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CDC7 inhibition impairs neuroendocrine transformation in lung and prostate tumors through MYC degradation

GSE252569 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2024/05/01 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 68 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
Prostate cancerThis series is part of our curated briefing on it.
Samples
68 samples: 16 conditions, mostly with about 4 replicates eachGroups 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
CDC7 inhibition impairs neuroendocrine transformation in lung and prostate tumors through MYC degradationSignal transduction and targeted therapy · 2024
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
CDC7 inhibition impairs neuroendocrine transformation in lung and prostate tumors through MYC degradation
Quintanal-Villalonga A, Kawasaki K, Redin E et al. · Signal transduction and targeted therapy 2024 · PMID 39054323 · doi:10.1038/s41392-024-01908-y
This dataset
Open GSE252569 in finder → Find more human RNA-seq datasets → Prostate 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 GSE252569_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 PRJNA1061199 and SRA study SRP481731. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39054323) ↗
Study design
16 conditions, mostly with about 4 replicates each
H146-Comb ×4 H146-Ctrl ×4 H146-Sim ×4 Lx33-Cis ×4 Lx33-Comb ×4 Lx33-Ctrl ×4 Lx33-Sim ×4 Lx761c-Ctrl ×4 +22 more

Supports a between-group comparison across 54 samples.

How we read this: 16 replicated groups read from 68 sample titles; they account for 54 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

+ 28 more — browse all 68 samples with per-sample file links →

More Prostate cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.