Integrated Molecular Analysis of Undifferentiated Uterine Sarcomas

Published OnlineFirst January 7, 2019; DOI: 10.1158/1078-0432.CCR-18-2792

Precision Medicine and Imaging Clinical Cancer Research Integrated Molecular Analysis of Undifferentiated Uterine Sarcomas Reveals Clinically Relevant Molecular Subtypes Amrei Binzer-Panchal1, Elin Hardell2,Bjorn€ Viklund1, Mehran Ghaderi2, Tjalling Bosse3, Marisa R. Nucci4, Cheng-Han Lee5, Nina Hollfelder1,Padraic Corcoran1, Jordi Gonzalez-Molina2,6, Lidia Moyano-Galceran6, Debra A. Bell7, John K. Schoolmeester7, Anna Ma sback€ 8, Gunnar B. Kristensen9, Ben Davidson10, Kaisa Lehti6,11, Anders Isaksson1, and Joseph W. Carlson2

Abstract

Purpose: Undifferentiated uterine sarcomas (UUS) are matrix (ECM), muscle function, and proliferation. A multi- rare, extremely deadly, sarcomas with no effective treatment. variable, adjusted Cox proportional hazard model demon- The goal of this study was to identify novel intrinsic molec- strated that RNA group, mitotic index, and hormone receptor ular UUS subtypes using integrated clinical, histopatholog- expression influence patient overall survival (OS). CNV arrays ic, and molecular evaluation of a large, fully annotated, revealed characteristic chromosomal changes for each group. patient cohort. Morphometry demonstrated that the ECM group, the most Experimental Design: Fifty cases of UUS with full clinico- aggressive, exhibited a decreased cell density and increased pathologic annotation were analyzed for gene expression nuclear area. A cell density cutoff of 4,300 tumor cells per mm2 (n ¼ 50), copy-number variation (CNV, n ¼ 40), cell could separate ECM tumors from the remaining cases with a morphometry (n ¼ 39), and protein expression (n ¼ 22). sensitivity of 83% and a specificity of 94%. IHC staining of Gene ontology and network enrichment analysis were used to MMP-14, Collagens 1 and 6, and Fibronectin proteins revealed relate over- and underexpressed genes to pathways and further differential expression of these ECM-related proteins, identi- to clinicopathologic and phenotypic findings. fying potential new biomarkers for this aggressive sarcoma Results: Gene expression identified four distinct groups of subgroup. tumors, which varied in their clinicopathologic parameters. Conclusions: Molecular evaluation of UUS provides novel Gene ontology analysis revealed differential activation of insights into the biology, prognosis, phenotype, and possible pathways related to genital tract development, extracellular treatment of these tumors.

Introduction leiomyosarcoma, low-grade and high-grade endometrial stromal sarcoma, and carcinosarcoma (2). Undifferentiated uterine sarcomas (UUS) are high-grade malig- Recent large-scale genomic studies of sarcomas have revealed nant mesenchymal tumors (1). These tumors are extremely rare, several important conclusions (3–5) First, they can be generally so knowledge of their biology, prognosis, and therapy has been dividedintotranslocationsarcomas, which show a diploid or limited to small case series with often patchy or limited follow-up. near-diploid genome, and karyotypically complex sarcomas, They are diagnosed after exclusion of other, more common, which often show large and complex chromosomal gains and mesenchymal tumors of the uterus and soft tissue, particularly losses of genetic material (6). Second, within traditionally

1Science for Life Laboratory, Department of Medical Sciences, Uppsala Univer- University of Oslo, Oslo, Norway. 11Genome-Scale Biology, Research Programs sity, Uppsala, Sweden. 2Department of Oncology-Pathology, Karolinska Unit, University of Helsinki, Helsinki, Finland. Institutet, and Department of Pathology and Cytology, Karolinska University Note: Supplementary data for this article are available at Clinical Cancer Hospital, Stockholm, Sweden. 3Department of Pathology, Leiden University Research Online (http://clincancerres.aacrjournals.org/). Medical Center, Leiden, the Netherlands. 4Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts. 5Department of Pathology and A. Binzer-Panchal and E. Hardell contributed equally to this article. 6 Laboratory Medicine, BC Cancer, Vancouver, BC, Canada. Department of A. Isaksson and J.W. Carlson contributed equally to this article. Microbiology, Tumor and Cell Biology, Biomedicum, Karolinska Institutet, Stock- holm, Sweden. 7Department of Laboratory Medicine and Pathology, Mayo Clinic, Corresponding Author: Joseph W. Carlson, Karolinska Institutet and Karolinska Rochester, Minnesota. 8Department of Pathology, Ska nes University Hospital, University Hospital, Cancer Center Karolinska, R8:3, 17176 Stockholm, Sweden. Lund, Sweden. 9Department Gynecologic Oncology and Institute for Cancer Phone: 46761130912; E-mail: [email protected] Genetics and Informatics, Norwegian Radium Hospital, Oslo University Hospital, doi: 10.1158/1078-0432.CCR-18-2792 Oslo, Norway. 10Department of Pathology, Norwegian Radium Hospital, Oslo University Hospital, Oslo; Institute for Clinical Medicine, The Medical Faculty, 2019 American Association for Cancer Research.

www.aacrjournals.org 2155

Binzer-Panchal et al.

