Comprehensive multiplexed autoantibody profiling of patients with advanced urothelial cancer
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View abstract on PubMed
Summary
This summary is machine-generated.This study profiled autoantibodies (AAbs) in metastatic urothelial cancer (mUC), identifying specific AAbs elevated in mUC patients and those linked to immune checkpoint inhibitor (ICI) therapy response. Further research is needed to understand humoral immunity in UC.
Area Of Science
- Oncology
- Immunology
- Cancer Biomarkers
Background
- Comprehensive autoantibody (AAb) profiling in metastatic urothelial cancer (mUC) is lacking.
- AAbs may aid in UC diagnosis, identify therapeutic targets, and correlate with treatment response and toxicity.
Purpose Of The Study
- To conduct a comprehensive profiling of AAbs in mUC patients.
- To identify AAbs associated with mUC diagnosis, response to systemic therapies (ICI and platinum-based chemotherapy), and immune-related adverse events (irAEs).
Main Methods
- Serum samples from 66 mUC patients and 38 healthy controls (HCs) were analyzed using the SeroTag immuno-oncology discovery array.
- AAbs against 1132 antigens were quantified, and associations with radiographic response and irAEs were evaluated using statistical models.
- Patients received either immune checkpoint inhibitors (ICI) or platinum-based chemotherapy (PBC).
Main Results
- Significantly elevated AAbs against cancer/testis antigens, HSPA1A, TP53, KRAS, and FGFR3 were found in mUC patients compared to HCs.
- Specific AAbs were associated with response (BRCA2, TP53, CTNBB1) or resistance (BICD2, UACA) to ICI therapy.
- AAbs against MITF, CDH3, and KDM4A correlated with irAE development in ICI-treated patients; higher AAb variance was linked to ICI response.
Conclusions
- This is the first comprehensive AAb profiling in mUC, identifying key AAbs elevated in mUC and those associated with ICI response.
- Findings are hypothesis-generating, necessitating further mechanistic studies on humoral immunity in urothelial cancer.
- Identified AAbs may serve as potential diagnostic or predictive biomarkers for mUC and its treatment outcomes.
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