). Affymetrix expression array,Oncoscan, and clinical metadata are available via the Gene-Expression Omnibus database repository accession numberGSE119043.

Quantitative cell morphometryQuPath v0.1.2 (https://github.com/qupath/qupath) open

source software was used for cell detection (19). Whole scannedslides, available for the majority of cases (39/50; 78%), werereviewed, blinded to clinical and molecular parameters, and two1.27 mm in diameter circles were selected as regions of interest(ROI). The automatic "Cell detection" was run on the ROI withthe default settings except the "Maximumarea" that was increasedto 3,400 mm2 due to large cells in particular samples. The resultsfrom the two ROIs were averaged to obtain a single value for thecase. The results were exported as a text file and further analyzedwith R (http://www.r-project.org).

IHCTMA sections were deparaffinized and rehydrated (2 � 10

minute Tissue Clear, 2 � 5 minute absolute EtOH, 1 � 5 minute96% EtOH, 1 � 10 minute 70% EtOH, 2 � 5 minute MQ H2O).Antigen retrieval was performed using 10 mmol/L sodium citratepH 6 (15 minute heat, 30 minute cool down, 2� 5 minute PBS).Endogenous peroxidase was quenched with 0.6% H2O2 for 10minutes, 2 � 5 minute PBS (for ImmPRESS kit) or with 0.03%H2O2 for 10 minutes, 1 minute H2O, 10 minute PBS [forTyramide Signal Amplification (TSA) kit].

For the ImmPRESS method, sections were blocked with 2.5%normal horse serum for 30 minutes (ImmPRESS, Vector Labora-tories; cat. #MP-7402). Sections were incubated withaMT1-MMP(LEM) ¼ MMP14 antibody (Millipore; cat #MAB3328) diluted1:100 in 2.5%normal horse serumovernight at 4�C in a humiditychamber. Secondary antibody incubation was performed withImmPRESS reagent (anti-mouse IgG coupled to peroxidase, Imm-PRESS, Vector Laboratories; cat #MP-7402) for 30 minutes at RT.Staining was revealed using DAB substrate (3 minute incubation,5 minutes in tap H2O). Sections were counterstained with aque-ous hematoxylin (1 minute incubation, rinsed with H2O), dehy-drated (1 � 2 minute 96% EtOH, 1 � 2 minute absolute EtOH,1� 5 minute Tissue Clear) and mounted with Eukitt (Sigma; cat.#25608-33-7).

For the TSA method, sections were blocked with TNB BlockingBuffer [0.1 mol/L Tris-HCl, pH 7.5; 0.15 mol/L NaCl; 0.5% (w/v)blocking reagent (PerkinElmer, cat. #FP1020)] for 30 minutes atRT. Primary antibodies were diluted in TNB blocking buffer asfollows: Collagen 1 (Abcam; cat. #ab34710) 1:200, Collagen 6(Abcam; cat. #ab6588) 1:200, fibronectin (Sigma; cat. #F3648)1:100. Primary antibody incubation was performed overnight at4�C in a humidity chamber. After 10-minute wash with TNT[0.1 mol/L Tris-Cl, pH 7.5; 0.15 mol/L NaCl; 0.1% (v/v) Tween20], sections were incubated with biotinylated secondary anti-body (diluted 1:200 in TNB) for 30 minutes, 1� 10minute TNT.Next, sections were incubated with SA-HRP (PerkinElmer; cat.#NEL750001EA, diluted 1:100 in TNB) for 30 minute, 1 � 10minute TNT, and with biotinylated tyramide (diluted 1:50 in

amplification buffer) for 10minutes, 1�10minute TNT. Sectionswere incubated again with SA-HRP (diluted 1:100 in TNB) for 30minutes, 1 � 10 minute TNT, and finally washed with PBS.Staining was revealed using AEC substrate (4 minute incubation,1 minute in MQ H2O). Sections were counterstained with hema-toxylin (1 minute incubation, rinsed with H2O) and mountedwith Aquatex (Millipore; cat. #108562).

