En zie ook de google search op onze website met het zoekwoord bloedtest.
3 januari 2025: Bron: Nature en Singlera Genomics
PanSeer is een bloedtest die via in bloed circulerend DNA jaren voordat zich symptomen voordoen kan voorspellen of iemand al kankercellen heeft die zich tot tumoren zullen ontwikkelen. Al in 2007 startten Chinese onderzoekers een groot bevolkingsonderzoek, de Taizhou Longitudinal Study van op dat moment 123.000 mensen die tot zover bekend geen ziekte hadden. In ieder geval geen symptomen toonden. A-symptomatisch.
Geregeld werd de bloedtest herhaald op 500 specifieke kenmerken die bij 5 verschillende vormen van kanker hoorden. Darmkanker, slokdarmkanker, longkanker, leverkanker en maagkanker. Maaar volgens het bedrijf zou deze bloedtest in feite voor alle vormen van kanker kunnen gelden. Alleen de specifieke kenmerken zouden dan voor sommige vormen van kanker moeten worden aangepast.
Uiteindelijk bewees de bloedtest dat bij de mensen waar binnen 1 tot 4 jaar de bloedtest kanker vaststelde de PanSeer bloedtest 95 procent accuraat dit had voorspeld.
Singlera Genoimics is erg actief op het gebied van bloedtesten (zie onderaan in artikel een aantal publicaties van dit bedrijf. Ook kreeg dit bedrijf bv voor de bloedtest alvleesklierkanker ook toestemming van de FDA voor gebruik.
Het originele studieverslag is in Nature gratis in te zien. Hier het abstract van de studie:
- Article
- Open access
- Published:
Non-invasive early detection of cancer four years before conventional diagnosis using a blood test
Nature Communications volume 11, Article number: 3475 (2020)
Abstract
Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80–93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93–98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89–98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care.
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Hong S. et al EBioMedicine. 2023 Cell-free DNA methylation biomarker for the diagnosis of papillary thyroid carcinoma. doi:10.1016/j.ebiom.2023.104497
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Chen S. et al BMC Genomics. 2022 Investigating the genomic alteration improved the clinical outcome of aged patients with lung carcinoma. doi:10.1186/s12864-021-08289-4
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Cai G. et al Gastroenterology. 2021 A Multilocus Blood-Based Assay Targeting Circulating Tumor DNA Methylation Enables Early Detection and Early Relapse Prediction of Colorectal Cancer. doi:10.1053/j.gastro.2021.08.054
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Jia Z. et al Clin Epigenetics. 2021 DNA methylation patterns at and beyond the histological margin of early-stage invasive lung adenocarcinoma radiologically manifested as pure ground-glass opacity. doi:10.1186/s13148-021-01140-3
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Zhou Y. et al Ann Transl Med. 2021 Novel ETV1 mutation in small cell lung cancer transformation resistant to EGFR tyrosine kinase inhibitors. doi:10.21037/atm-21-2625
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Xiong Y. et al Virchows Arch. 2021 Application of biomarkers in the diagnosis of uncertain samples of core needle biopsy of thyroid nodules. doi:10.1007%2Fs00428-021-03161-y
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Zhang H. et al J Clin Endocrinol Metab. 2021 DNA Methylation Haplotype Block Markers Efficiently Discriminate Follicular Thyroid Carcinoma from Follicular Adenoma. doi:10.1210/clinem/dgaa950
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Chen X. et al Nat Comm. 2020 Non-invasive early detection of cancer four years before conventional diagnosis using a blood test. doi: 10.1038/s41467-020-17316-z
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Guo S. et al Nat Genet. 2017 Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA. doi: 10.1038/ng.3805
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BLUEPRINT consortium. Nat Biotechnol. 2016 Quantitative comparison of DNA methylation assays for
biomarker development and clinical applications. doi: 10.1038/nbt.3605 -
Gole J. et al Nat Biotechnol. 2013 Massively parallel polymerase cloning and genome sequencing of
single cells using nanoliter microwells. doi: 10.1038/nbt.2720 -
Ruiz S. et al. Proc Natl Acad Sci U S A. 2012 Identification of a specific reprogramming-associated epigenetic signature in human induced pluripotent stem cells. doi: 10.1073/pnas.1202352109
