Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 Mar;476(3):337-351.
doi: 10.1007/s00428-019-02725-3. Epub 2019 Dec 17.

A review on tumor heterogeneity and evolution in multiple myeloma: pathological, radiological, molecular genetics, and clinical integration

Affiliations
Free article
Review

A review on tumor heterogeneity and evolution in multiple myeloma: pathological, radiological, molecular genetics, and clinical integration

Christian M Schürch et al. Virchows Arch. 2020 Mar.
Free article

Abstract

Recent research has dramatically advanced our understanding of the genetic basis of multiple myeloma (MM). MM displays enormous inter- and intratumoral heterogeneity, and underlies a clonal evolutionary process driven and shaped by diverse factors such as clonal competition, tumor microenvironment, host immunity, and therapy. Two main cytogenetic groups are distinguished: MM with recurrent translocations involving the immunoglobulin heavy chain locus and MM with hyperdiploidy involving the odd chromosomes. The disease virtually always starts with a preneoplastic prodromal phase-monoclonal gammopathy of undetermined significance-that variably progresses to symptomatic MM within a few months or many years. Tumor heterogeneity and its evolution in space and time have important consequences for the clinical management and outcome of MM patients. At diagnosis, spatial intratumoral heterogeneity poses a challenge for classification and risk stratification. During maintenance therapy, clonal evolution may complicate disease monitoring and promote drug resistance. Upon progression or transformation, identifying the dominant disease-driving neoplastic clones and elucidating their properties are key to tailor personalized therapy. In this review, we discuss tumor heterogeneity and clonal evolution in MM, integrating pathological, radiological, molecular genetics, and clinical data. Current and prospective classification schemes and prognostic parameters, incorporating new genetic and proteomic discoveries and advances in imaging, are highlighted. In addition, the roles of the tumor microenvironment, host immunity, and resistance mutations, and their effects on therapy, are discussed. An improved understanding of high-risk disease, tumor heterogeneity, and clonal evolution will guide future therapies and may ultimately lead towards a cure for MM.

Keywords: Multiple myeloma; Personalized medicine; Plasma cell neoplasms; Review; Tumor evolution; Tumor heterogeneity.

PubMed Disclaimer

References

    1. Manier S, Salem KZ, Park J, Landau DA, Getz G, Ghobrial IM (2017) Genomic complexity of multiple myeloma and its clinical implications. Nat Rev Clin Oncol 14:100–113. https://doi.org/10.1038/nrclinonc.2016.122 - DOI - PubMed
    1. Palumbo A, Avet-Loiseau H, Oliva S, Lokhorst HM, Goldschmidt H, Rosinol L, Richardson P, Caltagirone S, Lahuerta JJ, Facon T, Bringhen S, Gay F, Attal M, Passera R, Spencer A, Offidani M, Kumar S, Musto P, Lonial S, Petrucci MT, Orlowski RZ, Zamagni E, Morgan G, Dimopoulos MA, Durie BG, Anderson KC, Sonneveld P, San Miguel J, Cavo M, Rajkumar SV, Moreau P (2015) Revised international staging system for multiple myeloma: a report from International Myeloma Working Group. J Clin Oncol 33:2863–2869. https://doi.org/10.1200/JCO.2015.61.2267 - DOI - PubMed - PMC
    1. Bianchi G, Munshi NC (2015) Pathogenesis beyond the cancer clone(s) in multiple myeloma. Blood 125:3049–3058. https://doi.org/10.1182/blood-2014-11-568881 - DOI - PubMed - PMC
    1. Swanton C (2012) Intratumor heterogeneity: evolution through space and time. Cancer Res 72:4875–4882. https://doi.org/10.1158/0008-5472.CAN-12-2217 - DOI - PubMed - PMC
    1. Ding L, Wendl MC, McMichael JF, Raphael BJ (2014) Expanding the computational toolbox for mining cancer genomes. Nat Rev Genet 15:556–570. https://doi.org/10.1038/nrg3767 - DOI - PubMed - PMC