Evidence map›Paper›PMID 37033156›Full record

ReviewInnovation (Cambridge (Mass.))2023

Targeted protein degradation in cancers: Orthodox PROTACs and beyond.

Jin Li, Xinxin Chen, Aiping Lu, Chao Liang

Abstract readReview
In one paragraph

Review in Innovation (Cambridge (Mass.)), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Review
  2. Review
  3. Tricarbonyl Rhenium-Based PROTACs Degrade the SARS-CoV-2 Mpro Protease.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Review
  20. 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

4 authors.

Jin LiDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
Xinxin ChenDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
Aiping LuInstitute of Integrated Bioinfomedicine and Translational Science (IBTS), School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR 999077, China.
Chao LiangDepartment of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeted protein degradation (TPD) is emerging as a strategy to overcome the limitations of traditional small-molecule inhibitors. Proteolysis-targeting chimera (PROTAC) technology can be used to target proteins by hijacking the ubiquitin-proteasome system. Conceptually, PROTAC aims to target the "undruggable" majority of proteins in the human proteome. Through constant exploration and optimization of PROTACs and the exploitation of other TPD strategies over two decades, TPD has expanded from theoretical studies to clinical strategies, with practical applications in oncological, immunological, and other diseases. In this review, we introduce the mechanisms, features, and molecular targets of orthodox PROTACs and summarize the PROTAC drugs under study as cancer therapeutics in clinical trials. We also discuss PROTAC derivatives and other TPD strategies, such as lysosome-targeting chimeras, autophagy-targeting chimeras, and molecular glue strategies. Collectively, the studies summarized herein support the full potential of TPD in the biomedical industry.

Identifiers

PMID37033156
PMCPMC10074253

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.