A prognostic index integrating deep learning baseline PET/CT biomarkers and multi-omics profiling in diffuse large B cell lymphoma

[<sup>18</sup>F]-Fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) is essential for disease staging and treatment response evaluation in diffuse large B cell lymphoma (DLBCL). In this study, we analyze <sup>18</sup>F-FDG-PET scans from 1,024 newly diagnosed DLBCL patients, integrating with DNA and RNA sequencing data. Using the nnUNet deep learning framework and training on both AutoPET public and in-house datasets, we identify key baseline biomarkers-including total metabolic tumor volume (TMTV), Max MTV, and the standardized tumor dissemination biomarker-that demonstrate significant prognostic value. Further integrating PET biomarkers with clinical factors and LymphPlex genetic subtypes, we develop high TMTV, elevated lactate dehydrogenase (LDH), and EZB-like MYC+, MCD-like, and TP53<sup>Mut</sup> subtypes as risk factors to form the ClinicalPET LymphPlex model, efficiently distinguishing patient outcomes across different treatments. Notably, high TMTV correlates with an immunosuppressive tumor microenvironment, while elevated LDH is linked to increased metabolic activity and tumor proliferation. Collectively, our findings necessitate multimodal integration to enhance prognostic precision and advance personalized therapy in DLBCL.

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Publication Details

Journal
Cell Reports Medicine
Published
2025-11-01
DOI
https://doi.org/10.1016/j.xcrm.2025.102452
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
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article

A prognostic index integrating deep learning baseline PET/CT biomarkers and multi-omics profiling in diffuse large B cell lymphoma

Rongji Mu, Di Fu, Zhuo-Han Li, Weili Zhao et al.
Cell Reports Medicine
Lymphoma Diagnosis and Treatment
article

A prognostic index integrating deep learning baseline PET/CT biomarkers and multi-omics profiling in diffuse large B cell lymphoma

Rongji Mu, Di Fu, Zhuo-Han Li, Weili Zhao, Xin‐Yun Huang, Songfu Jiang, Shu Cheng, Hongmei Yi, Hongmei Jing, Wen Ning, He Li, Biao Li, Yue Wang, Xue Wang, Qing Shi, Fuhua Yan, Binshen Ouyang, Peng-Peng Xu, Ting Niu, Li Wang
article en

Abstract

[<sup>18</sup>F]-Fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) is essential for disease staging and treatment response evaluation in diffuse large B cell lymphoma (DLBCL). In this study, we analyze <sup>18</sup>F-FDG-PET scans from 1,024 newly diagnosed DLBCL patients, integrating with DNA and RNA sequencing data. Using the nnUNet deep learning framework and training on both AutoPET public and in-house datasets, we identify key baseline biomarkers-including total metabolic tumor volume (TMTV), Max MTV, and the standardized tumor dissemination biomarker-that demonstrate significant prognostic value. Further integrating PET biomarkers with clinical factors and LymphPlex genetic subtypes, we develop high TMTV, elevated lactate dehydrogenase (LDH), and EZB-like MYC+, MCD-like, and TP53<sup>Mut</sup> subtypes as risk factors to form the ClinicalPET LymphPlex model, efficiently distinguishing patient outcomes across different treatments. Notably, high TMTV correlates with an immunosuppressive tumor microenvironment, while elevated LDH is linked to increased metabolic activity and tumor proliferation. Collectively, our findings necessitate multimodal integration to enhance prognostic precision and advance personalized therapy in DLBCL.

Cell Reports MedicineVol. 6(11)
Shanghai Jiao Tong University (CN), Peking University (CN), Sichuan University (CN), Wenzhou Medical University (CN), Ruijin Hospital (CN), First Affiliated Hospital of Wenzhou Medical University (CN), West China Hospital of Sichuan University (CN), Peking University Third Hospital (CN), Shanghai Institute of Hematology (CN)
Openalex Percentile: Top 52%
Lymphoma Diagnosis and Treatment
DOIOpen Access PDFOpenAlex
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