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Transcriptome Analysis Reveals Potential Protective Effects and Biomarkers of Pien Tze Huang on CCl4-induced Liver Cancer (circRNA)

GSE268335 Mus musculus (mouse) Non-coding RNA profiling 18 samples Submitted 2024/05/26 Platform GPL21103
At a glance

Non-coding RNA profiling · mouse · 18 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Mus musculus (mouse)
Samples
18 samples: 6 × circRNA AC vs 6 × circRNA AT vs 6 × circRNA AXGroups 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)
Pien Tze Huang (PZH) is a traditional Chinese medicine which was widely utilized in Asia for hepatic diseases. We construct two groups liver cancer mice model using CCl4, one group using PZH treatment and another group didn?t treatment. We found that the liver functional indices including ALB, ALT and AST were significantly increased in non-PZH treatment group.
Read the full summary ↓
HE staining showed that inflammation was emerged surrounding the hepatic vein in the non-PZH treatment group, Masson staining revealed that there are blue collagenous fibre surrounding hepatic vein in the non-PZH treatment group, this result indicated that PZH cured the hepatic inflammation and cancer. We performed the mRNA,LncRNA,ciecRNA and miRNA sequencing aim to explore the drug target using PZH treatment on transcriptome level. 478 protein coding transcripts and 68 lncRNA transcripts were differentially expressed. Our research provided potential transcriptional therapeutic target for the clinical treatment using PZH.
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 GSE268335_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.

Also filed as BioProject PRJNA1116235 and SRA study SRP509823. Searching any of these in the dataset finder brings you back here.

Study design
6 × circRNA AC vs 6 × circRNA AT vs 6 × circRNA AX

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 18 sample titles; they account for 18 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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