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Targeting of HIF2-driven cachexia in kidney cancer

GSE289579 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/09/19 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × OS-RC-2, Veh 72 h, vs 3 × OS-RC-2, PT2399 72 h, vs 3 × OS-RC-2, sgCtrl, vs 3 × OS-RC-2, sgHIF2a,Groups 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.
Paper
Targeting of HIF2-driven cachexia in kidney cancerNature medicine · 2026
Summary (written by the submitters)
Kidney cancer frequently causes paraneoplastic syndromes, including hypercalcemia and cachexia, but the underlying mechanisms are incompletely understood. The most common form of kidney cancer, clear cell renal cell carcinoma (ccRCC), is frequently caused by loss of the pVHL tumor suppressor protein and the resulting upregulation of the HIF2 transcription factor.
Read the full summary ↓
We show that PTHLH, which resides on a ccRCC amplicon on chromosome 12p, is a direct HIF2 transcriptional target in ccRCC. Further, we show that the increased PTHLH expression is both necessary and sufficient for the induction of hypercalcemia and cachexia in preclinical orthotopic cell line tumor models. Consistent with these observations, two different allosteric HIF2 inhibitors, belzutifan and NKT2152, rapidly ameliorated hypercalcemia and cachexia in patients with ccRCC, including in some who did not exhibit objective tumor shrinkage. Our findings support prospective clinical studies to determine whether HIF2 inhibitors can be leveraged not only for tumor control, but also for the treatment of cancer-associated cachexia in renal cell carcinoma.
Published in
Targeting of HIF2-driven cachexia in kidney cancer
Abu-Remaileh M, Stransky LA, Bhalerao N et al. · Nature medicine 2026 · PMID 41315757 · doi:10.1038/s41591-025-04054-2
This dataset
Open GSE289579 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 GSE289579_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 PRJNA1223465 and SRA study SRP563848. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41315757) ↗
Study design
3 × OS-RC-2, Veh 72 h, vs 3 × OS-RC-2, PT2399 72 h, vs 3 × OS-RC-2, sgCtrl, vs 3 × OS-RC-2, sgHIF2a,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
More Kidney cancer datasets

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