High levels of interferon-gamma-inducible protein 30 blocks PD-L1-mediated lysosomal degradation and increase CD8+ immune cells infiltration to improve response to immunotherapy
RNA-seq (gene expression) · human · 25 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)
- Samples
- 25 samples
- 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
- Interferon-gamma-inducible protein 30 prevents IFN-γ-receptor 1 degradation to maintain PD-L1 and MHC-II levels in metastatic melanomaCell communication and signaling : CCS · 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 GSE261484_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 PRJNA1087272 and SRA study SRP494982. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run MLNM1 … MLNM30 and carry no group information.
- GSM8145189 MLNM1
- GSM8145190 MLNM2
- GSM8145191 MLNM3
- GSM8145192 MLNM4
- GSM8145193 MLNM5
- GSM8145194 MLNM6
- GSM8145195 MLNM7
- GSM8145196 MLNM8
- GSM8145197 MLNM9
- GSM8145198 MLNM10
- GSM8145199 MLNM11
- GSM8145200 MLNM12
- GSM8145201 MLNM13
- GSM8145202 MLNM15
- GSM8145203 MLNM16
- GSM8145204 MLNM17
- GSM8145205 MLNM19
- GSM8145206 MLNM21
- GSM8145207 MLNM22
- GSM8145208 MLNM24
- GSM8145209 MLNM26
- GSM8145210 MLNM27
- GSM8145211 MLNM28
- GSM8145212 MLNM29
- GSM8145213 MLNM30
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- GSE235092 Pre-existing skin-resident CD8 and γδ T cell circuits mediate immune response in Merkel cell carcinoma and Predict immunotherapy efficacy [bulkRNA-seq] 85 samples shares cd8, immunotherapy
- GSE139555 Peripheral clonal expansion of T lymphocytes associates with tumour infiltration and response to cancer immunotherapy 32 samples shares immunotherapy, infiltration
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- GSE266132 Impact of the Multiple Sclerosis associated genetic variant CD226 Gly307Ser on human CD8 T cell functions 80 samples shares cd8
- GSE317789 Single-cell and spatial profiling reveal cDC2A-CXCL13+ CD8+ T-epithelial cell crosstalk and cytotoxicity through TNFRSF9 in cutaneous and mucosal lichen planus 42 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.