IHC quantitationQupath v0.1.3, an updated pre-release version of Qupath

(https://github.com/petebankhead/qupath) open source soft-ware, was used for positive pixel counting on four TMAs withIHC stainings for Collagen 1, Collagen 6, Fibronectin, andMMP14. TMA slides that contain 22 of the cases were dearrayed,and the detected cores were manually adjusted so that the entiretissue sample was included. Tissue detection was performed withthe following changes to the default settings: Threshold was set to220, requested pixel size to 2 mm, minimum area to 15,000 mm2

and maximum fill area to 600 mm2. Subsequently, positive pixelswere counted with the following deviations from default: down-sample factor 2.0, Gaussian sigma 0.5 mm, "negative" hematox-ylin threshold 0.15 OD units, and "positive" DAB threshold0.1 OD units. The results were exported as text files and furtheranalyzed with R.

Bioinformatics and statistical analysisThe RNA raw data were normalized in the free Affymetrix

Expression Console Software provided by Thermo Fisher(www.thermofisher.com) using the robust multiarray averagemethod (20, 21). Subsequent analysis of the gene-expressiondata was carried out in the freely available statistical computinglanguage R. Unsupervised hierarchical clustering was done usingthe package "stats." To test for differentially expressed genesbetween the identified groups, an empirical Bayes moderated ttest was applied using the "limma" package available from theBioconductor project (www.bioconductor.org; refs. 22, 23). Toaddress the problem with multiple testing, the P values wereadjusted using the method of Benjamini and Hochberg (24). TheDatabase for Annotation, Visualization and Integrated Discovery(DAVID) v6.8 and the REVIGO ("REduce and VIsualize GeneOntology") tool was used to assess the over- and underexpressedgenes by organizing them into ontologies and summarizing themby reducing redundant GO terms (25–27). Kaplan–Meier anal-yses used the R-package "rms," Cox proportional hazard tests theR-package "survival." A t test was performed using R to test fordifferences in the percentage of positive pixels, nuclear area, andcells per area counts between RNA groups. The values included inthe t test were the mean of the two replicate cores present on theTMA or the mean of the two ROIs for each sample, when tworeplicates were available.

ResultsPatient cohort

Clinicopathologic characteristics of the patient cohort are pre-sented in Table 1. A total of 50 cases of UUS were included. Allcases were negative for the JAZF1–JJAZ1 and YWHAE–FAM22translocations (RT-PCR: 46 cases, FISH: 4 cases). The majority ofpatients died within 5 years after diagnosis (34, 68%), while theremainder were alive beyond 5 years (14, 28%). Two patients hada follow-up time less than 5 years (12 and 15 months,

Molecular Classification of UUS

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respectively). The mean follow-up time, including deceasedpatients, was 3.2 years (range, 0.1–18.8). Excluding deceasedpatients, the mean follow-up time was 9.3 years (1–18.8). Themajority of cases were included from the Karolinska UniversityHospital. The cases were almost evenly split into prognosticmitotic index groups. There was a predominance of uniform-typeUUS. Estrogen and progesterone receptor status was available inthe majority of cases.

RNA expression results revealed four distinct molecular groupsRNA expression analysis was successful on all cases (n¼ 50/50,

100%). Unsupervised clustering of RNA expression data revealedfour clusters (Fig. 1A), termed "Developmental," "Leiomyosar-coma (LMS)-like," "ECM," and "Low Proliferation" (Fig. 1A, asindicated in blue, yellow, green, and red, respectively). Thesegroupings are seen in the principal component analysis (Fig. 1B,same color scheme).

Examination of the gene-expression data focused on the 50most over- and underexpressed genes within each subgroup, asdetermined by the fold change. The top 15 over- and under-expressed genes are shown visually in a heat map (Fig. 1C).Kaplan–Meier curves (Fig. 1D) showed a significant variation inoverall survival between the RNA groups, with the ECM groupshowing the worst prognosis (log-rank test, P ¼ 0.0037). Theremaining groups shared a comparatively better survival.

DNA CNV revealed a spectrum of chromosomal changes, withparticular gains and losses associated with each RNA group

DNA CNV analysis was successful in the majority of cases (n¼40/50, 80%). This analysis revealed a spectrum of chromosomalcopy-number variation (CNV), from cases that were diploid ornear diploid to cases with extensive chromosomal aberrations.This variation is summarized in Fig. 2A, where the percentage ofthe genome showing diploid DNA sections is presented. Cases tothe right are diploid/near-diploid, while cases progressing to theleft show increasing nondiploid sections. Cases were divided into"LowCNV" (n¼ 15/40, 38%) and "HighCNV" (n¼ 25/40, 62%).

