2. Academic Validation
  3. Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

  • Nat Med. 2023 Mar;29(3):632-645. doi: 10.1038/s41591-022-02178-3.
Marta Larrayoz 1,  Maria J Garcia-Barchino 1,  Jon Celay 1,  Amaia Etxebeste 1,  Maddalen Jimenez 1,  Cristina Perez 1,  Raquel Ordoñez 1,  Cesar Cobaleda 2,  Cirino Botta 1 3,  Vicente Fresquet 1,  Sergio Roa 1,  Ibai Goicoechea 1,  Catarina Maia 1,  Miren Lasaga 1,  Marta Chesi 4,  P Leif Bergsagel 4,  Maria J Larrayoz 1,  Maria J Calasanz 1,  Elena Campos-Sanchez 2,  Jorge Martinez-Cano 2,  Carlos Panizo 5,  Paula Rodriguez-Otero 5,  Silvestre Vicent 6,  Giovanna Roncador 7,  Patricia Gonzalez 7,  Satoru Takahashi 8,  Samuel G Katz 9,  Loren D Walensky 10,  Shannon M Ruppert 11,  Elisabeth A Lasater 12,  Maria Amann 13,  Teresa Lozano 14,  Diana Llopiz 14,  Pablo Sarobe 14,  Juan J Lasarte 14,  Nuria Planell 15,  David Gomez-Cabrero 15 16,  Olga Kudryashova 17,  Anna Kurilovich 17,  Maria V Revuelta 18,  Leandro Cerchietti 18,  Xabier Agirre 1,  Jesus San Miguel 1 5,  Bruno Paiva 1 5,  Felipe Prosper 1 5,  Jose A Martinez-Climent 19
Affiliations

Affiliations

  • 1 Division of Hemato-Oncology, Center for Applied Medical Research CIMA, Cancer Center University of Navarra (CCUN), Navarra Institute for Health Research (IDISNA), CIBERONC, Pamplona, Spain.
  • 2 Immune System Development and Function Unit, Centro de Biologia Molecular Severo Ochoa, Consejo Superior de Investigaciones Cientificas/Universidad Autonoma, Madrid, Spain.
  • 3 Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, University of Palermo, Palermo, Italy.
  • 4 Department of Medicine, Mayo Clinic Arizona, Scottsdale, AZ, USA.
  • 5 Department of Hematology, Clinica Universidad de Navarra, CCUN, IDISNA, CIBERONC, Pamplona, Spain.
  • 6 Program in Solid Tumors, Center for Applied Medical Research CIMA, University of Navarra, IDISNA, CIBERONC, Pamplona, Spain.
  • 7 Monoclonal Antibodies Unit, Biotechnology Program, Spanish National Cancer Research Centre CNIO, Madrid, Spain.
  • 8 Department of Anatomy and Embryology, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.
  • 9 Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
  • 10 Department of Pediatric Oncology and Program in Cancer Chemical Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • 11 Oncology Biomarker Development, Genentech, South San Francisco, CA, USA.
  • 12 Department of Translational Oncology, Genentech, South San Francisco, CA, USA.
  • 13 Roche Innovation Center Zurich, Roche Pharmaceutical Research and Early Development (pRED), Schlieren, Switzerland.
  • 14 Program of Immunology and Immunotherapy, Center for Applied Medical Research CIMA, University of Navarra, IDISNA, CIBEREHD, Pamplona, Spain.
  • 15 Translational Bioinformatics Unit, Navarra-Biomed, Public University of Navarra, IDISNA, Pamplona, Spain.
  • 16 Biological and Environmental Sciences & Engineering Division, King Abdullah University of Science & Technology, Thuwal, Kingdom of Saudi Arabia.
  • 17 BostonGene, Waltham, MA, USA.
  • 18 Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, USA.
  • 19 Division of Hemato-Oncology, Center for Applied Medical Research CIMA, Cancer Center University of Navarra (CCUN), Navarra Institute for Health Research (IDISNA), CIBERONC, Pamplona, Spain. [email protected].
PMID: 36928817 DOI: 10.1038/s41591-022-02178-3
Abstract

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis. Integrative analyses of ∼500 mice and ∼1,000 patients revealed a common MAPK-MYC genetic pathway that accelerated time to progression from precursor states across genetically heterogeneous MM. MYC-dependent time to progression conditioned immune evasion mechanisms that remodeled the BM microenvironment differently. Rapid MYC-driven progressors exhibited a high number of activated/exhausted CD8+ T cells with reduced immunosuppressive regulatory T (Treg) cells, while late MYC acquisition in slow progressors was associated with lower CD8+ T cell infiltration and more abundant Treg cells. Single-cell transcriptomics and functional assays defined a high ratio of CD8+ T cells versus Treg cells as a predictor of response to immune checkpoint blockade (ICB). In clinical series, high CD8+ T/Treg cell ratios underlie early progression in untreated smoldering MM, and correlated with early relapse in newly diagnosed patients with MM under Len/Dex therapy. In ICB-refractory MM models, increasing CD8+ T cell cytotoxicity or depleting Treg cells reversed immunotherapy resistance and yielded prolonged MM control. Our experimental models enable the correlation of MM genetic and immunological traits with preclinical therapy responses, which may inform the next-generation immunotherapy trials.

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