NOTCH pathway activation is mediated by DTX1 loss of function mutations in DLBCL

A Abigail Dropik (1Mayo Clinic, Hematology, Rochester, United States) M Melissa Hopper (1Mayo Clinic, Hematology, Rochester, United States) J Janek Walker (1Mayo Clinic, Hematology, Rochester, United States) J Joseph Novak (1Mayo Clinic, Rochester, United States) M Miranda Siminski (1Mayo Clinic, Hematology, Rochester, United States) Z Zilin Xianyu (1Mayo Clinic, Hematology, Rochester, United States) M Michelle Manske (1Mayo Clinic, Hematology, Rochester, United States) X Xiaosheng Wu (1Mayo Clinic, Hematology, Rochester, United States) M Mark Kaplan (2Bristol Myers Squibb, Informatics and Predictive Sciences, Summit, United States) K Kerstin Wenzl (2Bristol Myers Squibb, Informatics and Predictive Sciences, Summit, United States) V Vivekananda Sarangi (3Mayo Clinic, Department of Quantitative Health Sciences, Rochester, United States) M Matthew Maurer (2Mayo Clinic, Rochester, United States) T Thomas Habermann (2Mayo Clinic, Rochester, United States) B Brian Link (13University of Iowa, Iowa City, United States) B Baoyu Chen D Daniel Billadeau R Rebecca King (1Mayo Clinic, Rochester, United States) T Thomas Witzig (2Mayo Clinic, Rochester, United States) S Stephen Ansell (1Mayo Clinic, Rochester, United States) J James Cerhan (2Mayo Clinic, Rochester, United States) A Anne Novak (1Mayo Clinic, Rochester, United States)

Abstract

Abstract Diffuse Large B Cell Lymphoma (DLBCL), the most common subtype of aggressive B-cell Non-Hodgkin Lymphoma (NHL), accounts for 30-40% of newly diagnosed NHL cases. Despite recent progress improving our understanding of molecular features of DLBCL, there is still a high relapse rate (~45%) among patients who undergo standard treatment (R-CHOP). Several groups have identified reproducible molecular clusters of DLBCL although, the biologic significance of many of the specific gene mutations within these clusters is poorly understood. DTX1 mutations are a feature of the BN2/C1 DLBCL classifiers and are among the mutations with unknown significance. BN2/C1 DLBCL are a mixture of ABC, GCB, and Unclassified cell of origin (COO) with a common signature being the presence of genetic alterations in genes known to regulate the NOTCH pathway; yet, these tumors lack transcriptional signatures of traditional NOTCH activation, suggesting a unique and undefined biology driven through non-canonical NOTCH pathway activation. DTX1 is an E3 ubiquitin ligase which directly binds the intracellular domain of the NOTCH receptor (NICD), targeting it for degradation, resulting in suppression of NOTCH pathway activity. We therefore hypothesize that DTX1 mutations lead to NOTCH pathway dysregulation and are a critical driver for a subset of BN2/C1 DLBCLs. Using whole exome sequencing (WES) data from 404 newly diagnosed DLBCL patients, we found 8% of patients with mutations in DTX1. Alterations in DTX1 were localized to the NICD binding domain, WWE1. In silico Alphafold modeling of DTX1 WWE1-interaction with NICD revealed that patient mutations clustered within predicted interacting surfaces with NICD. These findings lead to the hypothesis that mutations in the DTX1 WWE1 domain suppress its ability to bind to and degrade NICD, enhancing NOTCH pathway activation in DLBCL. To address this question, we first compared DTX1 protein expression by immunoblot in DTX1 WWE1 mutant (OCI-Ly3 and SUDHL2) and wildtype (WT) (OCI-Ly7, OCI-Ly19, SUDHL6, and U2932) DLBCL cell lines. We found higher expression of NICD1 (p=0.03) in OCI-Ly3 and NICD2 (p<0.0001) in SUDHL2 cell lines compared to WT. This increase was accompanied by an increase in NOTCH surface expression with higher NOTCH1 (p<0.0001) and NOTCH2 (p<0.0001) expression on OCI-Ly3 and SUDHL2 cells, respectively, compared to WT. To remove variability across cell lines we next used CRISPR to generate DTX1 knock out (KO) models using WT DTX1 DLBCL cell lines U2932 and OCI-Ly19. Analysis of NICD and NOTCH receptor protein expression confirmed our initial finding, showing an 8.5 and 4.8-fold increase of NICD1 and a 6 and 2.5-fold increase of NICD2 expression in the U2932 and OCI-Ly19 DTX1 KO cell lines, respectively, compared to empty vector (EV) controls. An increase in surface NOTCH1, and to a lesser extent NOTCH2, was seen in U2932 (p=0.01 and p=0.07, respectively) and OCI-Ly19 (p=0.001 and p=0.2, respectively) KO cells compared to EV controls. To identify pathways affected by DTX1 mutations, we next performed RNAseq on U2932 EV and KO cell lines. Of interest, we did not detect any significant changes in classical NOTCH driven genes (Hes1, Hey1, etc.), supporting prior studies on BN2/C1 tumors. However, we did identify potential non-canonical NOTCH-target genes that may contribute to lymphomagenesis. Gene expression in KO cells showed upregulation of genes involved in germinal center (GC) processes (AICDA, IRF4; p<0.001) and cellular growth and survival (IL6R, CCND2, STAT5B, BCL2; p<0.0001). Measurement of IL6R by flow cytometry and CyclinD2 by immunoblot further verified DTX1-mediated upregulation of IL6R (p<0.01) and CyclinD2 (p<0.01) for U2932 KO cells compared to EV control. We also observed downregulation of genes contributing to cell death (ex. BAX, CASP8, FAS; p<0.05) in KO cells compared to EV. Together, these novel findings support our hypothesis that DTX1 WWE1 mutations lead to dysregulation of the NOTCH pathway by driving overexpression of NICD and NOTCH, resulting in dysregulated expression of proteins involved in cell cycle, GC reaction, and apoptosis. We further provide new biologic insight into BN2/C1 DLBCL, ultimately highlighting a path toward novel therapeutic targets and the advancement of personalized medicine, as patients harboring these mutations may benefit from new therapies targeting inflammatory pathways, such as CELMoDs.

