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Whole transcriptome analysis of sinonasal sarcoma with translocation t(2;4)(q37.1;q31.3)

ABSTRACT: Conventioal cytogenetic on 2 sinonasal sarcoma (SNS) cases showed t(2;4)(q37.1;q31.3) translocation previously. The aim of this whole transcriptome analysis is to determine potential candidate genes involved in this translocation. Total RNA extracted from frozen cultured primary tumor cells from a SNS characterized at the cytogenetics level was subjected to Illumina whole transcriptome RNA-sequencing anslysis.

ORGANISM(S): Homo sapiens

SUBMITTER: Yan Asmann

PROVIDER: E-GEOD-52257 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Whole transcriptome analysis of sinonasal sarcoma with translocation t(2;4)(q37.1;q31.3)

Project description:Conventioal cytogenetic on 2 sinonasal sarcoma (SNS) cases showed t(2;4)(q37.1;q31.3) translocation previously. The aim of this whole transcriptome analysis is to determine potential candidate genes involved in this translocation.

2014-04-17 | GSE52257 | GEO

Gene expression profiling in sinonasal sarcoma

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Gene expression profiling in sinonasal sarcoma

Project description:Analyses of gene expression profiling in sinonasal sarcoma (SNS) harboring PAX3-MAML3 fusion gene or PAX3 rearrangement and other types of tumors without having such fusion or rearrangement. The results provide important information for further investigations of the PAX3-MAML3 fusion functions in SNS. Total RNA was obtained from FFPE tissues of 41 tumors including 8 SNS (6 with PAX3-MAML3 fusion and 2 with PAX3 rearrangement only) and 33 cases from other 10 different types of tumors. Gene expression profiling of fusion group including 8 SNA vs.non-fusion group including 33 control tumors were analyszed.

2014-04-17 | E-GEOD-52252 | biostudies-arrayexpress

Fusion discovery in breast cancer cell line

Project description:SnowShoes-FTD, a fusion transcript discovery tool, was used to identify fusions in breast cancer cell lines using the RNA-Seq data Total RNA extracted from cell lines. The total RNA was used for construction of RNA-Seq library for RNA-Sequencing.

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DNA methylation-based classification of sinonasal tumors [test set]

Project description:The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, whereas tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid cystic carcinomas are highly aggressive. Our findings have the potential to dramatically improve the diagnostic classification of sinonasal tumors and will fundamentally change the current perception of SNUCs.

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CC10 gene deletion: Effect on gene expression in the sinonasal mucosa

Project description:Comparative analysis of gene expression in murine sinonasal mucosa in wild-type and CC10-knockout littermates with allergic eosinophilic chronic rhinosinusitis. The data provide a comprehensive overview of genes expressed in the mouse sinonasal mucosa and show that the expression of several known and unidentified genes is modified by disruption of the CC10 gene. Total RNA isolated from sinonasal mucosae of 6- to 8-week-old mice, C57BL/6 strain, was used for this comparison. Three groups: wild-type control, wild-type with allergic eosinophilic chronic rhinosinusitis, and CC10-knockout with allergic eosinophilic chronic rhinosinusitis.

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DNA methylation-based classification of sinonasal tumors [reference set]

Project description:The histopathological diagnosis of sinonasal tumors is challenging as it encompasses a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we show that a machine learning algorithm based on DNA methylation is able to classify sinonasal tumors with clinical-grade reliability. We further show that tumors with SNUC morphology are not as undifferentiated as their current terminology suggests, but can be assigned to four molecular classes defined by distinct epigenic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SWI/SNF chromatin remodeling complex mutations and overall favorable clinical course, highly aggressive tumors that are driven by SMARCB1-deficiency and tumors that represent previously misclassified adenoid-cystic carcinomas. Our findings have the potential to dramatically improve the diagnostic of challenging sinonasal tumors and could fundamentally change the current perception of SNUCs.

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Human sinonasal cavity

Project description:Human sinonasal cavity Targeted loci environmental

| PRJNA407725 | ENA

CC10 gene deletion: Effect on gene expression in the sinonasal mucosa

2010-12-01 | GSE20969 | GEO

Gene expression profiling in sinonasal adenocarcinoma.

Project description:Transcriptional profiling of ethmoïd tumors samples comparing normal samples from the controlateral sinus. RNA were extracted from biopsies. Sinonasal adenocarcinomas are uncommon tumors developping in ethmoid sinus after wood dust exposure. Although the etiology of these tumors is well defined very little is known regarding the molecular basis of these tumors. In an attempt to identify genes involved in this disease we proceed to a gene expression profiling using cancer-dedicated microarrays, on matched samples of nine sinonasal adenocarcinomas and non-tumoral sinusal tissue. Among the genes with significant differential expression we selected: LGALS4, ACS5, CLU, BAX, PDGFRa, SRI and CCT5 for further exploration by quantitative real-time reverse-transcription-PCR on a larger set of tumors and confirmed the microarray data. Protein expression alterations were shown for LGALS4, ACS5, and CLU by immunohistochemistry. Our results suggest that two genes might be involved in the pathogenesis of these tumors: LGALS4 highly up-regulated, particularly in the most differentiated tumors, and CLU, whose expression was lost. After further evaluation these genes could be used as markers for a better characterization of these tumors and will potentially help to an earlier detection of cancer in woodworkers, who have high risk of developing sinonasal adenocarcinomas.

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