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Long non-coding RNA GRASLND affects melanoma phenotypic switch and modulates immunogenicity by inhibition of the IFNγ signaling pathway (IFNg treatment and GRASLND KD).

GSE273020 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/09/18 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 6 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
Long non-coding RNA GRASLND links melanoma differentiation and interferon-gamma responseFrontiers in molecular biosciences · 2024
Summary (written by the submitters)
Melanoma is a highly malignant tumor, that stands as the most lethal form of skin cancer and is characterized by notable phenotypic plasticity and intratumoral heterogeneity. Melanoma plasticity is involved in tumor growth, metastasis and therapy resistance. Long non-coding RNAs (lncRNAs) could influence plasticity due to their regulatory function.
Read the full summary ↓
However, their role and mode of action are poorly studied. Here, we show a relevance of lncRNA GRASLND in melanoma phenotypic switch, IFNγ signaling and immunogenicity. GRASLND knockdown revealed switching towards a dedifferentiated, slow-proliferating and highly-invasive cell state. Interestingly, GRASLND is overexpressed in differentiated melanomas and associated with poor prognosis. Accordingly, we found GRASLND expressed in immunological “cold” tumors and it negatively correlates with gene signatures of immune response activation. In line, silencing of GRASLND under IFNγ enhanced the expression of IFNγ-stimulated genes, including HLA-I antigen presentation, demonstrating suppressive activity of GRASLND on IFNγ signaling. Based on our findings, we hypothesize an adaptive resistance mechanism of melanoma cells evading the immune system via inhibition of IFNγ signaling by GRASLND overexpression and highlight its value as a negative prognostic factor for melanoma.
Published in
Long non-coding RNA GRASLND links melanoma differentiation and interferon-gamma response
Fischer KD, Tiwari S, Thier B et al. · Frontiers in molecular biosciences 2024 · PMID 39398277 · doi:10.3389/fmolb.2024.1471100
This dataset
Open GSE273020 in finder → Find more human 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 GSE273020_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: 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 PRJNA1139801 and SRA study SRP522114. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39398277) ↗
Study design
6 conditions, mostly in duplicate
501Mel, shlacZ, IFNγ-treated, uninduced, ×2 501Mel, shlacZ, IFNγ-treated, dox-induced, ×2 501Mel, sh4, IFNγ-treated, uninduced, ×2 501Mel, sh4, IFNγ-treated, dox-induced, ×2 501Mel, sh8, IFNγ-treated, uninduced, ×2 501Mel, sh8, IFNγ-treated, dox-induced, ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 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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