Clinically Relevant Molecular Subtypes in Leiomyosarcoma Xiangqian Guo1, Vickie Y

Published OnlineFirst April 20, 2015; DOI: 10.1158/1078-0432.CCR-14-3141

Biology of Human Tumors Clinical Cancer Research Clinically Relevant Molecular Subtypes in Leiomyosarcoma Xiangqian Guo1, Vickie Y. Jo2, Anne M. Mills3, Shirley X. Zhu1, Cheng-Han Lee4, Inigo Espinosa5, Marisa R. Nucci2, Sushama Varma1, Erna Forgo1, Trevor Hastie6, Sharon Anderson1, Kristen Ganjoo7, Andrew H. Beck8, Robert B. West1, Christopher D. Fletcher2, and Matt van de Rijn1

Abstract

Purpose: Leiomyosarcoma is a malignant neoplasm with histochemical markers; LMOD1 for subtype I leiomyosar- smooth muscle differentiation. Little is known about its molec- coma and ARL4C for subtype II leiomyosarcoma. A leiomyo- ular heterogeneity and no targeted therapy currently exists for sarcoma tissue microarray with known clinical outcome leiomyosarcoma. Recognition of different molecular subtypes was used to show that subtype I leiomyosarcoma is associ- is necessary to evaluate novel therapeutic options. In a previous ated with good outcome in extrauterine leiomyosarcoma study on 51 leiomyosarcomas, we identified three molecular while subtype II leiomyosarcoma is associated with poor subtypes in leiomyosarcoma. The current study was performed prognosis in both uterine and extrauterine leiomyosarcoma. to determine whether the existence of these subtypes could be The leiomyosarcoma subtypes showed significant differ- confirmed in independent cohorts. ences in expression levels for genes for which novel targeted Experimental Design: Ninety-nine cases of leiomyosarcoma therapies are being developed, suggesting that leiomyosar- were expression profiled with 30end RNA-Sequencing (3SEQ). coma subtypes may respond differentially to these targeted Consensus clustering was conducted to determine the optimal therapies. number of subtypes. Conclusion: We confirm the existence of 3 molecular sub- Results: We identified 3 leiomyosarcoma molecular subtypes in leiomyosarcoma using two independent datasets and types and confirmed this finding by analyzing publically show that the different molecular subtypes are associated available data on 82 leiomyosarcoma from The Cancer with distinct clinical outcomes. The findings offer an opportu- Genome Atlas (TCGA). We identified two new formalin-fixed, nity for treating leiomyosarcoma in a subtype-specific targeted paraffin-embedded tissue-compatible diagnostic immuno- approach. Clin Cancer Res; 1–11. 2015 AACR.

Introduction of leiomyosarcoma originates in various soft tissue sites where it is thought to often arise from smooth muscle cells Leiomyosarcoma is reported to represent as many as 24% of in vessel walls. all sarcomas (1, 2). Currently, no targeted therapy exists for The successful stratification of several tumors (including leiomyosarcoma and the tumor responds poorly to conven- breast cancer, lung cancer, and colon cancer) into molecular tional chemotherapy or radiotherapy. A significant proportion subtypes in the past decades has significantly improved our of leiomyosarcoma originates in the uterus, and the remainder knowledge of these malignancies and has led to changes in the therapeutic approach to these cancers (3–12). In a previous 1Department of Pathology, Stanford University School of Medicine, study, our group proposed the existence of three molecular Stanford, California. 2Department of Pathology, Brigham and subtypes of leiomyosarcoma by using microarray-based gene Women's Hospital and Harvard Medical School, Boston, Massachu- expression profiling on 51 fresh frozen samples of leiomyo- setts. 3Department of Pathology, University of Virginia, Charlottesville, Virginia. 4Division of Anatomical Pathology, Royal Alexandra Hospital, sarcoma (13). To validate this finding, we analyzed 99 leio- Edmonton, Alberta, Canada. 5Department of Pathology, Hospital de la myosarcoma cases collected at different institutions from the Santa Creu i Sant Pau, Autonomous University of Barcelona, Barce- 6 years 1991 to 2012 as an independent cohort, and performed lona, Spain. Department of Statistics, Stanford University, Stanford, fi 0 California. 7Stanford Comprehensive Cancer Center, Stanford Univer- expression pro ling with 3 end RNA sequencing (3SEQ; sity, Stanford, California. 8Department of Pathology, Beth Israel refs. 14–20). In addition, we analyzed the publically available Deaconess Medical Center and Harvard Medical School, Boston, expression profiling dataset from TCGA on 82 cases. Our ana- Massachusetts. lysis confirms the existence of three molecular subtypes in Note: Supplementary data for this article are available at Clinical Cancer leiomyosarcoma. Using two novel markers, we could distin- Research Online (http://clincancerres.aacrjournals.org/). guish the three subtypes by immunohistochemistry and corre- Corresponding Author: Matt van de Rijn, Department of Pathology, Stanford late the subtypes with clinical outcome. The recognition of University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305. Phone: these molecular subtypes in leiomyosarcoma may have clinical 650-498-7154; Fax: 650-723-1950; E-mail: [email protected] significance as the subtypes vary in their expression of a number doi: 10.1158/1078-0432.CCR-14-3141 of genes for which novel targeted therapies either already exist 2015 American Association for Cancer Research. or are being developed.

