T cells in B16 tumor model with ACT and checkpoint blockade - scRNA-seq, CITE-seq and TCRab [i35]
Single-cell RNA-seq · mouse · 15 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 15 samples: 15 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.
- Paper
- Proteostasis sustains T cell differentiation potential and tumor-infiltrating lymphocyte functionCell · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE311344_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1368984 and SRA study SRP648784. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 15 sample titles: 15 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.
- GSM9323825 I35H1_spleen_FBC
- GSM9323826 I35H1_spleen_GEX
- GSM9323827 I35H1_spleen_TCR
- GSM9323828 I35H2_B16_ACT_FBC
- GSM9323829 I35H2_B16_ACT_GEX
- GSM9323830 I35H2_B16_ACT_TCR
- GSM9323831 I35H3_LNinguinal_B16_ACT_FBC
- GSM9323832 I35H3_LNinguinal_B16_ACT_GEX
- GSM9323833 I35H3_LNinguinal_B16_ACT_TCR
- GSM9323834 I35H4_B16_ACTaPD1a41BB_FBC
- GSM9323835 I35H4_B16_ACTaPD1a41BB_GEX
- GSM9323836 I35H4_B16_ACTaPD1a41BB_TCR
- GSM9323837 I35H5_LNinguinal_B16_ACTaPD1a41BB_FBC
- GSM9323838 I35H5_LNinguinal_B16_ACTaPD1a41BB_GEX
- GSM9323839 I35H5_LNinguinal_B16_ACTaPD1a41BB_TCR
- GSE300288 Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq] 31 samples shares checkpoint, scrna-seq, blockade
- GSE270050 Expansion of Tumor-Infiltrating CD8+ T Cell Clonotypes Occurs in the Spleen in Response to Immune Checkpoint Blockade 29 samples shares checkpoint, blockade
- GSE254919 Extracellular vesicles from obese visceral adipose promote pancreatic cancer development and resistance to immune checkpoint blockade therapy [ATAC-seq] 12 samples shares checkpoint, blockade
- GSE334497 TROP2/claudin program mediates immune exclusion to impede checkpoint blockade in breast cancer 10 samples shares checkpoint, blockade
- GSE322551 Engineered bacteria as exogenous organelle mimics restore PTEN and p53 tumor suppressor functions for cancer therapy 30 samples shares act
- GSE286348 Macrophages foster anti-tumor immunity by ZEB1-dependent cytotoxic T cell chemoattraction 18 samples shares act
- GSE342477 Characterization of an Antagonistic Antibody reactive to human and mouse TNFR2 with Anti-tumor Capacity 9 samples shares act
- GSE307051 Active aldehydes accelerate CD8+ T cell exhaustion by metabolic alteration in the tumor microenvironment 3 samples shares act
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.