Single-cell RNA sequencing of ovarian, colorectal and breast cancer
Download from source ↗Dataset overview
Uncovering NK cell sabotage in gut diseases via single cell transcriptomics.
Abstract
The identification of immune environments and cellular interactions in the colon microenvironment is essential for understanding the mechanisms of chronic inflammatory disease. Despite occurring in the same organ, there is a significant gap in understanding the pathophysiology of ulcerative colitis (UC) and colorectal cancer (CRC). Our study aims to address the distinct immunopathological response of UC and CRC. Using single-cell RNA sequencing datasets, we analyzed the profiles of immune cells in colorectal tissues obtained from healthy donors, UC patients, and CRC patients. The colon tissues from patients and healthy participants were visualized by immunostaining followed by laser confocal microscopy for select targets. Natural killer (NK) cells from UC patients on medication showed reduced cytotoxicity compared to those from healthy individuals. Nonetheless, a UC-specific pathway called the BAG6-NCR3 axis led to higher levels of inflammatory cytokines and increased the cytotoxicity of NCR3+ NK cells, thereby contributing to the persistence of colitis. In the context of colorectal cancer (CRC), both NK cells and CD8+ T cells exhibited significant changes in cytotoxicity and exhaustion. The GALECTIN-9 (LGALS9)-HAVCR2 axis was identified as one of the CRC-specific pathways. Within this pathway, NK cells solely communicated with myeloid cells under CRC conditions. HAVCR2+ NK cells from CRC patients suppressed NK cell-mediated cytotoxicity, indicating a reduction in immune surveillance. Overall, we elucidated the comprehensive UC and CRC immune microenvironments and NK cell-mediated immune responses. Our findings can aid in selecting therapeutic targets that increase the efficacy of immunotherapy.
doi:10.1371/journal.pone.0315981 ↗ PMID 39752457 ↗ PMC11698320 ↗
Study facts
- Organism
- Homo sapiens
- Platform
- 10x Genomics Chromium
- Age group
- adult
- Disease groups
- —
- Anatomical sites
- —
Data availability
- Processed matrix
File types
CSV
Files and samples
- BT1303.counts.csv
- BT1304.counts.csv
- BT1305.counts.csv
- BT1306.counts.csv
- BT1307.counts.csv
- E-MTAB-8107.idf.txt
- E-MTAB-8107.sdrf.txt
- sc5rJUQ026.counts.csv
- sc5rJUQ033.counts.csv
- sc5rJUQ039.counts.csv
- sc5rJUQ042.counts.csv
- sc5rJUQ043.counts.csv
- sc5rJUQ045.counts.csv
- sc5rJUQ046.counts.csv
- sc5rJUQ050.counts.csv
- sc5rJUQ051.counts.csv
- sc5rJUQ053.counts.csv
- sc5rJUQ058.counts.csv
- sc5rJUQ060.counts.csv
- sc5rJUQ064.counts.csv
- scrEXT001.counts.csv
- scrEXT002.counts.csv
- scrEXT003.counts.csv
- scrEXT009.counts.csv
- scrEXT010.counts.csv
- scrEXT011.counts.csv
- scrEXT012.counts.csv
- scrEXT013.counts.csv
- scrEXT014.counts.csv
- scrEXT018.counts.csv
- scrEXT019.counts.csv
- scrEXT020.counts.csv
- scrEXT021.counts.csv
- scrEXT022.counts.csv
- scrEXT023.counts.csv
- scrEXT024.counts.csv
- scrEXT025.counts.csv
- scrEXT026.counts.csv
- scrEXT027.counts.csv
- scrEXT028.counts.csv
- scrEXT029.counts.csv
- scrJUQ059.counts.csv
- scrJUQ068.counts.csv
- scrJUQ070.counts.csv
- scrJUQ072.counts.csv
- scrSOL001.counts.csv
- scrSOL003.counts.csv
- scrSOL004.counts.csv
- scrSOL006.counts.csv
- scrSOL007.counts.csv
Strengths & limitations for reuse
Strengths
- Processed matrices are advertised
- Participant mapping is available
Limitations
- Not documented: raw counts are advertised
- Not documented: cell metadata are advertised
- Not documented: participant counts are documented
Extraction evidence & provenance
Each extracted field is shown with the source excerpt and location used to resolve it.
Assay
| Field | Value | Evidence |
|---|---|---|
assay.assay_type |
single-cell RNA sequencing |
Single-cell RNA sequencing of ovarian, colorectal and breast cancer Section |
assay.library_chemistry |
10x Genomics V2 barcoding chemistry |
Samples were processed using kits pertaining to V2 barcoding chemistry of 10X Genomics. Section |
assay.platform |
10x Genomics Chromium |
Chromium Single Cell 3′ or 5' Library, Gel Bead & Multiplex Kit and Chip Kit (10X Genomics Section |
assay.reference_genome |
hg38 |
aligned to the human reference genome hg38 Section |
assay.sequencing_type |
scrna_seq |
RNA-seq of coding RNA from single cells Section |
Cohort
| Field | Value | Evidence |
|---|---|---|
cohort.age_group |
adult |
Characteristics[developmental stage] adult Section |
Data_Assets
| Field | Value | Evidence |
|---|---|---|
data_assets.open_access |
True |
"isOpenAccess": "Y" Section |
data_assets.processed_matrix |
True |
Processed Data Section |
data_assets.raw_reads |
False |
Raw data files have been removed upon submitter's request. Section |
Processing
| Field | Value | Evidence |
|---|---|---|
processing.cell_type_annotation_method |
SingleR and canonical marker genes |
classified as T cells, B cells, plasma cells, and myeloid cells depending on cell type probability calculated by package named ‘SingleR’ and mean expressions of canonical marker genes Section |
processing.normalization_method |
Seurat NormalizeData and SCTransform |
We then normalized the combined data using SCTransform. Section |
processing.quality_control_reported |
True |
cells with at least 400 UMIs, between 200 and 6000 genes and less than 25% of mtRNA were retained Section |
Specimens
| Field | Value | Evidence |
|---|---|---|
specimens.number_of_samples |
49 |
"Sample count", "value": "49" Section |
specimens.participant_to_sample_mapping_available |
True inferred |
Characteristics[individual] Section |
specimens.specimen_type |
mixed |
Samples were collected during resection surgery or biopsy Section |