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of contingency analysis between one subtype and the other Translational Relevance 2 subtypes was measured by two-tailed Fisher exact test and c test Leiomyosarcoma is a malignant neoplasm with varying with GraphPad Prism5 software. Univariate and multivariate degrees of smooth muscle differentiation and complex genet- analysis by the Cox proportional hazard method was performed ic abnormalities. It can occur in a wide range of sites but is using the survival package in R. Analysis of gene ontology (GO) usually managed as a single disease in conventional therapy was done using DAVID Bioinformatics Resources version 6.7 and in clinical trials. The recognition of molecular subtypes (25, 26). CSF1-signature (27) positive, and CINSARC signature can lead to the identification of novel therapies that may (28) positive cases were identified as those cases that coordi- affect one of these subtypes preferentially. We confirmed nately highly expressed these signature genes with >0.3 correla- the results of an earlier study and determined the existence tion with the centroid as performed previously (19, 27, 29, 30). of 3 molecular subtypes in leiomyosarcoma using two Principal component analysis (PCA) was performed on square independent cohorts. We identified two new formalin-fixed, root transformed TPM with R package pcaMethods, ellipse con- paraffin-embedded (FFPE) tissue-compatible diagnostic tour of principal components (PC) was computed and drawn immunohistochemical markers for two of these subtypes: with R package car. LMOD1 for subtype I and ARL4C for subtype II, and showed that these molecular subtypes are associated with distinct TMA construction, immunohistochemistry staining, and clinical outcomes. Our study offers an opportunity for a scoring leiomyosarcoma subtype–specific targeted treatment. The tissue microarrays used in this study (TA-201 and TA-381) were constructed with Tissue Arrayer (Beecher Instru- ments). TA-201 included the leiomyosarcoma cases with clinic outcome data, while TA-381 was comprised of leiomyosarcoma Materials and Methods cases analyzed by 3SEQ. For immunohistochemical staining, sections underwent antigen retrieval and were stained with 3SEQ library construction and bioinformatics analysis anti-ARL4C antibody (1:120, Sigma, CAT#HPA028927) and fi Paraf n blocks of 99 leiomyosarcomas, 4 myometrium, 3 anti-LMOD1 antibody (1:20, Sigma, CAT#HPA028325) with leiomyoma, and 6 undifferentiated pleomorphic sarcomas from the EnVisionþsystem (Dako). The staining results were scored 1991 to 2012 from 9 hospitals were obtained with Institutional as follows: 3 (þþþ), strong staining (>30% positivity); 2 (þþ), review board approval and a waiver of consent due to the archival weak staining (10%–30%); 1 (þ), equivocal or uninterpretable nature of the specimens. Multiple 2 mm-diameter cores were re- (<10%); 0 (), absence of any staining. Hierarchical clustering fi embedded into paraf n blocks longitudinally and sectioned of immunohistochemical (IHC) results was performed with again to ensure the purity of tumor cells. After RNA isolation, software "Cluster3" with "uncentered Correlation" and "Cen- – 3SEQ libraries for next-generation sequencing based expression troid Linkage" and a clustered heatmap was visualized with fi pro ling were sequenced and analysis was performed as described Java TreeView (31, 32). previously (14–20). All gene expression profiling data used for this study have been deposited in the Gene Expression Omnibus (GEO) and are publicly accessible through GSE45510, GSE53844 Results and GSE54511. Consensus clustering identifies three molecular subtypes of After filtering data to genes with a SD greater than 100, trans- leiomyosarcoma based on gene expression data forming the data by log2 and gene-based centering, the Consensus We analyzed 99 cases of leiomyosarcoma by 3SEQ, a next- Clustering (R package ConsensusClusteringPlus; ref. 21) was used generation sequencing–based approach that quantifies the to determine the number of subtypes and to assign the subtype for number of 30 ends for each polyadenylated mRNA or lncRNA each leiomyosarcoma case. This was ran over 1,000 iterations with and that performs well on RNA isolated from FFPE material setting "Distance – (1-Pearson correlation), a 80% sample resam- (14–20). Clinical information of the cases is shown in Table 1 pling, 80% gene resampling, a maximum evaluated k of 12, and and Supplementary Table S1. The median age for this cohort is agglomerative hierarchical clustering algorithm." Silhouette 56 years, with 49 cases originating in the uterus and 49 cases width (R package cluster; ref. 22) was then calculated on the basis in extrauterine sites. For one case the origin was unknown. A of the assignment from ConsensusClusteringPlus to measure female:male ratio of 3.3:1 was noted in this cohort. Half of the accuracy of assignments from ConsensusClusteringPlus. Sep- the extrauterine leiomyosarcomas (24 cases) were from the arately, RNASeq data of 82 leiomyosarcoma cases were down- extremities, while the rest were from thoracic, abdominal, or loaded from the TCGA database. To compare with 3SEQ data, retroperitoneal regions. the TCGA data were normalized into TPM and analyzed with 3SEQ yielded an average of 18 million total reads after ConsensusClusteringPlus and Silhouette analysis as performed quality filtering and an average of 2 million uniquely mapping for 3SEQ data. Subclass mapping (23) was performed to deter- reads against human transcriptome (refMrna) per sample. All mine the common leiomyosarcoma subtypes identified in 3SEQ reads that uniquely mapped to an individual gene (UCSC and TCGA RNASeq datasets. genome browser, hg19) were combined to obtain a quantifi- To get subtype specific genes, SAMSeq (24) was performed on cation of the expression level for that gene. The genes with the both datasets between each subtype and all other subtypes with a highest degree of variation in expression levels across all false discovery rate (FDR) of 0.05. Kaplan–Meier plots were used samples were identified by filtering the dataset for genes with to compute the survival curves, and Log-rank (Mantel–Cox) test aSD100, yielding 1,300 genes. These were used to perform was used to determine the statistical significance of survival Consensus Clustering (21), a method that uses data resampling between groups by using GraphPad Prism5 software. Significance followed by iterative reclustering to estimate cluster stability