Kaplan–Meier curves showed a tendency to decreased overallsurvival for the high CNV tumors compared with the low CNVtumors (Fig. 2B). This difference was not significant (log-rankP ¼ 0.1743).

Gains and losses of chromosomal segments were analyzed foreach RNA group, and this revealed a number of significantdifferences in chromosomal segment composition. For example,the ECM group showed an increased frequency of 4q and 7qrelative gains, 6q relative loss, and LOH near the centromere ofchromosome 9 (Fig. 2C). Chromosomal segment compositionsfor the other RNA groups are presented in Supplementary Fig. S1.

Overall survival depended on clinicopathologic and moleculartumor properties

A Cox proportional hazard model was constructed, includingboth clinicopathologic and molecular characteristics (Table 2).The unadjusted (crude) model revealed that mitotic index groupand hormone receptor expression showed a significant influenceon overall survival. This has been seen previously for thesecases (12, 13). In the unadjusted (crude) model, RNA groupassignment was close to significance, with a P value of exactly0.05. The adjusted model showed that these three variables had asignificant impact on overall survival, with an explanatory power(r-square) of 0.43. In the adjusted model, the presence of positivehormone receptor expression (either estrogen or progesterone)was strongly protective (HR ¼ 0.21), while high mitotic index orECM-related gene-expression signature were indicators of a poorprognosis (HR ¼ 2.63 and 2.52, respectively).

Gene ontology and network enrichment analysis revealedbiological differences between RNA groups

The relationship betweenRNA subgroup and clinicopathologiccharacteristics is presented in Supplementary Table S1.

The first group contained 21 cases (42%). The GO terms seenin the overexpressed genes, as visualized by REVIGO (Fig. 3A),show ontologies related to developmental pathways, particu-larly the gynecologic tract, positive regulation of gene expres-sion and translation, and genes related to chromatin organi-zation. This REVIGO analysis complements the NEA, whichshowed a number of pathways related to proliferation, such aspeptide chain elongation. The low-expression GO terms includ-ed regulation of interferon gamma, leukocyte cell–cell adhe-sion, and other inflammatory pathways such as NF-kB, leuko-cyte activation, and response to type I interferon. Given thepresence of gene ontologies related to mesenchyme and repro-ductive structure development, as well as embryonic and tubemorphogenesis, this group was named the "Developmental"group. This group contained the highest frequency of highmitotic index cases. Most of the cases were uniform-type, fewsurvived past 5 years, and most showed negative hormonereceptor staining. They were roughly evenly divided into highand low CNV groups. Of the overexpressed genes in this group,HMGA2 is a candidate biomarker.

The second group contained 10 cases (20%). The GO termsseen in the overexpressed genes in this group were related tomuscle function, particularly actin cytoskeleton activation, car-diovascular system development, and circulatory system devel-opment (Fig. 3B). The NEA similarly showed smooth-musclecontraction as themost significant activated pathway. GO enrich-ment analysis of the 50underexpressed genes in this groupdidnotreveal any unifying ontologies. The majority of cases showed

Table 1. Clinicopathologic characteristics of the included cases of UUS

Total number of cases 50Time to last follow-up, all patients (years) 3.2 � 4.6 (0.1–18.8)Time to last follow-up, survivors (years) 9.3 � 5.5 (1–18.8)Long-term survivors (alive minimum 5 years) 14 (28%)Deceased prior to 5-year follow-up 34 (68%)Alive, follow-up less than 5 years 2 (4%)Cases included fromKarolinska University Hospital 17 (34%)Oslo University Hospital 13 (26%)Ska

�ne University Hospital 10 (20%)

Mayo Clinic 5 (10%)Vancouver General Hospital 4 (8%)Brigham and Women's Hospital 1 (2%)

Mitotic index group (13)High (>11.16 mitotic figures/mm2) 23 (46%)Low (<11.16 mitotic figures/mm2) 27 (54%)

Nuclear atypia (15)Uniform 33 (66%)Pleomorphic 13 (26%)Unknown 4 (8%)

Estrogen and progesterone receptor statusPositive 11 (22%)Negative 28 (56%)Unknown 11 (22%)






uniform-type nuclear atypia, but were otherwise roughly evenlydivided in terms of survival>5 years, hormone receptor positivity,andCNV group. Given the overexpression ofmuscle and smooth-muscle–related gene ontologies, this group was assigned as"leiomyosarcoma (LMS)-like." Of the overexpressed genes in thisgroup, MYH11, ACTG2, and MYLK, all recently described"secondary" smooth-muscle markers, are candidate biomarkers.

