Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreOvarian cancer is the deadliest gynecologic malignancy and the fifth leading cause for cancer related deaths among women in USA. Most patients have metastatic disease at the time of diagnosis and this causes the poor prognosis. Regulation of early steps of metastatic colonization - the rate limiting step of metastasis - is poorly understood. Using an organotypic 3D culture model of the omentum, we have mimicked the early stages of metastatic colonization in vitro. Using this, we have profiled the mRNA expression changes occurring in high grade serous ovarian cancer cell line Kuramochi, OVCAR4 and OVCAR8 when they are seeded on the 3D omentum culture compared to controls seeded on normal culture dishes. The ovarian cancer cells were separated by FACS after 2 days of culture and their RNA was isolated and RNA-seq was performed. Library preparation and next generation RNA sequencing was carried out at the Center for Genomics and Bioinformatics core facility, Indiana University, Bloomington. The library preparation was done using TruSeq Stranded mRNA HT Sample Prep kit (Illumina cat#RS-122-2103) according to the manufacturers protocol and 8-neucleotide barcodes were added for multiplexing. The barcoded libraries were cleaned by bead cut with AMPure XP beads (Beckman Coulter, cat#A63882), verified using Qubit3 fluorometer (ThermoFisher Scientific) and 2200 TapeStation bioanalyzer (Agilent Technologies), and then pooled. The pool was sequenced on NextSeq 500 (Illumina) with NextSeq75 High Output v2 kit (Illumina cat#FC-404-2005). SOURCE: Anirban,K,Mitra (anmitra@indiana.edu) - Myers Hall 200 Indiana University School of Medicine - Bloomington
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team