LHX2 drives neuroendocrine transformation in TP53/RB1-deficient prostate cancer
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 14 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Topic
- Prostate cancerThis series is part of our curated briefing on it.
- Samples
- 14 samples: 14 samples, each with a distinct title — no replicated groupsGroups 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.
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE328076_RAW.tar (it can run to tens of gigabytes).
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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1453808 and SRA study SRP692037. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 14 sample titles: 14 distinct titles with little repetition. 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.
- GSM9671916 PC3_Vec_1，ATAC
- GSM9671917 PC3_Vec_2，ATAC
- GSM9671918 PC3_201_1，ATAC
- GSM9671919 PC3_201_2，ATAC
- GSM9671920 PC3_203_1，ATAC
- GSM9671921 PC3_203_2，ATAC
- GSM9671922 PC_3_Vec，ATAC
- GSM9671923 PC_3_shLHX2，ATAC
- GSM9671924 PC-3-shRB1-1，ATAC
- GSM9671925 PC-3-shRB1-2，ATAC
- GSM9671926 LHX2-201-1F,CUT&TAG
- GSM9671927 LHX2-201-2F,CUT&TAG
- GSM9671928 LHX2-203-1F,CUT&TAG
- GSM9671929 LHX2-203-2,CUT&TAG
- GSE115501 RNA sequencing on circulating tumor cells from prostate cancer patients 136 samples same disease briefing · shares prostate
- GSE222467 The RNA binding proteins LARP4A and LARP4B promote tumour growth and metastasis in prostate cancer and osteosarcoma 12 samples same disease briefing · shares prostate
- GSE300947 A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors 6 samples same disease briefing · shares prostate
- GSE120181 Human prostate cancer cell line, 22Rv1: Control vs. luteolin treatment 2 samples same disease briefing · shares prostate
- GSE71008 Plasma extracellular RNA profiles in healthy and cancer patients 192 samples same disease briefing
- GSE242541 ONECUT2 is a druggable driver of luminal to basal breast cancer plasticity 12 samples same disease briefing
- GSE302864 DNMT3B drives neuroendocrine lineage plasticity and aggressive progression in prostate cancer 12 samples shares neuroendocrine, prostate, drives
- GSE291033 TP53 missense-specific transcriptional plasticity drives resistance against cell cycle inhibitors in pancreatic cancer [RNA-Seq] 12 samples shares tp53, drives
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.