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Integrative network pharmacology and machine learning identify potential targets of indole-3-lactic acid in
Jie Li1, Jian Zhang1, Jun Ke1
1Department of General Surgery, Xi'an International Medical Center Hospital, Xi'an, Shaanxi, China.
Abstract:
The treatment of colorectal cancer (CRC) remains challenging due to chemotherapy resistance and genetic heterogeneity. Indole-3-lactic acid (ILA), a tryptophan metabolite derived from gut microbiota, exhibits promising anti-inflammatory and anticancer properties; however, its specific molecular targets and regulatory mechanisms in CRC remain poorly understood. In this study, we combined network pharmacology and machine learning with molecular docking to identify candidate targets and pathways for ILA in CRC. We identified 39 ILA-CRC common targets, ultimately identifying four hub genes through the intersection of machine learning models. Validation in independent GEO datasets confirmed significant differential expression of these genes in CRC tissues. Functional enrichment analyses linked these genes to the PPAR, PI3K-AKT, and IL-17 signaling pathways, and gene set enrichment analysis further implicated ascorbate and aldarate metabolism, DNA replication, and fatty acid metabolism. Immune infiltration analysis indicated associations between hub gene expression and immune cell populations, including mast cells, neutrophils, and macrophages, suggesting potential involvement in the tumor immune microenvironment. Molecular docking supported favorable binding of ILA to all four hub proteins, and 100-ns molecular dynamics simulations specifically validated the dynamic stability of the ILA-HMOX1 complex. In conclusion, these results highlight EPHA2, HMOX1, MMP3, and PARP1 as candidate targets and suggest that ILA may influence CRC-related signaling, metabolic programs, and immune contexture, providing a theoretical foundation for developing gut microbiota-derived metabolites as novel anticancer strategies.
Insights
Indole-3-lactic acid (ILA), a gut microbe metabolite, shows potential against colorectal cancer (CRC). This study identified four key genes (EPHA2, HMOX1, MMP3, PARP1) as ILA targets, offering new anticancer strategies.
Area of Science:
- Oncology
- Microbiome Research
- Pharmacology
Background:
- Colorectal cancer (CRC) treatment faces challenges from drug resistance and genetic diversity.
- Indole-3-lactic acid (ILA), a gut microbiota metabolite, has shown anti-inflammatory and anticancer effects, but its CRC targets are unclear.
Purpose of the Study:
- To identify molecular targets and pathways of indole-3-lactic acid (ILA) in colorectal cancer (CRC) using integrated computational methods.
- To explore the potential of ILA as a novel therapeutic strategy derived from gut microbiota.
Main Methods:
- Network pharmacology, machine learning, and molecular docking were employed to identify ILA-CRC targets.
- Hub genes were identified, validated in public datasets, and analyzed for pathway and immune infiltration associations.
- Molecular dynamics simulations confirmed ILA binding stability with identified protein targets.
Main Results:
- Thirty-nine common targets for ILA and CRC were identified, with four hub genes (EPHA2, HMOX1, MMP3, PARP1) selected via machine learning.
- These hub genes were significantly differentially expressed in CRC tissues and linked to PPAR, PI3K-AKT, and IL-17 signaling pathways.
- ILA showed favorable binding to hub proteins, with stable dynamics observed for the ILA-HMOX1 complex, and associations with tumor immune microenvironment components were noted.
Conclusions:
- EPHA2, HMOX1, MMP3, and PARP1 are proposed as candidate targets for ILA in colorectal cancer.
- ILA may modulate CRC signaling, metabolism, and immunity, supporting its development as a microbiota-derived anticancer agent.
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