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Table 1. Patient characteristics (N ¼ 99) Patients, n (%) Subtype I Subtype II Subtype III Other LMSa Age (year) Median 56 55 55 60 57 Range 2–94 2–84 41–67 43–80 38–94 Sex Female 76 (77%) 22 18 12 24 Male 23 (23%) 13 4 1 5 Location Uterine 49 (49%) 9 13 12 15 TARb 25 (25%) 12 8 1 4 Extremities 24 (24%) 13 1 0 10 Unknown 1 (1%) 1 0 0 0 Grade Low 18 (18%) 10 3 0 2 Intermediate 19 (19%) 10 4 3 5 High 62 (63%) 15 15 10 22 Relapse Primary 62 (63%) 22 9 12 19 Local recur 27 (27%) 9 12 0 6 Metastasis 10 (10%) 4 1 1 4 Therapyc Yes 11 (11%) 4 4 1 2 No 86 (87%) 29 18 12 27 Unknown 2 (2%) 2 0 0 0 Total 99 35 22 13 29 aOther leiomyosarcoma, leiomyosarcoma with negative silhouette value. bTAR, thoracic/abdominal/retroperitoneal sites. cAny prior chemotherapy and radiotherapy. and to help determine the optimal number of clusters in a unknown primary site. In addition to the differences in the dataset. As shown in Fig. 1A and B, the greatest increase in the site of origin for the tumors examined there was a significant area under the CDF curve (empirical cumulative distribution difference in the percentage of samples derived from primary function) is seen when 3 molecular subtypes are assumed. lesions versus recurrences between the two cohorts. In the Assuming 4 molecular subtypes showed a lesser degree of 3SEQ cohort 37% of the cases were recurrences or metastases increase in the area under the CDF curve and showed no while only 2% of TCGA leiomyosarcoma cases were recurrent significant increase in the ability to classify the cases (Sup- and none were metastatic (Supplementary Table S2). The plementary Fig. S1). To keep the number of subtypes to a two datasets differed in two additional aspects. First, the TCGA manageable number, we focused on the existence of three dataset used fresh frozen material whereas our 3SEQ analysis molecular subtypes of leiomyosarcoma for this study. A con- was performed on FFPE material. Second, whole transcriptome sensus matrix of the probability that 2 cases of leiomyosar- RNASeq was used for the TCGA dataset while 3SEQ deter- coma will belong to the same subtype is shown in Fig. 1C. mines the gene expression level based on quantification of 30 Silhouette analysis (22) was performed to measure the confi- end reads. Despite these differences, analysis of the TCGA dence with which an individual leiomyosarcoma case could datasetproducedresultsverysimilartothosefoundinthe beassignedtoitssubtype(Fig.1D).Thisanalysisindicatedthat 3SEQ cohort. The TCGA dataset yielded 1,174 genes when all subtype II cases had a positive silhouette value while a filtered for a SD 100 (1,300 genes in the 3SEQ set). By subset of subtype I and III leiomyosarcoma had negative values. Consensus Clustering and Silhouette analysis, the TCGA data- Similar to studies performed by others, we used only the 70 set also showed the greatest increase in area under the CDF leiomyosarcoma cases with positive Silhouette values as the curve when three subtypes were used (Fig. 2A). Compared most reliable examples ("core" leiomyosarcoma cases) for with the cases studied by 3SEQ in our cohort the homogeneity subsequent analyses (3,8). In the group of 70 core leiomyo- of the subtypes in the TCGA cohort was greater as determined sarcoma cases, 35 belonged to subtype I, 22 to subtype II, while by consensus clustering (Fig. 2B), possibly due to the fact that 13 were subtype III. frozen material and not FFPE material was used for the cases in the TCGA cohort. To measure the reproducibility between Molecular subtypes of leiomyosarcoma can be reproduced in the 3SEQ and TCGA cohorts the cases with positive Silhouette an independent dataset values from both sets were analyzed by Subclass mapping To further explore the reproducibility of the three leiomyo- (23). The 3SEQ-subtype I and -subtype II types were signifi- sarcoma subtypes, we downloaded gene expression data for 82 cantly reproduced as subtype-C3 and -C1 in the TCGA cohort leiomyosarcoma cases from the TCGA database. Of these sam- with FDR corrected P values of 0.0090 for both. The 3SEQ- ples, 80 cases were primary leiomyosarcoma while 2 cases were subtype III did not reach statistical significance when it was recurrences. The origin of the tumors differed from the 99 cases compared with the remaining TCGA-subtype C2 (Fig. 2C; analyzed by 3SEQ with 19 leiomyosarcoma originating from P ¼ 0.0959). A substantial number of genes identified by the uterus, 13 cases from the extremities and 32 cases from SAMSeq in the 3SEQ and TCGA datasets showed overlap other extrauterine sites. The remaining 18 cases had an between 3SEQ subtypes I and II and the corresponding TCGA

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Figure 1. Identiﬁcation of three molecular subtypes in leiomyosarcoma (LMS). A, empirical cumulative distribution plots as a function of the number of molecular subtypes in 3SEQ cohort. B, relative increase in the area under the CDF curve with increasing number of molecular subtypes. C, consensus clustering matrix of leiomyosarcoma samples using 3 molecular subtypes. D, silhouette analysis of leiomyosarcoma samples based on the assignments from Consensus Clustering.

