Functional impact of genomic complexity on the transcriptome of multiple myeloma

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Abstract

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

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Ziccheddu, B., da Via, M. C., Lionetti, M., Maeda, A., Morlupi, S., Dugo, M., … Bolli, N. (2021). Functional impact of genomic complexity on the transcriptome of multiple myeloma. Clinical Cancer Research, 27(23), 6479–6490. https://doi.org/10.1158/1078-0432.CCR-20-4366

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