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Diep D. et al Nature Meth 2012 Library-free methylation sequencing with bisulfite padlock probes. doi: 10.1038/nmeth.1871
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Yamaguchi S. et al Nature 2012 Tet1 controls meiosis by regulating meiotic gene expression https://www.ncbi.nlm.nih.gov/pubmed/23151479
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Gore A. et al Nature 2011 Somatic coding mutations in human induced pluripotent stem cells. doi: 10.1038/nature09805
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Shoemaker R. et al. Genome Res. 2010. Allele-specific methylation is prevalent and is contributed by CpG-SNPs in the human genome. doi: 10.1101/gr.104695.109
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Deng J. et al. Nat Biotechnol. 2009. Targeted bisulfite sequencing reveals changes in DNA methylation associated with nuclear reprogramming. doi: 10.1038/nbt.1530
Reporting summary
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Data availability
Data from this study, including the methylation matrices, are available in the main text, supplementary materials, supplementary datasets, or have been deposited in GitHub in the repository NCOMMS-20-10056-T [https://github.com/ncomms-20-10056-t/ncomms-20-10056-t]. Full genetic sequencing data was not included in the informed consent, hence only the methylation status at each genomic position has been released. The TCGA dataset is available at at the GDC Data Portal [https://portal.gdc.cancer.gov/].
Code availability
The Python code utilized in this study has been deposited in GitHub in the repository NCOMMS-20-10056-T [https://github.com/ncomms-20-10056-t/ncomms-20-10056-t].
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Acknowledgements
We are grateful to the staffs at Fudan University Taizhou Institute of Health Sciences. We also appreciate the members of the survey teams and the participants for their contribution to this study. The TZL study was supported by the National Key Research and Development Program of China (grant number: 2017YFC0907000, 2017YFC0907500, 2019YFC1315800, 2019YF101103, and 2016YFC0901403), the National Natural Science Foundation of China (grant number: 91846302 and 81502870), the Key Basic Research grants from the Science and Technology Commission of Shanghai Municipality (grant number: 16JC1400501), the International S&T Cooperation Program of China (grant number: 2015DFE32790), the Shanghai Municipal Science and Technology Major Project program (grant number: 2017SHZDZX01), the International Science and Technology Cooperation Program of China (grant number: 2015DFE32790), and the 111 Project (B13016). Funding for the DNA methylation assays was provided by Singlera Genomics.
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Contributions
X.C., J.G., A.G., Y.G., K.Z., R.L., and L.J. designed the study, wrote and revised the manuscript. X.C., M.L., W.Y., S.Y., and L.J. supervised the TZL study. X.Y., Y.J., T.Z., C.S., X.Z., M.F., X.W., Y.Y., J.Z., Z.Y., and J.W. collected and organized samples from the TZL cohort. R.L., J.G., Q.H., X.L., L.C., Z.Z., H.N., Z.L., Z.X., H.S., J.D., and C.M. performed or supervised experimental protocols. A.G. and J.M. analyzed the experimental data and developed the classification model. All authors approved the final manuscript.
Corresponding authors
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Competing interests
J.G., A.G., Q.H., J.M., X.L., L.C., Z.Z., H.N., Z.L., Z.X., H.S., J.D., C.M., and R.L. are employees of Singlera Genomics. Y.G. and R.L. are board members of Singlera Genomics. J.G., A.G., and R.L. are inventors on a patent (US62/657,544) held by Singlera Genomics that covers basic aspects of the library preparation method used in this paper. K.Z. is a co-founder, equity holder, and paid consultant of Singlera Genomics. The terms of these arrangements are being managed by the University of California–San Diego in accordance with its conflict of interest policies. X.C., M.L., Z.Y., X.Y., Y.J., T.Z., C.S., X.Z., M.F., X.W., Y.Y., J.Z., J.W., S.Y., W.Y., and L.J. declare no competing interests.
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Chen, X., Gole, J., Gore, A. et al. Non-invasive early detection of cancer four years before conventional diagnosis using a blood test. Nat Commun 11, 3475 (2020). https://doi.org/10.1038/s41467-020-17316-z
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DOIhttps://doi.org/10.1038/s41467-020-17316-z
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