GEO series

Single-Cell Transcriptomic Landscape of Laryngeal Squamous Cell Carcinoma from Precancerous to Cancerous Lesions

GSE297537 Homo sapiens (human) Single-cell RNA-seq 6 samples Submitted 2026/08/25 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 6 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)
Samples: 6 samples: 6 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)

Laryngeal squamous cell carcinoma (LSCC), a significant and aggressive type of head and neck cancer, primarily originates from the precancerous lesions of the larynx. However, the mechanisms driving the progression from laryngeal precancerosis to carcinoma remain unclear. To address this and provide therapeutic candidates, we compile a single-cell transcriptome atlas of the laryngeal precancerous lesion, carcinoma in situ, and squamous cell carcinoma from patient samples.

Read the full summary ↓

We uncover the complex cellular landscape of these lesions, revealing distinct cell populations and their unique transcriptional profiles at various stages of disease progression. Notably, our analysis identifies a key subtype of epithelial cells in laryngeal precancerosis, characterized by the expression of TOP2A, HMGB2 and PTTG1, linked to aggressive LSCC behavior. Within this TOP2A+HMGB2+PTTG1+subset, polo-like kinase-1 (PLK1) emerged as a pivotal therapeutic target. Further studies demonstrate that a component derived from the Chinese Medicine Compound ReYanNingHeJi, quercetin, effectively target and inhibit PLK1 activity, thereby reducing cellular proliferation. Therefore, this study sheds new light on the understanding of precancerous lesions progression and offers potential candidates for clinical intervention.

This dataset

Open GSE297537 in finder → Find more human 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 GSE297537_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 PRJNA1265160. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 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 6 sample titles: 6 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

GSM8994139 sample 1 high-grade epithelial hyperplasia
GSM8994140 sample 2 high-grade epithelial hyperplasia
GSM8994141 sample 3 carcinoma in situ
GSM8994142 sample 4 carcinoma in situ
GSM8994143 sample 5 laryngeal squamous cell
GSM8994144 sample 6 laryngeal squamous cell

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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.