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Molecular characterization stratifies VQ myeloma cells into two clusters with distinct risk signatures and drug responses

Oncogene volume 42, pages 1751–1762 (2023)Cite this article

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Abstract

Multiple myeloma (MM) is a cancer of malignant plasma cells in the bone marrow and extramedullary sites. We previously characterized a VQ model for human high-risk MM. The various VQ lines display different disease phenotypes and survival rates, suggesting significant intra-model variation. Here, we use whole-exome sequencing and copy number variation (CNV) analysis coupled with RNA-Seq to stratify the VQ lines into corresponding clusters: Group A cells had monosomy chromosome (chr) 5 and overexpressed genes and pathways associated with sensitivity to bortezomib (Btz) treatment in human MM patients. By contrast, Group B VQ cells carried recurrent amplification (Amp) of chr3 and displayed high-risk MM features, including downregulation of Fam46c, upregulation of cancer growth pathways associated with functional high-risk MM, and expression of Amp1q and high-risk UAMS-70 and EMC-92 gene signatures. Consistently, in sharp contrast to Group A VQ cells that showed short-term response to Btz, Group B VQ cells were de novo resistant to Btz in vivo. Our study highlights Group B VQ lines as highly representative of the human MM subset with ultrahigh risk.

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Fig. 1: B-cell receptor repertoire analysis shows dominant clonality and low somatic hypermutation (SHM) rates in primary VQ cells and VQ cell lines.
Fig. 2: Whole-exome sequencing identifies recurrently mutated genes in VQ myeloma cells.
Fig. 3: Copy number variation (CNV) analysis stratifies VQ cells based on recurrent amplification of chromosome 3 and monosomy chromosome 5.
Fig. 4: RNA-Seq analysis reveals two distinct transcriptional clusters of VQ myeloma.
Fig. 5: VQ Group B myeloma cells have increased expression of cancer growth pathways and Amp1q-associated PBX1-FOXM1 gene signatures.
Fig. 6: High-risk multiple myeloma gene signatures are enriched in VQ Group B compared to VQ Group A and t-Vk12653 Vĸ*Myc cells.
Fig. 7: Group A and Group B VQ cells display distinct responses to bortezomib in vivo.

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Data availability

The next-generation sequencing datasets generated and analyzed during the current study are available in the Sequence Read Archive (SRA) at https://www.ncbi.nlm.nih.gov/sra, with BioProject accession number PRJNA947112, and Gene Expression Omnibus (GEO) at https://www.ncbi.nlm.nih.gov/geo, with accession number GSE226833. The code and scripts for data analysis are deposited onto Github: https://github.com/BRIwanglab/Oncogene2023.

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Acknowledgements

We would like to thank the University of Wisconsin Carbone Comprehensive Cancer Center (UWCCC) for use of its Shared Services (Small Molecule Screening Facility, Flow Cytometry Laboratory, Transgenic Animal Facility, and Experimental Pathology Laboratory) to complete this research. We would also like to thank Dr. Robert Burns for his assistance in initiating the CNV study. The Graphical Abstract for this work was created with BioRender.com. This work was supported by a fellowship from the NIH grant T32 GM081061 to EF, the startup fund 252840-00 from Marshfield Clinic Research Foundation to ZW, R01CA252937 to FA, R01CA152108 to JZ, R01AI079087 and R01HL130724 to DW, and additional support from the Trillium Fund, UWCCC Developmental Therapeutics Program Pilot Awards, and Immunotherapy Pilot Award.

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  1. These authors contributed equally: Evan Flietner, Mei Yu.

Authors and Affiliations

  1. McArdle Laboratory for Cancer Research, University of Wisconsin-Madison, Madison, WI, 53705, USA

    Evan Flietner, Govinda Poudel, Yun Zhou, Adhithi Rajagopalan, Yubin Feng, Yuqian Sun & Jing Zhang

  2. Department of Pathology and Laboratory Medicine, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53705, USA

    Evan Flietner

  3. Versiti Blood Research Institute, Milwaukee, WI, 53226, USA

    Mei Yu, Anthony J. Veltri & Demin Wang

  4. Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, 55902, USA

    Terra Lasho & Mrinal M. Patnaik

  5. Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA

    Zhi Wen

  6. Division of Hematology/Oncology, Department of Medicine, UW Comprehensive Cancer Center, University of Wisconsin-Madison, Madison, WI, 53705, USA

    Natalie S. Callander

  7. Division of Blood and Marrow Transplantation, Department of Medicine and Moores Cancer Center, University of California, San Diego, La Jolla, CA, 92093, USA

    Fotis Asimakopoulos

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Contributions

Conception and experimental design: EF, MY, DW and JZ. Experimental execution and data analysis: EF, MY, GP, AR, AJV, YZ, YF, YS and ZW. Technical and material support: TL and MMP. Writing, review, and/or revision of the manuscript: EF, MY, AJV, ZW, NSC, FA, DW and JZ. Study supervision: DW and JZ.

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Correspondence to Demin Wang or Jing Zhang.

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Flietner, E., Yu, M., Poudel, G. et al. Molecular characterization stratifies VQ myeloma cells into two clusters with distinct risk signatures and drug responses. Oncogene 42, 1751–1762 (2023). https://doi.org/10.1038/s41388-023-02684-9

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