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Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications

GSE263733 Homo sapiens (human) Single-cell RNA-seq 218 samples Submitted 2024/04/25 Platform GPL20795
At a glance

Single-cell RNA-seq · human · 218 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
218 samples: 57 conditions, mostly in duplicateGroups 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 transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implicationsMolecular cancer · 2024
Summary (written by the submitters)
Intratumoral heterogeneity (ITH) and tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) play important roles in tumor evolution and patient outcomes. However, the precise characterization of diverse cell populations and their crosstalk associated with PDAC progression and metastasis is still challenging. We performed single-cell RNA sequencing (scRNA-seq) of treatment-naive primary PDAC samples with and without paired liver metastasis samples to understand the interplay between ITH and TME in the PDAC evolution and its clinical associations.
Read the full summary ↓
scRNA-seq analysis revealed that even a small proportion (~30%) of basal-like malignant ductal cells could lead to poor chemotherapy response and patient survival and that epithelial-mesenchymal transition programs were largely subtype-specific. The clonal homogeneity significantly increased with more prevalent and pronounced copy number gains of oncogenes, such as KRAS and ETV1, and losses of tumor suppressor genes, such as SMAD2 and MAP2K4, along PDAC progression and metastasis. Moreover, diverse immune cell populations, including naive SELLhi regulatory T cells (Tregs) and activated TIGIThi Tregs, contributed to shaping immunosuppressive TMEs of PDAC through cellular interactions with malignant ductal cells in PDAC evolution. Importantly, the proportion of basal-like ductal cells negatively correlated with that of immunoreactive cell populations, such as cytotoxic T cells, but positively correlated with that of immunosuppressive cell populations, such as Tregs. We uncover that the proportion of basal-like subtype is a determinant for chemotherapy response and patient outcome, and that PDAC clonally evolves with subtype-specific dosage changes of cancer-associated genes by forming immunosuppressive microenvironments in its progression and metastasis.
Published in
Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications
Park JK, Jeong HO, Kim H et al. · Molecular cancer 2024 · PMID 38702773 · doi:10.1186/s12943-024-02003-0
This dataset
Open GSE263733 in finder → Find more human RNA-seq datasets → Pancreatic 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 GSE263733_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 PRJNA948891 and SRA study SRP429394. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38702773) ↗
Study design
57 conditions, mostly in duplicate
adult pancreas; PB2032-PAAD-T_S1_L ×8 adult pancreas; PB2032-PAAD-T_S2_L ×8 adult pancreas; PB2032-PAAD-T_S3_L ×8 adult pancreas; PB2032-PAAD-T_S4_L ×8 adult pancreas; PB2151-PAAD-N_S1_L ×4 adult pancreas; PB2151-PAAD-T_S1_L ×4 adult liver; PB2155-Livermeta-T_S1_L ×4 adult pancreas; PB2155-PAAD-N_S1_L ×4 +119 more

Supports a between-group comparison across 148 samples.

How we read this: 57 replicated groups read from 218 sample titles; they account for 148 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

+ 178 more — browse all 218 samples with per-sample file links →

More Pancreatic cancer datasets

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