Foundry120 atlas

Refining Colorectal Cancer Classification and Clinical Stratification Through a Single-Cell Atlas

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Dataset overview

Participants 16
Samples 23
Reuse readiness 6.7/10 evidence-backed score

Refining colorectal cancer classification and clinical stratification through a single-cell atlas.

Abstract

<h4>Background</h4>Colorectal cancer (CRC) consensus molecular subtypes (CMS) have different immunological, stromal cell, and clinicopathological characteristics. Single-cell characterization of CMS subtype tumor microenvironments is required to elucidate mechanisms of tumor and stroma cell contributions to pathogenesis which may advance subtype-specific therapeutic development. We interrogate racially diverse human CRC samples and analyze multiple independent external cohorts for a total of 487,829 single cells enabling high-resolution depiction of the cellular diversity and heterogeneity within the tumor and microenvironmental cells.<h4>Results</h4>Tumor cells recapitulate individual CMS subgroups yet exhibit significant intratumoral CMS heterogeneity. Both CMS1 microsatellite instability (MSI-H) CRCs and microsatellite stable (MSS) CRC demonstrate similar pathway activations at the tumor epithelial level. However, CD8+ cytotoxic T cell phenotype infiltration in MSI-H CRCs may explain why these tumors respond to immune checkpoint inhibitors. Cellular transcriptomic profiles in CRC exist in a tumor immune stromal continuum in contrast to discrete subtypes proposed by studies utilizing bulk transcriptomics. We note a dichotomy in tumor microenvironments across CMS subgroups exists by which patients with high cancer-associated fibroblasts (CAFs) and C1Q+TAM content exhibit poor outcomes, providing a higher level of personalization and precision than would distinct subtypes. Additionally, we discover CAF subtypes known to be associated with immunotherapy resistance.<h4>Conclusions</h4>Distinct CAFs and C1Q+ TAMs are sufficient to explain CMS predictive ability and a simpler signature based on these cellular phenotypes could stratify CRC patient prognosis with greater precision. Therapeutically targeting specific CAF subtypes and C1Q + TAMs may promote immunotherapy responses in CRC patients.

Study facts

Organism
Homo sapiens
Platform
10X Genomics Single Cell 5' Platform
Age group
Disease groups
Anatomical sites
colon

Data availability

  • Raw counts

File types CSV

Files and samples

Strengths & limitations for reuse

Strengths

  • Raw counts are advertised
  • Cell metadata are advertised
  • Participant mapping is available
  • Participant counts are documented

Limitations

  • Not documented: processed matrices are advertised
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.assay_type single-cell RNA sequencing
Single-cell RNA sequencing (scRNA-seq) was performed

Section series_overall_design, offset —

assay.library_chemistry 10X Genomics Single Cell 5'
10X Genomics Single Cell 5' Platform protocol

Section series_overall_design, offset —

assay.platform 10X Genomics Single Cell 5' Platform
using 10X Genomics Single Cell 5' Platform

Section series_overall_design, offset —

assay.reference_genome GRCh38/hg38
Assembly: GRCh38/hg38

Section samples, offset —

assay.sequencing_type scrna_seq
Single-cell RNA sequencing (scRNA-seq) was performed using 10X Genomics Single Cell 5' Platform.

Section series_overall_design, offset —

Cohort

FieldValueEvidence
cohort.total_participants 16
droplet-based scRNA-seq on 16 racially diverse, treatment naïve CRC patient tissue samples

Section series_summary, offset —

cohort.treatment_exposure_documented True
Patients with resectable untreated CRC

Section series_overall_design, offset —

Data_Assets

FieldValueEvidence
data_assets.cell_metadata True
GSE200997_GEO_processed_CRC_10X_cell_annotation.csv.gz

Section repository_files, offset —

data_assets.open_access True
Public on Apr 19 2022

Section series_status, offset —

data_assets.raw_counts True
GSE200997_GEO_processed_CRC_10X_raw_UMI_count_matrix.csv.gz

Section repository_files, offset —

data_assets.raw_reads False
we have privacy issues with raw data can we submit only count file and annotation files to the GEO database

Section series_overall_design, offset —

Processing

FieldValueEvidence
processing.doublet_detection_reported True
Doublet detection and any higher-order multiplets that were not dissociated during sample preparation were removed via the DoubletFinder (v2.0.2) package

Section samples, offset —

processing.quality_control_reported True
Genes detected in fewer than three cells and cells expressing less than 200 detected genes were filtered out and excluded from analysis.

Section samples, offset —

Specimens

FieldValueEvidence
specimens.anatomical_sites ['colon']
curative colon resection

Section series_overall_design, offset —

specimens.number_of_cells 49589
yielded 49,589 single cells

Section summary, offset —

specimens.number_of_samples 23
totaling 23 samples

Section summary, offset —

specimens.participant_to_sample_mapping_available True
Patient 1, Tumor, Right Side colon cancer

Section samples, offset —

specimens.specimen_type resection
underwent curative colon resection

Section series_overall_design, offset —