Application of Hi-C sequencing to detect oncogene rearrangements for diagnosis and treatment of large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.

Authors

Institutions

Publication Details

Journal
Blood Advances
Published
2026-06-16
DOI
https://doi.org/10.1182/bloodadvances.2026019675
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of Hi-C sequencing to detect oncogene rearrangements for diagnosis and treatment of large B-cell lymphoma

Michael Møller, Karen Dybkær, Weina Chen, Ken H. Young et al.
Blood Advances
Lymphoma Diagnosis and Treatment
article

Application of Hi-C sequencing to detect oncogene rearrangements for diagnosis and treatment of large B-cell lymphoma

Michael Møller, Karen Dybkær, Weina Chen, Ken H. Young, Govind Bhagat, Kristin Sikkink, Benjamin M. Parsons, Xiaoxian Zhao, Eric D. Hsi, Alex Hastie, Zijun Y. Xu‐Monette, Leon Bernal‐Mizrachi, Anthony D. Schmitt, Carlo Visco, Farzaneh Khajouei, Bangchen Wang, 吴得红, April Chiu, Zenggang Pan, Youli Zu, Wayne Tam, Chang Wang, Andrés J.M. Ferreri, Yong Li, Xin Cao, William W.L. Choi, Beibei Lv, Santiago Montes-Moreno, Shuna Yao, Alexandar Tzankov, Maurilio Ponzoni, J Han JM van Krieken
article en

Abstract

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.

Blood Advances
University of Verona (IT), Atrium Health Wake Forest Baptist (US), Gundersen Health System (US), Mayo Clinic (US), Radboud University Nijmegen (NL), Emory University (US), Vita-Salute San Raffaele University (IT), Baylor College of Medicine (US), Aalborg University Hospital (DK), Odense University Hospital (DK), San Raffaele University of Rome (IT), Zhengzhou University (CN), Hospital Base (CL), Hong Kong Sanatorium and Hospital (HK), Piedmont Cancer Institute (US), Arima Genomics (United States) (US), Donald & Barbara Zucker School of Medicine at Hofstra/Northwell (US), Methodist Hospital (US), Instituto de Investigación Marqués de Valdecilla (ES), Duke Medical Center (US), Henan Cancer Hospital (CN), Saint Louis University (US), University of Colorado Anschutz Medical Campus (US), The University of Texas Southwestern Medical Center (US), University of Colorado Denver (US)
Openalex Percentile: Top 7%
Lymphoma Diagnosis and Treatment
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.