Computational drug treatment simulations on projections of dysregulated protein networks derived from the myelodysplastic mutanome match clinical response in patients

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• 作者：Leylah Drusbosky^a ; Cindy Medina^a ; Regina Martuscello^a ; ¹ ; Kimberly E. Hawkins^a ; Myron Chang^b ; Jatinder K. Lamba^c ; Shireen Vali^d ; Ansu Kumar^d ; Neeraj Kumar Singh^d ; Taher Abbasi^d ; Mikkael A. Sekeres^e ; Mar Mallo^f ; Francesc Sole^f ; Rafael Bejar^g ; Christopher R. Cogle^a ; ^{christopher.cogle@medicine.ufl.edu}
• 关键词：MDS ; myelodysplastic syndromes ; AML ; acute myeloid leukemia ; AZA ; azacitidine ; DEC ; decitabine ; LEN ; lenalidomide ; HI ; hematological improvement ; SKY ; spectral karyotyping ; CNV ; copy number variation ; IWG ; International Working Group ; HMA ; hypomethylating agent ; PPV ; positive predictive value ; NPV ; negative predictive value ; CR ; complete response ; PR ; partial response
• 刊名：Leukemia Research
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：52
• 期：Complete
• 页码：1-7
• 全文大小：2097 K
• 卷排序：52

文摘

Computer modeling of MDS mutanome predicts response to HMAs with 80–100% accuracy. Modeling of MDS mutanome revealed biomarkers for drug response. Modeling of MDS mutanome unveils resistance pathways to drug therapies. Protein network mapping reveals potential targets of drug therapy.