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Mechanism study of RBX1 promoting renal clear cell carcinoma invasion, immune suppression, and sunitinib resistance

GSE304059 Homo sapiens (human) RNA-seq (gene expression) 614 samples Submitted 2026/02/28 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 614 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
Kidney cancerThis series is part of our curated briefing on it.
Samples
614 samples: 614 samples, each with a distinct title — no replicated groupsGroups 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)
Clear cell renal cell carcinoma (ccRCC) often exhibits drug resistance, highlight_x0002_ing the need to identify novel therapeutic targets. RING box protein 1 (RBX1), an E3 ubiquitin ligase associated with tumor progression, has an unclear role in ccRCC. This study investigated the clinical significance, molecular mech_x0002_anisms, and role of RBX1 in treatment resistance through multi-omics and functional analyses.
Read the full summary ↓
Analysis of The Cancer Genome Atlas (TCGA) data revealed that RBX1 is overexpressed in ccRCC and is associated with advanced dis_x0002_ease stages and poor prognosis. Functional enrichment studies linked RBX1 to processes such as cytoskeletal remodeling,extracellular matrix deposition, and lipid metabolism disorders.Additionally, tumors with high RBX1 expression exhibit an immunosuppressive microenvironment characterized by increased reg_x0002_ulatory T cells (Tregs) and elevated expression of immune checkpoint markers (LAG3/Galectin-9). In vitro experiments confirmed that RBX1 promotes ccRCC proliferation, migration, and invasion while conferring resistance to the standard targeted therapy drug sunitinib. Our findings suggest that RBX1 may serve as a key driver of ccRCC invasiveness and immune suppression. These discoveries indicate that RBX1 has the potential to become a prognostic biomarker and a target for precision therapy in advanced ccRCC.
This dataset
Open GSE304059 in finder → Find more human RNA-seq datasets → Kidney 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 GSE304059_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 PRJNA1298846. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
614 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from the first 400 of 614 sample titles: 400 distinct titles with little repetition. 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

+ 574 more — browse all 614 samples with per-sample file links →

More Kidney cancer datasets

Search all human RNA-seq datasets in GEO →

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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.