Evidence map›Paper›PMID 38129681›Full record

ArticleCancer gene therapy2024

The target atlas for antibody-drug conjugates across solid cancers.

Jiacheng Fang, Lei Guo, Yanhao Zhang, Qing Guo, Ming Wang, Xiaoxiao Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Cancer gene therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

17 citing papers in PubMed, 17 citations in OpenAlex.

  1. A modular framework for antibody-drug conjugate biomarkers.Nature reviews. Clinical oncology · 2026
    Review
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  3. Article
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  5. Review
  6. Review
  7. Article
  8. Review
  9. Advances in Nanobody-Based Platforms for Precision Cancer Diagnosis and Therapy.Polymer science & technology (Washington, D.C.) · 2025
    Review
  10. Review
  11. Diverse Roles of Antibodies in Antibody-Drug Conjugates.Pharmaceuticals (Basel, Switzerland) · 2025
    Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
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

6 authors at 4 institutions in 2 countries.

Jiacheng FangInterdisciplinary Institute of Medical Engineering, Fuzhou University, Fuzhou, Fujian, 350108, China.ORCID 0009-0002-3673-5343
Lei GuoInterdisciplinary Institute of Medical Engineering, Fuzhou University, Fuzhou, Fujian, 350108, China. gankLei@fzu.edu.cn.
Yanhao ZhangSchool of Ecology and Environment, Zhengzhou University, Zhengzhou, Henan, 450001, China.
Qing GuoDepartment of Chemistry, Hong Kong Baptist University, RRS812 Kowloon Tong, Hong Kong SAR, China.
Ming WangCollege of Food Science & Engineering, Northwest University, 229 Taibai North Road, Xi'an, Shaanxi, 710069, China. wangming@nwu.edu.cn.
Xiaoxiao WangState Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, RRS812, Kowloon Tong, Hong Kong SAR, China. wangxiaoxiao_523@163.com.
Hong Kong Baptist University · HKFujian Medical University · CNNorthwest University · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibody-Drug Conjugates (ADCs) represent a rapidly advancing category of oncology therapeutics, spanning the targeted therapy for both hematologic malignancies and solid cancers. A crucial aspect of ADC research involves the identification of optimal surface antigens that can effectively differentiate target cells from most mammalian cell types. Herein, we have devised an algorithm and compiled an extensive dataset annotating cell membrane proteins. This dataset is derived from comprehensive transcriptomic, proteomic, and genomic data encompassing 19 types of solid cancer as well as normal tissues. The aim is to uncover potential therapeutic surface antigens for precise ADC targeting. The resulting target landscape comprises 165 combinations of targets and indications, along with 75 candidates of cell surface proteins. Notably, 35 of these candidates possess characteristics suitable for ADC targeting, and have not been previously reported in ADC research and development. Additionally, we have identified a total of 159 ADCs from a pool of 760 clinical trials. Of these, 72 ADCs are presently undergoing interventional evaluation for a variety of solid cancer types, targeting 36 unique antigens. We conducted an analysis of their expression in normal tissues using this comprehensive annotation dataset, revealing a diverse range of profiles for the current ADC targets. Moreover, we emphasize that the biological impacts of target antigens have the potential to enhance their clinical effectiveness. We propose a comprehensive assessment of the drugability of target antigens, considering multiple facets. This study represents a thorough exploration of pan-cancer ADC targets over the past two decades, underscoring the potential of a comprehensive solid cancer target atlas to broaden the scope of ADC therapies.

Indexed as

Antineoplastic AgentsImmunoconjugatesNeoplasmsAnimalsAntigens, SurfaceHumansMammalsProteomicsAntigens, SurfaceAntineoplastic AgentsImmunoconjugates

Identifiers

PMID38129681
OpenAlexW4390055385

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.