The third group contained eight cases (16%). The GO termsseen in the overexpressed genes in this group were related toextracellular matrix disassembly, aminoglycan catabolism, andangiogenesis (Fig. 3C). GO enrichment analysis of the 50 under-expressed genes in this group did not reveal any unifying ontol-

ogies. The NEA showed ECM proteoglycans, ECM–receptor inter-action, and degradation of the extracellular matrix as the mostsignificantly overexpressed pathways. All 8 patients in this groupdied within 2 years. The cases were divided between uniform andpleomorphic type nuclear atypia, and close to evenly dividedbetween high- and low mitotic groups. None of these casesshowed positivity with hormone receptors. There was a predom-inance of tumors with high CNV. There was a trend towardincreased incidence of lymphovascular space invasion (LVSI) inthis group versus the rest of the cases (6/7 cases, 86%, vs. 13/20,65%, P value 0.301; note that only cases with all slides availablewere included in the statistics for LVSI). This group was assigned

Figure 1.

RNA expression analysis reveals distinct subgroups. Developmental (blue), LMS-like (yellow), ECM (green), and low proliferation (red). A, Unsupervisedhierarchical clustering of RNA expression reveals 4 distinct groups. The squares adjacent to the case abbreviation indicate survival status (yellow: alive at 5 years,red: death prior to 5 years, black: follow-up less than 5 years). B, Principal component analysis also demonstrates the presence of distinct expression basedsubgroups. C, Heat map showing the 15 most over- and underexpressed genes in each group. D, Kaplan–Meier curve showing overall survival foreach RNA group.






the name "ECM" group. Of the overexpressed genes in this group,MMP14, COL14A1, COL6A3, and FN1 are candidate biomarkers.

The fourth group contained 11 cases (22%). TheGO terms seenin this groupwere based on reduced expression of genes related tomitotic nuclear division, transcription, and regulation of geneexpression (Fig. 3D). The NEA revealed only one significantreduced pathway, RNA polymerase III transcription. GO enrich-ment analysis of the 50 overexpressed genes in this group did not

reveal any unifying ontologies. This group showed a correlationwith low mitotic index group, with only two cases from the highmitotic index group (ANOVA P ¼ 0.0458). Most cases showeduniform-type atypia. Theywere roughly evenly divided in survival>5 years, expression of hormone receptors and CNV high versuslow. This group was considered to represent a "low-proliferation"expression profile. Thus, mitotic index appears to be a candidatemarker for identification of this group.

Figure 2.

DNA CNV analysis reveals a spectrum of chromosomal changes.A, Diploid length curve, showing the percentage of DNA segments that were diploid as apercentage of the entire genome length, demonstrates that tumors had a distribution of CNV. B, Kaplan–Meier curve showing overall survival for each DNAgroup. C, Chromosomal segments showing gains (top diagram), losses (middle diagram), and LOH (bottom diagram) across the entire genome for the ECMgroup. These diagrams show the fraction of cases in the ECM group with segment change (gain, loss, or LOH) as the positive y-axis in percent, and the fraction ofcases with the same change that are not in the group as the negative y-axis. The difference between these two (i.e., the change is present in the ECM group vs.remainder) is then shown in the darker color. Significant differences at the P < 0.05 level between ECM and the remainder are shown in the lighter shaded regionsthat extend from�100% toþ100%.






