Effect of depletion of Setd1a on gene expression in mouse Undifferentiated Pleomorphic Sarcoma (UPS)
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ABSTRACT:
PROVIDER: PRJNA859693 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR20281081.fastq.gz | Fastqsanger.gz | |||
| SRR20281082.fastq.gz | Fastqsanger.gz | |||
| SRR20281083.fastq.gz | Fastqsanger.gz | |||
| SRR20281084.fastq.gz | Fastqsanger.gz | |||
| SRR20281085.fastq.gz | Fastqsanger.gz |
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Project description:Analysis of undifferentiated pleomorphic sarcoma/malignant fibrous histiocytoma-like tumors from LSL-KrasG12D, p53Fl/Fl mouse model of soft tissue sarcoma.
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Project description:Undifferentiated pleomorphic sarcoma (UPS) and related tumors are the most common type of soft tissue sarcoma. However, this spectrum of tumors has different etiologies with varying rates of metastasis and survival. Two dermal-based neoplasms in this class of pleomorphic sarcomas, atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS), are challenging to differentiate at initial biopsy but vary significantly in prognosis. We performed single-cell transcriptomics on five AFX and PDS biopsy specimens as well as both single-cell and spatial transcriptomics on one PDS excision specimen to better characterize these tumors. The top differential genes between AFX and PDS were predictive of overall survival in 17 other cancers included in the Human Protein Atlas. Of these genes, COL6A3 and BGN predicted overall survival and metastasis-free survival in independent cohorts of 46 and 38 UPS tumors, respectively. COL6A3 was most predictive of overall survival in UPS patients and outperformed an established sarcoma prognostic gene panel at predicting metastasis in UPS.
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Project description:As Setd1a is a methyltransferase targeting H3K4, we performed H3K4Me3 ChIP in control and Setd1a KO cell to observe the effects of Setd1a on H3K4Me3. Chromatin immunoprecipitation DNA-sequencing (ChIP-seq) for H3K4Me in control mouse UPS and Setd1a KO mouse UPS cells .
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Project description:Undifferentiated pleomorphic sarcoma (UPS) and related tumors are the most common type of soft tissue sarcoma. However, this spectrum of tumors has different etiologies with varying rates of metastasis and survival. Two dermal-based neoplasms in this class of pleomorphic sarcomas, atypical fibroxanthoma (AFX) and pleomorphic dermal sarcoma (PDS), are challenging to differentiate at initial biopsy but vary significantly in prognosis. We performed single-cell transcriptomics on five AFX and PDS biopsy specimens as well as both single-cell and spatial transcriptomics on one PDS excision specimen to better characterize these tumors. The top differential genes between AFX and PDS were predictive of overall survival in 17 other cancers included in the Human Protein Atlas. Of these genes, COL6A3 and BGN predicted overall survival and metastasis-free survival in independent cohorts of 46 and 38 UPS tumors, respectively. COL6A3 was most predictive of overall survival in UPS patients and outperformed an established sarcoma prognostic gene panel at predicting metastasis in UPS.
2024-11-08 | GSE281096 | GEO
Project description:To investigate the Setd1a function in the regulation of lung metastasis formation, we established mouse UPS cell lines in which each target gene has been knocked down by shRNA. We then performed gene expression profiling analysis using data obtained from RNA-seq
2024-05-24 | GSE208363 | GEO
Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS. Genomic DNA was extracted from a total of 49 samples, 31 Undifferentiated pleomorphic Sarcomas and 18 Leiomyosarcomas. The DNA was labeled using Bioprime array CGH labeling kit (Invitrogen). Promega pooled male DNA was used as reference. Labeled DNA was hybridized onto BAC arrays containing ~32 000 BAC clones printed in singlets. BAC arrays were produced at the SWEGENE DNA Microarray Facility at Lund University.
2010-10-08 | E-GEOD-13775 | biostudies-arrayexpress
Project description:Analysis of undifferentiated pleomorphic sarcoma/malignant fibrous histiocytoma like tumors from BrafCa, p53Fl/Fl mouse model of soft tissue sarcoma
2014-12-01 | GSE20049 | GEO
Project description:Analysis of undifferentiated pleomorphic sarcoma/malignant fibrous histiocytoma-like tumors from LSL-KrasG12D, p53Fl/Fl mouse model of soft tissue sarcoma. Murine soft tissue sarcomas (n = 17) were compared to normal muscle (n = 4). Tumors were isolated surgically from soft tissue sarcomas generated by conditional Kras and p53 alleles. Tumors were induced using an adenovirus expressing Cre recombinase. Normal muscle samples were isolated from mice of the same genotype without tumor induction.
2010-03-03 | E-GEOD-16779 | biostudies-arrayexpress
Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS.
2009-03-24 | GSE13775 | GEO
Project description:Background: Undifferentiated pleomorphic sarcoma (UPS), used to be called malignant fibrous histiocytoma (MFH), is a malignant soft tissue tumor of uncertain origin, and is characterized by morphology. UPS often share similar morphological characters with other sarcomas, especially Leiomyosarcoma. Leiomyosarcoma (LMS) is another malignant soft tissue sarcoma with complex genomic abnormalities, origin from smooth muscle. As a result, development of gene signature and/or biomarkers distinguishing UPS and LMS will definitely help the pathologist to precisely diagnose those patients. However, in the past, UPS was reported to be indistinguishable with LMS by genomic profiles. Methods and Results: In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. Overall, UPS was undistinguished with LMS by 3SEQ data, however, when we stratified LMS into three subtypes, UPS was shown to share similar expression pattern with Subtype II LMS, but had distinct molecular expression patterns with Subtype I and Subtype III LMS. Additional Immunohistochemistry staining by using LMS Subtype I and Subtype II markers validated that UPSs were positive for Subtype II marker ARL4C, but negative for Subtype I marker LMOD1. Furthermore, CD4 was shown to be significantly more highly expressed in UPS than LMS in both mRNA and protein levels. Conclusion: This study first reported that UPS shared similar gene expression pattern with subtype II LMS and UPS recapitulated the expression profiles of subtype II LMS. In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. In order to explore the molecular differences between UPS and LMS, We analyzed the expression data by SAMseq to identify the genes which were significantly differently expressed between UPS and LMS, between UPS and each LMS subtype.
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