Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence
Most of the current utilization of liquid biopsy (LBx) is based on analyzing cell-free DNA(cfDNA). There is limited data on using cell-free RNA (cfRNA) levels (liquid transcriptome) in LBx. The major hurdles for using liquid transcriptome is its low level in circulation and the dilutional effects of...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | The Journal of Liquid Biopsy |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S295019542400136X |
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| _version_ | 1850053947943813120 |
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| author | Maher Albitar Ahmad Charifa Sally Agersborg Andrew Pecora Andrew Ip Andre Goy |
| author_facet | Maher Albitar Ahmad Charifa Sally Agersborg Andrew Pecora Andrew Ip Andre Goy |
| author_sort | Maher Albitar |
| collection | DOAJ |
| description | Most of the current utilization of liquid biopsy (LBx) is based on analyzing cell-free DNA(cfDNA). There is limited data on using cell-free RNA (cfRNA) levels (liquid transcriptome) in LBx. The major hurdles for using liquid transcriptome is its low level in circulation and the dilutional effects of various tissues that may pour their RNA into circulation. We explored the potential of using artificial intelligence (AI) to normalize the cancer-specific cfRNA and to enable liquid transcriptome to predict diagnosis. cfRNA transcriptomic data from 1009 peripheral blood samples was generated by hybrid capture next generation sequencing (NGS). Using two-thirds of samples for training and one third for testing, we demonstrate that AI is able to distinguish between normal control (N = 368) and patients with solid tumors (N = 404) with AUC = 0.820 (95 % CI: 0.760–0.879), patients with myeloid neoplasms (N = 99) with AUC = 0.858 (95 % CI: 0.793–0.924) and patients with lymphoid neoplasms (N = 128) with AUC = 0.788 (95 % CI: 0.687–0.888). Specific diagnosis was also possible when patients with lung, breast, colorectal, and myelodysplastic subgroups were tested. This data suggests that liquid transcriptomics when used with AI has the potential of transforming “liquid biopsy” to “true” biopsy, replacing the need for tissue biopsy. |
| format | Article |
| id | doaj-art-befa01532a904e60b8fd727cf648cb17 |
| institution | DOAJ |
| issn | 2950-1954 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Journal of Liquid Biopsy |
| spelling | doaj-art-befa01532a904e60b8fd727cf648cb172025-08-20T02:52:24ZengElsevierThe Journal of Liquid Biopsy2950-19542024-12-01610027010.1016/j.jlb.2024.100270Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligenceMaher Albitar0Ahmad Charifa1Sally Agersborg2Andrew Pecora3Andrew Ip4Andre Goy5Genomic Testing Cooperative, Lake Forest, CA, USA; Corresponding author.Genomic Testing Cooperative, Lake Forest, CA, USAGenomic Testing Cooperative, Lake Forest, CA, USAJohn Theurer Cancer Center, Hackensack, NJ, USAJohn Theurer Cancer Center, Hackensack, NJ, USAJohn Theurer Cancer Center, Hackensack, NJ, USAMost of the current utilization of liquid biopsy (LBx) is based on analyzing cell-free DNA(cfDNA). There is limited data on using cell-free RNA (cfRNA) levels (liquid transcriptome) in LBx. The major hurdles for using liquid transcriptome is its low level in circulation and the dilutional effects of various tissues that may pour their RNA into circulation. We explored the potential of using artificial intelligence (AI) to normalize the cancer-specific cfRNA and to enable liquid transcriptome to predict diagnosis. cfRNA transcriptomic data from 1009 peripheral blood samples was generated by hybrid capture next generation sequencing (NGS). Using two-thirds of samples for training and one third for testing, we demonstrate that AI is able to distinguish between normal control (N = 368) and patients with solid tumors (N = 404) with AUC = 0.820 (95 % CI: 0.760–0.879), patients with myeloid neoplasms (N = 99) with AUC = 0.858 (95 % CI: 0.793–0.924) and patients with lymphoid neoplasms (N = 128) with AUC = 0.788 (95 % CI: 0.687–0.888). Specific diagnosis was also possible when patients with lung, breast, colorectal, and myelodysplastic subgroups were tested. This data suggests that liquid transcriptomics when used with AI has the potential of transforming “liquid biopsy” to “true” biopsy, replacing the need for tissue biopsy.http://www.sciencedirect.com/science/article/pii/S295019542400136XLiquid biopsycell-free DNA (cfDNA)cell-free RNA (cfRNA)Cancer diagnosisNext generation sequencingArtificial intelligence (AI) |
| spellingShingle | Maher Albitar Ahmad Charifa Sally Agersborg Andrew Pecora Andrew Ip Andre Goy Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence The Journal of Liquid Biopsy Liquid biopsy cell-free DNA (cfDNA) cell-free RNA (cfRNA) Cancer diagnosis Next generation sequencing Artificial intelligence (AI) |
| title | Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| title_full | Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| title_fullStr | Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| title_full_unstemmed | Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| title_short | Expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| title_sort | expanding the clinical utility of liquid biopsy by using liquid transcriptome and artificial intelligence |
| topic | Liquid biopsy cell-free DNA (cfDNA) cell-free RNA (cfRNA) Cancer diagnosis Next generation sequencing Artificial intelligence (AI) |
| url | http://www.sciencedirect.com/science/article/pii/S295019542400136X |
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