Image analysis revealed that the ECM group is characterized byreduced cell density and increased nuclear size

In order tomore closely examine the phenotypic characteristicsof the cases in relation to RNA expression, image analysis ofscannedH&E-stained tissue sectionswas performed. This revealeddistinct morphologic differences between the intrinsic groupsidentified by RNA expression analysis (Fig. 4A and B). Two ROIswere examined for each slide and averaged. Note that the imageanalysis algorithm had trouble reliably identifying the cyto-plasmic boundary of each cell, so cell density (as determinedfrom nuclei per unit area) was calculated. A total of 39 scannedslides were available, with each RNA group represented (DEV:16/21 cases, LMS-LIKE: 8/10 cases, ECM: 6/8 cases, and LOWPROLIFERATION: 9/11 cases). The ECM group showed a signif-icantly decreased cell density as well as an increased nuclear area(Fig. 4A and B). There was a negative correlation between celldensity and deposition of ECM proteins, which was statisticallysignificant for all 3 ECM proteins examined (Collage 1, Collagen6, and Fibronectin; see Supplementary Table S2). Given thisdistinct phenotype, the possibility of using a cutoff to identifyECM group cases purely from image analysis was investigated.Using a cell density cutoff of �4,300 cells per mm2 alloweddistinction of ECM tumors from the remaining tumors with asensitivity of 83% and a specificity of 94%.

Protein expression by IHC revealed distinct protein expressionprofiles across RNA groups

IHC was used to interrogate the protein expression of fourECM-related proteins. The ECM group was particularly selectedfor evaluation due to its extremely poor prognosis. These proteinswere selectedbasedonoverexpressed genes in the ECMgroup. Theexpression of matrix metalloproteinase 14 (MMP-14), Collagen1, Collagen 6, and Fibronectin was evaluated. Differences in

expression were seen between the RNA groups, with highestexpression seen for all these proteins in the ECM group(Fig. 4C–F), with a significant difference to the developmentalgroup in the Collagen 1, Collagen 6, and MMP-14. The LMS-likegroup showed the second highest expression, followed by thedevelopmental and low-proliferation groups.

DiscussionUUSs are aggressive mesenchymal tumors with an unclear

biology. These tumors have traditionally been grouped withinthe endometrial stromal sarcomas, given their lack of smooth-muscle differentiation by light microscopy and IHC. Due to theirrarity, well-annotated cohorts allowing evaluation of clinical,pathologic, and molecular characteristics have been lacking. Thishas led to difficulties with developing treatment strategies that canbe effective against these tumors. Recent comprehensive genomicstudies of soft-tissue sarcomas have revealed that, unlike epithe-lial malignancies, sarcomas are characterized by copy-numberalterations, with low mutational burdens and few recurrentlymutated genes (3). Transcriptomic diversity within sarcoma typesappears to define molecular subtypes related to patient progno-sis (3). A recent study using NGS methods identified numerousgenomic alterations (including copy-number gains) that weretargetable (28).

Previously, we have demonstrated the importance of mitoticindex and hormone receptor expression in the prognosis of thesetumors (12, 13). The goal of this study was to further that analysisusing molecular methods appropriate to sarcomas. Previousgenomic studies have indicated that sarcomas show variationsin gene expression and chromosomal gains and losses, but thatthey typically show few characteristic gene mutations. A furtherlimitation to the study of these cases is their rarity. This requires

Table 2. Cox proportional regression analysis for overall survival in relation to clinical and molecular features

Crude results(single explanatory variable)

Adjusted results(multiple explanatory variables)

r2 ¼ 0.43OS OS

Variable Number of patients HR P value HR P value

Mitotic indexLow 27 Reference ReferenceHigh 23 2.33 (1.21–4.50) 0.01�� 2.63 (1.27–5.45) 0.01��

Hormone receptor expressionNegative 28 Reference ReferencePositive 11 0.17 (0.06–0.50) <0.01�� 0.21 (0.07–0.65) 0.001��

N/A 11 0.70 (0.32–1.52) 0.37 0.7 (0.31–1.61) 0.4RNA groupDevelopmental 21 Reference ReferenceLMS-like 10 0.46 (0.19–1.14) 0.09 0.48 (0.18–1.27) 0.14ECM 8 2.39 (1.00–5.72) 0.05 2.52 (1.02–6.24) 0.045�

Low proliferation 11 0.52 (0.22–1.22) 0.13 0.98 (0.39–2.39) 0.96Nuclear atypiaUniform 33 ReferencePleomorphic 13 1.63 (0.81–3.26) 0.17N/A 4 1.34 (0.31–5.78) 0.69Cell densityLow 22 ReferenceHigh 15 1.26 (0.62–2.57) 0.53N/A 13 0.81 (0.35–1.89) 0.63CNV groupHigh 25 ReferenceLow 15 0.67 (0.32–1.41) 0.29N/A 10 0.46 (0.19–1.09) 0.08

NOTE: Significance test is indicated with � (P < 0.05) and �� (P < 0.01).






the use of archived, formalin-fixedmaterial with varying RNA andDNA quality.

