Metabolism-dependent secondary effect of anti-MAPK cancer therapy on DNA repair
RNA-seq (gene expression) · human · 24 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)
- Samples
- 24 samples: 8 conditions, mostly in triplicateGroups 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
- Metabolism-dependent secondary effect of anti-MAPK cancer therapy on DNA repairNAR cancer · 2024
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 GSE232711_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 PRJNA973614 and SRA study SRP438929. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 24 samples.
How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.
- GSM7350160 A375_MAPKi_R1 A375_MAPKi
- GSM7350161 A375_MAPKi_R2 A375_MAPKi
- GSM7350162 A375_MAPKi_R3 A375_MAPKi
- GSM7350163 A375_DMSO_R1 A375_DMSO
- GSM7350164 A375_DMSO_R2 A375_DMSO
- GSM7350165 A375_DMSO_R3 A375_DMSO
- GSM7350166 A375_CTRL_R1 A375_CTRL
- GSM7350167 A375_CTRL_R2 A375_CTRL
- GSM7350168 A375_CTRL_R3 A375_CTRL
- GSM7350169 A375_-Q_R1 A375_-Q
- GSM7350170 A375_-Q_R2 A375_-Q
- GSM7350171 A375_-Q_R3 A375_-Q
- GSM7372169 A375_MAPKi-0D_R1 A375_MAPKi-0D
- GSM7372170 A375_MAPKi-0D_R2 A375_MAPKi-0D
- GSM7372171 A375_MAPKi-0D_R3 A375_MAPKi-0D
- GSM7372172 A375_MAPKi-2D_R1 A375_MAPKi-2D
- GSM7372173 A375_MAPKi-2D_R2 A375_MAPKi-2D
- GSM7372174 A375_MAPKi-2D_R3 A375_MAPKi-2D
- GSM7372175 A375_MAPKi-9D_R1 A375_MAPKi-9D
- GSM7372176 A375_MAPKi-9D_R2 A375_MAPKi-9D
- GSM7372177 A375_MAPKi-9D_R3 A375_MAPKi-9D
- GSM7372178 A375_DMSO-0D_R1 A375_DMSO-0D
- GSM7372179 A375_DMSO-0D_R2 A375_DMSO-0D
- GSM7372180 A375_DMSO-0D_R3 A375_DMSO-0D
- GSE190564 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - whole tissue scRNA-Seq 62 samples shares therapy, repair
- GSE189185 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis. 117 samples shares therapy, repair
- GSE189184 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - Spatial Transcriptomics 16 samples shares therapy, repair
- GSE271689 Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer 586 samples shares therapy
- GSE222556 Neoadjuvant PARPi or Chemotherapy in Ovarian Cancer Informs Targeting Effector Treg Cells for Homologous-Recombination-Deficient Tumors [10x scRNA-seq] 67 samples shares therapy
- GSE315928 Differential T cell clonal dynamics underlie outcomes to frontline chemoimmunotherapy in advanced gastric cancer [paired scRNA/TCR-seq] 94 samples shares therapy
- GSE254249 Remodeling of T and endothelial cells during total neoadjuvant therapy in rectal cancer 92 samples shares therapy
- GSE211434 Diverse immune suppressing cancer communications with myeloid cells prevent T cell activation and recruitment and provide resistance to cell cycle inhibitor therapy 81 samples shares therapy
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.