Abstract
Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.
Original language | English |
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Pages (from-to) | 878-883 |
Number of pages | 6 |
Journal | Cancer discovery |
Volume | 15 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2 May 2025 |