ArticleJournal of hepatocellular carcinoma2026
Plasma Sphingolipid Profiling Predicts Radiosensitivity in Hepatocellular Carcinoma.
Article in Journal of hepatocellular carcinoma, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06864221 (Correlation Between Plasma Sphingolipid Metabolites and the Efficacy of Radiotherapy in Hepatocellular Carcinoma), which is not on this map. Cited by 1 paper.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Correlation Between Plasma Sphingolipid Metabolites and the Efficacy of Radiotherapy in Hepatocellular Carcinoma
Who cites it
1 citing paper in PubMed.
- Convergent adaptive architectures linking chemoresistance and radioresistance in chemoradiotherapy: a systems-level perspective.Frontiers in oncology · 2026Review
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Radiotherapy constitutes a cornerstone in the management of hepatocellular carcinoma (HCC), but its efficacy is limited by radioresistance. Sphingolipids, a class of bioactive lipids, have been implicated in the metabolic reprogramming associated with treatment resistance. However, the potential of circulating sphingolipids as non-invasive biomarkers to predict radiosensitivity in HCC patients remains unexplored. Patients and Methods: This prospective study enrolled 61 HCC patients scheduled for radiotherapy (NCT06864221). Pre-treatment plasma samples were analyzed via LC-MS/MS to quantify 13 sphingolipid species. The primary endpoint was objective response rate (ORR) per mRECIST at 12 weeks. Predictive models were developed using multivariate logistic regression with forward selection and LASSO, evaluated by AUC with bootstrap validation, calibration, and decision curve analysis. Longitudinal analysis was performed in a sub-cohort (n=25) with paired pre- and post-radiotherapy plasma samples. Results: The objective response rate was 54.1%. Univariable analysis identified a distinct sphingolipid signature in responders, characterized by significantly lower S1P and higher levels of CER(d18:1/20:0) and CER(d18:1/24:1). These candidate biomarkers, along with significant clinical variables, were entered into multivariate modeling. The optimal integrated model (Model 1), selected via forward selection, comprised S1P, CER(d18:1/20:0), and the clinical factors ALP and TBIL, and excelled at predicting response (bootstrap-corrected AUC=0.930). A second model based on ceramide/S1P balance (CER(d18:1/26:1)/S1P, Total CER(d18:1)/S1P, AFP) also performed robustly (bootstrap-corrected AUC=0.828). Both models showed clinical utility per decision curve analysis. Longitudinal analysis revealed a coordinated metabolic shift in responders, with reduced S1P and elevated CER(d18:1/26:0), supporting a radiation-induced "sphingolipid rheostat" shift toward apoptosis. Conclusion: This exploratory study provides the first clinical evidence that the baseline plasma sphingolipid profile is a potent, non-invasive predictor of HCC radiosensitivity, validating the "sphingolipid rheostat" theory. Our findings establish a framework for sphingolipid-guided precision radiotherapy and lay the necessary groundwork for future large-scale, multi-center validation trials, which hold significant potential to refine patient stratification and advance the development of novel metabolism-targeted interventions.
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