Comprehensive genomic analysis of refractory multiple myeloma reveals a complex mutational landscape associated with drug resistance and novel therapeutic vulnerabilities
Nicola Giesen,
Nagarajan Paramasivam,
Umut H. Toprak,
Daniel Huebschmann,
Jing Xu,
Sebastian Uhrig,
Mehmet Samur,
Stella Bähr,
Martina Fröhlich,
Sadaf S. Mughal,
Elias K. Mai,
Anna Jauch,
Carsten Müller-Tidow,
Benedikt Brors,
Nikhil Munshi,
Hartmut Goldschmidt,
Niels Weinhold,
Matthias Schlesner,
Marc S. Raab
Affiliations
Nicola Giesen
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Molecular Hematology/Oncology, Department of Internal Medicine V, Heidelberg University Hospital, and German Cancer Research Center (DKFZ), Heidelberg, Germany
Nagarajan Paramasivam
Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Heidelberg, Germany; Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg, Germany
Umut H. Toprak
Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Neuroblastoma Genomics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Daniel Huebschmann
Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg, Germany; Heidelberg Institute for Stem cell Technology and Experimental Medicine (HI-STEM), Heidelberg, Germany; Department of Pediatric Immunology, Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany; German Cancer Consortium (DKTK), Core Center Heidelberg, Germany
Jing Xu
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Molecular Hematology/Oncology, Department of Internal Medicine V, Heidelberg University Hospital, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Sebastian Uhrig
Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg, Germany; Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Mehmet Samur
Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
Stella Bähr
Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg, Germany
Martina Fröhlich
Computational Oncology, Molecular Diagnostics Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ) Heidelberg, Germany; Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Sadaf S. Mughal
Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Elias K. Mai
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
Anna Jauch
Institute for Human Genetics, Heidelberg University Hospital, Heidelberg, Germany
Carsten Müller-Tidow
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
Benedikt Brors
German Cancer Consortium (DKTK), Core Center Heidelberg, Germany; Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
Nikhil Munshi
Jerome Lipper Multiple Myeloma Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
Hartmut Goldschmidt
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
Niels Weinhold
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany
Matthias Schlesner
Bioinformatics and Omics Data Analytics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Marc S. Raab
Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Molecular Hematology/Oncology, Department of Internal Medicine V, Heidelberg University Hospital, and German Cancer Research Center (DKFZ), Heidelberg, Germany
The outcomes of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs) remain poor. In this study, we performed whole genome and transcriptome sequencing of 39 heavily pretreated relapsed/refractory MM (RRMM) patients to identify mechanisms of resistance and potential therapeutic targets. We observed a high mutational load and indications of increased genomic instability. Recurrently mutated genes in RRMM, which had not been previously reported or only observed at a lower frequency in newly diagnosed MM, included NRAS, BRAF, TP53, SLC4A7, MLLT4, EWSR1, HCFC2, and COPS3. We found multiple genomic regions with bi-allelic events affecting tumor suppressor genes and demonstrated a significant adverse impact of bi-allelic TP53 alterations on survival. With regard to potentially resistance conferring mutations, recurrently mutated gene networks included genes with relevance for PI and IMiD activity; the latter particularly affecting members of the Cereblon and the COP9 signalosome complex. We observed a major impact of signatures associated with exposure to melphalan or impaired DNA double-strand break homologous recombination repair in RRMM. The latter coincided with mutations in genes associated with PARP inhibitor sensitivity in 49% of RRMM patients; a finding with potential therapeutic implications. In conclusion, this comprehensive genomic characterization revealed a complex mutational and structural landscape in RRMM and highlights potential implications for therapeutic strategies.