Interdisciplinary

Machine Learning Reveals How Colorectal Cancer Hijacks Tryptophan Metabolism

AI Insight

This study used single-cell RNA sequencing and machine learning algorithms to investigate tryptophan metabolism patterns in colorectal cancer at the cellular level. The researchers found that macrophages and Paneth cells showed the highest tryptophan metabolic activity among different cell types, and identified two genes, CYP1A1 and aryl hydrocarbon receptor (AHR), as significantly upregulated in colorectal cancer tissues. These genes appear to be involved in regulating immune and inflammatory responses in the tumor microenvironment.


The identification of CYP1A1 and AHR as key players in tryptophan metabolism could provide new biomarkers for colorectal cancer diagnosis and potential therapeutic targets for treatment. Understanding which specific cell types drive abnormal metabolism in tumors may help develop more targeted interventions that focus on macrophages and Paneth cells.


Understand the Science

Machine learning 119 articles Explore Concept → Colorectal cancer Concept coming soon Tryptophan Concept coming soon

by Chen Zepeng, Wang Xingchen, Xiao Changfang, Cao Yongqing

Background

Colorectal cancer (CRC) is characterized by genetic variation, epigenetic alterations, microenvironmental imbalance, and metabolic reprogramming. Currently, abnormalities amino acid metabolism has been shown to play an important role in the occurrence and progression of CRC.

Methods

AUCell, UCell, singscore, ssGSEA and AddModuleScore algorithms were used to determine the pattern of tryptophan metabolism in CRC at the cellular level. Differential expression and correlation analyses were performed to identify core candidate genes associated with upregulation of metabolic activity. Four machine learning algorithms——random forest, Boruta, LASSO, and gradient boosting machine—were further integrated for feature selection. Finally, to enhance robustness and reduce algorithm‑specific bias, the results of these algorithms were combined to identify the key feature genes related to tryptophan metabolism in CRC.

Results

The findings demonstrated significant differences in tryptophan metabolic activity among different cell types in CRC, with macrophages and Paneth cells exhibiting higher activity. Among the tryptophan metabolism-related genes, CYP1A1 and aryl hydrocarbon receptor (AHR) were significantly upregulated in CRC, suggesting their involvement in regulating of immune response and inflammatory responses.

Conclusions

This study reveals, for the first time, the cellular pattern of tryptophan metabolism in CRC, with macrophages and Paneth cells playing a major role in tumor development. CYP1A1 and AHR were identified as consensus feature‑selected genes involved in tryptophan metabolism in CRC, highlighting their potential as biomarkers and therapeutic targets.

Source: Investigating tryptophan metabolism in colorectal cancer using Single-cell RNA sequencing based on machine learning techniques