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RNA-seq transcriptomic profiling reveals renoprotective mechanism of novel Psidium meroterpenoid derivatives (d)-G8 and (d)-G4 against cisplatin-induced acute kidney injury in human HK2 tubular epithelial cells

GSE339247 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/07/25 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 6 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)

Cisplatin is a first-line chemotherapeutic agent for multiple solid tumors, but its severe nephrotoxicity severely limits clinical application and frequently induces acute kidney injury (AKI), which may further progress to chronic kidney disease. Psidium meroterpenoids from guava possess multiple pharmacological activities, and our previous study synthesized a series of novel Psidium meroterpenoid analogs with renoprotective potential.

Read the full summary ↓

In this work, we systematically investigated the molecular mechanism of two lead chiral compounds (d)-G8 and (d)-G4 in alleviating cisplatin-induced renal injury via transcriptome sequencing. Human renal proximal tubular HK2 cells were used as the in vitro model, with 6 experimental groups (3 biological replicates per group, total 18 samples): untreated control group, 15 μM cisplatin injury model group, cisplatin + 2.5 μM (d)-G8 group, cisplatin + 10 μM (d)-G8 group, cisplatin + 2.5 μM (d)-G4 group, and cisplatin + 10 μM (d)-G4 group. Total RNA was extracted from all samples for paired-end RNA-seq on Illumina NovaSeq 6000 platform. Differential expressed genes (DEGs) were screened, followed by principal component analysis (PCA), Venn diagram analysis, heatmap clustering, GO and KEGG functional enrichment, as well as gene set enrichment analysis (GSEA). Transcriptomic results demonstrated that both (d)-G8 and (d)-G4 exerted significant renoprotective effects by upregulating copper efflux transporters ATP7A/ATP7B, activating AMPK-mediated autophagy pathway, improving mitochondrial homeostasis, and suppressing multiple inflammatory signaling cascades, with (d)-G8 showing more potent efficacy than (d)-G4. This RNA-seq dataset provides comprehensive transcriptional evidence for the anti-AKI activity of the two meroterpenoid derivatives, and identifies key gene targets and signaling pathways for the development of novel nephroprotective agents.

This dataset

Open GSE339247 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 GSE339247_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 PRJNA1498012 and SRA study SRP719656. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in triplicate

Control ×3 Model ×3 G4-2-5 ×3 G4-10 ×3 G8-2-5 ×3 G8-10 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 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

GSM9891803 Control-1 Control
GSM9891804 Control-2 Control
GSM9891805 Control-3 Control
GSM9891806 Model-1 Model
GSM9891807 Model-2 Model
GSM9891808 Model-3 Model
GSM9891809 G4-2-5-1 G4-2-5
GSM9891810 G4-2-5-2 G4-2-5
GSM9891811 G4-2-5-3 G4-2-5
GSM9891812 G4-10-1 G4-10
GSM9891813 G4-10-2 G4-10
GSM9891814 G4-10-3 G4-10
GSM9891815 G8-2-5-1 G8-2-5
GSM9891816 G8-2-5-2 G8-2-5
GSM9891817 G8-2-5-3 G8-2-5
GSM9891818 G8-10-1 G8-10
GSM9891819 G8-10-2 G8-10
GSM9891820 G8-10-3 G8-10

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