Dataset Information

The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma.

ABSTRACT: The development of sensitive and non-invasive "liquid biopsies" presents new opportunities for longitudinal monitoring of tumor dissemination and clonal evolution. The number of circulating tumor cells (CTCs) is prognostic in multiple myeloma (MM), but there is little information on their genetic features. Here, we have analyzed the genomic landscape of CTCs from 29 MM patients, including eight cases with matched/paired bone marrow (BM) tumor cells. Our results show that 100% of clonal mutations in patient BM were detected in CTCs and that 99% of clonal mutations in CTCs were present in BM MM. These include typical driver mutations in MM such as in KRAS, NRAS, or BRAF. These data suggest that BM and CTC samples have similar clonal structures, as discordances between the two were restricted to subclonal mutations. Accordingly, our results pave the way for potentially less invasive mutation screening of MM patients through characterization of CTCs.

SUBMITTER: Mishima Y

PROVIDER: S-EPMC5439509 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Publications

The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma.

Mishima Yuji Y Paiva Bruno B Shi Jiantao J Park Jihye J Manier Salomon S Takagi Satoshi S Massoud Mira M Perilla-Glen Adriana A Aljawai Yosra Y Huynh Daisy D Roccaro Aldo M AM Sacco Antonio A Capelletti Marzia M Detappe Alexandre A Alignani Diego D Anderson Kenneth C KC Munshi Nikhil C NC Prosper Felipe F Lohr Jens G JG Ha Gavin G Freeman Samuel S SS Van Allen Eliezer M EM Adalsteinsson Viktor A VA Michor Franziska F San Miguel Jesus F JF Ghobrial Irene M IM

Cell reports 20170401 1

The development of sensitive and non-invasive "liquid biopsies" presents new opportunities for longitudinal monitoring of tumor dissemination and clonal evolution. The number of circulating tumor cells (CTCs) is prognostic in multiple myeloma (MM), but there is little information on their genetic features. Here, we have analyzed the genomic landscape of CTCs from 29 MM patients, including eight cases with matched/paired bone marrow (BM) tumor cells. Our results show that 100% of clonal mutations ...[more]

PMID: 28380360

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Project description:Multiple Myeloma (MM) arises from malignant transformation and deregulated proliferation of clonal plasma cells (PCs) harbouring heterogeneous molecular anomalies. The effect of evolving mutations on clone fitness and their cellular prevalence shapes the progressing myeloma genome and impacts clinical outcomes. Although clonal heterogeneity in MM is well established, which subclonal mutations emerge/persist/perish with progression in MM and which of these can be targeted therapeutically remains an open question. In line with this, we have sequenced pairwise whole exomes of 62 MM patients collected at two time points, i.e., at diagnosis and on progression. Somatic variants were called using a novel ensemble approach where a consensus was deduced from four variant callers (Illumina's Dragen, Strelka2, SomaticSniper and SpeedSeq) and actionable/druggable gene targets were identified. A marked intraclonal heterogeneity was observed. Branching evolution was observed among 72.58% patients, of whom 64.51% had low TMBs (<10) and 61.29% had 2 or more founder clones. The hypermutator patients (with high TMB levels ≥10 to ≤100) showed a significant decrease in their TMBs from diagnosis (median TMB 77.11) to progression (median TMB 31.22). A distinct temporal fall in subclonal driver mutations was identified recurrently across diagnosis to progression e.g., in PABPC1, BRAF, KRAS, CR1, DIS3 and ATM genes in 3 or more patients suggesting such patients could be treated early with target specific drugs like Vemurafenib/Cobimetinib. An analogous rise in driver mutations was observed in KMT2C, FOXD4L1, SP140, NRAS and other genes. A few drivers such as FAT4, IGLL5 and CDKN1A retained consistent distribution patterns at two time points. These findings are clinically relevant and point at consideration of evaluating multi time point subclonal mutational landscapes for designing better risk stratification strategies and tailoring time to time risk adapted combination therapies in future.

Dataset Information

The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma.

Publications

The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma.

Similar Datasets

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