CAR T Cells Secreting NGF-Neutralizing scFv Enhance Efficacy in Clear Cell Renal Cell Carcinoma by Relieving Immunosuppression through Immunosympathectomy [bulk RNA-seq]
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: 17 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
- CAR T cells secreting NGF-neutralizing scFv enhance efficacy in clear cell renal cell carcinoma by relieving immunosuppression through immunosympathectomyJournal for immunotherapy of cancer · 2024
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 GSE279393_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 PRJNA1172611 and SRA study SRP538412. 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 17 sample titles: 17 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.
- GSM8569160 UT replicate 1, RNA-seq
- GSM8569161 UT replicate 2, RNA-seq
- GSM8569162 UT replicate 3, RNA-seq
- GSM8569163 V28z replicate 1, RNA-seq
- GSM8569164 V28z replicate 2, RNA-seq
- GSM8569165 V28z replicate 3, RNA-seq
- GSM8569166 V28z/αNGF replicate 1, RNA-seq
- GSM8569167 V28z/αNGF replicate 2, RNA-seq
- GSM8569168 V28z/αNGF replicate 3, RNA-seq
- GSM8569169 T_UT replicate 1, RNA-seq
- GSM8569170 T_UT replicate 2, RNA-seq
- GSM8569171 T_V28z replicate 1, RNA-seq
- GSM8569172 T_V28z replicate 2, RNA-seq
- GSM8569173 T_V28z replicate 3, RNA-seq
- GSM8569174 T_V28z/αNGF replicate 1, RNA-seq
- GSM8569175 T_V28z/αNGF replicate 2, RNA-seq
- GSM8569176 T_V28z/αNGF replicate 3, RNA-seq
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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.