Project description:Transcriptional profiling was conducted on RNA from 16 prostatic cancer cell lines to identify genes whose expression level correlate with sensitivity of an anti-tumor agent (dasatinib). Keywords: comparison of sensitive group versus resistant group of cell lines to agent
Project description:Transcriptional profiling was conducted on RNA from 16 prostatic cancer cell lines to identify genes whose expression level correlate with sensitivity of an anti-tumor agent Experiment Overall Design: Baseline gene expression profiling was performed using 16 prostatic cancer cell lines to identify expression signatures highly correlated with in vitro sensitivity to a particular agent
Project description:Solid tumors are complex organs comprising neoplastic cells and stroma, yet cancer cell lines remain widely used to study tumor biology, biomarkers and experimental therapy. Here, we performed a fully integrative analysis of global proteomic data comparing human colorectal cancer (CRC) cell lines to primary tumors and normal tissues. We found a significant, systematic difference between cell line and tumor proteomes, with a major contribution from tumor stroma proteomes. Nevertheless, cell lines overall mirrored the proteomic differences observed between tumors and normal tissues, in particular for genetic information processing and metabolic pathways, indicating that cell lines provide a system for the study of the intrinsic molecular programs in cancer cells. Intersection of cell line data with tumor data provided insights into tumor cell specific proteome alterations driven by genomic alterations. Our integration of cell line proteogenomic data with drug sensitivity data highlights the potential of proteomic data in predicting therapeutic response. We identified representative cell lines for the proteomic subtypes of primary tumors, and linked these to drug sensitivity data to identify subtype-specific drug candidates.
Project description:The goal of the study was to examine the transcriptional profile of pancreatic cancer cell lines and assess if the molecular subtypes observed in tumor samples were represented in existing cell line models. Cell line models allow us to investigate if the molecular subtype observed in tumor have unique sensitivity profiles to anticancer drugs. 29 pancreatic cancer cell lines were compared to a mixed reference pool of 30 pancreatic cancer cell lines to identify cell line specific gene expression.