subtypes (Supplementary Table S3). Importantly, ﬁve genes for that the existence of 3 molecular subtypes in leiomyosarcoma which we previously used immunohistochemical markers can be reproduced on the mRNA level across these different (13, 33) to identify subtype I leiomyosarcoma (CASQ2, datasets. ACTG2, MYLK, SLMAP,andCFL2) were shown to be highly expressed on the mRNA level in TCGA subtype C3, as was the Clinical features of leiomyosarcoma molecular subtypes in new subtype I marker LMOD1. In addition, the new marker three datasets ARL4C,whichidentiﬁes 3SEQ subtype II cases, was highly In the 3SEQ dataset, approximately 26%, 59%, and 92% of expressed in the corresponding TCGA subtype C1 (see below subtype I, subtype II, and subtype III leiomyosarcoma were and Supplementary Table S4). Together, these data indicate derived from the uterus with uterine leiomyosarcoma being

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Figure 2. Identification of molecular subtypes of leiomyosarcoma (LMS) in the TCGA data. A, empirical cumulative distribution plots as a function of the number of molecular subtypes in TCGA cohort. B, consensus clustering matrix of leiomyosarcoma samples using 3 molecular subtypes. C, subclass association (SA) matrix between 3SEQ data (subtype I, subtype II, subtype III) and TCGA data (subtype C1, subtype C2, subtype C3). P value is corrected with FDR. D, principal component analysis (PCA) of 70 core 3SEQ leiomyosarcoma cases with other diagnoses. Subtype I leiomyosarcoma, black circle; subtype II leiomyosarcoma, red triangle; subtype III leiomyosarcoma, green triangle; leiomyoma, cyan solid circle; myometrium, orange solid circle; undifferentiated pleomorphic sarcomas, blue solid pyramid. The elliptical contours represent the normal probability of 0.75. significantly associated with subtype III (c2 test; P ¼ 0.0005). I, II, and III, respectively. These results indicate that a subset of However, when evaluating only those 34 cases arising in the uterine leiomyosarcomas behave as independent molecular sub- uterus, we found that uterine leiomyosarcoma had a roughly type (subtype III) while another subset of uterine leiomyosar- equal chance of belonging to each of the molecular subtypes with coma together with extrauterine leiomyosarcoma belong to sub- 9, 13, and 12 cases belonging to subtype I, II, and III, respectively. type I and subtype II leiomyosarcoma. In the TCGA dataset, we In contrast, the extrauterine leiomyosarcoma were overrepresent- observed similar demographic characteristics as in the 3SEQ ed in subtype I and II, with 25, 9, and 1 cases belonging to subtype cohort, with TCGA C2–like 3SEQ subtype III being significantly