Translational Relevance Materials and Methods Patient cohort and central review Undifferentiated uterine sarcomas (UUS) are among the This retrospective patient cohort was assembled via interna- rarest and deadliest of the uterine sarcomas. This has hindered tional collaboration from seven collaborating centers. Ethical the molecular understanding of their biology and thus limited approval was obtained from the relevant local authorities. The the introduction of new therapies. This study uses a well- majority of cases were submitted to three levels of review. First, annotated, large cohort of UUS, combined with RNA expres- they were reviewed by the original diagnosing pathologist. Sec- sion, chromosomal copy number, computer-assisted histo- ond, a central review was performed by the participating expert logic analyses and IHC, to identify and describe four intrinsic gynecologic pathologist. Based on this review, a single represen- subtypes of these tumors. These subtypes vary in their biology, tative hematoxylin and eosin (H&E)-stained tumor slide was clinicopathologic parameters, and survival. The most aggres- selected for the third, central, review. Finally, the selected slides sive, ECM, subtype was characterized by a tumor cell pheno- were reviewed again at the Karolinska University Hospital. Mitotic type with distinct morphology and protein expression, which rate and grade of nuclear atypia was determined as described will provide means to identify these cases using current lab- previously (12, 13). IHC for estrogen receptor and progesterone oratory techniques. Unique chromosomal changes were sig- receptor was performed locally in clinical labs accredited for this nificantly associated with each group. Finally, gene ontology analysis. Representative FFPE tumor material containing a min- and network enrichment analysis identified target candidates imum of 70% tumor cells was submitted to the Karolinska for therapy. These results, from our hypothesis-generating University Hospital for isolation of DNA and RNA. One repre- comprehensive approach, will open new avenues to study sentative tumor slide was digitally scanned (Hamamatsu Nano- and stratify these tumors, with the long-term goal of devel- Zoomer, 40 scan) for image analysis. Exceptions to the above oping clinical interventions that will help improve patient protocol were Skanes University Hospital (n ¼ 10 patients), where survival. no second, local, review was performed; all slides were submitted for the third, central review, and Vancouver General Hospital (n ¼ 4 patients), where no central review was performed; mitotic count and atypia review were assessed by the participating pathologist. defined sarcoma subtypes are subtype-specific molecular characteristics that can govern biology, therapy, and prognosis (3,4).Thus,althoughgeneralconclusions regarding sarcoma RNA expression arrays biology can be made with these studies, further work is RNA quality was evaluated using the Agilent 2100 Bioanalyzer required to understand the subtype and location-specific system (Agilent Technologies Inc.). Total RNA (100 ng) from each fi changes that might govern biology, prognosis, and, ultimately, sample was used to generate ampli ed and biotinylated sense- therapy. strand cDNA from the entire expressed genome according to the fi Uterine sarcomas have a distinct biology from other soft- Sensation Plus FFPE Ampli cation and WT Labeling Kit (P/N fi tissuesarcomas.Theydemonstrateuniquetranslocations,such 703089, Rev.4 Thermo Fisher Scienti c Inc., Life Technologies). as JJAZ-JAZF1 and YWHAE-FAM22, that are not seen at other GeneChip ST Arrays (GeneChip Human Gene 2.1 ST Array Plate) fi tissue sites (7–9). Benign tissues of the female genital tract were hybridized, washed, stained, and nally scanned with the express hormone receptors, and this is retained in a subset of GeneTitan Multichannel (MC) Instrument, according to the sarcomas (10, 11). This expression has been demonstrated to GeneTitan Instrument User Guide for Expression Array Plates fi confer a better prognosis in leiomyosarcomas (10). Indeed, (PN 702933, Thermo Fisher, Scienti c Inc., Life Technologies). smooth-muscle tumors have a distinct biology depending upon whether they arise in the gynecologic tract or not (3, 5). DNA copy-number arrays Previously, our group has demonstrated that division into DNA quantity was measured using the Qubit Fluorometer. mitotic index groups has prognostic significance for overall Samples with low concentration of DNA were concentrated with survival (12, 13). Other studies have attempted to use atypia the use of MinElute Reaction Cleanup Kit (50) Cat no. 28204 to subdivide UUS into "uniform" and "pleomorphic" types (QIAGEN). During this procedure, the DNA binds to a column, is (14, 15). To date, no large-scale molecular characterization has rinsed with washing buffer, and finally eluted in nuclease-free been performed on UUSs. water. Research into therapies for gynecologic sarcomas has been DNA Array experiments were performed according to standard limited by the difficulty of assembling a sufficient number of protocols for Affymetrix OncoScan Arrays (Affymetrix OncoScan cases for clinical trials. Despite limited evidence, primary therapy FFPE Assay Kit User Guide (P/N 703175 Rev. 2), Affymetrix Inc.). is complete surgical resection, if possible. There are no conclusive Total genomic DNA (80 ng) was incubated overnight to anneal data regarding the use of adjuvant therapy in UUS, and the current the MIP probe. Each sample was then divided into two different suggestion is to use therapies indicated for soft-tissue sarcomas at channels, one for AT nucleotides and another for GC nucleotides. other sites (16). One study evaluated the use of pazopanib, a The gaps formed after the annealing process were filled using multitargeted receptor tyrosine kinase inhibitor, in pretreated, dNTPs and relevant reagents. Exonuclease removed nonligated metastatic uterine sarcomas (17). This study demonstrated clin- MIP probes and a cleavage enzyme linearized the circular MIP ically relevant efficacy and tolerability. probes. Then the DNA was amplified via two cycles of PCR and The goal of this study was to comprehensively examine the digested using the HaeIII enzyme. On the Oncoscan Arrays, biology of a large, well-annotated cohort of UUS, in order to hybridized probes were captured by streptavidin–phycoerythrin identify tumor-intrinsic molecular subgroups with biological, conjugates using the GeneChip Fluidics Station 450 and arrays clinical, and potential therapeutic significance. were scanned using GeneChip Scanner 3000 7G.

