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Updated: Sep 12, 2025
Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
Published on: February 7, 2021
Autoantibody profiling to predict response to the anti-PD-1 therapy, pembrolizumab, in rare tumors
M H Derbala1, J Hajjar2, B Stephen1
1Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Background:
Immune checkpoint inhibitors (ICIs) have limited response rates in selected patients and can cause potentially life-threatening immune-related adverse events (irAEs). This underscores the urgent need for the development of biomarkers predictive of ICI response. Pre-existing autoantibodies (AAbs) have been linked with responses to ICIs and the development of irAEs. We conducted AAb profiling to assess associations between baseline AAbs and clinical benefit (CB) in patients with rare tumors treated with anti-programmed cell death protein 1-based therapy.
Patients And Methods:
We conducted AAb profiling using Oncimmune's SeroTag multiplex antibody discovery technology and immune oncology array containing 1168 antigens. The study included 41 patients with rare tumors who received pembrolizumab compared with healthy controls. We carried out a significance analysis of microarrays to identify baseline AAbs present in these cancer patients and associations between these AAbs and CB (defined as complete response, partial response, or stable disease for ≥6 months). We also investigated associations between baseline AAbs and time to progression (TTP) and overall survival (OS) using Cox proportional hazards and Kaplan-Meier models.
Results:
Compared with healthy controls, patients with rare tumors had significantly higher levels of several AAbs at baseline, including those against interferon alpha antigens. Ten patients (24%) had CB. Several AAbs, including those targeting DNA ligase III (LIG3), were associated with CB, TTP, and OS.
Conclusion:
The predictive potential of AAbs as biomarkers of ICI therapy is promising. Further evaluation in larger cohorts is needed to validate our findings and elucidate the underlying mechanism.
