Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma.
Genetic program activity delineates risk, relapse, and therapy responsiveness in multiple myeloma.
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DOI：
10.1038/s41698-021-00185-0
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发表时间：
2021-06-28
影响因子：
7.9
通讯作者：
Baliga NS
中科院分区：
文献类型：
--
作者：
Wall MA;Turkarslan S;Wu WJ;Danziger SA;Reiss DJ;Mason MJ;Dervan AP;Trotter MWB;Bassett D;Hershberg RM;Lomana ALG;Ratushny AV;Baliga NS
Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to multiple lines of therapies. Therefore, we not only need the ability to predict which patients are at high risk for disease progression but also a means to understand the mechanisms underlying their risk. Here, we report a transcriptional regulatory network (TRN) for MM inferred from cross-sectional multi-omics data from 881 patients that predicts how 124 chromosomal abnormalities and somatic mutations causally perturb 392 transcription regulators of 8549 genes to manifest in distinct clinical phenotypes and outcomes. We identified 141 genetic programs whose activity profiles stratify patients into 25 distinct transcriptional states and proved to be more predictive of outcomes than did mutations. The coherence of these programs and accuracy of our network-based risk prediction was validated in two independent datasets. We observed subtype-specific vulnerabilities to interventions with existing drugs and revealed plausible mechanisms for relapse, including the establishment of an immunosuppressive microenvironment. Investigation of the t(4;14) clinical subtype using the TRN revealed that 16% of these patients exhibit an extreme-risk combination of genetic programs (median progression-free survival of 5 months) that create a distinct phenotype with targetable genes and pathways.
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影响因子：
11.5
作者：
Agnelli, Luca;Forcato, Mattia;Neri, Antonino
通讯作者：
Neri, Antonino
影响因子：
50.3
作者：
Anders L;Ke N;Hydbring P;Choi YJ;Widlund HR;Chick JM;Zhai H;Vidal M;Gygi SP;Braun P;Sicinski P
通讯作者：
Sicinski P
影响因子：
--
作者：
Aten JE;Fuller TF;Lusis AJ;Horvath S
通讯作者：
Horvath S
影响因子：
20.3
作者：
Bharti, AC;Shishodia, S;Aggarwal, BB
通讯作者：
Aggarwal, BB
影响因子：
20.3
作者：
Abe, M;Hiura, K;Matsumoto, T
通讯作者：
Matsumoto, T