Single-cell and bulk transcriptomic analysis of inflammation-metabolism programs and the tumor microenvironment of colorectal cancer liver metastasis
- 1Department of Gastrointestinal Surgery, Maanshan People's Hospital, No. 45, Hubei Road, Maanshan, Anhui, 243000, China
- 2Department of General Surgery, Wuhu Traditional Chinese Medicine Hospital, No. 430, Jiuhua South Road, Wuhu, Anhui, 241000, China
- 3Department of Anesthesiology and Surgery, Maanshan People's Hospital, No. 45, Hubei Road, Maanshan, Anhui, 243000, China
Abstract
Background: Colorectal cancer liver metastasis (CRLM) is a major cause of mortality in colorectal cancer (CRC) and develops within a heterogeneous tumor microenvironment (TME). How immune, stromal, and metabolic programs differ between primary CRC and matched liver metastases remains incompletely resolved.
Methods: We analyzed publicly available single-cell RNA sequencing (scRNA-seq) data from GSE178318 (15 specimens from six patients: six primary CRC samples, six matched liver metastases, and three peripheral-blood mononuclear cell samples) together with bulk RNA-seq data from GSE50760 (54 samples from 18 patients spanning normal colon, primary CRC, and liver metastasis). The single-cell workflow included quality control, score-based cell-type annotation, patient-level pseudobulk differential expression, pathway/module scoring, ligand-receptor co-expression analysis, and diffusion-map pseudotime. Bulk data were assessed using within-patient paired comparisons, co-expression analysis, and program-level scoring. Benjamini-Hochberg false-discovery-rate (FDR) correction was applied for multiple testing.
Results: After quality control, 132,915 single cells were retained. Liver metastases showed higher patient-level T/NK-cell fractions and lower malignant epithelial and B/plasma-cell fractions than primary tumors. In paired single-cell pseudobulk analysis, no gene remained significant at the prespecified FDR threshold, although nominal differences suggested extracellular-matrix and metabolic changes. Glycolysis scores were modestly higher and oxidative-phosphorylation scores modestly lower in liver metastases, whereas inflammatory and glycolytic scores were not correlated at the patient-tissue level. Ligand-receptor co-expression was strongest for MIF-CD74, VIM-CD44, and HLA-A-CD8A, with CAF/stromal and myeloid/TAM populations showing high aggregate outgoing scores. Diffusion pseudotime showed increasing EMT/invasion scores and decreasing glycolysis along the inferred transcriptomic ordering; this ordering is descriptive and not a longitudinal lineage. In the bulk cohort, 654 genes differed between liver metastasis and primary tumor, while cross-platform rank concordance was weak (Spearman rho=0.106).
Conclusions: Public single-cell and bulk datasets support compartment-associated differences in cellular composition and transcriptional programs in CRLM, with prominent stromal, myeloid, and metabolic features. However, limited patient numbers, cross-sectional sampling, weak cross-platform concordance, and the absence of experimental validation mean that the ligand-receptor and trajectory findings should be interpreted as hypothesis-generating rather than causal or clinically validated.
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BibTeX
@article{ma2026singlecell,
title = {{Single-cell and bulk transcriptomic analysis of inflammation-metabolism programs and the tumor microenvironment of colorectal cancer liver metastasis}},
author = {Zhen Ma and Wen Jiang and Jian Zhang and Lingyu Kong and Conghao Zhao and Fang Ma and Chenliang Wu},
journal = {Translational Oncology},
year = {2026},
month = oct,
doi = {10.1016/j.tranon.2026.103077},
url = {https://doi.org/10.1016/j.tranon.2026.103077},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Single-cell and bulk transcriptomic analysis of inflammation-metabolism programs and the tumor microenvironment of colorectal cancer liver metastasis
AU - Zhen Ma
AU - Wen Jiang
AU - Jian Zhang
AU - Lingyu Kong
AU - Conghao Zhao
AU - Fang Ma
AU - Chenliang Wu
PY - 2026
DA - 2026/10/21
JO - Translational Oncology
DO - 10.1016/j.tranon.2026.103077
UR - https://doi.org/10.1016/j.tranon.2026.103077
AB - Background: Colorectal cancer liver metastasis (CRLM) is a major cause of mortality in colorectal cancer (CRC) and develops within a heterogeneous tumor microenvironment (TME). How immune, stromal, and metabolic programs differ between primary CRC and matched liver metastases remains incompletely resolved. Methods: We analyzed publicly available single-cell RNA sequencing (scRNA-seq) data from GSE178318 (15 specimens from six patients: six primary CRC samples, six matched liver metastases, and three peripheral-blood mononuclear cell samples) together with bulk RNA-seq data from GSE50760 (54 samples from 18 patients spanning normal colon, primary CRC, and liver metastasis). The single-cell workflow included quality control, score-based cell-type annotation, patient-level pseudobulk differential expression, pathway/module scoring, ligand-receptor co-expression analysis, and diffusion-map pseudotime. Bulk data were assessed using within-patient paired comparisons, co-expression analysis, and program-level scoring. Benjamini-Hochberg false-discovery-rate (FDR) correction was applied for multiple testing. Results: After quality control, 132,915 single cells were retained. Liver metastases showed higher patient-level T/NK-cell fractions and lower malignant epithelial and B/plasma-cell fractions than primary tumors. In paired single-cell pseudobulk analysis, no gene remained significant at the prespecified FDR threshold, although nominal differences suggested extracellular-matrix and metabolic changes. Glycolysis scores were modestly higher and oxidative-phosphorylation scores modestly lower in liver metastases, whereas inflammatory and glycolytic scores were not correlated at the patient-tissue level. Ligand-receptor co-expression was strongest for MIF-CD74, VIM-CD44, and HLA-A-CD8A, with CAF/stromal and myeloid/TAM populations showing high aggregate outgoing scores. Diffusion pseudotime showed increasing EMT/invasion scores and decreasing glycolysis along the inferred transcriptomic ordering; this ordering is descriptive and not a longitudinal lineage. In the bulk cohort, 654 genes differed between liver metastasis and primary tumor, while cross-platform rank concordance was weak (Spearman rho=0.106). Conclusions: Public single-cell and bulk datasets support compartment-associated differences in cellular composition and transcriptional programs in CRLM, with prominent stromal, myeloid, and metabolic features. However, limited patient numbers, cross-sectional sampling, weak cross-platform concordance, and the absence of experimental validation mean that the ligand-receptor and trajectory findings should be interpreted as hypothesis-generating rather than causal or clinically validated.
SN - 1936-5233
ER -