Unraveling TIMP1: a multifaceted biomarker in colorectal cancer

Xiaode Qiu; Guangqian Quan; Wenquan Ou; Pengfei Wang; Xing Huang; Xinhua Li; Yufan Shen; Weifeng Yang; Jian Wang; Xiaohua Wu

doi:10.3389/fgene.2023.1265137

Unraveling TIMP1: a multifaceted biomarker in colorectal cancer

Front Genet. 2023 Sep 29:14:1265137. doi: 10.3389/fgene.2023.1265137. eCollection 2023.

Authors

Xiaode Qiu^{1

2}, Guangqian Quan^#², Wenquan Ou^#², Pengfei Wang³, Xing Huang², Xinhua Li⁴, Yufan Shen^{1

2}, Weifeng Yang², Jian Wang², Xiaohua Wu²

Affiliations

¹ Department of Clinical Medicine, Fujian Medical University, Fuzhou, China.
² Department of General Surgery, Affiliated Nanping First Hospital, Fujian Medical University, Nanping, China.
³ Department of Gastroenterology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping, China.
⁴ Department of Pathology, Affiliated Nanping First Hospital, Fujian Medical University, Nanping, China.

^# Contributed equally.

Abstract

Background: The pathogenic genes of colorectal cancer (CRC) have not yet been fully elucidated, and there is currently a lack of effective therapeutic targets. This study used bioinformatics methods to explore and experimentally validate the most valuable biomarkers for colorectal cancer and further investigate their potential as targets. Methods: We analyzed differentially expressed genes (DEGs) based on the Gene Expression Omnibus (GEO) dataset and screened out hub genes. ROC curve and univariate Cox analysis of The Cancer Genome Atlas (TCGA) dataset revealed the most diagnostically and prognostically valuable genes. Immunohistochemistry (IHC) experiments were then conducted to validate the expression level of these selected genes in colorectal cancer. Gene set enrichment analysis (GSEA) was performed to evaluate the enriched signaling pathways associated with the gene. Using the CIBERSORT algorithm in R software, we analyzed the immune infiltrating cell abundance in both high and low gene expression groups and examined the gene's correlation with immune cells and immune checkpoints. Additionally, we performed drug sensitivity analysis utilizing the DepMap database, and explored the correlation between gene expression levels and ferroptosis based on the The Cancer Genome Atlas dataset. Results: The study identified a total of 159 DEGs, including 7 hub genes: SPP1, MMP1, CXCL8, CXCL1, TIMP1, MMP3, and CXCL10. Further analysis revealed TIMP1 as the most valuable diagnostic and prognostic biomarker for colorectal cancer, with IHC experiments verifying its high expression. Additionally, GSEA results showed that the high TIMP1 expression group was involved in many cancer signaling pathways. Analysis of the TCGA database revealed a positive correlation between TIMP1 expression and infiltration of macrophages (M0, M1, M2) and neutrophils, as well as the expression of immune checkpoint genes, including CTLA-4 and HAVCR2. Drug sensitivity analysis, conducted using the DepMap database, revealed that colorectal cancer cell lines exhibiting elevated levels of TIMP1 expression were more responsive to certain drugs, such as CC-90003, Pitavastatin, Atuveciclib, and CT7001, compared to those with low levels of TIMP1. Furthermore, TIMP1 expression was positively correlated with that of ferroptosis-related genes, such as GPX4 and HSPA5. Conclusion: TIMP1 can be used as a biomarker for colorectal cancer and is associated with the immunological microenvironment, drug sensitivity, and ferroptosis inhibition in this disease.

Keywords: TIMP1; biomarkers; colorectal cancer; drug sensitivity; ferroptosis; immunological microenvironment.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and of this article. This research was funded by the Startup Fund for scientific research, Fujian Medical University (Grant number:2019QH1242).