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DNAPKCs as a therapeutic target in small cell lung cancer

GSE273409 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/08/27 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 36 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)
Topic
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
36 samples: 36 samples, each with a distinct title — no replicated groupsGroups 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
Targeting NHEJ activates STING signaling through MYC degradation to boost antitumor immunity in SCLCNature communications · 2026
Summary (written by the submitters)
Small cell lung cancer is the most aggressive form of lung cancer. Current frontline treatment of anti-PD-L1 with chemotherapy only results in a modest increase in overall survival and progression-free survival due to the poor immunogenic nature of SCLC. In this investigation, we report DNAPKcs inhibition sensitizes SCLC by inducing apoptosis and DNA damage leading to micro-nuclei formation.
Read the full summary ↓
These aberrant cytosolic DNA activates cGAS-STING pathway resulting in induction of type-I/II interferon and MHC class-I. This study provides evidence of proteasomal degradation of cMYC in a GSK3B dependent manner in response to DNAPKcs inhibition further enhancing pro-inflammatory immune pathways. Using two unique immune-competent SCLC GEM models, we show STING mediated modulation of tumor immune microenvironment by increasing CD8+ T cells, MHC-I+ cells, and M1 macrophages in response to DNAPKcs inhibition with anti-PD-L1 therapy. We further provide strong evidence of significant tumor regression in immune-competent GEMMs by treatment with DNAPKcs inhibitor alone and in combination DNAPKcsi and anti-PD-L1. Taken together this study reports induction of DNAPKcs inhibitor increases the efficacy of immune checkpoint blockade therapy remarkably by activating immune microenvironment in a STING-MYC dependent manner which is of significant translational value.
Published in
Targeting NHEJ activates STING signaling through MYC degradation to boost antitumor immunity in SCLC
Chakraborty S, Elliott A, Sen U et al. · Nature communications 2026 · PMID 41667501 · doi:10.1038/s41467-026-69262-x
This dataset
Open GSE273409 in finder → Find more human RNA-seq datasets → Small cell lung cancer landscape →
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 GSE273409_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 PRJNA1141562 and SRA study SRP523010. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41667501) ↗
Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 distinct titles with little repetition. 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
More Small cell lung cancer datasets

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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.