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associated with uterine leiomyosarcoma (P < 0.0001), while A search for the CSF1 signature, which we previously reported to TCGA C3 (subtype I) and TCGA C1 (subtype II) were overrep- be associated with poor outcome for both gynecologic and non- resented in extrauterine sites (Supplementary Table S2). These gynecologic leiomyosarcoma (27), in the 3SEQ data showed that results correlate well with our findings on 51 leiomyosarcoma the cases with a centroid correlation > 0.3 for the CSF1 signature cases from our previous dataset analyzed by gene microarrays, were overwhelmingly subtype II leiomyosarcoma (c2test; P < where the ratio of uterine leiomyosarcoma (13) also was higher in 0.0001). subtype III (10/24) than in subtype I (1/13) and subtype II (3/12), A total of 1,320 genes are significantly overexpressed and but did not reach significance (c2 test; P ¼ 0.1178). 7,544 genes are underexpressed in subtype III leiomyosarcoma Within the 3SEQ cohort, 18% (18) of tumors are low grade, when compared with the other two subtypes. Subtype III 19% (19) are intermediate grade, and 63% (62) are high grade overexpressed genes are enriched in GO biologic processes, by histologic analysis. Low-grade lesions were more frequent in including metabolic process, ion transport, and regulation of subtype I leiomyosarcoma, with 10 of 35 cases showing low- transcription (Supplementary Table S6). When considering grade histology while 3 of 22 of subtype II and 0 of 13 of only the genes with a mean level of expression 50 reads (TPM) subtype III leiomyosarcoma cases are low grade, respectively; or more in any subtype in the Stanford 3SEQ cohort the however, there was no statistically significant correlation number of overexpressed genes identified by SAMseq will between grade and molecular subtype (Table 1, c2 test; P ¼ decrease from 11,125 to 3,350. The same approach will 0.0989). The median age for subtype I, subtype II, and subtype decrease the number of genes in the TCGA cohort from III was 55, 55, and 60 years, respectively. One-way ANOVA 11,068 to 3,845. analysis showed that there was no significant difference in age between the three subtypes (P ¼ 0.3769). Identification of novel immunohistochemical markers for leiomyosarcoma subtype I and II Functional annotation of leiomyosarcoma molecular subtypes Through gene microarray analysis, we previously identified 5 based on subtype-specific genes in the 3SEQ dataset IHC markers (ACTG2, SLMAP, MYLK, CFL2, and CASQ2) that SAMSeq (24) was used to identify genes that were significantly could identify subtype I leiomyosarcoma in FFPE material over/underexpressed in each subtype of leiomyosarcoma ana- (13, 33). The quantitative nature of gene expression profiling by lyzed by 3SEQ, again using only those cases with a positive 3SEQ allowed for a more detailed search for additional immu- Silhouette value. In subtype I leiomyosarcoma, 5,900 genes are nohistochemical markers for leiomyosarcoma subtypes. LMOD1 relatively overexpressed while 1,900 genes are underexpressed mRNA was highly expressed in subtype I leiomyosarcoma. A compared with the other two subtypes (Supplementary Table S5). tissue microarray (TA-381) was generated that contained 58 of The overexpressed genes were enriched in Gene Ontology (GO) the 70 leiomyosarcoma cases with positive Silhouette values. Biology processes that included muscle contraction, muscle sys- Immunohistochemistry showed strong staining of a subset tem processes, and cytoskeleton organization. In addition, a leiomyosarcoma (Fig. 3A). LMOD1 stained positive in 31 leio- number of genes (LMOD1, MYOCD, CALD1, DES, CNN1, myosarcoma cases, 19 of which were subtype I leiomyosarcoma as ACTG2, SLMAP, and CASQ2) known to be involved in smooth assigned by 3SEQ analysis, in contrast, 21 of 27 LMOD1-negative muscle function were identified in this list, indicating that subtype leiomyosarcomas were subtype II or subtype III leiomyosarcoma. I was most associated with normal smooth muscle function LMOD1 protein expression therefore showed a significant asso- (Supplementary Table S6). Consistent with this finding, 4 sam- ciation with subtype I leiomyosarcoma (c2 test, P ¼ 0.0085; r ¼ ples of normal myometrium and 3 cases of benign uterine 0.8964, P < 0.0001, Spearman correlation; Supplementary Table leiomyoma were grouped with subtype I leiomyosarcoma in S7). Comparison of the LMOD1 staining results with the five principal component analysis (Fig. 2D) and clustered with sub- previously identified subtype I biomarkers (13, 33) showed that type I when analyzed by unsupervised hierarchical clustering with the highest correlation of IHC staining (0.65) was obtained the 70 leiomyosarcoma core samples (Supplementary Fig. S2A). between genes ACTG2, SLMAP, and LMOD1. CASQ2 had the As stated above, the overexpression of genes associated with lowest correlation with the 5 other genes (r ¼0.22) and we muscle function was also noted on the mRNA level in correspond- refined our panel of subtype I biomarkers to include ACTG2, ing subtype C3 from the TCGA dataset, while the subtype I SLMAP, LMOD1, CFL2, and MYLK, while omitting CASQ2. Using identified previously through gene microarray analysis had high this panel, the correlation for the new panel of markers was 0.47 levels of expression for these genes at both the mRNA and protein (Supplementary Fig. S3). Finally, staining of TA-381 showed a level (13). significant association (P < 0.0001) between LMOD1 immunos- In 3SEQ data on subtype II leiomyosarcoma, 5,100 genes were taining and mRNA levels as determined by 3SEQ LMOD1 mRNA significantly overexpressed and 2,087 genes were expressed at level (Fig. 3B). lower levels as compared with the other two subtypes of leio- Analysis of 3SEQ data showed high levels of mRNA expres- myosarcoma. These subtype II leiomyosarcoma-specific genes are sion for ARL4C in subtype II leiomyosarcoma. Using a FFPE enriched in GO biologic processes, including translation, trans- compatible antibody, strong staining was seen in a subset of lational elongation, and protein localization (Supplementary leiomyosarcoma cases (Fig. 3C) with positive staining in 30 Table S6). Subtype II showed significantly less muscle-specific leiomyosarcoma cases, 17 of which were subtype II leiomyo- genes than subtype I. Undifferentiated pleomorphic sarcoma is a sarcoma. Negative staining was seen in 28 leiomyosarcoma tumor type that fails to express differentiation markers and that cases, 23 of which were subtype I or subtype III leiomyosar- can be difficult to distinguish from leiomyosarcoma. Six cases of coma. This IHC result validates ARL4C to be a subtype II undifferentiated pleomorphic sarcomas grouped with subtype II leiomyosarcoma biomarker not only at the mRNA level (as leiomyosarcoma in principal component analysis (Fig. 2D) and determined by SAMSeq) but also at the protein level (c2 test, by unsupervised hierarchical clustering (Supplementary Fig. S2B). P ¼ 0.0033; r ¼ 0.5277, P < 0.0001, Spearman correlation;

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Figure 3. Immunohistochemical markers for subtype I and subtype II leiomyosarcoma (LMS). A, representative staining for LMOD1 (score þþþ) and CASQ2 (negative) for a subtype I leiomyosarcoma case (case # 10129; scale bar, 100 mm, 10). B, comparison of 3SEQ mRNA quantification and immunostaining results on TA-381 that contains 58 cases of leiomyosarcoma analyzed by 3SEQ; leiomyosarcoma cases positive for anti-LMOD1 staining have significantly higher mRNA expression levels (TPM) than leiomyosarcoma cases negative for anti-LMOD1 (P < 0.0001). The P value was derived from unpaired t test with Welch correction. C, positive and negative staining by ARL4C antibody for representative subtype II leiomyosarcoma (top, case # 10019) and subtype I leiomyosarcoma (bottom case # 9994; scale bar, 100 mm, 10). D, leiomyosarcoma cases positive for anti-ARL4C staining have significantly higher mRNA expression levels (TPM) than leiomyosarcoma cases negative for anti-ARL4C (P ¼ 0.0046).

