Transcriptomics profiling of some commonly used cell lines at the base-line culture condition
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ABSTRACT:
PROVIDER: PRJNA565366 | ENA |
REPOSITORIES: ENA
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Project description:Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels24, the transcriptome which represents the active program of a cell remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines. The raw sequence files were submitted to the European Genome-Phenome Archive (EGA) under accession EGAS00001000610 ( https://www.ebi.ac.uk/ega/datasets/EGAD00001000725 ). Processed, human non-identifiable data, together with a README file describing the data (140625_Klijn_README.txt) are available here in E-MTAB-2706.additional.*.zip files: https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2706/files .
2014-11-25 | E-MTAB-2706 | biostudies-arrayexpress
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Project description:Iodoacetamide is by far the most commonly used agent for alkylation of cysteine during sample preparation for proteomics. An alternative, 2-chloroacetamide, has been recently suggested to reduce the alkylation of residues other than cysteine, such as the N-terminus, Asp, Glu, Lys, Ser, Thr and Tyr. Here, we show that although 2-chloroacetamide reduces the level of off-target alkylation, it exhibits a range of adverse effects. The most significant of these was methionine oxidation, which increases to a maximum of 40% of all Met containing peptides compared to 2-5% with iodoacetamide. Increases were also observed for mono and dioxidised tryptophan. No additional differences between the alkylating reagents were observed for a range of other post-translational modifications and digestion parameters. The adverse impact of 2-chloroacetamide on methionine oxidation suggest it is not the ideal alkylating reagent for proteomics.
2017-08-16 | PXD007071 | Pride
Project description:Humans and other commonly used model organisms are resistant to cycloheximide-mediated biases in ribosome profiling experiments
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Project description:Background: Despite advances in therapeutics, outcomes for hepatocellular carcinoma (HCC) remain poor and there is an urgent need for efficacious systemic therapy. Unfortunately, drugs that are successful in preclinical studies often fail in the clinical setting, and we hypothesize that this is due to functional differences between primary tumors and commonly used preclinical models. In this study, we attempt to answer this question by comparing tumor morphology and gene expression profiles between primary tumors, xenografts and HCC cell lines. Methods: Hep G2 cell lines and tumor cells from patient tumor explants were subcutaneously (ectopically) injected into the flank and orthotopically into liver parenchyma of Mus Musculus SCID mice. The mice were euthanized after two weeks. RNA was extracted from the tumors, and gene expression profiling was performed using the Gene Chip Human Genome U133 Plus 2.0. Principal component analyses (PCA) and construction of dendrograms were conducted using Partek genomics suite. Results: PCA showed that the commonly used HepG2 cell line model and its xenograft counterparts were vastly different from all fresh, primary tumors. Expression profiles of primary tumors were also significantly divergent from their counterpart patient-derived xenograft (PDX) models, regardless of the site of implantation. Xenografts from the same primary tumors were more likely to cluster together regardless of site of implantation, although heat maps showed distinct differences in gene expression profiles between orthotopic and ectopic models. Conclusions: The data presented here challenges the utility of routinely used preclinical models. Models using HepG2 were vastly different from primary tumors and PDXs, suggesting that this is not clinically representative. Surprisingly, site of implantation (orthotopic versus ectopic) resulted in limited impact on gene expression profiles, and in both scenarios xenografts differed significantly from the original primary tumors, challenging the long-held notion that orthotopic PDX model is the gold standard preclinical model for HCC.
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Project description:Metabolic labeling with stable isotopes is a prominent technique for comparative quantitative proteomics and stable isotope labeling with amino acids in cell culture (SILAC) is the most commonly used approach. SILAC is, however, traditionally limited to simple tissue culture regiments and only rarely employed in the context of complex culturing conditions as those required for human embryonic stem cells (hESCs). Classic hESC culture is based on the use of mouse embryonic fibroblasts (MEFs) as a feeder layer and as a result possible xenogeneic contamination, contribution of unlabeled amino acids by the feeders, inter-laboratory variability of MEF preparation and the overall complexity of the culture system are all of concern in conjunction with SILAC. We demonstrate a feeder-free SILAC culture system based on a customised version of a commonly used chemically defined hESC medium developed by Ludwig et al. (2006) and commercially available as mTeSR1 . This medium, together with adjustments to the culturing protocol, facilitates reproducible labeling which is easily scalable to the protein amounts required by proteomic work flows. It greatly enhances the usability of quantitative proteomics as a tool for the study of mechanisms underlying hESCs differentiation and self-renewal. Mass spectrometric data was analysed using the MaxQuant suite of algorithms [version 1.3.0.5]. The data was searched against the Homo sapiens UniProtKB protein sequence database (downloaded on 10/24/2012, 68,108 entries including canonical and isoform sequence data). Enzyme specificity was set to trypsin, allowing for cleavage N-terminal to proline and between aspartic acid and proline. Carbamidomethylcysteine was set as a fixed modification, and oxidized methionine and N-acetylation were set as variable modifications. Labeled Arg and Lys were used as peptide modifications for quantitation. MaxQuant’s requantitation option was not used where incorporation efficiency and arginine to proline conversion were analyzed. The maximum mass deviation allowed was set at 20 ppm for the initial search, and 6 ppm for the main search for monoisotopic precursor ions; the mass error tolerance was set at 20 ppm for MS/MS peaks. A maximum of two missed cleavages and three labeled amino acids (arginine and lysine) were allowed. The required false discovery rates were set to 1% at the peptide and protein level (the protein level filter was disabled for incorporation efficiency and arginine to proline conversion testing), and the minimum required peptide length was set to 6 amino acids. Statistical analysis and plotting were performed using the R Statistical Programming Environment. The analyses performed are documented in an R package provided in the proteomeXchange repository and based on a publicly available collection of tools (RCFPD, URL: http://sourceforge.net/projects/rcfpd/).
2013-06-17 | PXD000151 | Pride