The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Identification of Liver Cancer-Specific Aptamers Using Whole Live Cells
Abstract
Liver cancer is the third most deadly cancers in the world. Unfortunately, there is no effective treatment. One of the major problems is that most cancers are diagnosed in the later stage, when surgical resection is not feasible. Thus, accurate early diagnosis would significantly improve the clinical outcome of liver cancer. Currently, there are no effective molecular probes to recognize biomarkers that are specific for liver cancer. The objective of our current study is to identify liver cancer cell-specific molecular probes that could be used for liver cancer recognition and diagnosis. We applied a newly developed cell-SELEX (Systematic Evolution of Ligands by EXponential enrichment) method for the generation of molecular probes for specific recognition of liver cancer cells. The cell-SELEX uses whole live cells as targets to select aptamers (designed DNA/RNA) for cell recognition. In generating aptamers for liver cancer recognition, two liver cell lines were used: a liver cancer cell line BNL 1ME A.7R.1 (MEAR) and a noncancer cell line, BNL CL.2 (BNL). Both cell lines were originally derived from Balb/cJ mice. Through multiple rounds of selection using BNL as a control, we have identified a panel of aptamers that specifically recognize the cancer cell line MEAR with Kd in the nanomolar range. We have also demonstrated that some of the selective aptamers could specifically bind liver cancer cells in a mouse model. There are two major new results (compared with our reported cell-SELEX methodology) in addition to the generation of aptamers specifically for liver cancer. The first one is that our current study demonstrates that cell-based aptamer selection can select specific aptamers for multiple cell lines, even for two cell lines with minor differences (MEAR cell is derived from BNL by chemical inducement); and the second result is that cell-SELEX can be used for adhesive cells and thus open the door for solid tumor selection and investigation. The newly generated cancer-specific aptamers hold great promise as molecular probes for cancer early diagnosis and basic mechanism studies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Lipocalins and Insulin Resistance: Etiological Role of Retinol-Binding Protein 4 and Lipocalin-2?
van Dam, R. M., & Hu, F. B. (2007) · Clinical Chemistry · doi:10.1373/clinchem.2006.080432 · Cited by 57
Cited by
Keefe, A. D., Pai, S., & Ellington, A. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3141 · Cited by 2,289
Aptamers from Cell-Based Selection for Bioanalytical Applications
Tan, W., Donovan, M. J., & Jiang, J. (2013) · Chemical Reviews · doi:10.1021/cr300468w · Cited by 649
Self-citationAptamer-integrated DNA nanostructures for biosensing, bioimaging and cancer therapy
Meng, H.-M., Liu, H., Kuai, H., Peng, R., Mo, L., & Zhang, X.-B. (2016) · Chemical Society Reviews · doi:10.1039/c5cs00645g · Cited by 608
Nimjee, S. M., White, R. R., Becker, R. C., & Sullenger, B. A. (2017) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010716-104558 · Cited by 607
The Chemical Biology of Aptamers
Mayer, G. (2009) · Angewandte Chemie International Edition · doi:10.1002/anie.200804643 · Cited by 592
Metadata
- Authors
- Shangguan, D., Meng, L., Cao, Z. C., Xiao, Z., Fang, X., Li, Y., Cardona, D., Witek, R. P., Liu, C., & Tan, W.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-01-05
- Volume
- 80
- Issue
- 3
- Pages
- 721-728
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2088202442
- Cited by
- 316
- References
- 1
- FWCI
- 8.31
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Identification of Liver Cancer-Specific Aptamers Using Whole Live Cells. https://app.cochat.ai/papers/10.1021/ac701962v
- The paper
- Shangguan, D., Meng, L., Cao, Z. C., Xiao, Z., Fang, X., Li, Y., Cardona, D., Witek, R. P., Liu, C., & Tan, W. (2008). Identification of Liver Cancer-Specific Aptamers Using Whole Live Cells. Analytical Chemistry. https://doi.org/10.1021/ac701962v
Data sources
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.