Dataset Information

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

ABSTRACT: Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and posttranscriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways; up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms; and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T- and B-cell activation, and NF-?B signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors.

SUBMITTER: Dvinge H

PROVIDER: S-EPMC4250124 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Dvinge Heidi H Ries Rhonda E RE Ilagan Janine O JO Stirewalt Derek L DL Meshinchi Soheil S Bradley Robert K RK

Proceedings of the National Academy of Sciences of the United States of America 20141110 47

Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and posttranscriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways; up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms; and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other g ...[more]

PMID: 25385641

Similar Datasets

Project description:Proteomic sample preparation typically involves multi-step workflows that can potentially perturb the biological system under analysis. These datasets were used to demonstrate that the entire processing pipeline, from cell lysis through elution of purified peptides, can be performed in a single, enclosed volume. This in-StageTip sample preparation method largely eliminates contamination or losses and is extremely robust and scalable. Peptides can be eluted in several fractions or in one step for single-run proteomics. In one day of gradient time we obtained the largest proteomes for budding and fission yeast to date. Applying the in-StageTip method to quadruplicate measurements of a human cell line yielded copy number estimates for more than 9000 human proteins. Data Analysis: MS raw files were analyzed by MaxQuant software (version 1.3.10.12) and peak lists were searched either against the human Uniprot FASTA database version 2/25/2012 (81213 entries), against the S. cerevisiae Uniprot FASTA database version 2/25/2012 (6649 entries) or the SGD based S. cerevisiae Fasta database orf_trans.20100105 (5904 entries), or against the S. pombe Uniprot FASTA database version 4/2/2013 (5096 entries) or pompep FASTA database version 4/2/2013 (5031 entries) and a common contaminants database (247 entries) by Andromeda search engine with cysteine carbamidomethylation as a fixed modification and N-terminal acetylation and methionine oxidation as variable modifications. False discovery rate (FDR) was set to 0.01 for proteins and peptides (minimum length of 7 amino acids) and was determined by searching a reverse database. Enzyme specificity was set as C-terminal to Arg and Lys, and a maximum of 2 miscleavages allowed. Peptide identification was performed with an allowed initial precursor mass deviation up to 7 ppm and an allowed fragment mass deviation 20 ppm. Quantification of SILAC pairs was carried out by MaxQuant with standard settings and without the re-quantification option.

Project description:BackgroundOrgan-specific gene expression contains rich information about in vivo biological processes. This kind of information, previously gathered through microarray profiling, has been proven fruitful to the understanding of specific mutants, regulatory events, signaling, and development. With the advent of the next-generation sequencing (NGS) of RNAs, more quantitative and detailed information of gene expressions than previously available can now be collected for each organ or organ developmental stages. The combination of an object-oriented experimental design and an efficient treatment of the high volume information generated through a NGS platform may offer a powerful tool for inferring previously intractable developmental processes.ResultsWe collected transcriptomic data over a Solexa/Illumina platform on samples of Ipomoea leaf, sepal, and petals (at three developmental stages), and presented a method for analyzing transcriptomic variations within and between organs. We demonstrated that in vivo signals of transcriptomes can be retrieved de novo through the NGS techniques, proper data handling, bioinformatic tools, and the current understanding of molecular networks. We found that numbers of transcribed genes from both nuclear and chloroplast genomes decreased by the same order of leaf → sepal →petal. Petal resembled leaf in cell division patterns and abundance level of commonly expressed organelle genes. Its chloroplast transcripts constituted a subset of those in leaf. Moreover, reconstructions of multiple metabolic networks for each organ enabled inferences of substance flow, providing transcript evidence for the path of sucrose in leaf to anthocyanin synthesis in petal.ConclusionOur results attest that developmental transcriptomes are highly informative for exploring connections between morphological traits and the associated molecular networks. Significant hypotheses have been developed, including that the petal is a derived organ of leaf and that its color can be modified by fluctuations of substance flow within the associated metabolic networks among organs.

Dataset Information

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Publications

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets