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HuProt identifies autoantibody signatures that have the potential to predict disease recurrence.
REQUEST INFOCancer research and treatment has been revolutionized with the advent of immune-based cancer therapy, also known as immunotherapy or immuno-oncology (IO). Unlike traditional cancer treatments like chemotherapy and radiation therapy, which aim to directly target cancer cells, immunotherapy works by enhancing or restoring the immune system\'s ability to detect and attack cancer cells. Checkpoint inhibitors are an example of this approach. These drugs block inhibitory checkpoints on immune cells, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1), allowing the immune system to recognize and attack cancer cells more effectively. Drugs like ipilimumab (targeting CTLA-4), pembrolizumab, and nivolumab (targeting PD-1) are examples of checkpoint inhibitors approved for various cancer types.
In the featured publication, HuProt™ microarray was used to identify autoantibody signatures that have the potential to predict both disease recurrence and immune-related adverse events in melanoma patients treated with checkpoint inhibitor adjuvant immunotherapy.
In addition to serum profiling applications, HuProt is an invaluable target identification tool which enables discovery of diverse tumor-associated targets at a proteome-wide scale. Applications include:
Purpose
Adjuvant immunotherapy produces durable benefit for patients with resected melanoma, but many develop recurrence and/or immune-related adverse events (irAE). We investigated whether baseline serum autoantibody (autoAb) signatures predicted recurrence and severe toxicity in patients treated with adjuvant nivolumab, ipilimumab, or ipilimumab plus nivolumab.
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