2156 Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research

Molecular Classiﬁcation of UUS

The OncoScan fluorescence intensity (CEL) files were normal- amplification buffer) for 10 minutes, 1 10 minute TNT. Sections ized with Affymetrix OncoScan Console v.1.3 with default set- were incubated again with SA-HRP (diluted 1:100 in TNB) for 30 tings. Segmentation was done with Nexus Copy Number v.9.0 minutes, 1 10 minute TNT, and finally washed with PBS. from BioDiscovery with the TuScan algorithm. Allele specific Staining was revealed using AEC substrate (4 minute incubation, copy-number analyses were performed with the Tumor Aberra- 1 minute in MQ H2O). Sections were counterstained with hema- tion Prediction Suite (TAPS) 2.0 (18). Affymetrix expression array, toxylin (1 minute incubation, rinsed with H2O) and mounted Oncoscan, and clinical metadata are available via the Gene- with Aquatex (Millipore; cat. #108562). Expression Omnibus database repository accession number GSE119043. IHC quantitation Qupath v0.1.3, an updated pre-release version of Qupath Quantitative cell morphometry (https://github.com/petebankhead/qupath) open source soft- QuPath v0.1.2 (https://github.com/qupath/qupath) open ware, was used for positive pixel counting on four TMAs with source software was used for cell detection (19). Whole scanned IHC stainings for Collagen 1, Collagen 6, Fibronectin, and slides, available for the majority of cases (39/50; 78%), were MMP14. TMA slides that contain 22 of the cases were dearrayed, reviewed, blinded to clinical and molecular parameters, and two and the detected cores were manually adjusted so that the entire 1.27 mm in diameter circles were selected as regions of interest tissue sample was included. Tissue detection was performed with (ROI). The automatic "Cell detection" was run on the ROI with the following changes to the default settings: Threshold was set to the default settings except the "Maximum area" that was increased 220, requested pixel size to 2 mm, minimum area to 15,000 mm2 to 3,400 mm2 due to large cells in particular samples. The results and maximum fill area to 600 mm2. Subsequently, positive pixels from the two ROIs were averaged to obtain a single value for the were counted with the following deviations from default: down- case. The results were exported as a text file and further analyzed sample factor 2.0, Gaussian sigma 0.5 mm, "negative" hematox- with R (http://www.r-project.org). ylin threshold 0.15 OD units, and "positive" DAB threshold 0.1 OD units. The results were exported as text files and further IHC analyzed with R. TMA sections were deparaffinized and rehydrated (2 10 minute Tissue Clear, 2 5 minute absolute EtOH, 1 5 minute Bioinformatics and statistical analysis 96% EtOH, 1 10 minute 70% EtOH, 2 5 minute MQ H2O). The RNA raw data were normalized in the free Affymetrix Antigen retrieval was performed using 10 mmol/L sodium citrate Expression Console Software provided by Thermo Fisher pH 6 (15 minute heat, 30 minute cool down, 2 5 minute PBS). (www.thermofisher.com) using the robust multiarray average Endogenous peroxidase was quenched with 0.6% H2O2 for 10 method (20, 21). Subsequent analysis of the gene-expression minutes, 2 5 minute PBS (for ImmPRESS kit) or with 0.03% data was carried out in the freely available statistical computing H2O2 for 10 minutes, 1 minute H2O, 10 minute PBS [for language R. Unsupervised hierarchical clustering was done using Tyramide Signal Amplification (TSA) kit]. the package "stats." To test for differentially expressed genes For the ImmPRESS method, sections were blocked with 2.5% between the identified groups, an empirical Bayes moderated t normal horse serum for 30 minutes (ImmPRESS, Vector Labora- test was applied using the "limma" package available from the tories; cat. #MP-7402). Sections were incubated with aMT1-MMP Bioconductor project (www.bioconductor.org; refs. 22, 23). To (LEM) ¼ MMP14 antibody (Millipore; cat #MAB3328) diluted address the problem with multiple testing, the P values were 1:100 in 2.5% normal horse serum overnight at 4C in a humidity adjusted using the method of Benjamini and Hochberg (24). The chamber. Secondary antibody incubation was performed with Database for Annotation, Visualization and Integrated Discovery ImmPRESS reagent (anti-mouse IgG coupled to peroxidase, Imm- (DAVID) v6.8 and the REVIGO ("REduce and VIsualize Gene PRESS, Vector Laboratories; cat #MP-7402) for 30 minutes at RT. Ontology") tool was used to assess the over- and underexpressed Staining was revealed using DAB substrate (3 minute incubation, genes by organizing them into ontologies and summarizing them 5 minutes in tap H2O). Sections were counterstained with aque- by reducing redundant GO terms (25–27). Kaplan–Meier anal- ous hematoxylin (1 minute incubation, rinsed with H2O), dehy- yses used the R-package "rms," Cox proportional hazard tests the drated (1 2 minute 96% EtOH, 1 2 minute absolute EtOH, R-package "survival." A t test was performed using R to test for 1 5 minute Tissue Clear) and mounted with Eukitt (Sigma; cat. differences in the percentage of positive pixels, nuclear area, and #25608-33-7). cells per area counts between RNA groups. The values included in For the TSA method, sections were blocked with TNB Blocking the t test were the mean of the two replicate cores present on the Buffer [0.1 mol/L Tris-HCl, pH 7.5; 0.15 mol/L NaCl; 0.5% (w/v) TMA or the mean of the two ROIs for each sample, when two blocking reagent (PerkinElmer, cat. #FP1020)] for 30 minutes at replicates were available. RT. Primary antibodies were diluted in TNB blocking buffer as follows: Collagen 1 (Abcam; cat. #ab34710) 1:200, Collagen 6 (Abcam; cat. #ab6588) 1:200, fibronectin (Sigma; cat. #F3648) Results 1:100. Primary antibody incubation was performed overnight at Patient cohort 4C in a humidity chamber. After 10-minute wash with TNT Clinicopathologic characteristics of the patient cohort are pre- [0.1 mol/L Tris-Cl, pH 7.5; 0.15 mol/L NaCl; 0.1% (v/v) Tween sented in Table 1. A total of 50 cases of UUS were included. All 20], sections were incubated with biotinylated secondary anti- cases were negative for the JAZF1–JJAZ1 and YWHAE–FAM22 body (diluted 1:200 in TNB) for 30 minutes, 1 10 minute TNT. translocations (RT-PCR: 46 cases, FISH: 4 cases). The majority of Next, sections were incubated with SA-HRP (PerkinElmer; cat. patients died within 5 years after diagnosis (34, 68%), while the #NEL750001EA, diluted 1:100 in TNB) for 30 minute, 1 10 remainder were alive beyond 5 years (14, 28%). Two patients had minute TNT, and with biotinylated tyramide (diluted 1:50 in a follow-up time less than 5 years (12 and 15 months,

www.aacrjournals.org Clin Cancer Res; 25(7) April 1, 2019 2157

Binzer-Panchal et al.