Supplementary Table S7). Comparison between 3SEQ mRNA leiomyosarcoma cases (Log-rank test; Fig. 4A; P ¼ 0.0101). levels and ARL4C immunohistochemistry showed a good asso- However, the difference in clinical outcome was mostly driven ciation (P ¼ 0.0046; Fig. 3D). Comparison between LMOD1 by the extrauterine leiomyosarcoma (Fig. 4B; P ¼ 0.0208) and and ARL4C protein expression and mRNA expression levels no difference in outcome was seen for subtype I leiomyosar- varied as expected across the leiomyosarcoma subtypes as coma from uterus (Fig. 4C; P ¼ 0.2113). The association with defined by 3SEQ (Supplementary Fig. S4). good outcome lost its significance in multivariate analysis when While in individual cases these markers may not definitely two prognostic signatures that we previously identified, ROR2 identify a case as belonging to a specific subtype, when com- (34) and the CSF1 response protein signature (27), were includ- bined these markers do allow us to distinguish large numbers of ed (Supplementary Tables S8 and S9). cases represented on a TMA in distinct molecular groups. No Subtype II leiomyosarcoma cases were defined as those outcome data were available for the leiomyosarcoma samples reacting for ARL4C on the outcome TMA. Staining for ARL4C used for 3SEQ analysis. To correlate the assignment of leiomyo- was seen in 25 of 111 available leiomyosarcoma cases (23%) sarcoma subtypes with outcome, we used immunostaining data and these cases were associated with a worse DSS when on TA-201 that contains 127 cases of leiomyosarcoma with all leiomyosarcoma were combined (log-rank test, Fig. 4D; known clinical outcome (27, 34). In this analysis, 48 of 127 P ¼ 0.0019). This finding was seen in both extrauterine (P ¼ (38%) leiomyosarcoma cases were defined as subtype I leio- 0.0352) and uterine (P ¼ 0.0461) leiomyosarcoma. While myosarcoma by their coordinate expression of all 5 subtype I subtype II was associated with poor outcome in a statistically reactive antibodies. These cases demonstrated a better disease- significant manner in univariate analysis (P ¼ 0.0030, Wald specific survival (DSS) when uterine and extrauterine leiomyo- test), this significance was also lost in the multivariate analysis sarcoma were analyzed together and compared to the remaining when prognosticators ROR2 and the CSF1 response protein

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Figure 4. IHC markers for subtype I and subtype II leiomyosarcoma (LMS) predict different clinical outcomes. TA-201 with 127 cases of leiomyosarcoma with known clinical outcome was stained for the panel of 5 subtype I leiomyosarcoma markers and the ARL4C marker for subtype II leiomyosarcoma. The P value was from log-rank (Mantel–Cox) test. Coordinate expression of subtype I biomarkers was associated with good outcome when analysed on all cases (A) but this was mainly due to an effect on extrauterine (EU) leiomyosarcoma (B) but not uterine (U) leiomyosarcoma (C). Subtype II biomarker ARL4C predicted worse outcome in leiomyosarcoma (D), with equal effect on extrauterine and uterine leiomyosarcoma (not shown).

signature were included (refs. 27, 34; Supplementary Tables S8 Table 2. Targets unique to leiomyosarcoma subtypes and S9). For correlation with outcome in the IHC analysis, Gene Therapeutic agents subtype III was defined as those cases that failed to classify as Genes overexpressed in subtype I either subtype I or II. When thus defined, subtype III had an ARAF Sorafenib, vemurafenib, dabrafenib, intermediate outcome (Supplementary Fig. S5) but failed to RAF inhibitors reach prognostic significance in univariate analysis (Supple- CCNE1 CDK2 Inhibitor mentary Table S8). KDR KDR Inhibitors NOTCH1 Notch Inhibitors FGFR2 Potential clinical applications of leiomyosarcoma subtyping FGFR Inhibitors FGFR1 FGFR Inhibitors To explore the potential for clinical implications in the recog- Genes overexpressed in subtype II nition of leiomyosarcoma subtypes, we compared the genes MCL1 Tubulins that are specifically overexpressed in each leiomyosarcoma CDK4 CDK4/6 Inhibitors subtype with genes from the TARGET V2 database known to CTNNB1 WNT Inhibitors be activated by mutations or amplifications (35). This database AURKA AURKA Inhibitors RHEB contains genes for which targeted therapy is either currently mTOR Inhibitors CCND2 CDK4/6 Inhibitors available or under development. A large number of these genes CCND1 Hormone therapy, CDK4/6 inhibitors werefoundtobeexpressedatdifferentlevelsbetweenthe3 MTOR Everolimus, temsirolimus, mTOR inhibitors molecular subtypes (Table 2). This suggests that leiomyosar- MAPK3 Erlotinib, fefitinib, EGFR inhibitors coma subtypes may respond differentially to those targeted MAPK1 Erlotinib, gefitinib, EGFR inhibitors therapies, an observation that may play a role in determining CCND3 CDK4/6 Inhibitors NOTCH2 the success rate of novel therapies in clinical trials. For several of Notch Inhibitors MAP2K2 MEK Inhibitors these targets there may be an incomplete correlation between Genes overexpressed in subtype III fi mRNA levels for the mutated or ampli ed target gene and MDM4 MDM4 Inhibitors response to drug, but this analysis nevertheless forms a first ERBB3 Pertuzumab step towards personalization of leiomyosarcoma patient care. EPHA3 Dasatinib, ephrin inhibitors In addition to the genes identified from the TARGET V2, ESR1 Hormonal therapy we studied the expression level of ROR2, a receptor tyrosine Genes overexpressed in subtype II and III EGFR Erlotinib, gefitinib, EGFR inhibitors kinase that plays a role in tumor progression and that has a low

