GEO series

Single cell transcriptome landscape of primary and metastatic tumor in colon cancer

GSE110009 Homo sapiens (human) Single-cell RNA-seq 76 samples Submitted 2022/07/30 Platform GPL20301

At a glance

Single-cell RNA-seq · human · 76 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: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 76 samples
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)

Colorectal Cancer ranks as the second-leading cause of cancer-related death worldwide. Recent progress in colon cancer research has vastly expanded our understanding of colon cancer on the cellular and molecular levels and have improved the survival of CRC patients considerably. However, most of these genomic and gene expression profiling were usually characterized by bulk tumor tissue.

Read the full summary ↓

In order to further understanding colon cancer, knowledge at the single cell level is urgently needed and expected to have clinical utility in cancer treatment. Single-cell transcriptome profiling of tumor tissues allows the characterization of heterogeneous tumor cells with neighbor microenvironment cell components and investigation of underlying mechanism of tumorigenesis and metastasis. Here, we adopt single cell RNA-Seq to colon cancer and analyze 3,585 cells from 6 patients with matching adjacent normal tissues, primary tumors and metastatic tumors. Most of tumor cells exhibit copy number variations and diverse CNV patterns existed. Novel markers have been identified to distinguish tumour from normal cells and even work for cancer cells that did not have CNVs. Compared with adjacent normal tissue, the number of stem cell and Paneth cell increased and the surrounding cancer-association cells like immune cells in microenvironment increased in tumour region. Moreover, the interaction of tumour cell and microenvironment cells have been elaborated. Our results demonstrate that colon cancer transcriptome has a wide range of intratumoral heterogeneity, which is shaped by tumor cells and cancer associated cells in the surrounding microenvironment.

This dataset

Open GSE110009 in finder → Find more human RNA-seq datasets → Colorectal 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 GSE110009_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 PRJNA432551 and SRA study SRP131982. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35974387) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 76 more — browse all 76 samples with per-sample file links →

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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.