Evidence map›Paper›PMID 37468977›Full record

ReviewBiomarker research2023

The application of Aptamer in biomarker discovery.

Yongshu Li, Winnie Wailing Tam, Yuanyuan Yu, Zhenjian Zhuo, Zhichao Xue, Chiman Tsang, Xiaoting Qiao, Xiaokang Wang, Weijing Wang, Yongyi Li and 2 more

Open access · goldAbstract readReview
In one paragraph

Review in Biomarker research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
11.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 72 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 8 institutions in 2 countries.

Yongshu LiCenter for Advanced Measurement Science, National Institute of Metrology, Beijing, China. yongshuli000@163.com.
Winnie Wailing TamLaw Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.
Yuanyuan YuLaw Sau Fai Institute for Advancing Translational Medicine in Bone and Joint Diseases (TMBJ), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.
Zhenjian ZhuoState Key Laboratory of Chemical Oncogenomic, Peking University Shenzhen Graduate School, Shenzhen, China.
Zhichao XueShenzhen Institute for Technology Innovation, National Institute of Metrology, Shenzhen, China.
Chiman TsangDepartment of Anatomical and Cellular Pathology, State Key Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong, China.
Xiaoting QiaoCenter for Advanced Measurement Science, National Institute of Metrology, Beijing, China.
Xiaokang WangDepartment of Pharmacy, Shenzhen Longhua District Central Hospital, Shenzhen, China.
Weijing WangShantou University Medical College, Shantou, China.
Yongyi LiLaboratory Animal Center, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
Yanyang TuResearch Center, Huizhou Central People's Hospital, Guangdong Medical University, Huizhou City, China. tufmmu@188.com.
Yunhua GaoCenter for Advanced Measurement Science, National Institute of Metrology, Beijing, China. gaoyh@nim.ac.cn.
National Institute of Metrology · CNHong Kong Baptist University · HKShenzhen Institute of Information Technology · CNChinese University of Hong Kong · HKHuizhou Central People's Hospital · CNLonggang Central Hospital · CNPeking University · CNShantou University Medical College · CN

Funding

National Key Research and Development Program of China 2022YFF0608401
6 · The paper itself

Abstract

Biomarkers are detectable molecules that can reflect specific physiological states of cells, organs, and organisms and therefore be regarded as indicators for specific diseases. And the discovery of biomarkers plays an essential role in cancer management from the initial diagnosis to the final treatment regime. Practically, reliable clinical biomarkers are still limited, restricted by the suboptimal methods in biomarker discovery. Nucleic acid aptamers nowadays could be used as a powerful tool in the discovery of protein biomarkers. Nucleic acid aptamers are single-strand oligonucleotides that can specifically bind to various targets with high affinity. As artificial ssDNA or RNA, aptamers possess unique advantages compared to conventional antibodies. They can be flexible in design, low immunogenicity, relative chemical/thermos stability, as well as modifying convenience. Several SELEX (Systematic Evolution of Ligands by Exponential Enrichment) based methods have been generated recently to construct aptamers for discovering new biomarkers in different cell locations. Secretome SELEX-based aptamers selection can facilitate the identification of secreted protein biomarkers. The aptamers developed by cell-SELEX can be used to unveil those biomarkers presented on the cell surface. The aptamers from tissue-SELEX could target intracellular biomarkers. And as a multiplexed protein biomarker detection technology, aptamer-based SOMAScan can analyze thousands of proteins in a single run. In this review, we will introduce the principle and workflow of variations of SELEX-based methods, including secretome SELEX, ADAPT, Cell-SELEX and tissue SELEX. Another powerful proteome analyzing tool, SOMAScan, will also be covered. In the second half of this review, how these methods accelerate biomarker discovery in various diseases, including cardiovascular diseases, cancer and neurodegenerative diseases, will be discussed.

Indexed as

AptamerBiomarker discoverycancerCardiovascular diseasesNeurodegeneration-related diseasesSELEXSOMAScan

Identifiers

PMID37468977
PMCPMC10354955
OpenAlexW4384818572

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.