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. 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 its prognostic signal in MM has not been thoroughly reported. 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. 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 that 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.

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Publication Details

Journal
Blood Cancer Journal
Published
2025-02-20
DOI
https://doi.org/10.1038/s41408-025-01230-y
Citations
2
Primary Topic
Insect Resistance and Genetics
Type
article
Field-Weighted Citation Impact
1.61

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article

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

Kylee H. Maclachlan, Viswatej Avutu, Saad Z. Usmani, Malin L. Hultcrantz et al.
2 citations
Blood Cancer Journal
Insect Resistance and Genetics
1.61
article

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

Kylee H. Maclachlan, Viswatej Avutu, Saad Z. Usmani, Malin L. Hultcrantz, Joseph O. Deasy, Anish K. Simhal, Larry Norton, Jung Hun Oh, Ross Firestone
article en
2 citations

Abstract

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. 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 its prognostic signal in MM has not been thoroughly reported. 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. 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 that 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.

Blood Cancer JournalVol. 15(1)
Memorial Sloan Kettering Cancer Center (US)
Simons Foundation, Conquer Cancer Foundation, Breast Cancer Research Foundation, American Society of Clinical Oncology, Memorial Sloan-Kettering Cancer Center, Russian Science Foundation
No poverty
Openalex Percentile: Top 19%
Insect Resistance and Genetics
1.61
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