# Construction of a prognostic model for colorectal cancer liver metastasis based on single-cell transcriptomics and regulation of the MIF pathway

**Authors:** Jianqiang Cao, Zhaobin He, HuiJie Gao, Yongzhe Yu, Shengbiao Yang, Xiqiang Wang, Jun Niu, Cheng Peng

PMC · DOI: 10.3389/fonc.2025.1588514 · Frontiers in Oncology · 2025-10-07

## TL;DR

This study builds a prognostic model for colorectal cancer liver metastasis using single-cell data and explores the MIF pathway's role in tumor spread.

## Contribution

A novel prognostic model for colorectal cancer liver metastasis based on single-cell transcriptomics and MIF pathway regulation.

## Key findings

- TPM2, RPS17, and TNNT1 are significantly elevated in metastatic colorectal cancer epithelial cells.
- SPINK4 expression is reduced in colorectal cancer with liver metastasis.
- The MIF pathway interacts with CD74 and CXCR4 to promote tumor invasion and migration.

## Abstract

Colorectal cancer is associated with a generally poor prognosis, primarily due to its often late diagnosis and the high propensity for liver metastasis. Current treatment strategies emphasize personalized approaches, integrating advanced targeted therapies based on specific molecular profiles to enhance outcomes. Continued research into molecular targets and innovative treatments is crucial for improving survival rates and managing disease progression.

We retrieved single-cell transcriptomic and bulk RNA-seq data from colorectal cancer samples in the GEO and TCGA databases. The analysis focused on changes in pathway and gene expression in epithelial cells during the metastatic progression. A prognostic risk model was developed based on differentially expressed genes, and experimental validation confirmed the differential expression of prognostic-related genes in colorectal cancer tissues.

During the process of liver metastasis in colorectal cancer, the interaction between MIF and its receptors, CD74 and CXCR4, is markedly intensified, promoting tumor cell invasion and migration. The expression levels of TPM2, RPS17, and TNNT1 were significantly elevated, while SPINK4 expression was reduced in the epithelial cells of colorectal cancer with liver metastasis. These findings were further validated experimentally. A prognostic model based on these genes predicted patients’ overall survival at 1, 3, and 5 years.

During liver metastasis in colorectal cancer, the expression levels of TPM2, RPS17, and TNNT1 were significantly elevated, SPINK4 expression was reduced in the epithelial cells. Furthermore, the interaction between the MIF pathway and its ligands, CD74/CXCR4, may play a important role in promoting tumor metastasis.

## Linked entities

- **Genes:** TPM2 (tropomyosin 2) [NCBI Gene 7169], RPS17 (ribosomal protein S17) [NCBI Gene 6218], TNNT1 (troponin T1, slow skeletal type) [NCBI Gene 7138], SPINK4 (serine peptidase inhibitor Kazal type 4) [NCBI Gene 27290], CD74 (CD74 molecule) [NCBI Gene 972], CXCR4 (C-X-C motif chemokine receptor 4) [NCBI Gene 7852]
- **Proteins:** MIF (macrophage migration inhibitory factor)
- **Diseases:** colorectal cancer (MONDO:0005575)

## Full-text entities

- **Genes:** CD74 (CD74 molecule) [NCBI Gene 972] {aka CLIP, DHLAG, HLADG, II, Ia-GAMMA, p33}, CXCR4 (C-X-C motif chemokine receptor 4) [NCBI Gene 7852] {aka CD184, D2S201E, FB22, HM89, HSY3RR, LCR1}, SPINK4 (serine peptidase inhibitor Kazal type 4) [NCBI Gene 27290] {aka HEL136, PEC-60, PEC60}, MIF (macrophage migration inhibitory factor) [NCBI Gene 4282] {aka GIF, GLIF, MMIF}, TPM2 (tropomyosin 2) [NCBI Gene 7169] {aka AMCD1, CMYO23, CMYP23, DA1, DA2B, DA2B4}, TNNT1 (troponin T1, slow skeletal type) [NCBI Gene 7138] {aka ANM, NEM5, STNT, TNT, TNTS}, RPS17 (ribosomal protein S17) [NCBI Gene 6218] {aka DBA4, RPS17L, RPS17L1, RPS17L2, S17, eS17}
- **Diseases:** liver metastasis (MESH:D009362), tumor (MESH:D009369), Colorectal cancer (MESH:D015179)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12537406/full.md

## References

60 references — full list in the complete paper: https://tomesphere.com/paper/PMC12537406/full.md

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Source: https://tomesphere.com/paper/PMC12537406