Biochemical network analysis of protein-protein interactions to follow-up T1 bladder cancer patients

Abstract

Bladder cancer (BCa) is a prevalent disease with a high risk of aggressive recurrence in T1-stage patients. Despite the efforts to anticipate recurrence, a reliable method has yet to be developed. In this work, we employed high-resolution mass spectrometry to compare the urinary proteome of T1-stage BCa patients with recurring versus non-recurring disease to uncover actionable clinical information predicting recurrence. All patients were diagnosed with T1-stage bladder cancer between the ages of 51 and 91, and urine samples were collected before medical intervention. Our results suggest that the urinary myeloperoxidase to cubilin ratio could be used as a new tool for predicting recurrence and that dysregulation of the inflammatory and immune systems may be a key driver of disease worsening. Furthermore, we identified neutrophil degranulation and neutrophil extracellular traps (NETs) as key pathways in the progression of T1-stage BCa. We propose that proteomics follow-up of the inflammatory and immune systems may be useful for monitoring the effectiveness of therapy. Significance: This article describes how proteomics can be used to characterize tumor aggressiveness in patients with the same diagnosis of bladder cancer (BCa). LC-MS/MS in combination with label free quantification (LFQ) were used to explore potential protein and pathway level changes related to the aggressiveness of the disease in 13 and 17 recurring and non-recurring T1 stage BCa patients. We have shown that the MPO/CUBN protein ratio is a candidate for a urine prognosis tool in BCa. Furthermore, we identify dysregulation of inflammation process as a driver for BCa recurrence and progression. Moreover, we propose using proteomics to track the effectiveness of therapy in the inflammatory and immune systems.