ArticleFrontiers in immunology2025
Single-cell and spatial transcriptomic analysis reveals tumor cell heterogeneity and underlying molecular program in colorectal cancer.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Metastatic immune microenvironment remodeling by malignant epithelial cells drives colorectal cancer hepatic metastasis: Multi-omics insights.Translational oncology · 2026Article
- From Bone Marrow Reserve to Metastatic Niche: How Neutrophil-Lineage Cells Shape Skeletal Colonization.International journal of molecular sciences · 2026Review
- Integrating Genomics, Radiomics, and Pathomics in Oncology: A Scoping Review and a Framework for AI-Enabled Surgomics.Bioengineering (Basel, Switzerland) · 2026Review
- An Insight into the Emerging Role of Extracellular Vesicle-derived Noncoding RNAs in Colorectal Cancer.MicroRNA (Shariqah, United Arab Emirates) · 2026Review
- Integrated perspectives on colorectal carcinogenesis: molecular pathogenesis, genomic alterations, diagnostic paradigms, therapeutic interventions and AI-driven directions in precision oncology.Frontiers in oncology · 2026Review
- Early prediction of pathological complete response in rectal cancer: a dynamic immune remodeling hypothesis during neoadjuvant treatment.Frontiers in oncology · 2026Article
- Immune Gene INHBA is Associated With Osteoarthritic Cartilage Damage and May Mediate the Temporal Activation of the TGF-β/p38 MAPK Pathway: Integrating Multiomics Machine Learning and Experimental Validation.Mediators of inflammation · 2026Article
- CBX8 suppresses autophagy-dependent senescence in colorectal cancer by modulating the mTOR signaling pathway.International journal of biological sciences · 2026Article
- SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.Computational and structural biotechnology journal · 2026Article
- Single-cell and spatial transcriptome profiling identifies the immunosuppressive spatial niche inJournal for immunotherapy of cancer · 2025Article
- Outcomes and survival trends following pelvic exenteration for locally advanced and recurrent rectal cancer: a 20-Year analysis from a tertiary cancer center in India.World journal of surgical oncology · 2025Article
- SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.bioRxiv : the preprint server for biology · 2025Article
- Exploration and Application of Malignant Cell Heterogeneity Analysis with Single-Cell Transcriptome Sequencing Technology.Aging and disease · 2025Review
- Editorial: Deciphering cell-cell interactions in triple-negative breast cancer.Frontiers in immunology · 2025Article
- Microbiota-host metabolism reprogramming in colorectal cancer: from pathogenesis to precision therapies.Frontiers in oncology · 2025Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer (CRC) is a highly heterogeneous tumor, with significant variation in malignant cells, posing challenges for treatment and prognosis. However, this heterogeneity offers opportunities for personalized therapy. Methods: The consensus non-negative matrix factorization algorithm was employed to analyze single-cell transcriptomic data from CRC, which helped identify malignant cell expression programs (MCEPs). Subsequently, a crosstalk network linking MCEPs with immune/stromal cell trajectory development was constructed using Monocle3 and NicheNet. Additionally, bulk RNA-seq data were utilized to systematically explore the relationships between MCEPs, clinical features, and genetic mutations. A prognostic model was then established through Lasso and Cox regression analyses, integrating clinical data into a nomogram for personalized risk prediction. Furthermore, key genes associated with MCEPs and their potential therapeutic targets were identified using protein-protein interaction networks, followed by molecular docking to predict drug-binding affinity. Results: We classified CRC malignant cell transcriptional states into eight distinct MCEPs and successfully constructed crosstalk networks between these MCEPs and immune or stromal cells. A prognostic model containing 15 genes was developed, demonstrating an AUC greater than 0.8 for prognostic evaluation over 1 to 10 years when combined with clinical features. A key drug target gene TIMP1 was identified, and several potential targeted drugs were discovered. Conclusion: This study demonstrated that characterization of the malignant cell transcriptional programs could effectively reveal the biological features of highly heterogeneous tumors like CRC and exhibit significant potential in tumor prognosis assessment. Our research provides new theoretical and practical directions for CRC prognosis and targeted therapy.
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