Evidence map›Paper›PMID 32451504›Full record

ArticleNature nanotechnology2020

Cancer diagnosis with DNA molecular computation.

Chao Zhang, Yumeng Zhao, Xuemei Xu, Rui Xu, Haowen Li, Xiaoyan Teng, Yuzhen Du, Yanyan Miao, Hsiao-Chu Lin, Da Han

Abstract read
PubMed Publisher
In one paragraph

Article in Nature nanotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
–field-weighted citation impact
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

74 citing papers in PubMed.

  1. Article
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  9. Review
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  11. Information Theory-Guided Detection of Biomarkers Using Programmable Aptamer Arrays.medRxiv : the preprint server for health sciences · 2025
    Article
  12. Article
  13. Article
  14. Multiplexed and high-bandwidth DNA computing circuits with superresolution DNA origami displays.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Article
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  20. DNA Sequential Logic Circuits for Reversible Counters and Dynamic Biomolecular Sensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article

14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Chao ZhangInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0000-0003-0399-1201
Yumeng ZhaoInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xuemei XuInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Rui XuInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Haowen LiInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaoyan TengDepartment of Laboratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Yuzhen DuDepartment of Laboratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Yanyan MiaoInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID http://orcid.org/0000-0002-6817-4117
Hsiao-Chu LinInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Da HanInstitute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, State Key Laboratory of Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. dahan@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-0804-2964

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early and precise cancer diagnosis substantially improves patient survival. Recent work has revealed that the levels of multiple microRNAs in serum are informative as biomarkers for the diagnosis of cancers. Here, we designed a DNA molecular computation platform for the analysis of miRNA profiles in clinical serum samples. A computational classifier is first trained in silico using miRNA profiles from The Cancer Genome Atlas. This is followed by a computationally powerful but simple molecular implementation scheme using DNA, as well as an effective in situ amplification and transformation method for miRNA enrichment in serum without perturbing the original variety and quantity information. We successfully achieved rapid and accurate cancer diagnosis using clinical serum samples from 22 healthy people (8) and people with lung cancer (14) with an accuracy of 86.4%. We envision that this DNA computational platform will inspire more clinical applications towards inexpensive, non-invasive and rapid disease screening, classification and progress monitoring.

Indexed as

Computers, MolecularBiomarkers, TumorComputational BiologyEarly Detection of CancerGene Expression ProfilingHumansLung NeoplasmsMicroRNAsBiomarkers, TumorMicroRNAs

Identifiers

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.