Kylee Maclachlan

Abstract RNA polymerase I (Pol I) transcription of ribosomal RNA genes (rDNA) is tightly regulated downstream of oncogenic pathways, and its dysregulation is a common feature in cancer. We evaluated CX-5461, the first-in-class selective rDNA transcription inhibitor, in a first-in-human, phase I dose-escalation study in advanced hematologic cancers. Administration of CX-5461 intravenously once every 3 weeks to 5 cohorts determined an MTD of 170 mg/m2, with a predictable pharmacokinetic profile. The dose-limiting toxicity was palmar–plantar erythrodysesthesia; photosensitivity was a dose-independent adverse event (AE), manageable by preventive measures. CX-5461 induced rapid on-target inhibition of rDNA transcription, with p53 activation detected in tumor cells from one patient achieving a clinical response. One patient with anaplastic large cell lymphoma attained a prolonged partial response and 5 patients with myeloma and diffuse large B-cell lymphoma achieved stable disease as best response. CX-5461 is safe at doses associated with clinical benefit and dermatologic AEs are manageable. Significance: CX-5461 is a first-in-class selective inhibitor of rDNA transcription. This first-in-human study establishes the feasibility of targeting this process, demonstrating single-agent antitumor activity against advanced hematologic cancers with predictable pharmacokinetics and a safety profile allowing prolonged dosing. Consistent with preclinical data, antitumor activity was observed in TP53 wild-type and mutant malignancies. This article is highlighted in the In This Issue feature, p. 983

Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate the whole genome sequence (WGS) profile of 18 MGUS and compare them with those from 14 SMMs and 80 MMs. We show that cases with a non-progressing, clinically stable myeloma precursor condition (n = 15) are characterized by later initiation in the patient's life and by the absence of myeloma defining genomic events including: chromothripsis, templated insertions, mutations in driver genes, aneuploidy, and canonical APOBEC mutational activity. This data provides evidence that WGS can be used to recognize two biologically and clinically distinct myeloma precursor entities that are either progressive or stable.

Abstract The landscape of structural variants (SV) in multiple myeloma remains poorly understood. Here, we performed comprehensive analysis of SVs in a large cohort of 752 patients with multiple myeloma by low-coverage long-insert whole-genome sequencing. We identified 68 SV hotspots involving 17 new candidate driver genes, including the therapeutic targets BCMA (TNFRSF17), SLAM7, and MCL1. Catastrophic complex rearrangements termed chromothripsis were present in 24% of patients and independently associated with poor clinical outcomes. Templated insertions were the second most frequent complex event (19%), mostly involved in super-enhancer hijacking and activation of oncogenes such as CCND1 and MYC. Importantly, in 31% of patients, two or more seemingly independent putative driver events were caused by a single structural event, demonstrating that the complex genomic landscape of multiple myeloma can be acquired through few key events during tumor evolutionary history. Overall, this study reveals the critical role of SVs in multiple myeloma pathogenesis. Significance: Previous genomic studies in multiple myeloma have largely focused on single-nucleotide variants, recurrent copy-number alterations, and recurrent translocations. Here, we demonstrate the crucial role of SVs and complex events in the development of multiple myeloma and highlight the importance of whole-genome sequencing to decipher its genomic complexity. See related commentary by Bergsagel and Kuehl, p. 221. This article is highlighted in the In This Issue feature, p. 215

PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.