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Updated: Jul 1, 2026
Profiling Ubiquitin and Ubiquitin-like Dependent Post-translational Modifications and Identification of Significant Alterations
Published on: November 7, 2019
Identifying of Ubiquitin-Fold Modifier 1 as a Potential Prognostic Biomarker for Unresectable Pancreatic Cancer by
Juan Wang1, Kun Xu2, Longjin Xu3
1Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People's Republic of China.
Background:
The prognosis for unresectable pancreatic cancer remains poor, with limited biomarkers available to predict treatment response and survival. This study aimed to identify novel protein biomarkers associated with therapeutic resistance in this disease.
Methods:
We performed proteomic analysis by Data-Independent Acquisition mass spectrometry on FFPE tissues from 10 patients with unresectable pancreatic cancer, comparing treatment-sensitive and treatment-resistant groups. Differentially expressed proteins were identified, and the candidate was validated by immunohistochemistry in an independent cohort of 91 patients. Survival analysis and Cox regression were used to evaluate the prognostic significance of protein expression.
Results:
In this study, proteomic analysis revealed Ubiquitin-fold modifier 1 (UFM1) as a significantly upregulated protein in treatment-resistant. High UFM1 expression was significantly associated with advanced TNM stage (P < 0.05) and poorer treatment response (P = 0.016). Patients with high UFM1 expression had significantly shorter median PFS (6.5 vs 12.0 months; HR = 0.335, 95% CI: 0.209-0.537, P < 0.001) and OS (10.4 vs 20.5 months; HR = 0.298, 95% CI: 0.184-0.484, P < 0.001) compared to those with low expression. Multivariate Cox regression confirmed UFM1 as an independent prognostic factor for both PFS (HR = 0.343, P < 0.001) and OS (HR = 0.304, P < 0.001).
Conclusion:
UFM1 is a promising prognostic biomarker for unresectable pancreatic cancer, with high expression indicating aggressive disease and inferior outcomes. These findings support its potential utility in risk stratification and treatment personalization.
