Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease

While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination o...

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Veröffentlicht in:Leukemia 2020-07, Vol.34 (7), p.1866-1874
Hauptverfasser: Mason, Mike J., Schinke, Carolina, Eng, Christine L. P., Towfic, Fadi, Gruber, Fred, Dervan, Andrew, White, Brian S., Pratapa, Aditya, Guan, Yuanfang, Chen, Hongjie, Cui, Yi, Li, Bailiang, Yu, Thomas, Chaibub Neto, Elias, Mavrommatis, Konstantinos, Ortiz, Maria, Lyzogubov, Valeriy, Bisht, Kamlesh, Dai, Hongyue Y., Schmitz, Frank, Flynt, Erin, Dan Rozelle, Danziger, Samuel A., Ratushny, Alexander, Dalton, William S., Goldschmidt, Hartmut, Avet-Loiseau, Herve, Samur, Mehmet, Hayete, Boris, Sonneveld, Pieter, Shain, Kenneth H., Munshi, Nikhil, Auclair, Daniel, Hose, Dirk, Morgan, Gareth, Trotter, Matthew, Bassett, Douglas, Goke, Jonathan, Walker, Brian A., Thakurta, Anjan, Guinney, Justin
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Sprache:eng
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Zusammenfassung:While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involves assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post-challenge analysis identified a novel expression-based risk marker, PHF19 , which has recently been found to have an important biological role in multiple myeloma. Lastly, we show that a simple four feature predictor composed of age, ISS, and expression of PHF19 and MMSET performs similarly to more complex models with many more gene expression features included.
ISSN:0887-6924
1476-5551
DOI:10.1038/s41375-020-0742-z