Induction of CDX2 as a differentiation therapy in colorectal cancers [cell lines]
RNA-seq (gene expression) · human · 12 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
- 12 samples: 12 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.
- Paper
- CANDiT: A machine learning framework for differentiation therapy in colorectal cancerCell reports. Medicine · 2025
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 GSE237624_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 PRJNA996063 and SRA study SRP456659. 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 12 sample titles: 12 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.
- GSM7634930 HCT116_DMSO_A1_S25
- GSM7634931 HCT116_DMSO_B1_S27
- GSM7634932 HCT116_DMSO_C1_S26
- GSM7634933 HCT116_PF_20uL_D1_S30
- GSM7634934 HCT116_PF_20uL_E1_S29
- GSM7634935 HCT116_PF_20uL_F1_S28
- GSM7634936 SW480_DMSO_G1_S32
- GSM7634937 SW480_DMSO_H1_S33
- GSM7634938 SW480_DMSO_A2_S31
- GSM7634939 SW480_PF_20uL_B2_S36
- GSM7634940 SW480_PF_20uL_C2_S35
- GSM7634941 SW480_PF_20uL_D2_S34
- GSE262796 Gene expression changes associated with acquired resistance to anti-EGFR therapy (cetuximab) in colorectal cancer cells 18 samples shares colorectal, therapy
- GSE271689 Enhancing Immunotherapy Outcomes: Spatial Multi-Omics Predictive Models for Non-Small Cell Lung Cancer 586 samples shares therapy
- GSE235090 Pre-existing skin-resident CD8 and γδ T cell circuits mediate immune response in Merkel cell carcinoma and Predict immunotherapy efficacy [scRNA_tissue] 192 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
- GSE286827 4-1BB+ Tregs and inhibitory progenitor exhausted T cells confer resistance to anti-PD-L1 and anti-CTLA-4 combination therapy 87 samples shares therapy
- GSE285963 Transcriptome profile of hepatocellular carcinoma in patients with atezolizumab plus bevacizumab therapy. 84 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.