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accession-icon SRP043080
Transcriptomic profiling of peripheral blood mononuclear cells from healthy individuals
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

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 post-transcriptional 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. This study is complemented by GSE61410: transcriptomic profiling of bone marrow cells from healthy individuals. Overall design: Peripheral blood mononuclear cells (PBMCs) were isolated from four healthy individuals, following an ex vivo incubation of variable length at either room temperature or on ice. RNA transcriptomes were measured using the Illumina HiSeq.

Publication Title

Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE1159
Expression profiles of acute myeloid leukemia patient samples
  • organism-icon Homo sapiens
  • sample-icon 291 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Expression profiles of acute myeloid leukemia patient samples.

Publication Title

Identification of genes with abnormal expression changes in acute myeloid leukemia.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE9476
Abnormal Expression Changes in AML
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Acute myeloid leukemia (AML) is one of the most common and deadly forms of hematopoietic malignancies. We hypothesized that microarray studies could identify previously unrecognized expression changes that only occur only in AML blasts. We were particularly interested in those genes with increased expression in AML, believing that these genes may be potential therapeutic targets.

Publication Title

Identification of genes with abnormal expression changes in acute myeloid leukemia.

Sample Metadata Fields

Sex, Disease

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accession-icon GSE67088
Vemurafenib resistance selects for highly malignant brain and lung-metastasizing melanoma cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

V600E being the most common mutation in BRAF, leads to constitutive activation of the MAPK signaling pathway. The majority of V600E BRAF positive melanoma patients treated with the BRAF inhibitor vemurafenib showed initial good clinical responses but relapsed due to acquired resistance to the drug. The aim of the present study was to identify possible biomarkers associated with the emergence of drug resistant melanoma cells. To this end we analyzed the differential gene expression of vemurafenib-sensitive and vemurafenib resistant brain and lung metastasizing melanoma cells.

Publication Title

Vemurafenib resistance selects for highly malignant brain and lung-metastasizing melanoma cells.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE23958
Gene expression and H3K9ac genome-wide maps following HDAC inhibition in mouse ES cells
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Pluripotency-related, valproic acid (VPA)-induced genome-wide histone H3 lysine 9 (H3K9) acetylation patterns in embryonic stem cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

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accession-icon GSE23956
Gene expression profiles of E14 ESCs treated with low levels of HDAC inhibitors for 16 hrs
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Gene expression profiles of E14 embryonic stem cells (ESCs) before and after treatment with low levels of the histone deacetylase (HDAC) inhibitors valproic acid (VPA) and sodium butyrate (NaBu).

Publication Title

Pluripotency-related, valproic acid (VPA)-induced genome-wide histone H3 lysine 9 (H3K9) acetylation patterns in embryonic stem cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE23957
Gene expression profiles of E14 ESCs treated with low levels of the HDAC inhibitor VPA for 4 hrs
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Gene expression profiles of E14 embryonic stem cells (ESCs) before and after treatment with low levels of the histone deacetylase (HDAC) inhibitor valproic acid (VPA).

Publication Title

Pluripotency-related, valproic acid (VPA)-induced genome-wide histone H3 lysine 9 (H3K9) acetylation patterns in embryonic stem cells.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE45553
Transcriptional profiling of ovarian cancer spheroids reveals genes and related biological pathways associated with cisplatin resistance
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Characterization of differential gene expression due to cisplatin resistance in human ovarian cancer spheroids by microarray analysis.

Publication Title

Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE44175
Expression data from mouse embyonic stem cell, neural progenitor and neuron
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The effect of HMGN1 protein on gene expression of mouse ESC, NP and Neurons were investigated by comparing the transcriptome between Hmgn1+/+ and Hmgn1 -/- cells.

Publication Title

HMGN1 modulates nucleosome occupancy and DNase I hypersensitivity at the CpG island promoters of embryonic stem cells.

Sample Metadata Fields

Specimen part

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accession-icon SRP063980
Gene expression analysis following JQ1 treatments in colon cancer lines
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNAseq is performed (50bp single end reads) on SW480, HT-29, HCT-15, HCT-116, COLO 205, and COLO 320 cell lines after DMSO or JQ1 treatment Overall design: Examination of transcriptomic changes after JQ1 treatment

Publication Title

CCAT1 is an enhancer-templated RNA that predicts BET sensitivity in colorectal cancer.

Sample Metadata Fields

No sample metadata fields

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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