Table 1. Clinicopathologic characteristics of the included cases of UUS Kaplan–Meier curves showed a tendency to decreased overall Total number of cases 50 survival for the high CNV tumors compared with the low CNV Time to last follow-up, all patients (years) 3.2 4.6 (0.1–18.8) tumors (Fig. 2B). This difference was not significant (log-rank – Time to last follow-up, survivors (years) 9.3 5.5 (1 18.8) P ¼ 0.1743). Long-term survivors (alive minimum 5 years) 14 (28%) Deceased prior to 5-year follow-up 34 (68%) Gains and losses of chromosomal segments were analyzed for fi Alive, follow-up less than 5 years 2 (4%) each RNA group, and this revealed a number of signi cant Cases included from differences in chromosomal segment composition. For example, Karolinska University Hospital 17 (34%) the ECM group showed an increased frequency of 4q and 7q Oslo University Hospital 13 (26%) relative gains, 6q relative loss, and LOH near the centromere of Skane University Hospital 10 (20%) chromosome 9 (Fig. 2C). Chromosomal segment compositions Mayo Clinic 5 (10%) Vancouver General Hospital 4 (8%) for the other RNA groups are presented in Supplementary Fig. S1. Brigham and Women's Hospital 1 (2%) Mitotic index group (13) Overall survival depended on clinicopathologic and molecular High (>11.16 mitotic figures/mm2) 23 (46%) tumor properties Low (<11.16 mitotic figures/mm2) 27 (54%) A Cox proportional hazard model was constructed, including Nuclear atypia (15) both clinicopathologic and molecular characteristics (Table 2). Uniform 33 (66%) Pleomorphic 13 (26%) The unadjusted (crude) model revealed that mitotic index group fi fl Unknown 4 (8%) and hormone receptor expression showed a signi cant in uence Estrogen and progesterone receptor status on overall survival. This has been seen previously for these Positive 11 (22%) cases (12, 13). In the unadjusted (crude) model, RNA group Negative 28 (56%) assignment was close to significance, with a P value of exactly Unknown 11 (22%) 0.05. The adjusted model showed that these three variables had a significant impact on overall survival, with an explanatory power (r-square) of 0.43. In the adjusted model, the presence of positive respectively). The mean follow-up time, including deceased hormone receptor expression (either estrogen or progesterone) patients, was 3.2 years (range, 0.1–18.8). Excluding deceased was strongly protective (HR ¼ 0.21), while high mitotic index or patients, the mean follow-up time was 9.3 years (1–18.8). The ECM-related gene-expression signature were indicators of a poor majority of cases were included from the Karolinska University prognosis (HR ¼ 2.63 and 2.52, respectively). Hospital. The cases were almost evenly split into prognostic mitotic index groups. There was a predominance of uniform-type Gene ontology and network enrichment analysis revealed UUS. Estrogen and progesterone receptor status was available in biological differences between RNA groups the majority of cases. The relationship between RNA subgroup and clinicopathologic characteristics is presented in Supplementary Table S1. RNA expression results revealed four distinct molecular groups The first group contained 21 cases (42%). The GO terms seen RNA expression analysis was successful on all cases (n ¼ 50/50, in the overexpressed genes, as visualized by REVIGO (Fig. 3A), 100%). Unsupervised clustering of RNA expression data revealed show ontologies related to developmental pathways, particu- four clusters (Fig. 1A), termed "Developmental," "Leiomyosar- larly the gynecologic tract, positive regulation of gene expres- coma (LMS)-like," "ECM," and "Low Proliferation" (Fig. 1A, as sion and translation, and genes related to chromatin organi- indicated in blue, yellow, green, and red, respectively). These zation. This REVIGO analysis complements the NEA, which groupings are seen in the principal component analysis (Fig. 1B, showed a number of pathways related to proliferation, such as same color scheme). peptide chain elongation. The low-expression GO terms includ- Examination of the gene-expression data focused on the 50 ed regulation of interferon gamma, leukocyte cell–cell adhe- most over- and underexpressed genes within each subgroup, as sion, and other inflammatory pathways such as NF-kB, leuko- determined by the fold change. The top 15 over- and under- cyte activation, and response to type I interferon. Given the expressed genes are shown visually in a heat map (Fig. 1C). presence of gene ontologies related to mesenchyme and repro- Kaplan–Meier curves (Fig. 1D) showed a significant variation in ductive structure development, as well as embryonic and tube overall survival between the RNA groups, with the ECM group morphogenesis, this group was named the "Developmental" showing the worst prognosis (log-rank test, P ¼ 0.0037). The group. This group contained the highest frequency of high remaining groups shared a comparatively better survival. mitotic index cases. Most of the cases were uniform-type, few survived past 5 years, and most showed negative hormone DNA CNV revealed a spectrum of chromosomal changes, with receptor staining. They were roughly evenly divided into high particular gains and losses associated with each RNA group and low CNV groups. Of the overexpressed genes in this group, DNA CNV analysis was successful in the majority of cases (n ¼ HMGA2 is a candidate biomarker. 40/50, 80%). This analysis revealed a spectrum of chromosomal The second group contained 10 cases (20%). The GO terms copy-number variation (CNV), from cases that were diploid or seen in the overexpressed genes in this group were related to near diploid to cases with extensive chromosomal aberrations. muscle function, particularly actin cytoskeleton activation, car- This variation is summarized in Fig. 2A, where the percentage of diovascular system development, and circulatory system devel- the genome showing diploid DNA sections is presented. Cases to opment (Fig. 3B). The NEA similarly showed smooth-muscle the right are diploid/near-diploid, while cases progressing to the contraction as the most significant activated pathway. GO enrich- left show increasing nondiploid sections. Cases were divided into ment analysis of the 50 underexpressed genes in this group did not "Low CNV" (n ¼ 15/40, 38%) and "High CNV" (n ¼ 25/40, 62%). reveal any unifying ontologies. The majority of cases showed

2158 Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research

Molecular Classiﬁcation of UUS

Figure 1. RNA expression analysis reveals distinct subgroups. Developmental (blue), LMS-like (yellow), ECM (green), and low proliferation (red). A, Unsupervised hierarchical 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 based subgroups. C, Heat map showing the 15 most over- and underexpressed genes in each group. D, Kaplan–Meier curve showing overall survival for each RNA group.

uniform-type nuclear atypia, but were otherwise roughly evenly ogies. The NEA showed ECM proteoglycans, ECM–receptor inter- divided in terms of survival > 5 years, hormone receptor positivity, action, and degradation of the extracellular matrix as the most and CNV group. Given the overexpression of muscle and smooth- signiﬁcantly overexpressed pathways. All 8 patients in this group muscle–related gene ontologies, this group was assigned as died within 2 years. The cases were divided between uniform and "leiomyosarcoma (LMS)-like." Of the overexpressed genes in this pleomorphic type nuclear atypia, and close to evenly divided group, MYH11, ACTG2, and MYLK, all recently described between high- and low mitotic groups. None of these cases "secondary" smooth-muscle markers, are candidate biomarkers. showed positivity with hormone receptors. There was a predom- The third group contained eight cases (16%). The GO terms inance of tumors with high CNV. There was a trend toward seen in the overexpressed genes in this group were related to increased incidence of lymphovascular space invasion (LVSI) in extracellular matrix disassembly, aminoglycan catabolism, and this group versus the rest of the cases (6/7 cases, 86%, vs. 13/20, angiogenesis (Fig. 3C). GO enrichment analysis of the 50 under- 65%, P value 0.301; note that only cases with all slides available expressed genes in this group did not reveal any unifying ontol- were included in the statistics for LVSI). This group was assigned

www.aacrjournals.org Clin Cancer Res; 25(7) April 1, 2019 2159

Binzer-Panchal et al.

