ArticlePloS one2012
Bioinformatic analysis of patient-derived ASPS gene expressions and ASPL-TFE3 fusion transcript levels identify potential therapeutic targets.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- ASPSCR1-TFE3 reprograms transcription by organizing enhancer loops around hexameric VCP/p97.Nature communications · 2024Article
- ASPSCR1::TFE3 orchestrates the angiogenic program of alveolar soft part sarcoma.Nature communications · 2023Article
- Facts and Hopes in Immunotherapy of Soft-Tissue Sarcomas.Clinical cancer research : an official journal of the American Association for Cancer Research · 2020Review
- Exploring the Histogenesis and Diagnostic Strategy Using Immunoassay and RT-PCR in Alveolar Soft Part Sarcoma.Pathology oncology research : POR · 2018Article
- Alveolar soft-part sarcoma of the prostate: a case report and review of the literature.International journal of clinical and experimental pathology · 2018Article
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- Biologic Activity of Autologous, Granulocyte-Macrophage Colony-Stimulating Factor Secreting Alveolar Soft-Part Sarcoma and Clear Cell Sarcoma Vaccines.Clinical cancer research : an official journal of the American Association for Cancer Research · 2015Article
- Calcium and P-glycoprotein independent synergism between schweinfurthins and verapamil.Cancer biology & therapy · 2015Article
- Modeling alveolar soft part sarcomagenesis in the mouse: a role for lactate in the tumor microenvironment.Cancer cell · 2014Article
- Metastatic Alveolar Soft Part Sarcoma Responsive to Pazopanib after Progression through Sunitinib and Bevacizumab: Two Cases.Case reports in oncologyArticle
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene expression data, collected from ASPS tumors of seven different patients and from one immortalized ASPS cell line (ASPS-1), was analyzed jointly with patient ASPL-TFE3 (t(X;17)(p11;q25)) fusion transcript data to identify disease-specific pathways and their component genes. Data analysis of the pooled patient and ASPS-1 gene expression data, using conventional clustering methods, revealed a relatively small set of pathways and genes characterizing the biology of ASPS. These results could be largely recapitulated using only the gene expression data collected from patient tumor samples. The concordance between expression measures derived from ASPS-1 and both pooled and individual patient tumor data provided a rationale for extending the analysis to include patient ASPL-TFE3 fusion transcript data. A novel linear model was exploited to link gene expressions to fusion transcript data and used to identify a small set of ASPS-specific pathways and their gene expression. Cellular pathways that appear aberrantly regulated in response to the t(X;17)(p11;q25) translocation include the cell cycle and cell adhesion. The identification of pathways and gene subsets characteristic of ASPS support current therapeutic strategies that target the FLT1 and MET, while also proposing additional targeting of genes found in pathways involved in the cell cycle (CHK1), cell adhesion (ARHGD1A), cell division (CDC6), control of meiosis (RAD51L3) and mitosis (BIRC5), and chemokine-related protein tyrosine kinase activity (CCL4).
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