GEO series

JAK inhibitor overcomes resistance to immune checkpoint inhibitor treatment in gastric cancer peritoneal dissemination in mouse

GSE250238 Mus musculus (mouse) RNA-seq (gene expression) 29 samples Submitted 2024/05/28 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 29 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: 29 samples: 6 conditions, mostly with about 5 replicates eachGroups 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: Janus kinase inhibitor overcomes resistance to immune checkpoint inhibitor treatment in peritoneal dissemination of gastric cancer in C57BL/6 J miceGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2024

Summary (written by the submitters)

Objective Cancer immunotherapy aims to unleash the immune system's potential against cancer cells, providing sustained relief for tumors responsive to immune checkpoint inhibitors (ICIs). While promising in gastric cancer (GC) trials, the efficacy of ICIs diminishes in the context of peritoneal dissemination. Our objective is to identify strategies to enhance the impact of ICI treatment specifically for cases involving peritoneal dissemination in GC.

Read the full summary ↓

Design The therapeutic efficacy of anti-PD1, CTLA4 treatment alone, or in combination, was assessed using the YTN16 peritoneal dissemination tumor model mice. Peritoneum and peritoneal exudate cells were collected for subsequent analysis. Immunohistochemical staining, flow cytometry, and bulk RNA-sequence analyses were conducted to evaluate the tumor microenvironment (TME). A JAK inhibitor (JAKi) was introduced based on the pathway analysis results. Results Anti-PD1 and anti-CTLA4 combination treatment (dual ICI treatment) demonstrated therapeutic efficacy in certain mice, primarily mediated by CD8+ T cells. However, in mice resistant to dual ICI treatment, even with CD8+ T cell infiltration, most of the T cells exhibited exhaustion phenotype. Notably, resistant tumors displayed abnormal activation of the JAK-STAT pathway compared to the untreated group, with observed infiltration of macrophages, neutrophils, and Tregs in the TME. The concurrent administration of JAKi rescued CD8+ T cells function and reshaped the immunosuppressive TME, resulting in enhanced efficacy of the dual ICI treatment. Conclusion Dual ICI treatment exerts its anti-tumor effects by increasing tumor- specific CD8+ T cell infiltration, and the addition of JAKi further improves ICI resistant by reshaping the immunosuppressive TME.

Published in

Janus kinase inhibitor overcomes resistance to immune checkpoint inhibitor treatment in peritoneal dissemination of gastric cancer in C57BL/6 J mice

Du WY, Masuda H, Nagaoka K et al. · Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 2024 · PMID 38805119 · doi:10.1007/s10120-024-01514-5

This dataset

Open GSE250238 in finder → Find more mouse 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 GSE250238_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 PRJNA1052717 and SRA study SRP478149. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38805119) ↗

Study design

6 conditions, mostly with about 5 replicates each

PD-1_d35 ×5 PD-1_CTLA-4_d35 ×5 Control_d35 ×5 Control_d21 ×5 PD-1_CTLA-4_d21 ×5 CTLA-4_d35 ×4

Supports a between-group comparison across 29 samples.

How we read this: 6 replicated groups read from 29 sample titles; they account for 29 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

GSM7976061 PD-1_d35_1 PD-1_d35
GSM7976062 PD-1_d35_2 PD-1_d35
GSM7976063 PD-1_d35_3 PD-1_d35
GSM7976064 PD-1_d35_4 PD-1_d35
GSM7976065 PD-1_d35_5 PD-1_d35
GSM7976066 CTLA-4_d35_1 CTLA-4_d35
GSM7976067 CTLA-4_d35_2 CTLA-4_d35
GSM7976068 CTLA-4_d35_3 CTLA-4_d35
GSM7976069 CTLA-4_d35_4 CTLA-4_d35
GSM7976070 PD-1_CTLA-4_d35_1 PD-1_CTLA-4_d35
GSM7976071 PD-1_CTLA-4_d35_2 PD-1_CTLA-4_d35
GSM7976072 PD-1_CTLA-4_d35_3 PD-1_CTLA-4_d35
GSM7976073 PD-1_CTLA-4_d35_4 PD-1_CTLA-4_d35
GSM7976074 PD-1_CTLA-4_d35_5 PD-1_CTLA-4_d35
GSM7976075 Control_d35_1 Control_d35
GSM7976076 Control_d35_2 Control_d35
GSM7976077 Control_d35_3 Control_d35
GSM7976078 Control_d35_4 Control_d35
GSM7976079 Control_d35_5 Control_d35
GSM7976080 Control_d21_1 Control_d21
GSM7976081 Control_d21_2 Control_d21
GSM7976082 Control_d21_3 Control_d21
GSM7976083 Control_d21_4 Control_d21
GSM7976084 Control_d21_5 Control_d21
GSM7976085 PD-1_CTLA-4_d21_1 PD-1_CTLA-4_d21
GSM7976086 PD-1_CTLA-4_d21_2 PD-1_CTLA-4_d21
GSM7976087 PD-1_CTLA-4_d21_3 PD-1_CTLA-4_d21
GSM7976088 PD-1_CTLA-4_d21_4 PD-1_CTLA-4_d21
GSM7976089 PD-1_CTLA-4_d21_5 PD-1_CTLA-4_d21

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