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 a percentage of the entire genome length, demonstrates that tumors had a distribution of CNV. B, Kaplan–Meier curve showing overall survival for each DNA group. C, Chromosomal segments showing gains (top diagram), losses (middle diagram), and LOH (bottom diagram) across the entire genome for the ECM group. 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 of cases 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 regions that extend from 100% to þ100%.

the name "ECM" group. Of the overexpressed genes in this group, reveal any unifying ontologies. This group showed a correlation MMP14, COL14A1, COL6A3, and FN1 are candidate biomarkers. with low mitotic index group, with only two cases from the high The fourth group contained 11 cases (22%). The GO terms seen mitotic index group (ANOVA P ¼ 0.0458). Most cases showed in this group were based on reduced expression of genes related to uniform-type atypia. They were roughly evenly divided in survival mitotic nuclear division, transcription, and regulation of gene >5 years, expression of hormone receptors and CNV high versus expression (Fig. 3D). The NEA revealed only one significant low. This group was considered to represent a "low-proliferation" reduced pathway, RNA polymerase III transcription. GO enrich- expression profile. Thus, mitotic index appears to be a candidate ment analysis of the 50 overexpressed genes in this group did not marker for identification of this group.

2160 Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research

Molecular Classiﬁcation of UUS

Table 2. Cox proportional regression analysis for overall survival in relation to clinical and molecular features Adjusted results Crude results (multiple explanatory variables) (single explanatory variable) r2 ¼ 0.43 OS OS Variable Number of patients HR P value HR P value Mitotic index Low 27 Reference Reference High 23 2.33 (1.21–4.50) 0.01 2.63 (1.27–5.45) 0.01 Hormone receptor expression Negative 28 Reference Reference Positive 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) 0.4 RNA group Developmental 21 Reference Reference LMS-like 10 0.46 (0.19–1.14) 0.09 0.48 (0.18–1.27) 0.14 ECM 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) 0.96 Nuclear atypia Uniform 33 Reference Pleomorphic 13 1.63 (0.81–3.26) 0.17 N/A 4 1.34 (0.31–5.78) 0.69 Cell density Low 22 Reference High 15 1.26 (0.62–2.57) 0.53 N/A 13 0.81 (0.35–1.89) 0.63 CNV group High 25 Reference Low 15 0.67 (0.32–1.41) 0.29 N/A 10 0.46 (0.19–1.09) 0.08 NOTE: Signiﬁcance test is indicated with (P < 0.05) and (P < 0.01).

Image analysis revealed that the ECM group is characterized by expression were seen between the RNA groups, with highest reduced cell density and increased nuclear size expression seen for all these proteins in the ECM group In order to more closely examine the phenotypic characteristics (Fig. 4C–F), with a significant difference to the developmental of the cases in relation to RNA expression, image analysis of group in the Collagen 1, Collagen 6, and MMP-14. The LMS-like scanned H&E-stained tissue sections was performed. This revealed group showed the second highest expression, followed by the distinct morphologic differences between the intrinsic groups developmental and low-proliferation groups. identified by RNA expression analysis (Fig. 4A and B). Two ROIs were examined for each slide and averaged. Note that the image analysis algorithm had trouble reliably identifying the cyto- Discussion plasmic boundary of each cell, so cell density (as determined UUSs are aggressive mesenchymal tumors with an unclear from nuclei per unit area) was calculated. A total of 39 scanned biology. These tumors have traditionally been grouped within slides were available, with each RNA group represented (DEV: the endometrial stromal sarcomas, given their lack of smooth- 16/21 cases, LMS-LIKE: 8/10 cases, ECM: 6/8 cases, and LOW muscle differentiation by light microscopy and IHC. Due to their PROLIFERATION: 9/11 cases). The ECM group showed a signif- rarity, well-annotated cohorts allowing evaluation of clinical, icantly decreased cell density as well as an increased nuclear area pathologic, and molecular characteristics have been lacking. This (Fig. 4A and B). There was a negative correlation between cell has led to difficulties with developing treatment strategies that can density and deposition of ECM proteins, which was statistically be effective against these tumors. Recent comprehensive genomic significant for all 3 ECM proteins examined (Collage 1, Collagen studies of soft-tissue sarcomas have revealed that, unlike epithe- 6, and Fibronectin; see Supplementary Table S2). Given this lial malignancies, sarcomas are characterized by copy-number distinct phenotype, the possibility of using a cutoff to identify alterations, with low mutational burdens and few recurrently ECM group cases purely from image analysis was investigated. mutated genes (3). Transcriptomic diversity within sarcoma types Using a cell density cutoff of 4,300 cells per mm2 allowed appears to define molecular subtypes related to patient progno- distinction of ECM tumors from the remaining tumors with a sis (3). A recent study using NGS methods identified numerous sensitivity of 83% and a specificity of 94%. genomic alterations (including copy-number gains) that were targetable (28). Protein expression by IHC revealed distinct protein expression Previously, we have demonstrated the importance of mitotic profiles across RNA groups index and hormone receptor expression in the prognosis of these IHC was used to interrogate the protein expression of four tumors (12, 13). The goal of this study was to further that analysis ECM-related proteins. The ECM group was particularly selected using molecular methods appropriate to sarcomas. Previous for evaluation due to its extremely poor prognosis. These proteins genomic studies have indicated that sarcomas show variations were selected based on overexpressed genes in the ECM group. The in gene expression and chromosomal gains and losses, but that expression of matrix metalloproteinase 14 (MMP-14), Collagen they typically show few characteristic gene mutations. A further 1, Collagen 6, and Fibronectin was evaluated. Differences in limitation to the study of these cases is their rarity. This requires

www.aacrjournals.org Clin Cancer Res; 25(7) April 1, 2019 2161

Binzer-Panchal et al.

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-like group. C, Overexpressed genes in the ECM group. D, Underexpressed genes in the low-proliferation group.

the use of archived, formalin-fixed material with varying RNA and cytokine mechanisms such as interferons. Our results would DNA quality. indicate that further, more functional, studies of these processes Gene-expression analysis of these tumors reveals four subtypes may be fruitful in identifying new therapeutic targets. with clinical significance. In particular, tumors in the ECM group Copy-number variation arrays showed, surprisingly, tumors show overexpression of extracellular matrix genes and appear to that were both near diploid, with low CNV, and high CNV tumors be particularly deadly, with all 8 patients in this group dying with extensive gains and losses. Previously, studies have success- within 2 years of diagnosis. The low-proliferation group correlates fully divided sarcomas into translocation-associated and karyo- well with the mitotic index group, thus indicating that prolifer- typically complex subtypes (6). Given the aggressive and high- ation in these tumors, as measured by the identification of mitotic grade nature of these tumors, our initial hypothesis was that these figures in light microscope, has a clear prognostic and biological tumors would all show a complex chromosomal heterogeneity. correlation. The LMS-like group cases that express muscle-related This was not the case, and roughly half the cases were diploid or genes and are thus possibly variants closely related to leiomyo- near diploid. This is an important finding for future studies and sarcoma. Finally, the developmental group showed activation of may indicate that there are as yet undiscovered translocations developmental genes and differences in expression of genes within these high-grade tumors. Furthermore, the CNV division related to immune function. These results indicate that these into high and low groups was not prognostic, indicating that even sarcomas may be modulating the host immune response using the near-diploid tumors can behave aggressively. Several recent

