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Synergistic Ultrasound-Activable Artificial Enzyme and Precision Gene Therapy to Suppress Redox Homeostasis and Malignant Phenotypes for Controllably Combacting Hepatocellular Carcinoma

GSE273283 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/07/26 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 9 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
Mus musculus (mouse)
Samples
9 samples: 3 × Hepa1-6 cells NC vs 3 × Hepa1-6 cells P-Por-Os vs 3 × Hepa1-6 cells P-Por-Os+USGroups 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)
Hepatocellular carcinoma (HCC) remains one of the most lethal malignant tumors. Multi-modal therapeutics for HCC have attracted increasing attention. However, designing a nanotherapeutic platform with effective chem-/sono- double-modal HCC therapies is still challenging. Here, we first designed a novel porphyrin-based nanomase (Porzyme) P-Por-Os with nano-sonosensitivity for HCC therapy.
Read the full summary ↓
Endowed with a large hollow spherical structure of poly porphyrins, which efficiently improved the electron transport capacity of polyporphyrins and exposed the active site of superficial metal atoms, P-Por-Os effectively catalyzed the production of ROS from H2O2. This so-called Chemodynamic Therapy (CDT) was further significantly reinforced by Sonodynamic Therapy (SDT) and achieving this therapeutic ultrasound-controlled anti-tumor effects in HCC. More importantly, we developed an metallothionein-2A (MT2A)-targeted enhancement to reverse the resistance to ROS and suppress cancer progression, which could theoretically be termed Precision Gene Therapy (PGT). Overall, the new therapeutic schedule with the triple-combination of P-Por-Os-based CDT, SDT, and PGT achieved remarkable anti-HCC effectiveness. This study reported an innovative artificial enzyme P-Por-Os with high tumor-killing activity and proposed a new triple-combination with CDT, SDT and PGT treatment strategy for HCC.
This dataset
Open GSE273283 in finder → Find more mouse RNA-seq datasets →
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 GSE273283_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 PRJNA1141173 and SRA study SRP522691. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Hepa1-6 cells NC vs 3 × Hepa1-6 cells P-Por-Os vs 3 × Hepa1-6 cells P-Por-Os+US

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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
Datasets on a similar topic

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