Gene-expression analysis of these tumors reveals four subtypeswith clinical significance. In particular, tumors in the ECM groupshow overexpression of extracellular matrix genes and appear tobe particularly deadly, with all 8 patients in this group dyingwithin 2 years of diagnosis. The low-proliferation group correlateswell with the mitotic index group, thus indicating that prolifer-ation in these tumors, asmeasured by the identification ofmitoticfigures in light microscope, has a clear prognostic and biologicalcorrelation. The LMS-like group cases that express muscle-relatedgenes and are thus possibly variants closely related to leiomyo-sarcoma. Finally, the developmental group showed activation ofdevelopmental genes and differences in expression of genesrelated to immune function. These results indicate that thesesarcomas may be modulating the host immune response using

cytokine mechanisms such as interferons. Our results wouldindicate that further, more functional, studies of these processesmay be fruitful in identifying new therapeutic targets.

Copy-number variation arrays showed, surprisingly, tumorsthat were both near diploid, with lowCNV, and high CNV tumorswith extensive gains and losses. Previously, studies have success-fully divided sarcomas into translocation-associated and karyo-typically complex subtypes (6). Given the aggressive and high-grade nature of these tumors, our initial hypothesis was that thesetumors would all show a complex chromosomal heterogeneity.This was not the case, and roughly half the cases were diploid ornear diploid. This is an important finding for future studies andmay indicate that there are as yet undiscovered translocationswithin these high-grade tumors. Furthermore, the CNV divisioninto high and low groups was not prognostic, indicating that eventhe near-diploid tumors can behave aggressively. Several recent

Figure 3.

RNA ontology, as visualized using REVIGO, for each RNA group. A,Overexpressed genes in the developmental group. B,Overexpressed genes in the LMS-likegroup. C,Overexpressed genes in the ECM group.D, Underexpressed genes in the low-proliferation group.






studies using array CGH in uterine smooth-muscle tumors haveindicated that genomic complexity is prognostic in that group oftumors (29, 30). Our findings, in contrast, appear to indicate thatgenetic complexity is not prognostic in UUS, and thus chromo-somal complexity as a prognostic marker is subtype specific. Thepresence of distinct chromosomal changes that correlate witheach RNA subtype is also interesting. Further study will berequired to dissect the relationship between chromosomal gainsand loss and gene expression.

The survival analysis revealed that, in addition to previouslydescribed prognostic markers, mitotic index and hormone recep-tor expression, expression signature-based division to RNA groupwas also prognostic. This was true even in the adjusted model.Indeed, the RNA group showed a hazard ratio close to that seenwith the mitotic index group. This result indicates that reliableprospective studies of these sarcomas will need to take genetranscription into account, and developing models of treatmentand behavior of these tumors will probably require routine use oftranscriptomic methods such as RNA sequencing.

Several identified pathways that are potentially targetablehave been identified in the molecular analysis presented here.First, targeting ECMmechanisms may lead to active therapies inthese tumors. The tumor microenvironment consists of a com-

plex network of blood and lymphatic vessels, immune cells,cancer-associated fibroblasts, and extracellular matrix compo-nents. One of the most highly overexpressed genes in this groupwas fibronectin. This gene, which expresses a class of high-molecular-weight adhesive glycoproteins, has been investigatedas a potential treatment target. It has a central role in ECMsignaling and exists in multiple isoforms. It is possible theseisoforms could be individually targeted using, for example,monoclonal antibodies (31–33). Other ECM-related genesoverexpressed in this group include matrix metalloproteinases,such as MMP2 and MMP14. Although drugs have been devel-oped against MMPs, initial trials were unsuccessful. There has,however, been renewed interest in developing new therapiestargeting specific MMP activities (34). The overexpression ofMMP has been associated in other tumors with aggressivebehavior. In UUS, there was a trend to an increased incidenceof LVSI in the ECM group.

