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ALKBH5 cooperated with LINC00659 promote gastric cancer progression by JAK1 mRNA m6A-YTHDF2-dependent modification [2-m6A]

GSE182542 Homo sapiens (human) RNA-seq (gene expression) 2 samples Submitted 2024/08/17 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 2 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
Gastric cancerThis series is part of our curated briefing on it.
Samples
2 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)
N6-methyladenosine (m6A) modification is the most prevalent RNA epigenetic regulation in eukaryotic cells. Recent studies focused on the association between m6A and non-coding RNAs. The demethylase ALKBH5 acts as critical oncogenes or tumor suppressors through multiple mechanisms in various cancers. Here, we find that ALKBH5 is highly expressed in GC tissues and is associated with poor prognosis.
Read the full summary ↓
ALKBH5 promoted the proliferation and metastasis both in vitro and in vivo. ALKBH5 was recruited by LINC00659, which removed m6A modifications of JAK1, leading to the upregulated expression of JAK1.Since ALKBH5 and LINC00659 have oncogenic role in gastric cancer (GC) progression with poor prognosis, ALKBH5-LINC00659/m6A/JAK1 axis can be new biological mechanisms behind GC development and future therapeutic opportunities.
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 GSE182542_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 PRJNA756695 and SRA study SRP333557. Searching any of these in the dataset finder brings you back here.

Samples in this study

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