GEO series

Single-Cell RNA Sequencing Identifies Stem-Like Subpopulations and Their Gene Signature in Lung Adenocarcinoma Progression

GSE333596 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/07/31 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Topic: Lung cancerThis series is part of our curated briefing on it.
Samples: 12 samples: 12 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.

Summary (written by the submitters)

Lung adenocarcinoma (LUAD) exhibits substantial intra-tumor heterogeneity (ITH), contributing to disease progression and therapeutic challenges. This study utilized single-cell RNA sequencing (scRNA-seq) to profile cells from stage I and III LUAD tumors and matched normal tissues, aiming to delineate malignant cell states and identify tumor-propagating subpopulations.

Read the full summary ↓

Unsupervised clustering revealed eight major cell lineages, with epithelial cells dominating in tumors and a shift toward immunosuppressive niches in advanced stages, including elevated T cell exhaustion and pro-angiogenic macrophages. Malignant cells formed 11 subclusters, with stage III tumors enriched for invasive and immunosuppressive states. Pseudotime analysis suggested evolutionary trajectories from alveolar-like to squamous and stress-responsive lineages. Using CytoTRACE to infer stemness without predefined markers, we identified sub-cancer stem cells (sub-CSCs) predominantly in stage III, characterized by high transcriptional diversity and a core signature involving cytoskeleton motility, immune modulation, metabolic reprogramming, and protein homeostasis. A four-gene panel demonstrated strong prognostic value in independent cohorts. These findings provide insights into stemness-driven progression in LUAD and nominate potential targets for addressing heterogeneity.

This dataset

Open GSE333596 in finder → Find more human RNA-seq datasets → 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 GSE333596_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1471638 and SRA study SRP704456. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 8 samples read as cases, 4 as controls.

How we read this: Read from 12 sample titles: 12 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

GSM9769647 LUAD stage I tumor sample T1A
GSM9769648 LUAD stage I tumor sample T1B
GSM9769649 LUAD stage III tumor sample T2A
GSM9769650 LUAD stage III tumor sample T2B
GSM9769651 Adjacent normal tissue N1A (matched to T1A)
GSM9769652 Adjacent normal tissue N1B (matched to T1B)
GSM9769653 Adjacent normal tissue N2A (matched to T2A)
GSM9769654 Adjacent normal tissue N2B (matched to T2B)
GSM9769655 LUAD stage I tumor sample S1T
GSM9769656 LUAD stage I tumor sample S1N
GSM9769657 LUAD stage III tumor sample S3T
GSM9769658 LUAD stage III tumor sample S3N

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Search all human RNA-seq datasets in GEO →

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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.