RNA seq of breast cancer cells treated with different concentration gradients of Thapsigargin (TG), Tunicamycin (TM), and FCCP.
RNA-seq (gene expression) · human · 44 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
- 44 samples: 22 conditions, mostly in duplicateGroups 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.
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 GSE281194_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: 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 PRJNA1182711 and SRA study SRP543650. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 44 samples.
How we read this: 22 replicated groups read from 44 sample titles; they account for 44 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.
- GSM8613001 FCCP_1.25_1 FCCP_1.25
- GSM8613002 FCCP_1.25_2 FCCP_1.25
- GSM8613003 FCCP_2.5_1 FCCP_2.5
- GSM8613004 FCCP_2.5_2 FCCP_2.5
- GSM8613005 FCCP_5_1 FCCP_5
- GSM8613006 FCCP_5_2 FCCP_5
- GSM8613007 FCCP_DMSO_1 FCCP_DMSO
- GSM8613008 FCCP_DMSO_2 FCCP_DMSO
- GSM8613009 FCCP_MG132_1 FCCP_MG132
- GSM8613010 FCCP_MG132_2 FCCP_MG132
- GSM8613011 FCCP_3_MA_1 FCCP_3_MA
- GSM8613012 FCCP_3_MA_2 FCCP_3_MA
- GSM8613013 TG_0_5_1 TG_0_5
- GSM8613014 TG_0_5_2 TG_0_5
- GSM8613015 TG_1_1 TG_1
- GSM8613016 TG_1_2 TG_1
- GSM8613017 TG_2_1 TG_2
- GSM8613018 TG_2_2 TG_2
- GSM8613019 TG_DMSO_1 TG_DMSO
- GSM8613020 TG_DMSO_2 TG_DMSO
- GSM8613021 TG_MG132_1 TG_MG132
- GSM8613022 TG_MG132_2 TG_MG132
- GSM8613023 TG_ISRIB_1 TG_ISRIB
- GSM8613024 TG_ISRIB_2 TG_ISRIB
- GSM8613025 TG_melatonin_1 TG_melatonin
- GSM8613026 TG_melatonin_2 TG_melatonin
- GSM8613027 TG_4u8C_1 TG_4u8C
- GSM8613028 TG_4u8C_2 TG_4u8C
- GSM8613029 TM_0_5_1 TM_0_5
- GSM8613030 TM_0_5_2 TM_0_5
- GSM8613031 TM_1_1 TM_1
- GSM8613032 TM_1_2 TM_1
- GSM8613033 TM_2_1 TM_2
- GSM8613034 TM_2_2 TM_2
- GSM8613035 TM_DMSO_1 TM_DMSO
- GSM8613036 TM_DMSO_2 TM_DMSO
- GSM8613037 TM_MG132_1 TM_MG132
- GSM8613038 TM_MG132_2 TM_MG132
- GSM8613039 TM_ISRIB_1 TM_ISRIB
- GSM8613040 TM_ISRIB_2 TM_ISRIB
+ 4 more — browse all 44 samples with per-sample file links →
- GSE104193 Hypoxia-mediated translational activation of ITGB3 in breast cancer cells enhances TGF-β signalling and malignant features in vitro and in vivo 32 samples same disease briefing · shares breast
- GSE104675 Role for the Transcriptional Activator ZRF1 in Breast Cancer Progression and Endocrine Resistance 6 samples same disease briefing · shares breast
- GSE10886 A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes 226 samples same disease briefing · shares breast
- GSE11121 The humoral immune system has a key prognostic impact in node-negative breast cancer 200 samples same disease briefing · shares breast
- GSE10885 An integromic analysis reveals that metaplastic carcinomas are distinct from basal-like tumors. 244 samples same disease briefing
- GSE281511 RNA seq of liver cancer cells treated with different concentration gradients of Thapsigargin (TG), Tunicamycin (TM), and FCCP 44 samples shares fccp, concentration, thapsigargin, tunicamycin, different, gradients, treated
- GSE232322 Differential gene expression in breast cancer cell lines treated with a Baicalein at 100 uM concentration 12 samples shares concentration, different, treated, breast
- GSE249009 RNA sequencing analysis of isoginkgetin and thapsigargin treated HCT116 and HCT116 ATF4 deficient cells 48 samples shares thapsigargin, treated
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.