Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 747

The DOI matches its Crossref record.

Aptamers Generated from Cell-SELEX for Molecular Medicine: A Chemical Biology Approach

Open access
Fang, Xiaohong, Tan, Weihong·2010·Accounts of Chemical Research

Abstract

Molecular medicine is an emerging field focused on understanding the molecular basis of diseases and translating this information into strategies for diagnosis and therapy. This approach could lead to personalized medical treatments. Currently, our ability to understand human diseases at the molecular level is limited by the lack of molecular tools to identify and characterize the distinct molecular features of the disease state, especially for diseases such as cancer. Among the new tools being developed by researchers including chemists, engineers, and other scientists is a new class of nucleic acid probes called aptamers, which are ssDNA/RNA molecules selected to target a wide range of molecules and even cells. In this Account, we will focus on the use of aptamers, generated from cell-based selections, as a novel molecular tool for cancer research. Cancers originate from mutations of human genes. These genetic alterations result in molecular changes to diseased cells, which, in turn, lead to changes in cell morphology and physiology. For decades, clinicians have diagnosed cancers primarily based on the morphology of tumor cells or tissues. However, this method does not always give an accurate diagnosis and does not allow clinicians to effectively assess the complex molecular alterations that are predictive of cancer progression. As genomics and proteomics do not yet allow a full access to this molecular knowledge, aptamer probes represent one effective and practical avenue toward this goal. One special feature of aptamers is that we can isolate them by selection against cancer cells without prior knowledge of the number and arrangement of proteins on the cellular surface. These probes can identify molecular differences between normal and tumor cells and can discriminate among tumor cells of different classifications, at different disease stages, or from different patients. This Account summarizes our recent efforts to develop aptamers through cell-SELEX for the study of cancer and apply those aptamers in cancer diagnosis and therapy. We first discuss how we select aptamers against live cancer cells. We then describe uses of these aptamers. Aptamers can serve as agents for molecular profiling of specific cancer types. They can also be used to modify therapeutic reagents to develop targeted cancer therapies. Aptamers are also aiding the discovery of new cancer biomarkers through the recognition of membrane protein targets. Importantly, we demonstrate how molecular assemblies can integrate the properties of aptamers and, for example, nanoparticles or microfluidic devices, to improve cancer cell enrichment, detection and therapy.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ar900101s

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 747

Metadata

Authors
Fang, X., & Tan, W.
Venue
Accounts of Chemical Research
Published
2009-09-14
Volume
43
Issue
1
Pages
48-57
ISSN
  • 0001-4842 (ISSN-L)
  • 1520-4898
OpenAlex
W2073883364
Cited by
747
References
0
FWCI
14.52
Type
journal article
Language
en
Open access
green

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: Aptamers Generated from Cell-SELEX for Molecular Medicine: A Chemical Biology Approach. https://app.cochat.ai/papers/10.1021/ar900101s
The paper
Fang, X., & Tan, W. (2010). Aptamers Generated from Cell-SELEX for Molecular Medicine: A Chemical Biology Approach. Accounts of Chemical Research. https://doi.org/10.1021/ar900101s

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.