Foundry120 atlas

Gene expression profile at single cell level from the colorectal cancer (CRC)

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Dataset overview

Participants None
Samples 26
Reuse readiness 5.1/10 evidence-backed score

Oncogenic KRAS Drives Lipofibrogenesis to Promote Angiogenesis and Colon Cancer Progression.

Abstract

Oncogenic KRAS (KRAS*) contributes to many cancer hallmarks. In colorectal cancer, KRAS* suppresses antitumor immunity to promote tumor invasion and metastasis. Here, we uncovered that KRAS* transforms the phenotype of carcinoma-associated fibroblasts (CAF) into lipid-laden CAFs, promoting angiogenesis and tumor progression. Mechanistically, KRAS* activates the transcription factor CP2 (TFCP2) that upregulates the expression of the proadipogenic factors BMP4 and WNT5B, triggering the transformation of CAFs into lipid-rich CAFs. These lipid-rich CAFs, in turn, produce VEGFA to spur angiogenesis. In KRAS*-driven colorectal cancer mouse models, genetic or pharmacologic neutralization of TFCP2 reduced lipid-rich CAFs, lessened tumor angiogenesis, and improved overall survival. Correspondingly, in human colorectal cancer, lipid-rich CAF and TFCP2 signatures correlate with worse prognosis. This work unveils a new role for KRAS* in transforming CAFs, driving tumor angiogenesis and disease progression, providing an actionable therapeutic intervention for KRAS*-driven colorectal cancer.<h4>Significance</h4>This study identified a molecular mechanism contributing to KRAS*-driven colorectal cancer progression via fibroblast transformation in the tumor microenvironment to produce VEGFA driving tumor angiogenesis. In preclinical models, targeting the KRAS*-TFCP2-VEGFA axis impaired tumor progression, revealing a potential novel therapeutic option for patients with KRAS*-driven colorectal cancer. This article is featured in Selected Articles from This Issue, p. 2489.

Study facts

Organism
Homo sapiens
Platform
NextSeq 500
Age group
—
Disease groups
—
Anatomical sites
Liver tumor, Liver normal, Colon tumor, Colon normal

Data availability

  • Processed matrix

File types MTXTSV

Files and samples

Strengths & limitations for reuse

Strengths

  • Raw reads are advertised
  • Processed matrices are advertised
  • Cell metadata are advertised

Limitations

  • Not documented: raw counts 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

FieldValueEvidence
assay.assay_type Expression profiling by high throughput sequencing
"series_type": "Expression profiling by high throughput sequencing"

Section series_type, offset —

assay.library_chemistry 10x Genomics single cell 3’ v3
Library was performed according to the manufacter’s instructions (single cell 3’ v3 protocol, 10x Genomics).

Section sample_values_with_sample_counts.extract_protocol, offset —

assay.platform NextSeq 500
"instrument_model": "NextSeq 500"

Section samples, offset —

assay.reference_genome GRCh38-3.0.0
Assembly: GRCh38-3.0.0

Section —, offset —

assay.sequencing_type scrna_seq
We used single cell RNAsequencing (scRNA-seq) to analyze the diversity of CRC.

Section —, offset —

Data_Assets

FieldValueEvidence
data_assets.cell_metadata True
barcodes.tsv.gz

Section sample_values_with_sample_counts, offset —

data_assets.open_access True
Public on Sep 25 2023

Section series, offset —

data_assets.processed_matrix True
Supplementary files format and content: Tab-separated values files and matrix files

Section —, offset —

data_assets.raw_reads True
GSE231559_RAW.tar

Section —, offset —

Specimens

FieldValueEvidence
specimens.anatomical_sites ['Liver tumor', 'Liver normal', 'Colon tumor', 'Colon normal']
"source_name": {"Liver tumor": 9, "Liver normal": 8, "Colon tumor": 6, "Colon normal": 3}

Section sample_values_with_sample_counts.source_name, offset —

specimens.number_of_samples 26
"sample_count": 26

Section sample_count, offset —