A novel tumor cell origin-based risk score (TCOMRS) to predict liver metastasis and guide treatment in colon adenocarcinoma
Year: 2026
Type: article
Abstract: Background: Liver metastasis (LM) is a major determinant of poor prognosis in colon adenocarcinoma (COAD), yet reliable biomarkers for identifying patients at high metastatic risk remain limited. This study aimed to develop and validate a tumor cell origin-based metastasis risk score (TCOMRS) for characterizing LM-associated transcriptional features in COAD and to identify key molecular regulators involved in liver metastatic progression. Methods: Single-cell RNA sequencing (scRNA-seq) profiles from primary tumors and LM were integrated to identify distinct malignant-cell subpopulations and delineate their cellular origins. TCOMRS was constructed based on a one-class logistic regression (OCLR) algorithm trained with 4,512 malignant cells derived from LM, enabling assessment of the similarity between primary tumor cells and LM-associated malignant phenotypes. The clinical relevance of TCOMRS was validated across multiple independent cohorts, including The Cancer Genome Atlas (TCGA)-COAD, GSE39582, GSE38832, and GSE161158. Results: Elevated TCOMRS was consistently associated with unfavorable overall survival, increased tumor stemness, and the presence of LM. Moreover, patients with low TCOMRS demonstrated improved responsiveness to immune checkpoint blockade therapy, suggesting potential utility in therapeutic decision-making. Mechanistically, fatty acid-binding protein 1 (FABP1) was identified as a key driver of LM, facilitating epithelial-mesenchymal transition and metastatic colonization. FABP1 expression correlated strongly with TCOMRS and metastatic propensity. Conclusions: Our findings establish TCOMRS as a robust biomarker for risk stratification and FABP1 as a promising therapeutic target, offering valuable insights for personalized treatment strategies in COAD.
Source: Translational Cancer Research
Language: English
Topic: Cancer Cells and Metastasis
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7224112708