2162 Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research

Molecular Classiﬁcation of UUS

Figure 4. Image analysis results of morphometry (n ¼ 39) and IHC (n ¼ 22) reveal distinct differences, particularly between the ECM developmental groups. Boxplots showing 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. Cell density 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 between each group is indicated by a red line with either (P < 0.05) or (P < 0.01).

studies using array CGH in uterine smooth-muscle tumors have plex network of blood and lymphatic vessels, immune cells, indicated that genomic complexity is prognostic in that group of cancer-associated fibroblasts, and extracellular matrix compo- tumors (29, 30). Our findings, in contrast, appear to indicate that nents. One of the most highly overexpressed genes in this group genetic complexity is not prognostic in UUS, and thus chromo- was fibronectin. This gene, which expresses a class of high- somal complexity as a prognostic marker is subtype specific. The molecular-weight adhesive glycoproteins, has been investigated presence of distinct chromosomal changes that correlate with as a potential treatment target. It has a central role in ECM each RNA subtype is also interesting. Further study will be signaling and exists in multiple isoforms. It is possible these required to dissect the relationship between chromosomal gains isoforms could be individually targeted using, for example, and loss and gene expression. monoclonal antibodies (31–33). Other ECM-related genes The survival analysis revealed that, in addition to previously overexpressed in this group include matrix metalloproteinases, described prognostic markers, mitotic index and hormone recep- such as MMP2 and MMP14. Although drugs have been devel- tor expression, expression signature-based division to RNA group oped against MMPs, initial trials were unsuccessful. There has, was also prognostic. This was true even in the adjusted model. however, been renewed interest in developing new therapies Indeed, the RNA group showed a hazard ratio close to that seen targeting specific MMP activities (34). The overexpression of with the mitotic index group. This result indicates that reliable MMP has been associated in other tumors with aggressive prospective studies of these sarcomas will need to take gene behavior. In UUS, there was a trend to an increased incidence transcription into account, and developing models of treatment of LVSI in the ECM group. and behavior of these tumors will probably require routine use of The developmental group showed reduced expression of sev- transcriptomic methods such as RNA sequencing. eral immune regulatory pathways, particularly NF-kB. This tran- Several identified pathways that are potentially targetable scription factor forms protein complexes that bind and regulate have been identified in the molecular analysis presented here. target genes via consensus DNA promoter regions. It is typically First, targeting ECM mechanisms mayleadtoactivetherapiesin considered pro-oncogenic, stimulating proliferation, preventing these tumors. The tumor microenvironment consists of a com- apoptosis, regulating tumor angiogenesis, and promoting

www.aacrjournals.org Clin Cancer Res; 25(7) April 1, 2019 2163

Binzer-Panchal et al.

metastasis (35). Reduction in the expression of TNF-alpha, leu- ods are not difficult to set up. This morphometry method may kocyte adhesion, and leukocyte activation indicate a reduction in thus allow the ECM-related subgroup of UUS to be identified immunostimulatory molecules, and potentially reflect mechan- using readily available methods. IHC using ECM-related proteins isms by which this subgroup escapes host immune surveil- Collagen 1, Collagen 6, and MMP-14 also allowed identification lance (36). Clearly, untangling the immunomodulatory effects of this subgroup, and further confirm the role of ECM-related of these pathways and how they can best be targeted will require signaling in certain subgroups of UUS. These proteins warrant further studies. However, these hypothesis-generating results can further analysis and consideration as potential diagnostic and serve as an indicator that help to assess if immune therapies will be prognostic biomarkers in UUS. useful in these tumors (37). The findings in this study indicate several potential changes The increased expression of muscle-related genes in the LMS- in the diagnosis of these tumors. First, overall survival appears like group indicates that these tumors might best be considered to depend on mitotic index, hormone receptor expression, a variant of leiomyosarcoma and grouped with them in clinical and the ECM subgroup. Both mitotic index and ECM subgroup trials and treatment planning. During the inclusion and exclu- had an essentially equal contribution in the risk model for sion phase of this study, the goal was to err on the side of decreased overall survival (HR ¼ 2.63 vs. 2.52). Expression of excluding any case that could be conceivable called leiomyo- hormone receptors was protective (HR ¼ 0.21). Thus, the sarcoma. Thus, these cases would not be diagnosed as leio- diagnostic algorithm should incorporate these variables. Spe- myosarcoma using current methods. The RNA expression cifically, patients whose tumors are in the high mitotic index results, however, indicate that the tumors in this LMS-like group or ECM group have an extremely high risk of death. subgroup express several muscle-related genes, such as MYH11, Cell density, using a cutoff of 4,300 cells per mm2,appearsto ACTG2, and MYLK. The proteins expressed by these genes have be a good surrogate for the ECM subgroup. Patients without recently been used to identify poorly differentiated leiomyo- these, and showing positive expression of hormone receptors, sarcomas and represent several candidate biomarkers to iden- have a chance for long-term survival. Thus, these diagnostic tify these tumors (38). Finally, the low-proliferation group parameters allow identification of patients with an extremely appears to confirm a biological equivalent to the mitotic index poor prognosis (typically death within 2 years of diagnosis) group, with reduced expression of a number of proliferation- and an improved prognosis (chance for long-term survival is related genes. Notably, two cases in the low-proliferation group possible). also had a high mitotic index. This may be due to tumor In summary, this study provides the most detailed examination heterogeneity—the area used for mitotic count was not neces- of an incredibly rare and deadly sarcoma type yet published. The sarily the area used for molecular analysis. results of this work indicate that routine pathologic parameters, Image analysis revealed morphologic differences in the such as mitotic index and hormone receptor IHC, can be com- most aggressive, ECM-related, sarcoma subgroup. The reduced plemented with RNA expression analysis, to provide biological cell density and increased nuclear size demonstrates a pheno- and prognostic insights. Furthermore, these results identify sev- typic correlation to the RNA expression data. There was a eral gene pathways that appear to be active in the deadly tumors, negative correlation between ECM protein deposition and cell and which may be amenable to therapeutic intervention. Finally, density, supporting the interpretation that the decrease in cell image analysis confirms that the RNA groups show morphometric density is due to increased deposition of ECM proteins. A differences, particularly the most aggressive ECM group. Given relationship between myxoid stromal amount and gene expres- that image analysis is more easily available than RNA expression sion was recently identified in a comprehensive transcriptomic analysis, this may provide a valuable diagnostic method for analysis of myxofibrosarcoma and undifferentiated pleomor- identifying these tumors. phic sarcoma (3). That study indicated that those two sarcomas are not distinct entities, but rather fall along a spectrum, with Disclosure of Potential Conflicts of Interest varying amounts of overexpression of myxoid stromal-related J.W. Carlson reports receiving commercial research grants from Thermo genes. Fisher Scientific and reports receiving speakers bureau honoraria from Roche. Surprisingly, nuclear size did not correlate with chromosomal No potential conflicts of interest were disclosed by the other authors. CNV. Based on the IHC results, it appears that this decrease in cell density is related to an increase in ECM-related proteins. Nuclear Authors' Contributions size has classically been associated with variations in ploidy, but Conception and design: J.W. Carlson the nuclear envelope is also affected by biomechanical forces, Development of methodology: M. Ghaderi, A. Isaksson, J.W. Carlson which in turn result from the tumor cell microenvironment. These Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): E. Hardell, B. Viklund, C.-H. Lee, L. Moyano- forces may explain the increase in nuclear size in the ECM Galceran, D.A. Bell, J.K. Schoolmeester, A. Masb€ack, G.B. Kristensen, subgroup. It is important to note that, while in epithelial tumors, fi K. Lehti, A. Isaksson, J.W. Carlson ECM can be produced by cancer-associated broblasts, sarcomas Analysis and interpretation of data (e.g., statistical analysis, biostatistics, are tumors of mesenchymal tissues. Hypothetically, the malig- computational analysis): A. Binzer-Panchal, E. Hardell, B. Viklund, nant sarcoma cells are themselves producing ECM components N. Hollfelder, P. Corcoran, J. Gonzalez-Molina, A. Isaksson, J.W. Carlson because of this mesenchymal origin. Writing, review, and/or revision of the manuscript: A. Binzer-Panchal, Several potential biomarkers that correlate with the most E. Hardell, B. Viklund, T. Bosse, M.R. Nucci, C.-H. Lee, D.A. Bell, € aggressive, ECM, subgroup have been identified in this work. J.K. Schoolmeester, A. Masback, G.B. Kristensen, B. Davidson, A. Isaksson, J.W. Carlson First, image morphometry using H&E-stained sections was able to Administrative, technical, or material support (i.e., reporting or organizing identify the most aggressive subgroup and may provide a valuable data, constructing databases): E. Hardell, B. Viklund, T. Bosse, C.-H. Lee, tool to routine histologic examination. Routine H&E staining is B. Davidson, A. Isaksson, J.W. Carlson readily available in all pathology labs, and morphometry meth- Study supervision: A. Isaksson, J.W. Carlson

