Work

Pre-diagnostic plasma proteomics profile uncovers new biomarkers and mechanistic insights for incident kidney cancer

Year: 2025

Type: article

Abstract: BACKGROUND: The pathophysiological changes driving incident kidney cancer remain unclear. This study aimed to identify protein biomarkers and underlying mechanisms using pre-diagnostic plasma proteomics. MATERIALS AND METHODS: Among 48 851 UK Biobank participants, 165 were diagnosed with kidney cancer, and 2911 plasma proteins were analyzed. Dynamic changes in significant proteins were assessed up to 15 years before diagnosis using locally estimated scatterplot smoothing method. A mediation analysis using a four-component framework was conducted to evaluate the mediating role of proteomic features in the associations of body mass index (BMI) and smoking with kidney cancer risk. Additionally, an absolute shrinkage and selection operator regression model was developed for proteomics-based risk prediction. RESULTS: Over a follow-up period exceeding 11 years, 24 proteins were significantly associated with kidney cancer risk ( P < 0.05, Bonferroni-corrected for 2911), with Hepatitis A Virus Cellular Receptor 1 (HAVCR1) exhibiting the most statistically significant association (HR = 3.18, 95% CI: 2.70-3.74, P = 1.11 × 10 -40 ). Trajectory modeling revealed that HAVCR1 exhibited the most significant fluctuations, with abnormal expression detectable up to 15 years before diagnosis. Unsupervised clustering identified four distinct protein trajectory patterns, suggesting different mechanisms may drive kidney cancer progression at various stages. Proteomic data mediated the effects of BMI and smoking on cancer risk, contributing 38.6% and 9.2% to the risk, respectively. The proteomic model significantly improved kidney cancer risk prediction compared to the clinical model (concordance index [C-index]: 0.811 vs. 0.713, P = 0.029), with HAVCR1 alone demonstrating comparable discriminative ability (C-index: 0.754). CONCLUSIONS: This large-scale plasma proteomics study highlights the potential of biomarkers, particularly HAVCR1, for early detection and insight into kidney cancer pathophysiology.

Source: International Journal of Surgery

DOI: 10.1097/js9.0000000000003474

Authors: Wen Liu, Wei Chen, Dahai Dong, Guiming Zhang, Nianzeng Xing

Institutions: Chinese Academy of Medical Sciences & Peking Union Medical College, Cancer Hospital of Chinese Academy of Medical Sciences, State Key Laboratory of Molecular Oncology, Affiliated Hospital of Qingdao University

Language: English

Topic: Renal cell carcinoma treatment

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,450