The developmental group showed reduced expression of sev-eral immune regulatory pathways, particularly NF-kB. This tran-scription factor forms protein complexes that bind and regulatetarget genes via consensus DNA promoter regions. It is typicallyconsidered pro-oncogenic, stimulating proliferation, preventingapoptosis, regulating tumor angiogenesis, and promoting

Figure 4.

Image analysis results of morphometry (n¼ 39) and IHC (n¼ 22) reveal distinct differences, particularly between the ECM developmental groups. Boxplotsshowing differences in cell density (A) nuclear area (B), and IHC for MMP-14 (C), Collagen 1 (D), Collagen 6 (E), and Fibronectin (F) for each RNA group. Celldensity is reported in cells per mm2� 1,000. Nuclear area is given in micrometer squared� 1,000. IHC is % of the tissue that is positive. Significance test betweeneach group is indicated by a red line with either � (P < 0.05) or �� (P < 0.01).






metastasis (35). Reduction in the expression of TNF-alpha, leu-kocyte adhesion, and leukocyte activation indicate a reduction inimmunostimulatory molecules, and potentially reflect mechan-isms by which this subgroup escapes host immune surveil-lance (36). Clearly, untangling the immunomodulatory effectsof these pathways and how they can best be targeted will requirefurther studies. However, these hypothesis-generating results canserve as an indicator that help to assess if immune therapieswill beuseful in these tumors (37).

The increased expression of muscle-related genes in the LMS-like group indicates that these tumors might best be considereda variant of leiomyosarcoma and grouped with them in clinicaltrials and treatment planning. During the inclusion and exclu-sion phase of this study, the goal was to err on the side ofexcluding any case that could be conceivable called leiomyo-sarcoma. Thus, these cases would not be diagnosed as leio-myosarcoma using current methods. The RNA expressionresults, however, indicate that the tumors in this LMS-likesubgroup express several muscle-related genes, such as MYH11,ACTG2, and MYLK. The proteins expressed by these genes haverecently been used to identify poorly differentiated leiomyo-sarcomas and represent several candidate biomarkers to iden-tify these tumors (38). Finally, the low-proliferation groupappears to confirm a biological equivalent to the mitotic indexgroup, with reduced expression of a number of proliferation-related genes. Notably, two cases in the low-proliferation groupalso had a high mitotic index. This may be due to tumorheterogeneity—the area used for mitotic count was not neces-sarily the area used for molecular analysis.

Image analysis revealed morphologic differences in themost aggressive, ECM-related, sarcoma subgroup. The reducedcell density and increased nuclear size demonstrates a pheno-typic correlation to the RNA expression data. There was anegative correlation between ECM protein deposition and celldensity, supporting the interpretation that the decrease in celldensity is due to increased deposition of ECM proteins. Arelationship between myxoid stromal amount and gene expres-sion was recently identified in a comprehensive transcriptomicanalysis of myxofibrosarcoma and undifferentiated pleomor-phic sarcoma (3). That study indicated that those two sarcomasare not distinct entities, but rather fall along a spectrum, withvarying amounts of overexpression of myxoid stromal-relatedgenes.

Surprisingly, nuclear size did not correlate with chromosomalCNV. Based on the IHC results, it appears that this decrease in celldensity is related to an increase in ECM-related proteins. Nuclearsize has classically been associated with variations in ploidy, butthe nuclear envelope is also affected by biomechanical forces,which in turn result from the tumor cellmicroenvironment. Theseforces may explain the increase in nuclear size in the ECMsubgroup. It is important to note that, while in epithelial tumors,ECM can be produced by cancer-associated fibroblasts, sarcomasare tumors of mesenchymal tissues. Hypothetically, the malig-nant sarcoma cells are themselves producing ECM componentsbecause of this mesenchymal origin.

