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Combination therapy with oncolytic virus and adoptively transferred T cells or mRNA vaccine amplifies antitumor effects [RNA-Seq]

GSE235289 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/15 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
12 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.
Summary (written by the submitters)
Adoptive T-cell therapy or oncolytic virotherapy has made significant progress, but the efficacy was limited by the lack of infiltration into solid tumors when used alone. Here, an oncolytic virus (rVSV-LCMVG) was designed and combined with adoptively transferred T cells. By turning cold tumors hot, in B16 tumor-bearing mice, combination therapy showed superior antitumor effects than monotherapy, whether rVSV-LCMVG was administered intratumorally or intravenously.
Read the full summary ↓
Combination therapy significantly increased cytokine and chemokine levels within tumors and sensitized refractory tumors by boosting T-cell recruitment, down-regulating the expression of PD1, and restoring effector-T cell function. To offer a combination therapy with greater translational value, mRNA vaccines were introduced to induce tumor-specific T cells instead of adoptively transferred T cells, and exhibited comparable amplified anti-tumor effects. This study proposed a rational combination therapy of oncolytic virus with adoptive T-cell transfer or mRNA vaccines encoding tumor-associated antigens, in terms of synergistic efficacy and mechanism.
This dataset
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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 GSE235289_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 PRJNA985654 and SRA study SRP445021. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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