Project description:We report the application of ribosome profiling using high-throughput sequencing and total mRNA used for normalisation upon depletion of ELP3 protein in B16 melanoma cells.
Project description:This SuperSeries is composed of the following subset Series: GSE11580: Time course RA-treatment of B16 mouse melanoma cells GSE11584: Melan-a mouse melanocytes vs. B16 mouse melanoma cells Keywords: SuperSeries Refer to individual Series
Project description:The aim of this study was to gain insight into the ribosome occupancy on different genes and codons in Zpr1-depleted cells vs. WT Zpr1 cells
Project description:Gene expression signature of Treg cells in B16 melanoma was measured and compared to B16-infiltrating CD4+ Tconv cells and CD8+ T cells as well as splenic Treg cells, CD4+ Tconv cells and CD8+ T cells.
Project description:Tumor resistance to anti-cancer drugs is a major huddle in chemotherapy. To identify cancer genes that contribute to chemoresistance, B16 mouse melanoma cells were used as a model. We used microarrays to decipher the specific gene regulation in doxorubicine treated B16 mouse melanoma cells. Keywords: Time course
Project description:This laboratory focuses on selectin mediated recruitment during adoptive immunotherapy for metastatic cancer. This study seeks to determine changes in the expression levels of Fucosyltransferases, Selectins, and cytokines in normal and inflamed mouse skin, melanoma tumor tissue of different sizes, and tumor cells grown in culture. Since the ability to treat the tumor effectively is directly related to the size of the tumor, differences in glyco-expression patterns may be of interest. In this study, five groups were hybridized and analyzed using the GLYCOv2 array. Each group was analyzed in triplicate. The groups were: Normal mouse skin, normal mouse skin inflamed by treatment with Oxazolone, B16-OVA melanoma tissue from 6 day tumors, B16-OVA melanoma tissue from 11 day tumors, and B16-OVA grown in cell culture.
Project description:We wanted to correlate the protein cargo of secreted exosomes with gene expression pattern in B16-F1 and B16-F1R2. For that purpose, we performed RNA sequencing analysis of B16-F1, B16-F1R2 and B16-F1R2L (Fig.1E). We identified >3000 genes significantly up-regulated and >1000 significantly down-regulated in B16-F1R2 model compared to B16-F1, using a false discovery rate (FDR) of 0.05.