Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma
Abstract Background Multi‐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. Methods We developed a comprehensive multi‐omics solution...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | Clinical and Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ctm2.70174 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832586820796284928 |
|---|---|
| author | Weilong Zhang Bangquan Ye Yang Song Ping Yang Wenzhe Si Hairong Jing Fan Yang Dan Yuan Zhihong Wu Jiahao Lyu Kang Peng Xu Zhang Lingli Wang Yan Li Yan Liu Chaoling Wu Xiaoyu Hao Yuqi Zhang Wenxin Qi Jing Wang Fei Dong Zijian Zhao Hongmei Jing Yanzhao Li |
| author_facet | Weilong Zhang Bangquan Ye Yang Song Ping Yang Wenzhe Si Hairong Jing Fan Yang Dan Yuan Zhihong Wu Jiahao Lyu Kang Peng Xu Zhang Lingli Wang Yan Li Yan Liu Chaoling Wu Xiaoyu Hao Yuqi Zhang Wenxin Qi Jing Wang Fei Dong Zijian Zhao Hongmei Jing Yanzhao Li |
| author_sort | Weilong Zhang |
| collection | DOAJ |
| description | Abstract Background Multi‐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. Methods We 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. Results For 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. Conclusions Our 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. |
| format | Article |
| id | doaj-art-cebca33887d941c69c4818e4cdbb4b34 |
| institution | Kabale University |
| issn | 2001-1326 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Medicine |
| spelling | doaj-art-cebca33887d941c69c4818e4cdbb4b342025-01-25T04:00:38ZengWileyClinical and Translational Medicine2001-13262025-01-01151n/an/a10.1002/ctm2.70174Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphomaWeilong Zhang0Bangquan Ye1Yang Song2Ping Yang3Wenzhe Si4Hairong Jing5Fan Yang6Dan Yuan7Zhihong Wu8Jiahao Lyu9Kang Peng10Xu Zhang11Lingli Wang12Yan Li13Yan Liu14Chaoling Wu15Xiaoyu Hao16Yuqi Zhang17Wenxin Qi18Jing Wang19Fei Dong20Zijian Zhao21Hongmei Jing22Yanzhao Li23Department of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of Laboratory MedicinePeking University Third HospitalBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaBOE Technology Group Co., LtdBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaBOE Technology Group Co., LtdBeijingChinaDepartment of HematologyLymphoma Research CenterPeking University Third HospitalBeijingChinaBOE Technology Group Co., LtdBeijingChinaAbstract Background Multi‐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. Methods We 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. Results For 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. Conclusions Our 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.https://doi.org/10.1002/ctm2.70174cfDNADLBCLearly diagnosisintegrated modelmulti‐omicstreatment prediction |
| spellingShingle | Weilong Zhang Bangquan Ye Yang Song Ping Yang Wenzhe Si Hairong Jing Fan Yang Dan Yuan Zhihong Wu Jiahao Lyu Kang Peng Xu Zhang Lingli Wang Yan Li Yan Liu Chaoling Wu Xiaoyu Hao Yuqi Zhang Wenxin Qi Jing Wang Fei Dong Zijian Zhao Hongmei Jing Yanzhao Li Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma Clinical and Translational Medicine cfDNA DLBCL early diagnosis integrated model multi‐omics treatment prediction |
| title | Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma |
| title_full | Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma |
| title_fullStr | Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma |
| title_full_unstemmed | Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma |
| title_short | Integrating multi‐omics features enables non‐invasive early diagnosis and treatment response prediction of diffuse large B‐cell lymphoma |
| title_sort | integrating multi omics features enables non invasive early diagnosis and treatment response prediction of diffuse large b cell lymphoma |
| topic | cfDNA DLBCL early diagnosis integrated model multi‐omics treatment prediction |
| url | https://doi.org/10.1002/ctm2.70174 |
| work_keys_str_mv | AT weilongzhang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT bangquanye integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT yangsong integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT pingyang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT wenzhesi integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT hairongjing integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT fanyang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT danyuan integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT zhihongwu integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT jiahaolyu integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT kangpeng integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT xuzhang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT lingliwang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT yanli integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT yanliu integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT chaolingwu integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT xiaoyuhao integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT yuqizhang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT wenxinqi integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT jingwang integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT feidong integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT zijianzhao integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT hongmeijing integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma AT yanzhaoli integratingmultiomicsfeaturesenablesnoninvasiveearlydiagnosisandtreatmentresponsepredictionofdiffuselargebcelllymphoma |