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Cited by 351

The DOI matches its Crossref record; 136 of the 136 references it cites were found in a registry or an index.

Detecting Circulating Tumor Cells: Current Challenges and New Trends

Open access
Hong, Bin, Zu, Youli·2013·Theranostics

Abstract

Circulating tumor cells (CTCs) in the blood stream play a critical role in establishing metastases. The clinical value of CTCs as a biomarker for early cancer detection, diagnosis, prognosis, prediction, stratification, and pharmacodynamics have been widely explored in recent years. However, the clinical utility of current CTC tests is limited mainly due to methodological constraints. In this review, the pros and cons of the reported CTC assays are comprehensively discussed. In addition, the potential of tumor cell-derived materials as new targets for CTC detection, including circulating tumor microemboli, cell fragments, and circulating DNA, is evaluated. Finally, emerging approaches for CTC detection, including telomerase-based or aptamer-based assays and cell functional analysis, are also assessed. Expectantly, a thorough review of the current knowledge and technology of CTC detection will assist the scientific community in the development of more efficient CTC assay systems.

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Metadata

Authors
Hong, B., & Zu, Y.
Venue
Theranostics
Published
2013
Volume
3
Issue
6
Pages
377-394
ISSN
1838-7640 (ISSN-L)
OpenAlex
W2166535928
Cited by
351
References
136
FWCI
9.11
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Detecting Circulating Tumor Cells: Current Challenges and New Trends. https://app.cochat.ai/papers/10.7150/thno.5195
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Hong, B., & Zu, Y. (2013). Detecting Circulating Tumor Cells: Current Challenges and New Trends. Theranostics. https://doi.org/10.7150/thno.5195

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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.