Patient Stratification

HuProt for Treatment Strategies and Disease Prediction

Predict disease progression and identify individuals at higher risk of complications or disease recurrence

Patient stratification involves categorizing individuals with a particular disease or condition into subgroups based on the presence or absence of specific autoantibodies. This stratification approach can help tailor treatment strategies, predict disease progression, and identify individuals at higher risk of complications or disease recurrence. For example, patients with certain autoantibodies may have a higher risk of developing complications or experiencing disease flares, as is the case with systemic lupus erythematosus (SLE). By analyzing the pattern of autoantibody reactivity in cancer patients, clinicians can identify distinct subtypes associated with different clinical outcomes or treatment responses.

In the featured publication, baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCL patients. In the discovery phase (n=20) HuProt™ was used to expound AAb profiles. In the verification phase (n=181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. In conclusion this study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the International Prognostic Index (IPI) in DLBCL.