ArticleBMC medical genomics2025
Multi-modal characteristics of LncRNA-derived subtypes in colorectal cancer.
Article in BMC medical genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A new paradigm in postoperative colorectal cancer surveillance: integrating advanced imaging and multi-omics.Frontiers in physiology · 2025Review
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7 authors.
Funding
Abstract
backgroundThe growing knowledge of long non-coding RNA (LncRNA) has suggested the role and predictive potential of LncRNA in cancer, but has not been translated into effective practical tools. The morbidity of colorectal cancer (CRC) has been declining because of effective screening tools. However, the mechanism of the disease is not well understood.
methodsThe LncRNAs that extracted using univariable Cox analysis were explored for the potential functions and applied for classification of LncRNA-derived subtypes of CRC. Multi-modal data involving microscope to macroscope levels were applied to evaluate the molecular, cell, and medical image characteristics of LncRNA-derived subtypes. Radiomic signature calculated by LASSO regression analysis was utilized for distinguishing the CRC subtypes. The performance of LncRNA and radiomic signature were assessed with respect to its calibration, discrimination, and clinical usefulness.
resultsThe LncRNA signature composed of 8 LncRNAs significantly associated with prognosis, metabolism, and organismal system showed good performance in patients’ prognosis assessment (AUC, 0.717; time-dependent ROC > 0.71). Patients separated into two subtypes (HRG vs. LRG) based on the LncRNA signature displayed notable prognostic differences (Kaplan-Meier, p < 0.001). Multi-modal analysis indicated obvious heterogeneity between HRG and LRG subgroups, mainly focused on the abnormal enrichment of glycerophospholipid metabolism pathway, different cellular differentiation, and density level characteristics in the tumor region. In addition, the radiomic signature showed good accuracy (AUC, 0.919), discrimination (p < 0.05), and generalization ability (external independent test cohort, p < 0.05) for LncRNA-derived subgroups assessment.
conclusionThis study described the multi-modal characteristics landscape of LncRNA-derived subtypes in CRC and strengthened the connection from microscope to macroscope levels.
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