[2207.09264] Flow Rate Independent Multiscale Liquid Biopsy for Precision Oncology Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Quantitative Biology > Quantitative Methods arXiv:2207.09264 (q-bio) [Submitted on 19 Jul 2022 ( v1 ), last revised 14 Nov 2022 (this version, v2)] Title: Flow Rate Independent Multiscale Liquid Biopsy for Precision Oncology Authors: Jing Yan , Jie Wang , Robert Dallmann , Renquan Lu , Jérôme Charmet View a PDF of the paper titled Flow Rate Independent Multiscale Liquid Biopsy for Precision Oncology, by Jing Yan and 4 other authors View PDF Abstract: Immunoaffinity-based liquid biopsies of circulating tumor cells (CTCs) hold great promise for cancer management, but typically suffer from low throughput, relative complexity and post-processing limitations. Here we address these issues simultaneously by decoupling and independently optimizing the nano-, micro- and macro-scales of an enrichment device that is simple to fabricate and operate. Unlike other affinity-based devices, our scalable mesh approach enables optimum capture conditions at any flow rate, as demonstrated with constant capture efficiencies, above 75% between 50-200 uL/min. The device achieved 96% sensitivity and 100% specificity when used to detect CTCs in the blood of 79 cancer patients and 20 healthy controls. We demonstrate its post processing capacity with the identification of potential responders to immune checkpoint inhibition therapy and the detection of HER2 positive breast cancer. The results compare well with other assays, including clinical standards. This suggests that our approach, which overcomes major limitations associated with affinity-based liquid biopsies, could help improve cancer management. Comments: 19 pages, 5 figures (+ supplementary materials: 16 pages, 10 figures) Subjects: Quantitative Methods (q-bio.QM) Cite as: arXiv:2207.09264 [q-bio.QM] (or arXiv:2207.09264v2 [q-bio.QM] for this version) https://doi.org/10.48550/arXiv.2207.09264 Focus to learn more arXiv-issued DOI via DataCite Related DOI : https://doi.org/10.1021/acssensors.2c02577 Focus to learn more DOI(s) linking to related resources Submission history From: Jerome Charmet [ view email ] [v1] Tue, 19 Jul 2022 13:23:27 UTC (1,715 KB) [v2] Mon, 14 Nov 2022 07:52:51 UTC (1,698 KB) Full-text links: Access Paper: View a PDF of the paper titled Flow Rate Independent Multiscale Liquid Biopsy for Precision Oncology, by Jing Yan and 4 other authors View PDF view license Current browse context: q-bio.QM < prev | next > new | recent | 2022-07 Change to browse by: q-bio References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from