Integration of Machine Learning Algorithms and Single‐Cell Sequencing Analysis Reveals the Efferocytosis‐Related Molecular Subtype and Prognostic Scoring Index in Colon Adenocarcinoma DOI

Kun Ju,

Xiaolei Liu, Qian Wang

et al.

Journal of Gastroenterology and Hepatology, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

ABSTRACT Background Colon adenocarcinoma (COAD) is a leading cause of cancer‐related mortality, with limited therapies for advanced stages. Efferocytosis, the clearance apoptotic cells, modulates tumor immunity and progression. We investigated efferocytosis‐related genes (ERRGs) in COAD through multiomics integration. Methods analyzed data from public databases to identify differentially expressed ERRGs their molecular subtypes. An ERRG score index was developed using integrated machine learning algorithms evaluate its predictive capacity. Single‐cell sequencing vitro functional assays were performed validate key findings. Results Among 162 ERRGs, 22 dysregulated COAD. Three subtypes exhibited distinct prognoses, immune profiles, therapy responses. The system accurately predicted clinical outcomes, low scores correlating improved survival sensitivity certain drugs. analysis highlighted TIMP1 as regulator, confirmed by knockdown suppressing proliferation migration vitro. Conclusion demonstrate prognostic therapeutic relevance COAD, providing insights into subtyping immunotherapy prediction. emerges potential target, warranting further validation.

Language: Английский

Integration of Machine Learning Algorithms and Single‐Cell Sequencing Analysis Reveals the Efferocytosis‐Related Molecular Subtype and Prognostic Scoring Index in Colon Adenocarcinoma DOI

Kun Ju,

Xiaolei Liu, Qian Wang

et al.

Journal of Gastroenterology and Hepatology, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

ABSTRACT Background Colon adenocarcinoma (COAD) is a leading cause of cancer‐related mortality, with limited therapies for advanced stages. Efferocytosis, the clearance apoptotic cells, modulates tumor immunity and progression. We investigated efferocytosis‐related genes (ERRGs) in COAD through multiomics integration. Methods analyzed data from public databases to identify differentially expressed ERRGs their molecular subtypes. An ERRG score index was developed using integrated machine learning algorithms evaluate its predictive capacity. Single‐cell sequencing vitro functional assays were performed validate key findings. Results Among 162 ERRGs, 22 dysregulated COAD. Three subtypes exhibited distinct prognoses, immune profiles, therapy responses. The system accurately predicted clinical outcomes, low scores correlating improved survival sensitivity certain drugs. analysis highlighted TIMP1 as regulator, confirmed by knockdown suppressing proliferation migration vitro. Conclusion demonstrate prognostic therapeutic relevance COAD, providing insights into subtyping immunotherapy prediction. emerges potential target, warranting further validation.

Language: Английский

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