Evidence map›Paper›PMID 39776291›Full record

ArticleClinical and translational medicine2025

Integrating multi-omics features enables non-invasive early diagnosis and treatment response prediction of diffuse large B-cell lymphoma.

Weilong Zhang, Bangquan Ye, Yang Song, Ping Yang, Wenzhe Si, Hairong Jing, Fan Yang, Dan Yuan, Zhihong Wu, Jiahao Lyu and 14 more

Abstract read
In one paragraph

Article in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Review
  6. Illuminating diabetesWorld journal of diabetes · 2025
    Review
  7. Liquid Biopsy: The Challenges of a Revolutionary Approach in Oncology.International journal of molecular sciences · 2025
    Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Weilong ZhangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Bangquan YeBOE Technology Group Co., Ltd, Beijing, China.ORCID 0009-0002-8474-7795
Yang SongBOE Technology Group Co., Ltd, Beijing, China.
Ping YangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Wenzhe SiDepartment of Laboratory Medicine, Peking University Third Hospital, Beijing, China.
Hairong JingBOE Technology Group Co., Ltd, Beijing, China.
Fan YangBOE Technology Group Co., Ltd, Beijing, China.
Dan YuanBOE Technology Group Co., Ltd, Beijing, China.
Zhihong WuBOE Technology Group Co., Ltd, Beijing, China.
Jiahao LyuBOE Technology Group Co., Ltd, Beijing, China.
Kang PengBOE Technology Group Co., Ltd, Beijing, China.
Xu ZhangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Lingli WangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Yan LiDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Yan LiuDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Chaoling WuDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Xiaoyu HaoDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Yuqi ZhangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Wenxin QiDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Jing WangDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Fei DongDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.
Zijian ZhaoBOE Technology Group Co., Ltd, Beijing, China.
Hongmei JingDepartment of Hematology, Lymphoma Research Center, Peking University Third Hospital, Beijing, China.ORCID 0000-0003-4958-2489
Yanzhao LiBOE Technology Group Co., Ltd, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMulti-omics features of cell-free DNA (cfDNA) can effectively improve the performance of non-invasive early diagnosis and prognosis of cancer. However, multimodal characterization of cfDNA remains technically challenging.

methodsWe developed a comprehensive multi-omics solution (COMOS) to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA. The COMOS was tested on 214 plasma samples of diffuse large B-cell lymphoma (DLBCL) and matched healthy controls.

resultsFor early diagnosis, COMOS improved the area under the curve (AUC) value to .993 compared with the individual omics model, with a sensitivity of 95% at 98% specificity. Detection sensitivity achieved 91% at 99% specificity in early-stage patients, while the AUC values of the individual omics model were 0.942, 0.968, 0.989, 0.935, 0.921, 0.781 and 0.917, respectively, with lower sensitivity and specificity. In the treatment response cohort, COMOS yielded a superior sensitivity of 88% at 86% specificity (AUC, 0.903). COMOS has achieved excellent performance in early diagnosis and treatment response prediction.

conclusionsOur study provides an effectively improved approach with high accuracy for the diagnosis and prognosis of DLBCL, showing great potential for future clinical application. KEY POINTS: A comprehensive multi-omics solution to specifically obtain an extensive fragmentomics landscape, presented by breakpoint characteristics of nucleosomes, CpG islands, DNase clusters and enhancers, besides typical methylation, copy number alteration of cfDNA. Integrated model of cfDNA multi-omics could be used for non-invasive early diagnosis of DLBCL. Integrated model of cfDNA multi-omics could effectively evaluate the efficacy of R-CHOP before DLBCL treatment.

Indexed as

Lymphoma, Large B-Cell, DiffuseAdultAgedBiomarkers, TumorCell-Free Nucleic AcidsCyclophosphamideDoxorubicinEarly Detection of CancerEarly DiagnosisFemaleHumansMaleMiddle AgedMultiomicsPrognosisRituximabBiomarkers, TumorCell-Free Nucleic AcidsCyclophosphamideDoxorubicinRituximabcfDNADLBCLearly diagnosisintegrated modelmulti‐omicstreatment prediction

Identifiers

PMID39776291
PMCPMC11705727

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.