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level of expression in normal human tissues. This molecule has colleagues (41) identified a 200 gene signature for leiomyo- been proposed as a novel therapeutic target in leiomyosarcoma sarcoma by expression profiling different subtypes of 177 soft (34) and other tumors (36–38) and was found to be more tissue sarcomas, this signature was characterized by overexpres- frequently expressed in subtype II leiomyosarcoma than in sion of muscle-specific genes and was shown to be highly the other subtypes (FDR < 0.05). Immunostaining for the expressed in 12 of 40 leiomyosarcoma cases by supervised ROR2 protein on the TMA containing cases analyzed by 3SEQ clustering. Villacis and colleagues (42) performed gene expres- similarly showed a correlation with subtype II leiomyosarcoma sion profiling and supervised clustering with 587 genes (c2 test, P ¼ 0.0347,). expressed differentially between undifferentiated pleomorphic sarcomas and leiomyosarcoma, and found that a subset of leiomyosarcoma that highly expressed muscle function Discussion associated genes clustered separately from undifferentiated Leiomyosarcoma is a malignant soft tissue tumor with com- pleomorphic sarcomas and other leiomyosarcoma cases. plex genetic abnormalities. In clinical practice, the tumors are In contrast to subtype I leiomyosarcoma, subtype II treated differently depending on whether they originate from leiomyosarcoma showed no significant smooth muscle differ- the uterus or from extrauterine sites. However, this distinction entiation by GO analysis and therefore represents a less differ- is not based on a molecular rationale and appears based, at entiated form of leiomyosarcoma. Undifferentiated pleomor- least in part, on clinical subspecialization. Recently Italiano and phic sarcoma is a type of sarcoma that lacks any indication colleagues demonstrated a molecular difference between leio- of differentiation by histologic examination and by immuno- myosarcoma occurring in the retroperitoneum and extremities histochemical analysis. Hierarchical clustering of the core (39), but this article does not include uterine lesions. Leiomyo- leiomyosarcoma cases with 6 cases of undifferentiated pleo- sarcomas are tumors that exhibit varying degrees of smooth morphic sarcomas showed coclustering of undifferentiated muscle differentiation and often appear to be derived from pleomorphic sarcomas with subtype II leiomyosarcoma. Others smooth muscle cells in the myometrium. They can also arise have studied the relation between leiomyosarcoma and undif- from the walls of blood vessels or connective tissues through- ferentiated pleomorphic sarcomas by molecular studies but did out the body. Conventional chemotherapy and radiotherapy not take into account the existence of leiomyosarcoma subtypes only have limited effects and surgical resection remains the (43). Villacis and colleagues performed gene expression pro- best option for treatment. Characterization of molecular sub- filing of 22 leiomyosarcoma and 22 undifferentiated pleomor- types in malignancies can lead to better individualization of phic sarcomas, and did not identify a clear distinction of treatment. In a prior study on 51 cases of leiomyosarcoma for expression profiles of undifferentiated pleomorphic sarcomas which frozen tissue was available, we used 44,000 spotted and leiomyosarcoma by either unsupervised clustering or even cDNA arrays for gene expression profiling and obtained data supervised clustering using a gene list derived from SAM anal- that indicated that at least 3 molecular subtypes exist in ysis. However, when performing supervised clustering with 587 leiomyosarcoma (13). This study relied on the availability of genes expressed differentially between undifferentiated fresh frozen tissues and as a result only small numbers of pleomorphic sarcomas and leiomyosarcoma, a subset of leio- leiomyosarcoma cases could be studied. The 3SEQ approach myosarcoma that consisted predominantly of retroperitoneal can use FFPE materials and renders a digital rather than an leiomyosarcoma clustered separately from undifferentiated analog readout for gene expression levels with a higher signal to pleomorphic sarcomas and the remaining leiomyosarcoma, in noise ratio and allows for accurate measurement of genes part based on higher expression of muscle function associated expressed at a wide range of levels, including those with low genes in the retroperitoneal leiomyosarcoma (42). These find- levels of expression. 3SEQ analysis on 99 samples of leiomyo- ings partially overlap with our results; in our study 6 retroper- sarcoma and data on a third cohort of 82 leiomyosarcoma cases itoneal leiomyosarcoma were analyzed, 4 of which grouped in from the TCGA study were obtained. Despite the differences in subtype I with 2 cases grouping in subtype II, the subtype most methodology and sample selection between these three associated with undifferentiated pleomorphic sarcomas. cohorts, remarkable similarities were apparent and indicated Subtype III leiomyosarcoma is the only subtype that shows a the existence of three molecular subtypes in leiomyosarcoma. preference for a specific anatomic site and was more likely to be Subtype I leiomyosarcoma expresses most genes associated from uterus (Fisher exact test; P ¼ 0.005). Only one of 13 subtype with muscle function by Gene Ontology annotation. The sim- III leiomyosarcoma did not originate from the uterus and pre- ilarity of subtype I leiomyosarcoma to smooth muscle differ- sented in the scrotum. However, uterine leiomyosarcoma as a entiation was also supported by the fact that subtype I cases group was evenly distributed over the 3 subtypes. clustered with samples of leiomyoma and myometrium. Final- Neither uterine nor extrauterine leiomyosarcoma have ly, we observed high expression levels for LMOD1 in subtype I clinically accepted prognostic molecular markers, and histo- leiomyosarcoma, a smooth muscle cell-restricted gene that is logic grading to predict clinical outcome is controversial in preferentially expressed in differentiated smooth muscle cells uterine leiomyosarcoma. Several molecular prognosticators (40). The expression of smooth muscle markers in subtype I (28, 39, 41, 44, 45) have previously been reported in leiomyo- suggest a tumor subtype that is closer to the smooth muscle sarcoma. By genomic and expression profiling of 183 sarcomas, cells than subtype II and III. However this similarity is not Chibon and colleagues established a prognostic signature call- captured by the objective measurement of histologic grade, as ed Complexity Index in Sarcoma (CINSARC), that includes 67 no correlation between grade and molecular subtype was genes related to mitosis and chromosome management. This found. Others have noticed the existence of a subset of leio- signature was shown to be associated with metastatic outcome myosarcoma that express muscle function related genes at in sarcomas, including leiomyosarcoma, and even in lympho- higher levels than other leiomyosarcoma cases. Francis and mas and breast carcinoma. The CINSARC signature is a

