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Glucocorticoid promotes metastasis of colorectal cancer via co-regulation of glucocorticoid receptor and TET2 (RNA-Seq)

GSE256159 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2024/06/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
21 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Background Glucocorticoids (GCs), commonly used for anti-inflammatory and cancer treatments, have been linked to the promotion of cancer metastasis. Yet, the molecular mechanisms behind this potential remain poorly understood. Clarifying these mechanisms is crucial for a nuanced understanding and potential refinement of GC therapies in the context of cancer treatment.
Read the full summary ↓
Methods In HEK293T cells, co-immunoprecipitation (Co-IP) and chromatin immunoprecipation sequencing (ChIP-seq) were used with antibodies of GR and TET family proteins (TET1, TET2, TET3). Drup repositioning was performed through the LINCS database, using common genes of GR and TET2 in HEK293 and HCT116 cell lines with CRC differentially expressed genes (DEGs). Cell migration and invasion were tested in colorectal cancer (CRC) cell lines with varying glucocorticoid receptor (GR) expression, i.e., HCT116 and HT29 cell lines. Findings Dexamethasone (Dex) treatment resulted in a significant difference in cell migration rates in two CRC cell lines with disparate GR expression levels. Co-IP and ChIP-seq analyses substantiated the interaction between GR and TET family proteins in HEK293T cells. Belinostat, the selected compound, was successfully validated for its potential to counteract the effects of GC-induced inversion in CRC cells in vitro. Transcriptomic analyses of Belinostat-treated HCT116 cells revealed down-regulation of target genes associated with cancer metastasis.. Interpretation This study provides valuable insights into the molecular mechanisms underlying GC-induced metastasis, introducing newly repositioned compounds that could serve as potential adjuvant therapy to GC treatment. Furthermore, it opens avenues for exploring novel drug candidates for CRC treatment.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, 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, or the whole study as GSE256159_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1078347 and SRA study SRP490605. Searching any of these in the dataset finder brings you back here.

Samples in this study

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