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Affymetrix SNP array data for pediatric rhabdomyosarcoma (RMS)

ABSTRACT: To elucidate the pathogenesis of rhabdomyosarcoma (RMS), particularly for different subgroups, we performed a SNP array-based copy number analysis of 54 RMS specimens from primary cases with ERMS (N = 30), ARMS (N = 14), unclassified RMS (N = 1), and RMS of unknown histology (N = 3) together with 7 RMS-derived cell lines. The ERMS subtype was characterized by hyperploidy and was significantly associated with gains of chromosomes 2, 8, and 12, whereas majority of ARMS cases exhibited near-diploid copy number profiles. Recurrent loss of heterozygosity (LOH) of chromosomes 3 (28.6%) and 15q (35.7%) was detected in ARMS. Uniparental disomy/polysomy of 11p was commonly found in both tumor types. Focal gains/amplifications were associated mostly with PAX3-FOXO1 (5/10) or PAX7-FOXO1 (6/6) fusions, but novel amplified regions were also found, including the IRS2 in 2 ARMS. Gain of 13q was significantly associated with good patient outcome in ERMS. These findings not only illustrate genetic differences between ARMS and ERMS but also provide novel insights into the pathogenesis of RMS.

ORGANISM(S): Homo sapiens

PROVIDER: GSE41263 | GEO | 2013/08/12

SECONDARY ACCESSION(S): PRJNA176458

REPOSITORIES: GEO

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Affymetrix SNP array data for pediatric rhabdomyosarcoma (RMS)

Project description:To elucidate the pathogenesis of rhabdomyosarcoma (RMS), particularly for different subgroups, we performed a SNP array-based copy number analysis of 46 RMS specimens from primary cases with ERMS (N = 21), ARMS (N = 14), unclassified RMS (N = 1), and RMS of unknown histology (N = 3) together with 7 RMS-derived cell lines. The ERMS subtype was characterized by hyperploidy and was significantly associated with gains of chromosomes 2, 8, and 12, whereas majority of ARMS cases exhibited near-diploid copy number profiles. Recurrent loss of heterozygosity (LOH) of chromosomes 3 (28.6%) and 15q (35.7%) was detected in ARMS. Uniparental disomy/polysomy of 11p was commonly found in both tumor types. Focal gains/amplifications were associated mostly with PAX3-FOXO1 (5/10) or PAX7-FOXO1 (6/6) fusions, but novel amplified regions were also found, including the IRS2 in 2 ARMS. Gain of 13q was significantly associated with good patient outcome in ERMS. These findings not only illustrate genetic differences between ARMS and ERMS but also provide novel insights into the pathogenesis of RMS. Copy number analysis of Affymetrix 50K/250K SNP arrays was performed for 46 RMS samples.

2013-08-12 | E-GEOD-41263 | biostudies-arrayexpress

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2016-12-01 | E-MTAB-5321 | biostudies-arrayexpress

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Project description:Rhabdomyosarcomas (RMS) are rare but very aggressive tumours of childhood that arise as a consequence of regulatory disruption of the growth and differentiation pathways of myogenic precursor cells. Based on morphology, two major RMS subtypes can be identified: embryonal RMS (ERMS) and alveolar (ARMS). To better understand the global function of miRNA in RMS, we analyzed the expression profile of 8 different RMS cell lines (3 PAX3/FOXO1 positive and 5 PAX3/FOXO1 negative RMS) using the mirVana miRNA Probe Set V1 (Ambion). The miRNA microarray platform was able to distinguish PAX3/FOXO1 positive (RH4, RH30, RH28) and negative RMS (RD, CCA, SMS-CTR, RH36, RH18) cell lines through the expression pattern of about 90 miRNAs. Since the translocation positive RMS patients fared worse than the negative counterpart our results demonstrated the potential of miRNA expression profiling to classify different RMS subtypes, in agreement to previous gene expression studies, and set the basis for a further functional characterization of selected miRNAs implicated in RMS pathogenesis and in the different clinical behaviour and aggressiveness of the two RMS subtypes. We decided to study miRNAs with the greatest difference in expression between PAX3/FOXO1 positive and negative RMS:miR-23a, miR-27a and miR-199a.

