GEO series

Dasatinib Remodels the Tumor Microenvironment and Sensitizes Small Cell Lung Cancer to Immunotherapy [DASAITC]

GSE297817 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/07/17 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 15 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: 15 samples: 4 × C vs 4 × DASATINIB vs 4 × DASATINIB_ITC vs 3 × ITCGroups 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.

Summary (written by the submitters)

Effective strategies to reinvigorate the immune system are needed to improve outcomes in small cell lung cancer (SCLC). Targeting Src family kinases with dasatinib (Dasa) can elicit immunomodulatory effects in some cancer types. Here, we explored the potential of combining Dasa with immune checkpoint blockade in SCLC. While the SCLC models were refractory to anti-PD-1 or anti-CTLA4 monotherapy, anti-PD-1 and anti-CTLA4 combination immunotherapy (ITc) induced a significant antitumor response.

Read the full summary ↓

Further, the Dasa+ITc combination was superior to ITc or Dasa alone. Dasa+ITc activity was mediated by CD4+ T cells, MHC-II+ antigen presenting cells (APCs), and natural killer (NK) cells, as depletion of these populations impeded the combination treatment antitumor efficacy. Increased tumor infiltration of CD4+ and CD8+ T cells, NK cells, M1-like macrophages, and CD11c+ APCs and a reduction of regulatory T cells (Tregs) and M2-like macrophages were found in Dasa+ITc-treated mice. Dasa increased CCL5 in NK cells and reduced Treg cell conversion from CD4+ lymphocytes. Dasa+ITc therapy elicited robust antitumor efficacy in 3D co-cultures of immune and SCLC cells. In vivo experiments showed that CCL5 was necessary for the Dasa+ITc response. In SCLC immunotherapy-treated patients, a gene signature including CD4, CIITA, and tumor mutational burden predicted good prognosis. On-treatment CCL5 plasma levels were increased only in patients with long progression-free survival, and pre-treatment secretomics identified cytokines related to myeloid cells significantly associated with poor prognosis. In summary, combining Dasa with immunotherapy represents a strategy to treat SCLC, with CCL5 as a cytokine that could serve to monitor response.

This dataset

Open GSE297817 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 GSE297817_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 PRJNA1266224 and SRA study SRP586934. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

4 × C vs 4 × DASATINIB vs 4 × DASATINIB_ITC vs 3 × ITC

Supports a between-group comparison across 15 samples.

How we read this: 4 replicated groups read from 15 sample titles; they account for 15 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

GSM9000228 C_1 C
GSM9000229 C_2 C
GSM9000230 C_3 C
GSM9000231 C_4 C
GSM9000232 DASATINIB_1 DASATINIB
GSM9000233 DASATINIB_2 DASATINIB
GSM9000234 DASATINIB_3 DASATINIB
GSM9000235 DASATINIB_4 DASATINIB
GSM9000236 ITC_1 ITC
GSM9000237 ITC_2 ITC
GSM9000238 ITC_3 ITC
GSM9000239 DASATINIB_ITC_1 DASATINIB_ITC
GSM9000240 DASATINIB_ITC_2 DASATINIB_ITC
GSM9000241 DASATINIB_ITC_3 DASATINIB_ITC
GSM9000242 DASATINIB_ITC_4 DASATINIB_ITC

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