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Transduction signaling signature of Wilms tumor revealed by parallel analysis of kidney differentiation

GSE25965 Homo sapiens (human) Expression microarray 78 samples Submitted 2011/12/07 Platform GPL9692
At a glance

Expression microarray · human · 78 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Topic
Wilms tumourThis series is part of our curated briefing on it.
Samples
78 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Precise regulation of transduction signaling pathways genes is crucial for correct differentiation of kidney cells and perturbation may lead to tumor onset. Wilms tumors (WT), or nephroblastoma, originates from the metanephric blastema cells, which were unable to complete the differentiation, resulting in a triphasic tumor composed by distinct cell types, blastemal, epithelial and stromal, where the former harbor molecular characteristics similar to cells of the earliest stages of kidney development.
Read the full summary ↓
In this study, to identify key early events involved in the disruption of correct cell signaling during kidney differentiation that can drive WT, we developed a cDNA platform containing genes from signaling transduction pathways. By using bioinformatics tools, we defined high conserved regions between human and mouse orthologous genes and assessed the gene modulation in blastemal cells captured from WT and differentiated kidneys (DK) in human and from four temporal stages of kidney differentiation in mouse. We found 18 genes, whose transcriptional level of the earliest phases of blastemal cell differentiation was recapitulated in WT. PAX2, FZD10, SHPK, WNT5B, FZD2, CRABP2, FRZB, GRK7, TESK1, HDGF and IGF2 were up- and MAPK9, PIK3CA, FRAT2, ITPR3, CDH6, HIPK1 and TIMP3 were down-regulated in WT respectively. Hierarchical clustering based on the expression of this gene set grouped DK from both species, human and mouse, and discriminated them from fetal kidney and WT in human, and the earliest kidney stages in mouse, validating the model proposed by this study and reveling a transduction signaling signature of WT. High robustness of this data was detected since expression level was tested by quantitative RT-PCR in the initial and independent sample set, with 75 and 56% of agreement. Agreement of 62% was also observed in protein level assessing blastemal component of an independent group of 137 WT. Protein expression of CRABP2, IGF2, GRK7, TESK1, HDGF, WNT5B, FZD2 and TIMP3 was also characterized in human fetal kidneys revealing interesting aspects of kidney differentiation. This study identified key genes modulated during kidney differentiation which may play a determinant role for WT onset. As far as we know, FZD10, FRZB, HDGF, MAPK9, FRAT2, SHPK, WNT5B, GRK7, TESK1, HDGF, PIK3CA, ITPR3, HIPK1 and TIMP3 were not previously associated to WT.
This dataset
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE25965_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA135435. Searching any of these in the dataset finder brings you back here.

Samples in this study

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