Biology subjects

Hultcrantz, M.

Publications and source records attributed to Hultcrantz, M..

4 recordsLinked to original sources

bioRxiv2024

High WEE1 expression is independently linked to poor survival in multiple myeloma

Current prognostic scores in multiple myeloma (MM) currently rely on disease burden and a limited set of genomic alterations. Some studies have suggested gene expression panels may predict clinical outcomes, but none are presently utilized in clinical practice. We therefore analyzed the MMRF CoMMpass dataset (N=659) and identified a high-risk group (top tertile) and a low-risk group (bottom tertile) based on WEE1 expression sorted in descending order. The tyrosine kinase WEE1 is a critical cell cycle regulator during the S-phase and G2M-checkpoint. Abnormal WEE1 expression has been implicated in multiple cancers including breast, ovarian, and gastric cancers, but has not until this time been implicated in MM. PFS was significantly different (p <1e-9) between the groups, which was validated in two independent microarray gene expression profiling (GEP) datasets from the Total Therapy 2 (N=341) and 3 (N=214) trials. Our results show WEE1 expression is prognostic independent of known biomarkers, differentiates outcomes associated with known markers, is upregulated independently of its interacting neighbors, and is associated with dysregulated P53 pathways. This suggests that WEE1 expression levels may have clinical utility in prognosticating outcomes in newly diagnosed MM and may support the application of WEE1 inhibitors to MM preclinical models. Determining the causes of abnormal WEE1 expression may uncover novel therapeutic pathways.

cancer biology↗

bioRxiv2020

Copy number signatures predict chromothripsis and associate with poor clinical outcomes in patients with newly diagnosed multiple myeloma

Chromothripsis is detectable in 20-30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study, we interrogate 752 NDMM patients using whole genome sequencing (WGS) to study the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC=0.90) and can be used to identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis was confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC=0.97) and an independent series of 34 NDMM (AUC=0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we were able to predict both the presence of chromothripsis (AUC=0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data.

genomics↗

bioRxiv2020

Whole genome sequencing provides evidence of two biologically and clinically distinct entities of asymptomatic monoclonal gammopathies: progressive versus stable myeloma precursor condition

Multiple myeloma (MM) is consistently preceded by precursor conditions recognized clinically as monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM). We interrogate, for the first time, 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 patients 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.

cancer biology↗

bioRxiv2019

Revealing the impact of recurrent and rare structural variants in multiple myeloma

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug targets BCMA (TNFRSF17) and SLAMF7. Complex SVs, including chromothripsis and templated insertions, were present in 61 % of patients and frequently resulted in the simultaneous acquisition of multiple drivers. After accounting for all recurrent events, 63 % of SVs remained unexplained. Intriguingly, these rare SVs were associated with up to 7-fold enrichment for outlier gene expression, indicating that many rare driver SVs remain unrecognized and are likely important in the biology of individual tumors.

genomics↗