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Cited by 284

The DOI matches its Crossref record; 120 of the 120 references it cites were found in a registry or an index.

Circulating tumor cell isolation for cancer diagnosis and prognosis

Open access
Deng, Zicheng, Wu, Shengming, Wang, Yilong, Shi, Donglu·2022·eBioMedicine

Abstract

Circulating tumor cells (CTCs) are tumor cells that shed from the primary tumor and intravasate into the peripheral blood circulation system responsible for metastasis. Sensitive detection of CTCs from clinical samples can serve as an effective tool in cancer diagnosis and prognosis through liquid biopsy. Current CTC detection technologies mainly reply on the biomarker-mediated platforms including magnetic beads, microfluidic chips or size-sensitive microfiltration which can compromise detection sensitivity due to tumor heterogeneity. A more sensitive, biomarker independent CTCs isolation technique has been recently developed with the surface-charged superparamagnetic nanoprobe capable of different EMT subpopulation CTC capture from 1 mL clinical blood. In this review, this new strategy is compared with the conventional techniques on biomarker specificity, impact of protein corona, effect of glycolysis on cell surface charge, and accurate CTC identification. Correlations between CTC enumeration and molecular profiling in clinical blood and cancer prognosis are provided for clinical cancer management.

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Metadata

Authors
Deng, Z., Wu, S., Wang, Y., & Shi, D.
Venue
eBioMedicine
Publisher
Elsevier BV
Published
2022-09
Volume
83
Pages
104237
ISSN
2352-3964 (ISSN-L)
OpenAlex
W4293480811
Cited by
284
References
120
FWCI
16.53
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Circulating tumor cell isolation for cancer diagnosis and prognosis. https://app.cochat.ai/papers/10.1016/j.ebiom.2022.104237
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Deng, Z., Wu, S., Wang, Y., & Shi, D. (2022). Circulating tumor cell isolation for cancer diagnosis and prognosis. eBioMedicine. https://doi.org/10.1016/j.ebiom.2022.104237

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.