Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies
Abstract Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liqu...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
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| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-023-00484-8 |
| _version_ | 1797388564491665408 |
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| author | Kiran Challa Daniel Paysan Dominic Leiser Nadia Sauder Damien C. Weber G. V. Shivashankar |
| author_facet | Kiran Challa Daniel Paysan Dominic Leiser Nadia Sauder Damien C. Weber G. V. Shivashankar |
| author_sort | Kiran Challa |
| collection | DOAJ |
| description | Abstract Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation. |
| first_indexed | 2024-03-08T22:42:39Z |
| format | Article |
| id | doaj.art-bea726c9a7a442469715f647d72a9656 |
| institution | Directory Open Access Journal |
| issn | 2397-768X |
| language | English |
| last_indexed | 2024-03-08T22:42:39Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Precision Oncology |
| spelling | doaj.art-bea726c9a7a442469715f647d72a96562023-12-17T12:05:28ZengNature Portfolionpj Precision Oncology2397-768X2023-12-017111310.1038/s41698-023-00484-8Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsiesKiran Challa0Daniel Paysan1Dominic Leiser2Nadia Sauder3Damien C. Weber4G. V. Shivashankar5Mechano-Genomic Group, Division of Biology and Chemistry, Paul-Scherrer InstituteMechano-Genomic Group, Division of Biology and Chemistry, Paul-Scherrer InstituteCenter for Proton Therapy, Paul-Scherrer InstituteCenter for Proton Therapy, Paul-Scherrer InstituteCenter for Proton Therapy, Paul-Scherrer InstituteMechano-Genomic Group, Division of Biology and Chemistry, Paul-Scherrer InstituteAbstract Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.https://doi.org/10.1038/s41698-023-00484-8 |
| spellingShingle | Kiran Challa Daniel Paysan Dominic Leiser Nadia Sauder Damien C. Weber G. V. Shivashankar Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies npj Precision Oncology |
| title | Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| title_full | Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| title_fullStr | Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| title_full_unstemmed | Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| title_short | Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| title_sort | imaging and ai based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies |
| url | https://doi.org/10.1038/s41698-023-00484-8 |
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