Circulating Tumour DNA Analysis for Tumour Genome Characterisation and Monitoring Disease Burden in Extramedullary Multiple Myeloma.
Sridurga MithraprabhuShreerang SirdesaiMaoshan ChenTiffany KhongAndrew SpencerPublished in: International journal of molecular sciences (2018)
Mutational characterisation in extramedullary multiple myeloma (EM-MM) patients is challenging due to inaccessible EM plasmacytomas, unsafe nature of multiple biopsies and the spatial and temporal genomic heterogeneity apparent in MM (Graphical abstract). Conventional monitoring of disease burden is through serum markers and PET-CT, however these modalities are sometimes inadequate (serum markers), not performed in a timely manner (PET-CT) and uninformative for identifying mutations driving disease progression. DNA released into the blood by tumour cells (ctDNA) contains the predominant clones derived from the multiple disease foci. Blood-derived ctDNA can, therefore, provide a holistic illustration of the major drivers of disease progression. In this report, the utility of ctDNA, as an adjunct to currently available modalities in EM-MM, is presented for a patient with EM and oligosecretory (OS) disease. Whole exome sequencing of contemporaneously acquired tumour tissue and matched ctDNA samples revealed the presence of spatial and temporal genetic heterogeneity and the identification of pathways associated with drug resistance. Longitudinal monitoring of plasma samples revealed that ctDNA can be utilised to define the dynamic clonal evolution co-existent with disease progression and as an adjunct non-invasive marker of tumour burden.
Keyphrases
- pet ct
- circulating tumor
- multiple myeloma
- single cell
- cell free
- positron emission tomography
- circulating tumor cells
- end stage renal disease
- genome wide
- risk factors
- prognostic factors
- gene expression
- magnetic resonance imaging
- computed tomography
- oxidative stress
- magnetic resonance
- cell cycle arrest
- signaling pathway
- cell proliferation
- endoplasmic reticulum stress
- cell death
- bioinformatics analysis