mRNA transcriptome sequencing of tumor cells, TRMs, MDMs, Monocytes and CD8+ T cells from tumor lungs of KrasLSL-G12D/+Lkb1fl/fl (KL), KrasLSL-G12D/+Lkb1fl/flGpx4m/m(KLG4) after Ad-cre injection and tamoxifen treatment
RNA-seq (gene expression) · mouse · 17 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
- Mus musculus (mouse)
- Samples
- 17 samples: 8 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
- Tumor cell-specific loss of GPX4 reprograms triacylglycerol metabolism to escape ferroptosis and impair antitumor immunity in non-small cell lung cancerProtein & cell · 2026
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 GSE281154_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: 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 PRJNA1182392 and SRA study SRP543353. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 8 replicated groups read from 17 sample titles; they account for 16 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.
- GSM8611865 Tumor_cell_KL_1 Tumor_cell_KL
- GSM8611866 Tumor_cell_KL_2 Tumor_cell_KL
- GSM8611867 Tumor_cell_KLG4_1 Tumor_cell_KLG4
- GSM8611868 Tumor_cell_KLG4_2 Tumor_cell_KLG4
- GSM8611869 TRMs_KL_1 TRMs_KL
- GSM8611870 TRMs_KL_2 TRMs_KL
- GSM8611871 TRMs_KLG4_1 TRMs_KLG4
- GSM8611872 TRMs_KLG4_2 TRMs_KLG4
- GSM8611873 MDMs_KL_1 MDMs_KL
- GSM8611874 MDMs_KL_2 MDMs_KL
- GSM8611875 MDMs_KLG4_1 MDMs_KLG4
- GSM8611876 MDMs_KLG4_2 MDMs_KLG4
- GSM8611877 CD8+_T_KL_1 CD8+_T_KL
- GSM8611878 CD8+_T_KL_2 CD8+_T_KL
- GSM8611879 CD8+_T_KLG4_1 CD8+_T_KLG4
- GSM8611880 CD8+_T_KLG4_2 CD8+_T_KLG4
- GSM8611881 Monocytes_KL_1
- GSE296763 Mitochondrial respiration is necessary for CD8 T cell proliferation and cell fate 99 samples shares cd8
- GSE334845 Discovery of Tcf7 regulators with clonally-resolved CRISPR screens identifies Trim28 as a mediator of CD8 T cell differentiation in tumors [RNA-Seq] 86 samples shares cd8
- GSE302682 Sleeping Beauty mutagenesis identifies BACH2 and other regulators promoting CD8+ T cell persistence and effector function under tumor-associated chronic antigen stimulation - RNAseq 66 samples shares cd8
- GSE337601 XCR1+ and CD11b+ migratory dendritic cells cooperate for the crosspriming of intratumoral CD8+ T cells with a tissue-resident memory phenotype [RNA-Seq] 36 samples shares cd8
- GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 samples shares cd8
- GSE338265 Smad4 and Eomes converge on a shared transcriptional program associated with inflammatory CD8 T-cell differentiation 31 samples shares cd8
- GSE248272 Therapeutically targeting perivascular macrophage effector function improves CD8+ T-cell infiltration and response to chemotherapeutic drugs in cancer 30 samples shares cd8
- GSE331107 The transcription factor AFF3 is necessary to maintain metabolic quiescence in naïve CD8 T cells and prevent premature immune aging 30 samples shares cd8
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.