The biological and clinical impact of deletions before and after large chromosomal gains in multiple myeloma.

Acquisition of a hyperdiploid (HY) karyotype or immunoglobulin heavy chain (IGH) translocations are considered key initiating events in multiple myeloma (MM). To explore if other genomic events can precede these events, we analyzed whole-genome sequencing (WGS) data from 1173 MM samples. Integrating molecular time and structural variants (SV) within early chromosomal duplications, we indeed identified pre-gain deletions in 9.4% of HY patients without IGH translocations, challenging HY as the earliest somatic event. Remarkably, these deletions affected tumor suppressor genes (TSG) and/or oncogenes in 2.4% of HY patients without IGH translocations, supporting their role in MM pathogenesis. Furthermore, our study points to post-gain deletions as novel driver mechanisms in MM. Using multi-omics approaches to investigate their biological impact, we found associations with poor clinical outcome in newly diagnosed patients and profound effects on both oncogene and TSG activity, despite the diploid gene status. Overall, this study provides novel insights into the temporal dynamics of genomic alterations in MM.

Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis.

Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.

Metabolic Labeling of RNAs Uncovers Hidden Features and Dynamics of the Arabidopsis Transcriptome.

Transcriptome analysis by RNA sequencing (RNA-seq) has become an indispensable research tool in modern plant biology. Virtually all RNA-seq studies provide a snapshot of the steady state transcriptome, which contains valuable information about RNA populations at a given time but lacks information about the dynamics of RNA synthesis and degradation. Only a few specialized sequencing techniques, such as global run-on sequencing, have been used to provide information about RNA synthesis rates in plants. Here, we demonstrate that RNA labeling with the modified, nontoxic uridine analog 5-ethynyl uridine (5-EU) in Arabidopsis (Arabidopsis thaliana) seedlings provides insight into plant transcriptome dynamics. Pulse labeling with 5-EU revealed nascent and unstable RNAs, RNA processing intermediates generated by splicing, and chloroplast RNAs. Pulse-chase experiments with 5-EU allowed us to determine RNA stabilities without the need for chemical transcription inhibitors such as actinomycin and cordycepin. Inhibitor-free, genome-wide analysis of polyadenylated RNA stability via 5-EU pulse-chase experiments revealed RNAs with shorter half-lives than those reported after chemical inhibition of transcription. In summary, our results indicate that the Arabidopsis nascent transcriptome contains unstable RNAs and RNA processing intermediates and suggest that polyadenylated RNAs have low stability in plants. Our technique lays the foundation for easy, affordable, nascent transcriptome analysis and inhibitor-free analysis of RNA stability in plants.

Pre-Clinical Assessment of SAR442257, a CD38/CD3xCD28 Trispecific T Cell Engager in Treatment of Relapsed/Refractory Multiple Myeloma.

Current treatment strategies for multiple myeloma (MM) are highly effective, but most patients develop relapsed/refractory disease (RRMM). The anti-CD38/CD3xCD28 trispecific antibody SAR442257 targets CD38 and CD28 on MM cells and co-stimulates CD3 and CD28 on T cells (TCs). We evaluated different key aspects such as MM cells and T cells avidity interaction, tumor killing, and biomarkers for drug potency in three distinct cohorts of RRMM patients. We found that a significantly higher proportion of RRMM patients (86%) exhibited aberrant co-expression of CD28 compared to newly diagnosed MM (NDMM) patients (19%). Furthermore, SAR442257 mediated significantly higher TC activation, resulting in enhanced MM killing compared to bispecific functional knockout controls for all relapse cohorts (Pearson's r = 0.7). Finally, patients refractory to anti-CD38 therapy had higher levels of TGF-ß (up to 20-fold) compared to other cohorts. This can limit the activity of SAR442257. Vactoserib, a TGF-ß inhibitor, was able to mitigate this effect and restore sensitivity to SAR442257 in these experiments. In conclusion, SAR442257 has high potential for enhancing TC cytotoxicity by co-targeting CD38 and CD28 on MM and CD3/CD28 on T cells.

Resolving the spatial architecture of myeloma and its microenvironment at the single-cell level.

In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.

Comparison of NGS and MFC Methods: Key Metrics in Multiple Myeloma MRD Assessment.

In order to meet the challenges in data evaluation and comparability between studies in multiple myeloma (MM) minimal residual disease (MRD) assessment, the goal of the current study was to provide a step-by-step evaluation of next-generation sequencing (NGS) and multicolor flow cytometry (MFC) data. Bone marrow (BM) sample pairs from 125 MM patients were analyzed by NGS and MFC MM MRD methods. Tumor load (TL) and limit of detection (LOD) and quantification (LOQ) were calculated. The best-fit MRD cut-off was chosen as 1 × 10-5, resulting in an overall 9.6% (n overall = 12 (NGS n = 2, MFC n = 10)) nonassessable cases. The overall concordance rate between NGS and MFC was 68.0% (n = 85); discordant results were found in 22.4% (11.2% (n = 14) of cases in each direction. Overall, 55.1% (n = 60/109) and 49.5% (n = 54/109) of patients with a serological response ≥ very good partial response (VGPR) showed BM MRD negativity by NGS and MFC, respectively. A good correlation in the TL assessed by both techniques was found (correlation coefficient = 0.8, n = 40, p < 0.001). Overall, our study shows good concordance between MM BM MRD status and TL when comparing NGS and MFC at a threshold of 10-5. However, a sufficient number of analyzed events and calculation of MRD key metrics are essential for the comparison of methods and evaluability of data at a specific MRD cut-off.