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HIF-2-dependent Regulation of PTHrP and Paraneoplastic Hypercalcemia in Aggressive Clear Cell Renal Cell Carcinoma [RNA-seq]

GSE308449 Homo sapiens (human) RNA-seq (gene expression) 52 samples Submitted 2025/10/07 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 52 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
52 samples: 21 conditions, mostly in duplicateGroups 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
HIF-2-Dependent Regulation of PTHrP and Paraneoplastic Hypercalcemia in Aggressive Clear-Cell Renal Cell CarcinomaCancer discovery · 2025
Summary (written by the submitters)
Hypercalcemia (HC) in renal cell carcinoma (RCC) patients is associated with reduced survival. HC often involves PTHrP. PTHrP is induced by hypoxia, but whether HIF-2 plays a role in HC is unknown. Here we show that HC is reproduced by transplanting patient tumors (tumorgrafts, TG) in mice resulting in functional deterioration, weight loss, calcium deposition and organ damage.
Read the full summary ↓
Treatment with PT2399, a specific HIF-2 inhibitor, rapidly normalized calcium levels, downregulated PTHrP and reduced HIF-2 binding to the PTHLH promoter. Interestingly, while the PTHLH locus was generally more accessible in TG(HC), PT2399 did not grossly affect chromatin accessibility, which was consistent with genome-wide studies where promoter accessibility was only reduced in a minority of PT2399-downregulated genes. As in TGs, paraneoplastic HC in humans was associated with clear cell histology and sarcomatoid/rhabdoid differentiation. Interestingly, HC (and PTHrP) was swiftly corrected by the related PT2977/belzutifan drug in a prospective patient with sarcomatoid ccRCC. Our data supports the evaluation of HIF-2 antagonists for ccRCC patients with humoral hypercalcemia of malignancy, which may serve as a predictive biomarker of response (along with PTHrP reduction).
Published in
HIF-2-Dependent Regulation of PTHrP and Paraneoplastic Hypercalcemia in Aggressive Clear-Cell Renal Cell Carcinoma
Mal A, Xie B, Gray Z et al. · Cancer discovery 2025 · PMID 41065553 · doi:10.1158/2159-8290.CD-25-0638
This dataset
Open GSE308449 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 GSE308449_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 PRJNA1330614 and SRA study SRP622484. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41065553) ↗
Study design
21 conditions, mostly in duplicate
XP1059c7_P ×2 XP1059c7_V ×2 XP1087c7_P ×2 XP1087c7_V ×2 XP1139c8_V ×2 XP1152c8_P ×2 XP1152c8_V ×2 XP1169c13_P ×2 +23 more

Supports a between-group comparison across 42 samples.

How we read this: 21 replicated groups read from 52 sample titles; they account for 42 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

+ 12 more — browse all 52 samples with per-sample file links →

More Kidney cancer datasets

Search all human RNA-seq datasets in GEO →

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