LMS is an aggressive malignant neoplasm, and its molecular pathogenesis is poorly understood. Treatment options are limited, and there is a major clinical interest in gaining a better understanding of LMS pathogenesis to facilitate the development of targeted therapies.
Several prior studies have performed gene expression profiling on relatively small numbers (n=3–13) of LMS samples (Baird et al., 2005
; Henderson et al., 2005
; Nakayama et al., 2007
; Nielsen et al., 2002
; Quade et al., 2004
; Ren et al., 2003
; Segal et al., 2003
; Shmulevich et al., 2002
; Skubitz and Skubitz, 2003
). Due to the small number of cases in each study it is difficult to draw conclusions on the heterogeneity within LMS based on these data. Francis et al. performed gene expression profiling on 177 soft tissue tumors, including 40 LMS samples. They identified a distinct cluster of 11 LMSs that clustered together, while the remaining 29 LMS samples showed more heterogeneous patterns of gene expression (Francis et al., 2007
). The distinct cluster of 11 LMS cases from this dataset were reported to show high expression levels of a group of muscle-associated genes, many of which were also identified as highly expressed in Group I/muscle-enriched LMS in our study (including CALD1, SLMAP, ACTG2, CFL2, MYLK, ACTA2, MBNL1, TPM1, PPP1R12A, DTNA, FZD6, PPP1R12A, CLIC4, CDC42EP3, BARD1, TPM1, RAB27A, MAP1B, EDIL). We find a similar muscle-enriched LMS cluster in our dataset and in the Baird dataset (Baird et al., 2005
). Our findings and those from the literature suggest that multiple molecular subtypes of LMS exist and that the “muscle-enriched” subtype has been reproducibly identified in at least 2 of the largest datasets.
Several prior reports have looked at CGH changes in LMS. Meza-Zepeda et al. performed aCGH on 12 LMS samples and 7 gastrointestinal stromal tumors and observed that LMS showed more genomic losses than gains with the most frequent minimal regions of loss at 10q21.3 and 13q14.2-q14.3, each detected in 9 of 12 LMS samples in their study (Meza-Zepeda et al., 2006
). In our study, we identified loss at 10q21.3 in 5 of 12 Group I/muscle-enriched samples and in none of the Group II or III samples. We identified loss at 13q14.2 in 6 of 12 Group I/muscle-enriched samples, 0 of 1 Group II samples, and 2 of 7 Group III samples. The common region of 13q14.2 that was lost in all 8 samples includes the RB1
gene, a well-characterized tumor-suppressor whose loss has been shown to contribute to sarcomagenesis (Landis-Piwowar et al., 2008
). Meza-Zepeda et al
also noted loss at 16q21.2-q22.1 in 6 of 12 samples and 1p36.32-p36.21 in 4 of 12 samples, which are both changes we find in our study, specifically in Group I/muscle-enriched LMS. Larramendy et al
evaluated 102 malignant fibrous histiocytomas (MFH) and 82 LMS cases by conventional comparative genomic hybridization (Larramendy et al., 2008
) and identified 11 regions with significantly increased losses in LMS compared to MFH, including 1p36.1~pter (10% of LMS vs 1% of MFH), and 16qter (34% of LMS vs. 3% of MFH), both of which were identified as lost in most Group I/muscle-enriched LMS cases in our analysis. We note that the 1p36 region contains PRDM16
and the 16q24.3 region contains FANCA
. To our knowledge, our study is the first to integrate aCGH data with gene expression analysis.
Prognosis in LMS is currently predicted using a combination of traditional clinicopathologic features (Kattan et al., 2002
). There are currently no molecular biomarkers utilized in prognostication in LMS in clinical practice. Gene expression microarrays have been used to identify signatures to predict metastasis in LMS (Lee et al., 2004
). Our group has previously identified macrophage infiltration (Lee et al., 2008
) and the CSF1 response signature (Espinosa et al., 2009b
) as predictors of poor prognosis in LMS. In the current study, we have identified protein markers from the Group I/muscle-enriched LMS subtype and demonstrated that their expression correlates with improved DSS. These findings suggest that despite showing increased genomic complexity, Group I/muscle-enriched LMS may be intrinsically less aggressive and more differentiated than other LMS subtypes. In a multivariate model incorporating traditional clinicopathologic features (size, grade, necrosis, site) as well as the CSF1 response signature and the Group I/muscle-enriched markers, we find that only the CSF1 response signature and the number of positive muscle-enriched markers emerged as significant predictors of survival, with the CSF1 response signature correlating with poor prognosis and the expression of Group I/muscle-enriched markers correlating with improved prognosis. These prognostic biomarkers, which can be measured with immunohistochemistry on paraffin embedded formalin fixed tissue, may prove useful for the clinical management of LMS. Ultimately, we hope that the characterization of distinct molecular subtypes in LMS will lead not only to the identification of clinically useful prognostic markers, but also to the development of treatments to target specific molecular aberrations observed in the subtypes.