Several potential biomarkers that correlate with the mostaggressive, ECM, subgroup have been identified in this work.First, imagemorphometry usingH&E-stained sections was able toidentify themost aggressive subgroup andmay provide a valuabletool to routine histologic examination. Routine H&E staining isreadily available in all pathology labs, and morphometry meth-

ods are not difficult to set up. This morphometry method maythus allow the ECM-related subgroup of UUS to be identifiedusing readily available methods. IHC using ECM-related proteinsCollagen 1, Collagen 6, and MMP-14 also allowed identificationof this subgroup, and further confirm the role of ECM-relatedsignaling in certain subgroups of UUS. These proteins warrantfurther analysis and consideration as potential diagnostic andprognostic biomarkers in UUS.

The findings in this study indicate several potential changesin the diagnosis of these tumors. First, overall survival appearsto depend on mitotic index, hormone receptor expression,and the ECM subgroup. Both mitotic index and ECM subgrouphad an essentially equal contribution in the risk model fordecreased overall survival (HR ¼ 2.63 vs. 2.52). Expression ofhormone receptors was protective (HR ¼ 0.21). Thus, thediagnostic algorithm should incorporate these variables. Spe-cifically, patients whose tumors are in the high mitotic indexgroup or ECM group have an extremely high risk of death.Cell density, using a cutoff of 4,300 cells per mm2, appears tobe a good surrogate for the ECM subgroup. Patients withoutthese, and showing positive expression of hormone receptors,have a chance for long-term survival. Thus, these diagnosticparameters allow identification of patients with an extremelypoor prognosis (typically death within 2 years of diagnosis)and an improved prognosis (chance for long-term survival ispossible).

In summary, this study provides themost detailed examinationof an incredibly rare and deadly sarcoma type yet published. Theresults of this work indicate that routine pathologic parameters,such as mitotic index and hormone receptor IHC, can be com-plemented with RNA expression analysis, to provide biologicaland prognostic insights. Furthermore, these results identify sev-eral gene pathways that appear to be active in the deadly tumors,and which may be amenable to therapeutic intervention. Finally,image analysis confirms that the RNAgroups showmorphometricdifferences, particularly the most aggressive ECM group. Giventhat image analysis is more easily available than RNA expressionanalysis, this may provide a valuable diagnostic method foridentifying these tumors.

Disclosure of Potential Conflicts of InterestJ.W. Carlson reports receiving commercial research grants from Thermo

Fisher Scientific and reports receiving speakers bureau honoraria from Roche.No potential conflicts of interest were disclosed by the other authors.

Authors' ContributionsConception and design: J.W. CarlsonDevelopment of methodology: M. Ghaderi, A. Isaksson, J.W. CarlsonAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): E. Hardell, B. Viklund, C.-H. Lee, L. Moyano-Galceran, D.A. Bell, J.K. Schoolmeester, A. Ma

�sb€ack, G.B. Kristensen,

K. Lehti, A. Isaksson, J.W. CarlsonAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): A. Binzer-Panchal, E. Hardell, B. Viklund,N. Hollfelder, P. Corcoran, J. Gonzalez-Molina, A. Isaksson, J.W. CarlsonWriting, review, and/or revision of the manuscript: A. Binzer-Panchal,E. Hardell, B. Viklund, T. Bosse, M.R. Nucci, C.-H. Lee, D.A. Bell,J.K. Schoolmeester, A. Ma

�sb€ack, G.B. Kristensen, B. Davidson, A. Isaksson,

J.W. CarlsonAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): E. Hardell, B. Viklund, T. Bosse, C.-H. Lee,B. Davidson, A. Isaksson, J.W. CarlsonStudy supervision: A. Isaksson, J.W. Carlson






AcknowledgmentsJ.W. Carlson and E. Hardell were supported by Radiumhemmets

forskningsfonder, Stockholm l€ans landsting, Cancerfonden, Magnus Berg-valls Stiftelse, Thermo Fisher Scientific, and B. Davidson was supportedby the National Sarcoma Foundation at the Norwegian RadiumHospital.

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received September 8, 2018; revisedNovember 12, 2018; acceptedDecember20, 2018; published first January 7, 2019.

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2019;25:2155-2165. Published OnlineFirst January 7, 2019.Clin Cancer Res Amrei Binzer-Panchal, Elin Hardell, Björn Viklund, et al. Reveals Clinically Relevant Molecular SubtypesIntegrated Molecular Analysis of Undifferentiated Uterine Sarcomas

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