Global gene expression profiling of PAX‐FKHR fusion‐positive alveolar and PAX‐FKHR fusion‐negative embryonal rhabdomyosarcomas

Abstract

Paediatric rhabdomyosarcomas (RMS) are classified into two major subtypes based on histological appearance, embryonal (ERMS) and alveolar (ARMS), but this clinically critical distinction is often difficult on morphological grounds alone. ARMS, the more aggressive subtype, is associated in most cases with unique recurrent translocations fusing the PAX3 or PAX7 transcription factor genes to FKHR. In contrast, ERMS lacks unique genetic alterations. To identify novel diagnostic markers and potential therapeutic targets, we analysed the global gene expression profiles of these two RMS subtypes in 23 ARMS (16 PAX3-FKHR, 7 PAX7-FKHR) and 15 ERMS (all PAX-FKHR-negative) using Affymetrix HG-U133A oligonucleotide arrays. A statistically stringent supervised comparison of the ARMS and ERMS expression profiles revealed 121 genes that were significantly differentially expressed, of which 112 were higher in ARMS, including genes of interest as potential diagnostic markers or therapeutic targets, such as CNR1, PIPOX (sarcosine oxidase), and TFAPbeta. Interestingly, many known or putative downstream targets of PAX3-FKHR were highly overexpressed in ARMS relative to ERMS, including CNR1, DCX, ABAT, ASS, JAKMIP2, DKFZp762M127, and NRCAM. We validated the highly differential expression of five genes, including CNR1, DKFZp762M127, DCX, PIPOX, and FOXF1 in ARMS relative to ERMS by quantitative RT-PCR on an independent set of samples. Finally, we developed a ten-gene microarray-based predictor that distinguished ARMS from ERMS with approximately 95% accuracy both in our data by cross-validation and in an independent validation using a published dataset of 26 samples. The gene expression signature of ARMS provides a source of potential diagnostic markers, therapeutic targets, and PAX-FKHR downstream genes, and can be used to reliably distinguish these sarcomas from ERMS.

The muscle-specific microRNA miR-206 blocks human rhabdomyosarcoma growth in xenotransplanted mice by promoting myogenic differentiation

“…Differentiation-based nontoxic treatments would be most desirable also for solid tumors, especially in the case of pediatric cancers (RMS or neuroblastomas) or of deadly brain tumors that are impossible to treat surgically or are resistant to traditional therapies (GBM). Our results were obtained in vivo, using cells of 2 RMS subtypes, harboring remarkably different genetic lesions (27), including nonfunctional mutations of p53 (48). Silber's results (42) were obtained in cell culture, using murine tumor-derived stem cells and also long-established human GBM cell lines.…”

“…While most ARMSs carry the pathogenetic translocation PAX3/7-FKHR (25,26), ERMSs do not carry a distinct genetic lesion and generally follow a more favorable course. The expression profiles of ARMSs and ERMSs differ widely (27), but cell lines established from both types of tumor, as well as primary tumors, consistently express rather high levels of the Met receptor (28), a potential target of miR-1 and miR-206.…”

Prognostic value of PAX3/7–FOXO1 fusion status in alveolar rhabdomyosarcoma: Systematic review and meta-analysis

“…Although there are the distinct histological differences between typical ARMS and ERMS, recent gene expression profiling based on microarray shows that fusion negative ARMS more closely resembles ERMS than fusion ONCH-1975 positive ARMS [20,27,30,31]. Therefore, the expression of the fusion gene may provide additional biological properties to a subset of ARMS cases, despite the similar morphological characteristics by traditional histological examination.…”

Proteomics of Bone and Soft Tissue Sarcomas

“…This paradigm encourages the strategy of applying molecular classification to diagnosis and treatment of sarcomas. Gene expression studies further validate a molecular approach by confirming that morphologically recognisable sarcomas can be classified on the basis of distinct expression cluster sub-sets [11][12][13][14][15][16][17][18][19][20][21]. Proteomics is an exciting alternative to genomics-based analysis and several lines of evidence show that analysing protein expression in this way is particularly advantageous in cancer research.…”