ASCI / Emerging-Generation Awards, 2026

Amin Nassar, MD, is a physician–scientist whose research bridges human genetics, immunology, and computational science to advance precision oncology. A medical oncologist and post-doctoral fellow at Yale, Dr. Nassar has published more than 70 peer-reviewed papers, including 21 as first or co–first author in leading journals such as The New England Journal of Medicine, Cancer Cell, and Nature Communications. His work integrates genomic analysis, population genetics, and translational science to redefine how biomarkers are developed, validated, and equitably applied in cancer care. His early studies at Dana-Farber Cancer Institute revealed ancestry-related biases in an FDA-approved biomarker, tumor mutational burden (TMB), and led to a recalibration approach that improves biomarker accuracy and equity across diverse patient populations. He next showed that next-generation sequencing detects mismatch-repair deficiency with far greater precision than immunohistochemistry, transforming how this FDA-approved biomarker is used to guide immunotherapy. This discovery will inform future diagnostic standards and help expand access to effective immunotherapies worldwide. More recently, he co-led a Nature Communications study mapping the molecular and clinical landscape of large-cell neuroendocrine carcinoma, nominating novel therapeutic vulnerabilities in this rare and aggressive lung cancer subtype.

At Yale, Dr. Nassar’s research unites human genetics, clinical informatics, and artificial intelligence to predict toxicity and optimize therapeutic precision in immuno-oncology. His work has been recognized with multiple national awards, eight invited lectureships, and editorial appointments across top oncology journals, underscoring his emerging leadership in the field. Dr. Nassar’s long-term vision is to build a multidisciplinary laboratory that integrates computational modeling, population genomics, and translational immunology to generate predictive, ancestry-inclusive biomarkers and clinically deployable algorithms that personalize cancer therapy—fulfilling the promise of precision immuno-oncology for every patient.