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

Q: What biological pathways were associated with high WEE1 expression?

High WEE1 expression was associated with dysregulated P53 pathways, supporting a potential mechanistic link to disease behavior.

Sep 23, 2026

Uploaded by Liam

High WEE1 expression is proposed as an independent prognostic marker in multiple myeloma (MM), where current risk models rely on disease burden and limited genomic alterations. Using the MMRF CoMMpass cohort (N=659), the study stratified patients by WEE1 expression into high- and low-risk groups and found significantly different progression-free survival (PFS). The prognostic separation was validated in independent Total Therapy 2 (N=341) and 3 (N=214) microarray gene expression datasets. The results indicate WEE1 adds prognostic value beyond known biomarkers, reflects outcome differences tied to known markers, and is associated with dysregulated P53 pathways, supporting potential clinical utility and rationale for WEE1 inhibitors.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages8

Reading Time20 min

AccessFree to download

Introduction

Current prognostic scoring in multiple myeloma

Gene expression signatures and prior network analyses

Biological role of WEE1 and rationale for investigation

Methods and validation (cohort and datasets)

CoMMpass stratification

Total Therapy 2 and 3 validation

Blood Cancer [Journal](Journal www.nature.com/bcj)[ www.nature.com/bcj](Journal www.nature.com/bcj) ARTICLE OPEN High WEE1 expression is independently linked to poor survival in multiple myeloma Anish K. Simhal 1 ✉, Ross S. Firestone 2, Jung Hun Oh 1, Viswatej Avutu3, Larry Norton3, Malin Hultcrantz 2, Saad Z. Usmani 2 , Kylee H. Maclachlan 2 and Joseph O. Deasy1 © The Author(s) 2025 | | 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 Journal (2025)15:22; [https://doi.org/10.1038/s41408-025-01230-y](https://doi.org/10.1038/s41408-025-01230-y) | | | | | | INTRODUCTION Multiple myeloma (MM) is a hematologic malignancy associated with a malignant proliferation of plasma cells [1] . Although the disease is usually responsive to upfront therapies, MM remains incurable even in patients who achieve undetectable levels of disease, with relapse considered largely inevitable [2] . The genomic makeup of MM is highly heterogeneous, and different studies have identiﬁed multiple subtypes associated with varying prognostic outcomes using different data modalities [1, 3–5] . Standard methods to prognosticate the length of progression-free survival (PFS) include the International Staging System (ISS) [6], Revised ISS (R-ISS) [7], and the Second Revision of the ISS (R2-ISS) [8] . These tools rely on surrogates for disease burden and identiﬁcation of speciﬁc tumor cytogenetic abnormalities. These scoring systems each have a PFS concordance index (c-index) below 60%, leaving room for improvement [9, 10] . In addition to providing genomic information, scoring systems informed by gene expression have been proposed for prognostication, including GEP70 and SKY92 [11, 12]. These expression-based signatures have shown potentially complementary information to ISS staging [11]. In [5], we conducted a large unsupervised genomic network study where we applied a novel measure of network connectivity, Ollivier-Ricci curvature, to RNA-sequencing (RNA-seq) and copy number alteration (CNA) data from newly diagnosed MM (NDMM) patients. We examined patterns of gene-gene interactions in MM and identiﬁed novel pathways and genes associated with poor prognosis. By examining the impact of gene expression via a network, we identiﬁed a novel eight-gene signature: BUB1, MCM6, NOSTRIN, PAM, RNF115, SNCAIP, SPRR2A, and WEE1. Of these eight genes, WEE1 was the only gene that w

FAQs

What biological pathways were associated with high WEE1 expression?

High WEE1 expression was associated with dysregulated P53 pathways, supporting a potential mechanistic link to disease behavior.

Sep 23, 2026

Uploaded by Liam