Dr. Elli Papaemmanuil et al. published the paper Unified classification and risk-stratification in Acute Myeloid Leukemia in Nature Communications. In it they use use comprehensive molecular profiling data from 3,653 patients to characterize and validate 16 molecular classes describing 100% of AML patients. Each class represents diverse biological AML subgroups, and is associated with distinct...Read More

Dr. Kevin M. Boehm et al. published the paper Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer in Nature Cancer. In it they assemble a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discover quantitative features, such as tumor nuclear size on staining with...Read More

Dr. Benjamin Greenbaum co authored the paper, “Neoantigen quality predicts immunoediting in survivors of pancreatic cancer” along with Marta Łuksza et al. in the journal Nature .  In it they investigate how 70 human pancreatic cancers evolved over 10 years. They find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic...Read More

Dr. Elli Papaemmanuil co authored the paper, “Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers” along with N. Shukla et al. in the journal Nature Communications.  In it they explore how the utility of cancer whole genome and transcriptome sequencing (cWGTS) in oncology is increasingly recognized. However, implementation of cWGTS...Read More

Dr. Benjamin Greenbaum co authored the paper “Fundamental immune–oncogenicity trade-offs define driver mutation fitness” along with David Hoyos et al. in the journal Nature. In it, they propose a unified theoretical ‘free fitness’ framework that parsimoniously integrates multimodal genomic, epigenetic, transcriptomic and proteomic data into a biophysical model of the rate-limiting processes underlying the fitness advantage...Read More

Dr. Nikolaus Schultz co authored the paper, “Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients“, along with Nguyen et al. in the journal Cell. In it, they assembled MSK-MET, a pan-cancer cohort of over 25,000 patients with metastatic diseases. By analyzing genomic and clinical data from this cohort, they identified associations...Read More