Article Details

Journal Blood
Volume / Issue Vol. 146, Issue Supplement 1
Published November 03, 2025
Pages 1771-1771
ISSN 0006-4971
Publisher Elsevier BV

Journal Info

Blood

Elsevier BV

ISSN: 0006-4971 Health Sciences

Authors (21)

A

Abigail Dropik

1Mayo Clinic, Hematology, Rochester, United States

M

Melissa Hopper

1Mayo Clinic, Hematology, Rochester, United States

J

Janek Walker

1Mayo Clinic, Hematology, Rochester, United States

J

Joseph Novak

1Mayo Clinic, Rochester, United States

M

Miranda Siminski

1Mayo Clinic, Hematology, Rochester, United States

Z

Zilin Xianyu

1Mayo Clinic, Hematology, Rochester, United States

M

Michelle Manske

1Mayo Clinic, Hematology, Rochester, United States

X

Xiaosheng Wu

1Mayo Clinic, Hematology, Rochester, United States

M

Mark Kaplan

2Bristol Myers Squibb, Informatics and Predictive Sciences, Summit, United States

K

Kerstin Wenzl

2Bristol Myers Squibb, Informatics and Predictive Sciences, Summit, United States

V

Vivekananda Sarangi

3Mayo Clinic, Department of Quantitative Health Sciences, Rochester, United States

M

Matthew Maurer

2Mayo Clinic, Rochester, United States

T

Thomas Habermann

2Mayo Clinic, Rochester, United States

B

Brian Link

13University of Iowa, Iowa City, United States

B

Baoyu Chen

D

Daniel Billadeau

R

Rebecca King

1Mayo Clinic, Rochester, United States

T

Thomas Witzig

2Mayo Clinic, Rochester, United States

S

Stephen Ansell

1Mayo Clinic, Rochester, United States

J

James Cerhan

2Mayo Clinic, Rochester, United States

A

Anne Novak

1Mayo Clinic, Rochester, United States