TCOF1 in Extracellular Vesicles predicts survival in HCC patients treated with High-Dose Conformal Radiotherapy.
2/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: hepatocellular carcinoma undergoing radiation therapy
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
More broadly, these findingssupport the integration of EV-based biomarkers into translational research and the development of noninvasive approaches to personalized cancer care. [CLINICAL TRIAL NUMBER] DRKS00010587.
OpenAlex 토픽 ·
Extracellular vesicles in disease
Erythropoietin and Anemia Treatment
Venous Thromboembolism Diagnosis and Management
[BACKGROUND & AIMS] Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide.
- p-value p<0.05
- p-value p<0.001
APA
Daniel Puhr-Westerheide, Elif Ece Ocal, et al. (2026). TCOF1 in Extracellular Vesicles predicts survival in HCC patients treated with High-Dose Conformal Radiotherapy.. JHEP reports : innovation in hepatology, 101853. https://doi.org/10.1016/j.jhepr.2026.101853
MLA
Daniel Puhr-Westerheide, et al.. "TCOF1 in Extracellular Vesicles predicts survival in HCC patients treated with High-Dose Conformal Radiotherapy.." JHEP reports : innovation in hepatology, 2026, pp. 101853.
PMID
41942033 ↗
Abstract 한글 요약
[BACKGROUND & AIMS] Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. The lack of reliable biomarkers to predict treatment response limits patient stratification and personalized therapy. Extracellular vesicles (EVs) represent a minimally invasive source of tumor-derived proteins that may reflect treatment-relevant biological changes. This study investigated EV-based protein profiling in HCC patients undergoing high-dose conformal radiotherapy to identify prognostic biomarkers associated with treatment response and overall survival.
[METHODS] Plasma samples from 37 HCC patients treated with high-dose-rate interstitial brachytherapy (HDR-BT) were analyzed. EVs were isolated using EV-Trap magnetic beads (Tymora Analytical, West Lafayette, IN). Proteomic profiling was performed by mass spectrometry to identify differential protein expression between responders and non-responders. Statistical analyses included Fisher's exact and Mann-Whitney U tests. Survival was assessed using Kaplan-Meier and log-rank tests, and prognostic factors were evaluated by univariate and multivariate Cox regression. A two-sided p<0.05 was considered significant.
[RESULTS] A total of 2,187 unique EV proteins were identified, of which 25 showed differential expression between patients' sub-groups. EV-TCOF1 was strongly associated with poor survival, with HR 6.64 (CI 2.24-19.69) and p<0.001. Multivariate analysis confirmed EV-TCOF1 as an independent predictor of overall survival. IHC analysis supported the tumoral origin of EV-TCOF1. External validation further demonstrated TCOF1 as a robust prognostic marker.
[CONCLUSIONS] EV-TCOF1 emerged as a candidate biomarker associated with therapy response and shorter OS in an explorative cohort of HCC patients undergoing local high-dose conformal radiotherapy. These findings highlight the potential of EV-based proteomics as a minimally invasive tool to refine prognostic assessment in HCC and the emerging role of EV-TCOF1 specifically warrants further investigation to validate its clinical utility.
[IMPACT AND IMPLICATIONS] This study addresses the need for reliable, minimally invasive biomarkers to predict treatment response and survival in patients with hepatocellular carcinoma undergoing radiation therapy. As component of liquid biospy, circulating extracellualr vesicles provide a noninvasive window into tumor biology. EV-associated TCOF1 may inform risk-adapted treatment planning, surveillance strategies and the identification of patients who could benefit from alternative therapies. More broadly, these findingssupport the integration of EV-based biomarkers into translational research and the development of noninvasive approaches to personalized cancer care.
[CLINICAL TRIAL NUMBER] DRKS00010587.
[METHODS] Plasma samples from 37 HCC patients treated with high-dose-rate interstitial brachytherapy (HDR-BT) were analyzed. EVs were isolated using EV-Trap magnetic beads (Tymora Analytical, West Lafayette, IN). Proteomic profiling was performed by mass spectrometry to identify differential protein expression between responders and non-responders. Statistical analyses included Fisher's exact and Mann-Whitney U tests. Survival was assessed using Kaplan-Meier and log-rank tests, and prognostic factors were evaluated by univariate and multivariate Cox regression. A two-sided p<0.05 was considered significant.
[RESULTS] A total of 2,187 unique EV proteins were identified, of which 25 showed differential expression between patients' sub-groups. EV-TCOF1 was strongly associated with poor survival, with HR 6.64 (CI 2.24-19.69) and p<0.001. Multivariate analysis confirmed EV-TCOF1 as an independent predictor of overall survival. IHC analysis supported the tumoral origin of EV-TCOF1. External validation further demonstrated TCOF1 as a robust prognostic marker.
[CONCLUSIONS] EV-TCOF1 emerged as a candidate biomarker associated with therapy response and shorter OS in an explorative cohort of HCC patients undergoing local high-dose conformal radiotherapy. These findings highlight the potential of EV-based proteomics as a minimally invasive tool to refine prognostic assessment in HCC and the emerging role of EV-TCOF1 specifically warrants further investigation to validate its clinical utility.
[IMPACT AND IMPLICATIONS] This study addresses the need for reliable, minimally invasive biomarkers to predict treatment response and survival in patients with hepatocellular carcinoma undergoing radiation therapy. As component of liquid biospy, circulating extracellualr vesicles provide a noninvasive window into tumor biology. EV-associated TCOF1 may inform risk-adapted treatment planning, surveillance strategies and the identification of patients who could benefit from alternative therapies. More broadly, these findingssupport the integration of EV-based biomarkers into translational research and the development of noninvasive approaches to personalized cancer care.
[CLINICAL TRIAL NUMBER] DRKS00010587.
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