Evidence map›Paper›PMID 36320481›Full record

ArticleChemical science2022

A stimulus-responsive hexahedron DNA framework facilitates targeted and direct delivery of native anticancer proteins into cancer cells.

Wenjiao Zhou, Fang Yang, Shunmei Li, Ruo Yuan, Yun Xiang

Abstract read
In one paragraph

Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Wenjiao ZhouSchool of Chemistry and Chemical Engineering, Chongqing University of Technology Chongqing 400054 P. R. China.
Fang YangKey Laboratory of Luminescence Analysis and Molecular Sensing, Ministry of Education, School of Chemistry and Chemical Engineering, Southwest University Chongqing 400715 P. R. China yunatswu@swu.edu.cn.
Shunmei LiKey Laboratory of Luminescence Analysis and Molecular Sensing, Ministry of Education, School of Chemistry and Chemical Engineering, Southwest University Chongqing 400715 P. R. China yunatswu@swu.edu.cn.
Ruo YuanKey Laboratory of Luminescence Analysis and Molecular Sensing, Ministry of Education, School of Chemistry and Chemical Engineering, Southwest University Chongqing 400715 P. R. China yunatswu@swu.edu.cn.
Yun XiangKey Laboratory of Luminescence Analysis and Molecular Sensing, Ministry of Education, School of Chemistry and Chemical Engineering, Southwest University Chongqing 400715 P. R. China yunatswu@swu.edu.cn.ORCID https://orcid.org/0000-0003-2982-425X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The targeted and direct intracellular delivery of proteins plays critical roles in biological research and disease treatments, yet remains highly challenging. Current solutions to such a challenge are limited by the modification of proteins that may potentially alter protein functions inside cells or the lack of targeting capability. Herein, we develop a stimulus-responsive and bivalent aptamer hexahedron DNA framework (HDF) for the targeted and direct delivery of native therapeutic proteins into cancer cells. The unmodified proteins are caged inside the HDF nanostructures assembled from six programmable single stranded DNAs to protect the proteins from degradation by cathepsins and enhance their targeting capability and delivery efficiency with the nanostructure-integrated aptamers. In addition, the protein drugs can be selectively released from the HDF nanostructures by the intracellular ATP molecules to induce tumor cell apoptosis, highlighting their promising application potential for cell biology and precise protein medicines.

Identifiers

PMID36320481
PMCPMC9516948

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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.