UAMS Smoldering Myeloma Timeline Cohort

To better understand the pattern of genetic changes over time, we performed whole exome sequencing of sequential bone marrow samples from 9 patients taken overtime including some paired SMM/newly diagnosed MM/Relapse MM samples. Samples from 9 patients (9 controls and 53 tumors) underwent whole exome sequencing with an additional capture for the IGH, IHK, IGL, and MYC loci. DNA was obtained from either CD138+ cells from the bone marrow of smoldering myeloma patients through time (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using NimbleGen's MedExome. After PCR amplification hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.

Type: Other
Archiver: EGA European Genome-Phenome Archive

1 Dataset 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001005056	To better understand the pattern of genetic changes over time, we performed whole exome sequencing of sequential bone marrow samples from 9 patients taken overtime including some paired SMM/newly diagnosed MM/Relapse MM samples. Samples from 9 patients (9 controls and 53 tumors) underwent whole exome sequencing with an additional capture for the IGH, IHK, IGL, and MYC loci. DNA was obtained from either CD138+ cells from the bone marrow of smoldering myeloma patients through time (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using NimbleGen's MedExome. After PCR amplification hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.	NextSeq 500	62

Publications	Citations
The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma. Boyle EM, Deshpande S, Tytarenko R, Ashby C, Wang Y, Bauer MA, Johnson SK, Wardell CP, Thanendrarajan S, Zangari M, Facon T, Dumontet C, Barlogie B, Arbini A, Rustad EH, Maura F, Landgren O, Zhan F, van Rhee F, Schinke C, Davies FE, Morgan GJ, Walker BA. Nat Commun 12: 2021 293	33
Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes. Bustoros M, Anand S, Sklavenitis-Pistofidis R, Redd R, Boyle EM, Zhitomirsky B, Dunford AJ, Tai YT, Chavda SJ, Boehner C, Neuse CJ, Rahmat M, Dutta A, Casneuf T, Verona R, Kastritis E, Trippa L, Stewart C, Walker BA, Davies FE, Dimopoulos MA, Bergsagel PL, Yong K, Morgan GJ, Aguet F, Getz G, Ghobrial IM. Nat Commun 13: 2022 3449	5

Publications

Citations

The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma.
Boyle EM, Deshpande S, Tytarenko R, Ashby C, Wang Y, Bauer MA, Johnson SK, Wardell CP, Thanendrarajan S, Zangari M, Facon T, Dumontet C, Barlogie B, Arbini A, Rustad EH, Maura F, Landgren O, Zhan F, van Rhee F, Schinke C, Davies FE, Morgan GJ, Walker BA. Nat Commun 12: 2021 293

Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes.
Bustoros M, Anand S, Sklavenitis-Pistofidis R, Redd R, Boyle EM, Zhitomirsky B, Dunford AJ, Tai YT, Chavda SJ, Boehner C, Neuse CJ, Rahmat M, Dutta A, Casneuf T, Verona R, Kastritis E, Trippa L, Stewart C, Walker BA, Davies FE, Dimopoulos MA, Bergsagel PL, Yong K, Morgan GJ, Aguet F, Getz G, Ghobrial IM. Nat Commun 13: 2022 3449