← BioTransfer GEO Dataset Finder
GEO series

Single-cell RNA Sequencing Reveals the Heterogeneity in Differentiation Trajectory and Tumor Microenvironment Leading to More Aggressive Phenotypes of Papillary Thyroid Cancer in Children and Young Adult Patients

GSE281736 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2025/01/01 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
Thyroid 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.
Paper
Single-Cell RNA Sequencing Reveals the Heterogeneity in Differentiation Trajectory and Tumor Microenvironment Leading to More Aggressive Phenotypes of Papillary Thyroid Cancer in Children and Young Adult PatientsAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
Summary (written by the submitters)
The tumor ecosystem heterogeneity of papillary thyroid carcinoma (PTC) is poorly characterized especially in children and young adult patients (CAYA-PTC). Here, we used single-cell RNA sequencing to profile transcriptomes map from eleven patients’ paratumors and localized tumors, covering comprehensive clinical courses of PTC. Compared with adult-PTC, CD4T_Tfh and CD8T_Tex cells were significantly higher in CAYA-PTC patients which closely related to metastasis.
Read the full summary ↓
Along the differentiation trajectory, we discover three phenotypes of thyrocytes population (normal, BRAF-like, Fusion-like), whose composition shapes bulk molecular subtypes and tumor characteristics. Furthermore, our data identifies CAYA-PTC patients lack a “mild-state (BRAF-like)” malignant thyrocyte population. This different differentiation states indicates PTC cells quickly develop into invasion and metastasis in CAYA patients, while they gradually progress over a long time in adult patients. In addition, extracellular matrix cancer-associated fibroblasts(emCAFs_LAMP5) interact with endothelial cells and thyrocytes, ultimately promoting tumor angiogenesis and metastasis, which plays a more evident role in CAYA patients. FAP was highly expressed in emCAF_LAMP5 and positive correlated with LAMP5 in CAYA-PTC tissues. Therefore, ⁶⁸Ga-FAPI-PET have the potential to be used as a promising diagnostic method for CAYA patients with failed by traditional 18F-FDG-PET/CT. Together, our findings provide insight into the CAYA-PTC ecosystem that suggests distinct diagnostic, prognostic and therapeutic implications compared to adults.
Published in
Single-Cell RNA Sequencing Reveals the Heterogeneity in Differentiation Trajectory and Tumor Microenvironment Leading to More Aggressive Phenotypes of Papillary Thyroid Cancer in Children and Young Adult Patients
Guo K, Yang L, Huang Z et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2025 · PMID 40719066 · doi:10.1002/advs.202417672
This dataset
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.

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 GSE281736_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1185392 and SRA study SRP544817. Searching any of these in the dataset finder brings you back here.

Study design
12 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 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
More Thyroid cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.