Integrated single-cell and spatial transcriptomic analyses identify TRIP6 as a prognostic and EMT-associated biomarker in colorectal cancer

Engineering notes

Key topics: autonomous driving, prediction. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Background Colorectal cancer (CRC) is characterized by profound molecular heterogeneity and complex tumor–microenvironment interactions, which contribute to invasion, metastasis, and variable clinical outcomes. More effective prognostic biomarkers and therapeutic targets are still needed. Methods We integrated single-cell RNA sequencing, spatial transcriptomics, multi-cohort bulk transcriptomic data, drug response prediction, and in vitro experiments to characterize malignant epithelial states in CRC and identify clinically relevant biomarkers and candidate therapeutics. Stemness, copy number variation, pathway activity, and cell–cell communication were analyzed at single-cell resolution. A prognostic model was established using epithelial marker genes and validated across TCGA and five GEO cohorts through a consensus machine-learning framework. Drug sensitivity was evaluated using CTRP and PRISM datasets, and candidate compounds were further prioritized through a network-based drug repositioning strategy. Spatial transcriptomics was used to define the tissue localization of key genes, and functional assays were performed to assess the role of TRIP6 in CRC cells. Results Malignant epithelial cells exhibited increased stemness, frequent aneuploidy, enhanced glycolysis, along with upregulation of the Wnt/β-catenin and PI3K-AKT-mTOR signaling cascades. Cell–cell communication analysis revealed prominent extracellular matrix-related interactions linking cancer-associated fibroblasts and epithelial cells, suggesting a microenvironmental contribution driving epithelial–mesenchymal transition (EMT). The prognostic model showed stable predictive performance across independent cohorts. Among the model genes, TRIP6 was identified as a risk-associated candidate and was enriched at the tumor–stroma invasive boundary by spatial transcriptomic analysis. In vitro , TRIP6 knockdown suppressed CRC cell proliferation and migration, promoted apoptosis, and partially reversed EMT-associated marker expression, supporting a potential role for TRIP6 in malignant progression. In addition, drug prediction analyses identified several compounds with potential therapeutic relevance for high-risk patients. Conclusion This study provides a multi-omic framework for understanding CRC progression and suggests that TRIP6 may be involved in linking microenvironmental signaling to invasive phenotypes, with potential value for prognostic stratification and therapeutic exploration.

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