2164 Clin Cancer Res; 25(7) April 1, 2019 Clinical Cancer Research

Molecular Classiﬁcation of UUS

Acknowledgments The costs of publication of this article were defrayed in part by the payment of advertisement J.W. Carlson and E. Hardell were supported by Radiumhemmets page charges. This article must therefore be hereby marked in forskningsfonder, Stockholm l€ans landsting, Cancerfonden, Magnus Berg- accordance with 18 U.S.C. Section 1734 solely to indicate this fact. valls Stiftelse, Thermo Fisher Scientiﬁc, and B. Davidson was supported by the National Sarcoma Foundation at the Norwegian Radium Received September 8, 2018; revised November 12, 2018; accepted December Hospital. 20, 2018; published ﬁrst January 7, 2019.

References 1. IARC, Kurman RJ, Carcangiu ML, Herrington CS, Roung RH. 19. Bankhead P, Loughrey MB, Fernandez JA, Dombrowski Y, McArt DG, WHO classification of tumours of female reproductive organs [Internet]. Dunne PD, et al. QuPath: open source software for digital pathology Kurman RJ, Carcangiu ML, Herrington CS, Young RH, editors. France: IARC image analysis. Sci Rep 2017;7:1–7. Press; 2014 [cited 2015 Apr 13]. 20. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, 2. Lee CH, Nucci MR. Endometrial stromal sarcoma – the new genetic et al. Exploration, normalization, and summaries of high density oligo- paradigm. Histopathology 2015;67:1–19. nucleotide array probe level data. Biostatistics 2003;4:249–64. 3. Abeshouse A, Adebamowo C, Adebamowo SN, Akbani R, Akeredolu T, Ally 21. Li C, Wong WH. Model-based analysis of oligonucleotide arrays: expres- A, et al. Comprehensive and integrated genomic characterization of adult sion index computation and outlier detection. Proc Natl Acad Sci U S A soft tissue sarcomas. Cell 2017;171:950–65.e28. 2001;98:31–6. 4. Barretina J, Taylor BS, Banerji S, Ramos AH, Lagos-Quintana M, Decarolis 22. Smyth GK. Linear models and empirical bayes methods for assessing PL, et al. Subtype-specific genomic alterations define new targets for soft- differential expression in microarray experiments. Stat Appl Genet Mol tissue sarcoma therapy. Nat Genet 2010;42:715–21. Biol 2004;3:Article3. 5. Guo X, Jo VY, Mills AM, Zhu SX, Lee CH, Espinosa I, et al. Clinically relevant 23. Smyth GK. Limma: linear models for microarray data. In: Gentleman molecular subtypes in leiomyosarcoma. Clin Cancer Res 2015;21: R, Carey V, Dudoit S, Irizarry S, Huber W, editors. 1st ed. Bioinfor- 3501–11. matics and Computational Biology Solutions Using R and Biocon- 6. Taylor BS, Barretina J, Maki RG, Antonescu CR, Singer S, Ladanyi M. ductor (Statistics for Biology and Health). New York: Springer; 2005. Advances in sarcoma genomics and new therapeutic targets. Nat Rev p. 397–420. Cancer 2011;11:541–57. 24. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical 7. LeeCH,OuWB,Marino-EnriquezA,ZhuM,MayedaM,WangY,etal. and powerful approach to multiple testing [Internet]. J R Stat Soc B 1995; 14-3-3 fusion oncogenes in high-grade endometrial stromal sarcoma. 289–300. Proc Natl Acad Sci U S A 2012;109:929–34. 25. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis 8. Croce S, Hostein I, Ribeiro A, Garbay D, Velasco V, Stoeckle E, et al. YWHAE of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009; rearrangement identified by FISH and RT-PCR in endometrial stromal 4:44–57. sarcomas: genetic and pathological correlations. Mod Pathol 2013;26: 26. Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: 1390–400. paths toward the comprehensive functional analysis of large gene lists. 9. Koontz JI, Soreng AL, Nucci M, Kuo FC, Pauwels P, van Den Berghe H, et al. Nucleic Acids Res 2009;37:1–13. ˇ ˇ Frequent fusion of the JAZF1 and JJAZ1 genes in endometrial stromal 27. Supek F, Bosˇnjak M, Skunca N, Smuc T. Revigo summarizes and visualizes tumors. Proc Natl Acad Sci U S A 2001;98:6348–53. long lists of gene ontology terms. PLoS One 2011;6:e21800. 10. Davidson B, Kjæreng ML, Førsund M, Danielsen HE, Kristensen GB, 28. Lucchesi C, Khalifa E, Laizet Y, Soubeyran I. Targetable alterations in adult Abeler VM. Progesterone receptor expression is an independent prog- patients with soft-tissue sarcomas insights for personalized therapy. nosticator in FIGO stage I uterine leiomyosarcoma. Am J Clin Pathol JAMA Oncol 2018;4:1398–404. 2016;145:449–58. 