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powerful predictor of tumor metastasis and could improve the ential response in that subtype for which the target gene is patient selection for chemotherapy (28). To investigate the expressed at higher levels. significance of leiomyosarcoma subtypes on clinical outcome, In summary, we used gene expression profiling and immu- we stained a TMA containing cores from 127 leiomyosarcoma nohistochemical assays to demonstrate the existence of 3 dis- cases with clinical outcome with the IHC markers for subtype I tinct molecular subtypes in leiomyosarcoma in two indepen- and II leiomyosarcoma. Subtype I leiomyosarcoma was asso- dent sets of cases and showed that they are associated with ciated with good outcome in extrauterine leiomyosarcoma, distinct clinical outcomes. These findings indicate distinct bio- while subtype II was associated with poor outcome in univar- logic subclasses in leiomyosarcoma that may respond different- iate analysis. In this context, it is interesting to note that the ly to novel therapeutic approaches. association between muscle gene expression and better clinical outcome is a finding that was also reported in various ways Disclosure of Potential Conflicts of Interest by other immunohistochemical studies (18, 45). While sub- C-H. Lee is a member of the AstraZeneca Ovarian Cancer Advisory Board. typing of leiomyosarcoma by immunohistochemistry can No potential conflicts of interest were disclosed by the other authors. help predict clinical outcome, in multivariate analysis the subtype I and II biomarkers were outperformed by the previ- Authors' Contributions ously described markers ROR2 and the "CSF1 protein response Conception and design: X. Guo, R.B. West, M. van de Rijn Development of methodology: X. Guo, S. Zhu, R.B. West, M. van de Rijn signature" (27, 34). The association between immunohisto- fi Acquisition of data (provided animals, acquired and managed patients, chemically de ned subtype II leiomyosarcoma with poor out- provided facilities, etc.): X. Guo, V.Y. Jo, A.M. Mills, S.X. Zhu, C.-H. Lee, come was consistent with previously published gene expression I. Espinosa, M.R. Nucci, S. Anderson, C.D. Fletcher, M. van de Rijn profiling data. The CINSARC signature was significantly asso- Analysis and interpretation of data (e.g., statistical analysis, biostatistics, ciated with subtype II leiomyosarcoma but not with the other computational analysis): X. Guo, T. Hastie, K. Ganjoo, A.H. Beck, R.B. West, subtypes (P ¼ 0.0279 by Fisher exact test). C.D. Fletcher, M. van de Rijn Writing, review, and/or revision of the manuscript: X. Guo, V.Y. Jo, C.-H. Lee, At this time, no targeted therapies exist for leiomyosarcoma. I. Espinosa, E. Forgo, K. Ganjoo, A.H. Beck, R.B. West, C.D. Fletcher, M. van de The recognition of molecular subtypes in malignancy has led Rijn to the identification of targets that are unique to a subset of the Administrative, technical, or material support (i.e., reporting or organizing cases in a variety of tumors that include breast cancer, colon data, constructing databases): X. Guo, V.Y. Jo, S.X. Zhu, S. Varma, M. van de cancer, bladder cancer and glioblastoma, and others (3–12). In Rijn previous studies, we have identified ROR2, a receptor tyrosine Study supervision: X. Guo, M. van de Rijn kinase (34) and the presence of intratumoral macrophages Acknowledgments (27) as prognostic markers in both uterine and extrauterine fi The authors thank the Stanford Center for Genomics and Personalized leiomyosarcoma. On the basis of our nding, subtype II Medicine with help on Illumina sequencing and Alayne Brunner, Patricia leiomyosarcoma, which has high levels of ROR2 expression, Marian Robinson, Joanna Przybyl, and other labmates for sample collection, would benefit most from drugs targeting this molecule either helpful discussions and experimental design. as a single drug or in combination with CD47-based therapy (34, 46, 47). Grant Support Here we report that the molecular subtypes in leiomyosar- This study was supported by the NIH (grant no. CA 112270; to M. van de coma show differential expression of a large number of genes Rijn) and the Fund for Health Research (FIS PI12/01645; to I. Espinosa). The costs of publication of this article were defrayed in part by the payment for which therapeutics either currently exist or are under devel- advertisement fi of page charges. This article must therefore be hereby marked opment. These subtype speci ctargetsmaynotshowasignif- in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. icant response when leiomyosarcoma cases are considered as a single homogenous entity in a clinical trial. Recognition of Received December 17, 2014; revised April 7, 2015; accepted April 11, 2015; molecular subtypes in leiomyosarcoma may highlight prefer- published OnlineFirst April 20, 2015.

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Clinically Relevant Molecular Subtypes in Leiomyosarcoma

Xiangqian Guo, Vickie Y. Jo, Anne M. Mills, et al.

Clin Cancer Res Published OnlineFirst April 20, 2015.

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