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A Promising Natural G6PD Inhibitor for Potential Therapeutic Strategies in DLBCL

GSE254385 Homo sapiens (human) RNA-seq (gene expression) 2 samples Submitted 2024/07/31 Platform GPL16791
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
Diffuse large B-cell lymphomaThis 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)
Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin lymphoma, has a high degree of clinical and biological heterogeneity. Although most patients can be cured with R-CHOP immunochemotherapy,30-40% of patients have progression or recurrence after treatment. Therefore, there is an urgent need to find new treatments to improve the survival rate of this group of patients.
Read the full summary ↓
Natural small molecule drugs have unique advantages as anticancer agents due to their low toxicity and multiple targets. This project aims to explore potentially effective natural compounds as new therapeutic strategies for DLBCL. We found that Cinobufagin is a potentially effective therapeutic agent for DLBCL. Glucose 6 phosphate dehydrogenase (G6PD), a risk factor for poor prognosis in DLBCL, was a direct target of Cinobufagin. By inhibiting the enzyme activity of G6PD, Cinobufagin could inhibit DNA synthesis and the production of reductive NADPH, thereby inducing ROS accumulation and apoptosis of DLBCL cells. Our findings provide new strategies for the treatment of DLBCL.
This dataset
Open GSE254385 in finder → Find more human RNA-seq datasets → Diffuse large B-cell lymphoma 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 GSE254385_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 PRJNA1070285 and SRA study SRP486272. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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