Neutral tumor evolution in myeloma is associated with poor prognosis.

Recent studies suggest that the evolutionary history of a cancer is important in forecasting clinical outlook. To gain insight into the clonal dynamics of multiple myeloma (MM) and its possible influence on patient outcomes, we analyzed whole exome sequencing tumor data for 333 patients from Myeloma XI, a UK phase 3 trial and 434 patients from the CoMMpass study, all of which had received immunomodulatory drug (IMiD) therapy. By analyzing mutant allele frequency distributions in tumors, we found that 17% to 20% of MM is under neutral evolutionary dynamics. These tumors are associated with poorer patient survival in nonintensively treated patients, which is consistent with the reduced therapeutic efficacy of microenvironment-modulating IMiDs. Our findings provide evidence that knowledge of the evolutionary history of MM has relevance for predicting patient outcomes and personalizing therapy.

[1]  G. Morgan,et al.  Prediction of outcome in newly diagnosed myeloma: a meta-analysis of the molecular profiles of 1905 trial patients , 2017, Leukemia.

[2]  Florian Markowetz,et al.  A saltationist theory of cancer evolution , 2016, Nature Genetics.

[3]  Funda Meric-Bernstam,et al.  Punctuated Copy Number Evolution and Clonal Stasis in Triple-Negative Breast Cancer , 2016, Nature Genetics.

[4]  N. Munshi,et al.  APRIL and BCMA promote human multiple myeloma growth and immunosuppression in the bone marrow microenvironment. , 2016, Blood.

[5]  Marc J. Williams,et al.  Identification of neutral tumor evolution across cancer types , 2016, Nature Genetics.

[6]  Xuemei Lu,et al.  Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution , 2015, Proceedings of the National Academy of Sciences.

[7]  A. Balmain,et al.  Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers , 2015, Nature Medicine.

[8]  Gordon Cook,et al.  Mutational Spectrum, Copy Number Changes, and Outcome: Results of a Sequencing Study of Patients With Newly Diagnosed Myeloma. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[9]  C. Curtis,et al.  A Big Bang model of human colorectal tumor growth , 2015, Nature Genetics.

[10]  N. McGranahan,et al.  Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. , 2015, Cancer cell.

[11]  Gordon Cook,et al.  APOBEC family mutational signatures are associated with poor prognosis translocations in multiple myeloma , 2014, Nature Communications.

[12]  G. Morgan,et al.  A molecular diagnostic approach able to detect the recurrent genetic prognostic factors typical of presenting myeloma , 2014, Genes, chromosomes & cancer.

[13]  N. Potter,et al.  Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma , 2014, Leukemia.

[14]  G. Parmigiani,et al.  Heterogeneity of genomic evolution and mutational profiles in multiple myeloma , 2014, Nature Communications.

[15]  G. Morgan,et al.  A TC classification-based predictor for multiple myeloma using multiplexed real-time quantitative PCR , 2013, Leukemia.

[16]  Irmtraud M. Meyer,et al.  The clonal and mutational evolution spectrum of primary triple-negative breast cancers , 2012, Nature.

[17]  H. Avet-Loiseau.  Ultra high-risk myeloma. , 2010, Hematology. American Society of Hematology. Education Program.