← BioTransfer GEO Dataset Finder
GEO series

Transcriptome profiling associated with CARD11 overexpression in Colorectal Cancer implicates a potential role for Tumour Immune Microenvironment and Cancer pathways modulation via NF-κB

GSE266390 Homo sapiens (human) RNA-seq (gene expression) 35 samples Submitted 2024/07/31 Platform GPL24014
At a glance

RNA-seq (gene expression) · human · 35 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
Colorectal cancerThis series is part of our curated briefing on it.
Samples
35 samples: 10 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
Transcriptome Profiling Associated with CARD11 Overexpression in Colorectal Cancer Implicates a Potential Role for Tumor Immune Microenvironment and Cancer Pathways Modulation via NF-κBInternational journal of molecular sciences · 2024
Summary (written by the submitters)
The immune system plays a critical role in inflammation by initiating responses to infection or tissue damage. NF-κB pathway plays a key role in inflammation and innate immunity, as well as other cellular activities. Furthermore, dysregulation of this well-choreographed pathway has been observed in many diseases, including cancer. CARD11 is a key molecule in the BCL-10, MALT1 (CBM) complex which is involved in transducing the signal downstream of the NF-κB pathway.
Read the full summary ↓
This study aims to understand how overexpression of CARD11 adversely affects the prognosis in colorectal cancer (CRC) as it progresses towards aggressive form of the disease and the role that CARD11 plays in modulating the immune response across the different stages of CRC. To identify some of the cellular pathways activated as a result of CARD11, whole tran-scriptomics analysis was carried comparing the transcriptomic profile of CARD11-overexpressed HCT-116 and HT-29 CRC cell lines with empty vector-transfected cell lines as well as comparing adenoma and carcinoma CRC patients with CARD11- and CARD11+ expression. The whole tran-scriptomics and bioinformatics analysis results strongly suggested that CARD11 appears to play a key role in CRC progression. Absolute Gene Set Enrichment Analysis (absGSEA) on HCT-116 transcriptomics data showed that CARD11 overexpression promotes cell growth, and tissue re-modeling as well as enhancing the cell’s immune response. Some of the underlying genes in-volved in such processes through co-expression with CARD11 include EP300, KDM5A, HIF1A, NFKBIZ, and DUSP1. Results for HT-29 showed that CARD11 overexpression induces chemotaxis and ECM organization pathways through co-expression of IL1RN, MDK, and SPP1 as well as var-ious chemokines including CXCL1, CXCL3 and CCL22 which were shown to contribute to the more invasive stage of CRC. For patients, the adenoma patients include genes related to tumour immune microenvironment such as IL6ST, genes related to collagen family as well as other genes related to transition to CRC such as GLI3 and PIEZO2. While carcinoma patients show dramatic increase in the expression of MAPK8IP2 in CARD11+ carcinoma patients in addition to other genes related to cancer processes including EMB, EPHB6, and CPEB4. Taken together, the results show that CARD11 overexpression contributes to the progression of CRC through modu-lation of various tumour immune microenvironment pathways and activation of cancer path-ways possibly via the dysregulation of NF-κB. To our knowledge, this is probably the first study that investigates the role of CARD11 in CRC and the genes and pathways associated with CARD11 overexpression may provide insights into the early diagnostic and possible therapeutic targets for CRC.
Published in
Transcriptome Profiling Associated with CARD11 Overexpression in Colorectal Cancer Implicates a Potential Role for Tumor Immune Microenvironment and Cancer Pathways Modulation via NF-κB
Alhosani F, Ilce BY, Alhamidi RS et al. · International journal of molecular sciences 2024 · PMID 39408697 · doi:10.3390/ijms251910367
This dataset
Open GSE266390 in finder → Find more human RNA-seq datasets → Colorectal 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 GSE266390_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 PRJNA1106895 and SRA study SRP505241. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39408697) ↗
Study design
10 conditions, mostly in triplicate
AD_CARD11_POS ×6 CA_1_CARD11_NEG ×5 AD_CARD11_NEG ×4 CA2_2_CARD11_POS ×3 CA2_2_CARD11_NEG ×3 HT_C ×3 HT_T ×3 HCT_C ×3 +2 more

Supports a between-group comparison across 35 samples.

How we read this: 10 replicated groups read from 35 sample titles; they account for 35 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
More Colorectal 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.