29. Croce S, Ribeiro A, Brulard C, Noel J-C, Amant F, Stoeckle E, et al. Uterine 11. Binder AK, Winuthayanon W, Hewitt SC, Couse JF, Farms T, Operations A, smooth muscle tumor analysis by comparative genomic hybridization: a et al. Steroid receptors in the uterus and ovary. 4th ed. In: Plant TM, useful diagnostic tool in challenging lesions. Mod Pathol 2015;28: Zeleznik AJ, editors. Knobil and Neill's Physiology of Reproduction. 1001–10. London: Academic Press; 2015. p. 1099–193. 30. Croce S, Ducoulombier A, Ribeiro A, Lesluyes T, Noel J, Amant F, 12. Gremel G, Liew M, Hamzei F, Hardell E, Selling J, Ghaderi M, et al. A et al. Genome profiling is an efficient tool to avoid the STUMP prognosis based classification of undifferentiated uterine sarcomas: classification of uterine smooth muscle lesions: a comprehensive identification of mitotic index, hormone receptors and YWHAE-FAM22 array-genomic hybridization analysis of 77 tumors. Mod Pathol translocation status as predictors of survival. Int J Cancer 2015;136: 2018;31:816–28. 1608–18. 31. Venning FA, Wullkopf L, Erler JT. Targeting ECM disrupts cancer progres- 13. Hardell E, Josefson S, Ghaderi M, Skeie-Jensen T, Westbom-Fremer S, sion. Front Oncol 2015;5:1–15. Cheek EH, et al. Validation of a mitotic index cutoff as a prognostic marker 32. Bhome R, Al Saihati HA, Goh RW, Bullock MD, Primrose JN, Thomas in undifferentiated uterine sarcomas. Am J Surg Pathol 2017;41:1231–7. GJ, et al. Translational aspects in targeting the stromal tumour micro- 14. Kurihara S, Oda Y, Ohishi Y, Kaneki E, Kobayashi H, Wake N, et al. environment: from bench to bedside. New Horizons Transl Med 2016; Coincident expression of beta-catenin and cyclin D1 in endometrial 3:9–21. stromal tumors and related high-grade sarcomas. Mod Pathol 2010;23: 33. Kaspar M, Zardi L, Neri D. Fibronectin as target for tumor therapy. Int J 225–34. Cancer 2006;118:1331–9. 15. Kurihara S, Oda Y, Ohishi Y, Iwasa A, Takahira T, Kaneki E, et al. Endo- 34. Vandenbroucke RE, Libert C. Is there new hope for therapeutic matrix metrial stromal sarcomas and related high-grade sarcomas: immunohis- metalloproteinase inhibition? Nat Rev Drug Discov 2014;13:904–27. tochemical and molecular genetic study of 31 cases. Am J Surg Pathol 2008; 35. Xia Y, Shen S, Verma IM. NF-kB, an active player in human cancers. 32:1228–38. Cancer Immunol Res 2014;2:823–30. 16. El-khalfaoui K, Bois A, Heitz F, Kurzeder C, Sehouli J. Current and future 36. van Horssen R, Ten Hagen TL, Eggermont AM. TNF-alpha in cancer options in the management and treatment of uterine sarcoma. Ther Adv treatment: molecular insights, antitumor effects, and clinical utility. Med Oncol 2014;6:21–8. Oncologist 2006;11:397–408. 17. Kim H, Kim Y, Lee SJ, Lee J, Park SH. Pazopanib monotherapy in the 37. Galluzzi L, Vacchelli E, Pedro JB, Buque A, Senovilla L, Baracco EE, et al. treatment of pretreated, metastatic uterine sarcoma: a single-center retro- Classification of current anticancer immunotherapies. Oncotarget 2014;5: spective study. J Gynecol Oncol 2018;29:e3. 12472–508. 18. Rasmussen M, Sundstrom€ M, Kultima H, Botling J, Micke P, Birgisson H, 38. Demicco EG, Boland GM, Savannah KJB, Lusby K, Eric D, Ingram D, et al. et al. Allele-specific copy number analysis of tumor samples with aneu- Progressive loss of myogenic differentiation in leiomyosarcoma has prog- ploidy and tumor heterogeneity. Genome Biol 2011;12:R108. nostic value. Histopathology 2015;66:627–38.

www.aacrjournals.org Clin Cancer Res; 25(7) April 1, 2019 2165

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

Amrei Binzer-Panchal, Elin Hardell, Björn Viklund, et al.

Clin Cancer Res 2019;25:2155-2165. Published OnlineFirst January 7, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/1078-0432.CCR-18-2792

Supplementary Access the most recent supplemental material at: Material http://clincancerres.aacrjournals.org/content/suppl/2019/01/07/1078-0432.CCR-18-2792.DC1

Cited articles This article cites 33 articles, 6 of which you can access for free at: http://clincancerres.aacrjournals.org/content/25/7/2155.full#ref-list-1

Citing articles This article has been cited by 2 HighWire-hosted articles. Access the articles at: http://clincancerres.aacrjournals.org/content/25/7/2155.full#related-urls

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at Subscriptions [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://clincancerres.aacrjournals.org/content/25/7/2155. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.