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.

中文翻译：

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基因组复杂性对多发性骨髓瘤转录组的功能影响

目的：多发性骨髓瘤是一种生物学异质性浆细胞疾病。在这项研究中，我们旨在剖析基因突变、拷贝数异常 (CNA) 和染色体重排 (CR) 对转录组的功能影响。此外，我们应用基因转录组学方法来识别用于个性化治疗的特定生物标志物。实验设计：我们分析了来自 CoMMpass 研究的 IA12 版本的 514 名新诊断患者，解释了多发性骨髓瘤驱动基因的突变、结构变异、拷贝数片段和原始转录本计数。我们进行了计算机药物敏感性筛选 (DSS)，在使用 Celligner 算法将细胞系锚定到原发性肿瘤样本后询问癌症依赖图 (DepMap) 数据集。结果：免疫球蛋白易位，超二倍体和 chr(1q) gain/amps 与最高数量的失调基因相关。其他 CNA 和特定基因突变对特定通路的影响较低但非常明显。许多复发基因显示出热点 (HS) 特异性效应。双重打击多发性骨髓瘤的临床相关性在我们的分析中找到了强大的生物学基础。肿瘤抑制因子的双等位基因缺失和 chr(1q) 扩增显示出对基因表达、与细胞周期、增殖和免疫治疗靶点表达相关的通路失调的最大影响。此外，我们的计算机 DSS 表明，不仅 t(11;14)，而且 chr(1q)gain/amps 和 CYLD 失活都预测了 BCL2 轴转录物的差异表达和对维奈托克的反应。结论：多发性骨髓瘤基因组结构和转录组具有严格的联系，由 CNA 和 CR 主导。基因突变尤其影响致癌基因的 HS 突变和双等位抑癌基因失活。最后，全面的基因转录组学分析可以识别特定的失调途径和候选生物标志物，用于多发性骨髓瘤的个性化治疗。