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Phosphorylation of SIK1 by Akt1 activates STAT3 signal pathway in breast cancer cell.

GSE223214 Homo sapiens (human) RNA-seq (gene expression) 2 samples Submitted 2024/07/01 Platform GPL24676
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
Breast 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)
As a member of AMPK-related kinases, salt-inducible kinase 1 (SIK1) regulates energy response-related physiopathological processes, such as gluconeogenesis and lipid metabolism. More recently, instead of AMPK, SIK1 has been strikingly defined as a major player for tumor suppressor liver kinase 1 (LKB1) deficient NSCLC. However, the exact roles and upstream regulators of SIK1 in breast cancer are not well defined.We found that Akt1 can directly phosphorylate SIK1 and inhibit the kinase activity of SIK1, promoting the progress of breast cancer.
Read the full summary ↓
To investigate the mechanism of Akt1 phosphorylated SIK1 promoting the progression of breast cancer, we constructed a stable expression of SIK1 WT and S435D in BT549, and then performed gene expression profiling analysis.
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 GSE223214_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 PRJNA925229 and SRA study SRP418197. Searching any of these in the dataset finder brings you back here.

Samples in this study

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