TGF-β Pathways Stratify Colorectal Cancer into Two Subtypes with Distinct Cartilage Oligomeric Matrix Protein (COMP)...

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Colorectal cancers (CRCs) are a major global cause of cancer mortality.
• The molecular characteristics of TGF-β pathway-inducing CRCs are not fully understood.

Purpose of the Study:

• To identify molecular features distinguishing TGF-β pathway-inducing colorectal cancer subtypes.
• To discover novel biomarkers for CRC subtype prediction and potential therapeutic targets.

Main Methods:

• Unsupervised hierarchical clustering and weighted gene co-expression network analysis were used to stratify CRC samples.
• A machine learning algorithm integrating LASSO, XGBoost, and random forest regression identified key genes.
• Bioinformatic analyses focused on COMP-related immune infiltration and functions.

Main Results:

• The integrated machine learning approach identified COMP as a crucial hub gene.
• COMP demonstrated significant predictive value for CRC subtypes (AUC = 0.91).
• COMP is upregulated in various cancers, particularly advanced CRCs, and influences immune infiltration (M2 macrophages, cancer-associated fibroblasts).

Conclusions:

• COMP serves as a reliable signature for CRC subtype prediction.
• These findings offer a new target for TGFβ-targeted anticancer drugs.
• The results can aid in clinical decision-making for CRC patients.