4.7 Article

Functional Impact of Genomic Complexity on the Transcriptome of Multiple Myeloma

Journal

CLINICAL CANCER RESEARCH
Volume 27, Issue 23, Pages 6479-6490

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-20-4366

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Funding

  1. European Research Council under the European Union [817997]
  2. Associazione Italiana Ricerca sul Cancro [IG16722, IG10136, IG24365, IG20541]
  3. Multiple Myeloma Research Foundation
  4. Perelman Family Foundation
  5. Riney Family Multiple Myeloma Research Program Fund
  6. Memorial Sloan Kettering Cancer Center NCI Core Grant [P30 CA 008748]
  7. Sylvester Comprehensive Cancer Center NCI Core Grant [P30 CA 240139]
  8. American Society of Hematology
  9. European Research Council (ERC) [817997] Funding Source: European Research Council (ERC)

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The study identified the impact of gene mutations, copy-number abnormalities, and chromosomal rearrangements on the transcriptome of multiple myeloma patients, revealing distinct effects on deregulated genes, pathways, and biomarkers for personalized treatments. Immunoglobulin translocations, hyperdiploidy, and chr(1q) gain/amps were found to have the highest association with deregulated genes. Mutations in oncogenes and inactivation of tumor suppressor genes had a significant impact on gene expression. Comprehensive analysis helps in identifying specific deregulated pathways and candidate biomarkers for personalized treatments in multiple myeloma.
Purpose: Multiple myeloma is a biologically heterogenous plasma-cell disorder. In this study, we aimed at dissecting the functional impact on transcriptome of gene mutations, copy-number abnormalities (CNA), and chromosomal rearrangements (CR). Moreover, we applied a geno-transcriptomic approach to identify specific biomarkers for personalized treatments. Experimental Design: We analyzed 514 newly diagnosed patients from the IA12 release of the CoMMpass study, accounting for mutations in multiple myeloma driver genes, structural variants, copy-number segments, and raw-transcript counts. We performed an in silico drug sensitivity screen (DSS), interrogating the Cancer Dependency Map (DepMap) dataset after anchoring cell lines to primary tumor samples using the Celligner algorithm. Results: Immunoglobulin translocations, hyperdiploidy and chr(1q)gain/amps were associated with the highest number of deregulated genes. Other CNAs and specific gene mutations had a lower but very distinct impact affecting specific pathways. Many recurrent genes showed a hotspot (HS)-specific effect. The clinical relevance of double-hit multiple myeloma found strong biological bases in our analysis. Biallelic deletions of tumor suppressors and chr(1q)-amplifications showed the greatest impact on gene expression, deregulating pathways related to cell cycle, proliferation, and expression of immunotherapy targets. Moreover, our in silico DSS showed that not only t(11;14) but also chr(1q)gain/amps and CYLD inactivation predicted differential expression of transcripts of the BCL2 axis and response to venetoclax. Conclusions: The multiple myeloma genomic architecture and transcriptome have a strict connection, led by CNAs and CRs. Gene mutations impacted especially with HS-mutations of oncogenes and biallelic tumor suppressor gene inactivation. Finally, a comprehensive geno-transcriptomic analysis allows the identification of specific deregulated pathways and candidate biomarkers for personalized treatments in multiple myeloma.

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