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mTORC1 activation induces B7-H3–dependent metabolic reprogramming in renal cell carcinoma (RCC)

GSE307301 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/07/07 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 6 × Kidney, TSC2 KO vs 3 × Kidney WT vs 3 × Kidney, TSC2 B7-H3 dKOGroups 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)
Renal cell carcinoma (RCC) affects over 435,000 people worldwide each year and remains a significant cause of cancer mortality. Aberrant activation of pathways such as mTORC1 is frequently observed in RCC, yet the mechanisms by which mTORC1 contributes to tumor development remain poorly understood. The lack of suitable animal models has limited progress in uncovering these mechanisms and advancing targeted treatments.
Read the full summary ↓
Here, we performed single-cell transcriptomic, proteomic, and metabolomic profiling of kidneys from mice with embryonic Tsc2 deletion at E17.5, which revealed a distinct tumor cell population characterized by intercalated cell signatures, co-expression of Foxi1 and Rhcg, and hyperactivated mTORC1. These lesions closely resemble human chromophobe renal cell carcinoma (ChRCC), a subtype of RCC. The tumors show marked upregulation of the immune checkpoint molecule B7-H3. Mechanistically, the transcription factor NRF1 is elevated in Tsc2-deficient lesions and drives B7-H3 expression in tumor cells. In human specimens, B7-H3 is broadly expressed in both classical and sarcomatoid ChRCC and correlates with hallmark markers FOXI1, MUC2, and HEPACAM2. Strikingly, B7-H3 deletion in mice suppresses Tsc2 loss–driven cystic and tumor formation, restores amino acid metabolism, and attenuates aminoacyl-tRNA biosynthesis and proteasome activity. Collectively, these findings identify B7-H3 as a functional driver of Tsc2-mediated ChRCC and a promising therapeutic target in TSC-associated renal tumors.
This dataset
Open GSE307301 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 GSE307301_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1315170 and SRA study SRP617538. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × Kidney, TSC2 KO vs 3 × Kidney WT vs 3 × Kidney, TSC2 B7-H3 dKO

Supports a between-group comparison across 12 samples.

How we read this: 3 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
Datasets on a similar topic

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