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Gene expression of HCT-116 cell lines treated with EVs isolated using GlyExo-Capture method

GSE266634 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2024/05/12 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 7 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.
Summary (written by the submitters)
Extracellular vesicles (EVs) play a crucial role in facilitating intercellular communication. The microRNA profiles carried by EVs often exhibit variations between tumor patients and healthy individuals, making them promising biomarkers. These biomarkers are implicated in oncogenic processes and tumor metastasis upon uptake by recipient cells.
Read the full summary ↓
To investigate the impact of EV biomarkers on tumorigenesis, we exposed HCT-116 cell lines to EVs isolated from the serum of both tumor patients and healthy individuals. In comparison to cell lines treated with extracellular vesicles (EVs) from healthy individuals and blank controls, cell lines treated with EVs from HCC sources exhibit significant alterations in the expression of certain genes associated with pathways related to liver cancer. Our findings shedlight on the intricate interplay between EVs and tumor progression.
This dataset
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.

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 GSE266634_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1108006 and SRA study SRP505798. Searching any of these in the dataset finder brings you back here.

Study design
7 conditions, mostly in triplicate
HCC+ EVs treatment1 ×3 HCC+ EVs treatment2 ×3 HCC+ EVs treatment3 ×3 HCC- EVs treatment1 ×3 HCC- EVs treatment2 ×3 HCC- EVs treatment3 ×3 Blank control ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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
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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.