Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goal of this study is to compare the differentially expressed transcriptomes between CD133+ liver cancer stem cells versus CD133- non cancer stem cells by RNA-Seq profiling
Project description:To explore the role of small nucleolar RNA (snoRNA) on self-renewal of liver cancer stem cells (CSCs), we isolated liver CSCs (CD133+CD13+) and Non-CSCs (CD133-CD13-) from huamn liver tumor tissues.
Project description:CD133 is a marker of cancer stem cells. DAP5 is a is a translation initiation factor. The goal of the experiment was to characterize the proteomic differences between CD133+/- cells in the WT vs DAP5 depleted background. To this aim, 4 populations of human cells were FACS sorted: shNT_CD133-, shNT CD133+, shDAP5_ CD133-, shDAP5_CD133+. The collected cell pellets were subjected to LC-MS/MS analysis.
Project description:Hepatocellular carcinoma (HCC) represents the major subtype of liver cancer, characterized with a high rate of recurrence and heterogeneity. Liver cancer stem cells (CSCs) may account for a hierarchical organization of heterogeneous cancer cells. However, how liver CSCs sustain their self-renewal remains largely unknown. We used microarrays to discover the long non-coding RNAs (lncRNAs) expression underlying cell stem cell (CSC) and non cell stem cell (non-CSC) and identified distinct lncRNAs during this process. We sorted CD13+CD133+ and CD13-CD133- cells from Hep3B, Huh7, and PLC/PRF/5 HCC cell lines as liver CSCs and non-CSCs, then hybridized on Affymetrix microarrays. We sought to identify distinct lncRNAs in liver CSCs.
Project description:To understand the gene expression profiling of cancer stem cells of laryngeal squamous carcinoma, the total RNA of CD133+CD44+ laryngeal cancer stem cells (isolated from LSCC cell line TU-177, named TDP), CD133-CD44- cells (TDN) and parental TU-177 (unsorted TU-177 cells, named TPT) was extracted, followed by RNA sequencing. Differentially expression of lncRNA, mRNA, and circRNA was identified.
Project description:To understanding the miRNA expression profiling of cancer stem cells of laryngeal squamous carcinoma, the total RNA of CD133+CD44+ laryngeal cancer stem cells (isolated from LSCC cell line TU-177, named TDP), CD133-CD44- cells (TDN) and parental TU-177 (unsorted TU-177 cells, named TPT) was extracted, followed by miRNA sequencing. Differentially expressed miRNAs were identified.
Project description:Epithelial cell cultures derived from benign and HRPC tissue biopsies were expanded in culture for 2-3 weeks. CD133+ and CD133- cells were isolated using the miltenyi magnetic bead system after adherence to collagen. CD133+ and CD133- RNA was isolated and amplified using the RiboAmp HS kit and expression profiling performed using the CRUK WGA gene set. Keywords: Tumour vs normal comparison
Project description:To identify the gene expression signature associated with CD133, the well-known stem cell markers, three gastric cancer cell lines were obtained (KATO-III, SNU201 and SNU601). Cultured gastric cancer celllines were sorted into CD133+ and CD133- population by FACS sorting and microarray-based gene expression profiling was performed.
Project description:We identified a novel mechanism by which IL-6/STAT3 signaling up-regulates CD133 expression and promotes HCC progression. STAT3 activation upregulates the expression of CD133 during liver carcinogenesis. Targeting STAT3-mediated CD133 overexpression may represent a promising therapeutic strategy for HCC patients via eradicating the liver tumor microenviornment. To develop novel cancer therapeutic strategies by identification of signaling pathways or biomarkers and understanding their functions on cancer stem cell biology, we determined CD133 expression and STAT3 activation with tumor microenvironment in HCC patient tissues. The relation of STAT3 activation and CD133 expression was investigated by luciferase assay, shRNA knock-down, and chromatin immunoprecipitation assay in HCC cells, and in vivo xenograft model.
