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Next Generation sequencing Facilitates Quantitative Analysis of α-KG and control Transcriptomes in MKN74 and AGS cell lines

GSE285448 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/01/03 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × MKN74 cell lines, α-KG treated，24h, vs 3 × MKN74 cell lines, control，24h, vs 3 × AGS cell lines, α-KG treated，24h, vs 3 × AGS cell lines, control，24h,Groups are read from the sample names, not from the paper. Check the list below.
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.
Paper
Integrative machine learning reveals the biological function and prognostic significance of α-ketoglutarate in gastric cancerOncology letters · 2025
Summary (written by the submitters)
In recent years, gastric cancer (GC) has garnered significant attention due to its poor response to treatment, unfavorable prognosis, and the lack of reliable biomarkers for predicting disease progression and therapeutic outcomes. α-Ketoglutarate (α-KG), a critical metabolite involved in cellular energy metabolism and epigenetic regulation during tumor development, has emerged as a potential prognostic biomarker for GC.
Read the full summary ↓
To explore this potential, we utilized publicly available datasets from the TCGA and GEO databases to analyze α-KG-related genes and establish the α-KG Index (AKGI). By evaluating the predictive performance of the AKGI model, we confirmed its robust capability to predict survival outcomes in gastric cancer patients.By analyzing signaling pathways and biological functions correlated with AKGI, we elucidated the regulatory mechanisms and biological roles of α-KG in gastric cancer. These insights were validated through cellular experiments, where α-KG treatment was shown to significantly inhibit gastric cancer cell proliferation, migration, and invasion.Taken together, our data demonstrate AKGI offers a valuable framework for advancing our understanding of the role and mechanisms of α-KG in gastric cancer.
Published in
Integrative machine learning reveals the biological function and prognostic significance of α-ketoglutarate in gastric cancer
Liu F, Sun X, Zeng Y et al. · Oncology letters 2025 · PMID 40606305 · doi:10.3892/ol.2025.15138
This dataset
Open GSE285448 in finder → Find more human RNA-seq datasets → Gastric cancer landscape →
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.

Series matrix ↓
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 GSE285448_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1203647 and SRA study SRP554104. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40606305) ↗
Study design
3 × MKN74 cell lines, α-KG treated，24h, vs 3 × MKN74 cell lines, control，24h, vs 3 × AGS cell lines, α-KG treated，24h, vs 3 × AGS cell lines, control，24h,

Supports a case/control comparison: 6 samples read as cases, 6 as controls.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
More Gastric cancer datasets

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