2015-05-04 | GSE52677 | GEO

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Project description:Rhabdomyosarcomas (RMS) represent a family of aggressive soft tissue sarcomas that present in both the pediatric and adult setting. Pathologic risk stratification for RMS has been based on histologic subtype, with poor outcomes observed in alveolar rhabdomyosarcoma (ARMS) and adult-type pleomorphic rhabdomyosarcoma (PRMS) compared to embryonal rhabdomyosarcoma (ERMS). Recent genomic sequencing studies have expanded the spectrum of RMS, with several new molecularly defined entities, including fusion-driven spindle cell/sclerosing rhabdomyosarcoma (SC/SRMS) and MYOD1-mutant SC/SRMS. Comprehensive genomic analysis has previously defined the mutational and copy number spectrum for the more common ERMS and ARMS, as well as revealed corresponding methylation signatures. In contrast, genetic and epigenetic correlates have not been defined for the rare SC/SRMS or PRMS histologic subtypes. Herein, we present genomic sequencing, copy number analysis, and methylation profiling of the largest cohort of molecularly characterized RMS samples to date. We identified two novel methylation subtypes, one having SC/SRMS histology and defined by MYOD1 p. L122R mutations and the other matching adult type PRMS. Selected tumors from adolescent patients grouped with the PRMS methylation class, expanding the age range of these rare tumors. Pediatric patients in the MYOD1-mutant group, as well as those clustering with PRMS, appear to have poor overall survival.

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microRNA-27a contributes to rhabdomyosarcoma cell proliferation through suppression of RARA and RXRA

Project description:This SuperSeries is composed of the SubSeries listed below. Background: Rhabdomyosarcomas (RMS) are rare but very aggressive tumors of childhood that arise as a consequence of regulatory distruption of the growth and differentiation pathways of myogenic precursor cells. Based on morphology, two major RMS subtypes can be identified: embryonal RMS (ERMS) and alveolar (ARMS). So, it is essential to unravel the molecular mechanisms involved in cancer pathogenesis and in disease progression. MicroRNAs are endogenous small non-coding RNAs with a key role in tumorigenesis. Methodology/Principal Findings: To better understand the involvement of miRNAs in RMS, we analyzed the expression profile of 8 different RMS cell lines (4 ARMS and 4 ERMS). The miRNA population from each cell line was compared to a reference sample consisting of a pool of each total RNA sample mixed in equal amount. We identified a 16 miRNAs signature that discriminates translocation positive (ARMS) and negative RMS (ERMS). We focused our attention on the role of miR-27a that is up-regulated in the more aggressive RMS cell lines (ARMS translocation positive) where probably it acts as an oncogene. miR-27a-overexpressing cells showed a significant enhance of the proliferation rate, paralleled by a decrease of cells in G1 phase. We demonstrated that miR-27a is implicated in cell cycle control by targeting the retinoic acid alpha receptor (RARA) and retinoic X receptor alpha (RXRA). Conclusions: Our results demonstrated the potential of miRNA expression signature to better classify different RMS subtypes and settled the basis for a potential therapeutic role of miR-27a in RMS through modulation of retinoic acid receptors expression.

2015-05-04 | GSE52679 | GEO

Proteomic profiling of rhabdomyosarcoma-derived exosomes yield functional role for extracellular vesicles

Project description:In this study, we interrogated the protein composition of exosomes purified from cell culture supernatants of 5 different RMS cell lines, by LC-MS/MS technology and analysis using bio-informatics tools. We attempted to characterize the differences and similarities between exosomes derived from ERMS and ARMS cells, and common as well as unique characteristics of RMS exosome protein content when compared to that of other cancer and non-cancer cells. Our results identify potential protein exosome biomarkers for RMS to be further investigated in future clinical studies.

2019-08-29 | PXD007755 | Pride

circ-ZNF609 regulates G1-S progression in Rhabdomyosarcoma

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2018-12-14 | GSE117609 | GEO

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