Evidence map›Paper›PMID 29642542›Full record

ReviewPharmaceuticals (Basel, Switzerland)2018

Antibody-Drug Conjugates for Cancer Therapy: Chemistry to Clinical Implications.

Nirnoy Dan, Saini Setua, Vivek K Kashyap, Sheema Khan, Meena Jaggi, Murali M Yallapu, Subhash C Chauhan

Open access · goldAbstract readReview
In one paragraph

Review in Pharmaceuticals (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.

0numbers the graph read from it
0cells of the map it votes in
97citing papers in PubMed
22.6field-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

97 citing papers in PubMed, 218 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Investigation of Antibody-Drug Conjugates by Mass Spectrometry.Advances in experimental medicine and biology · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Resistance to antibody-drug conjugates: A review.Acta pharmaceutica Sinica. B · 2025
    Review
  14. Review
  15. Review
  16. Review
  17. Review
  18. Review
  19. Review
  20. Article

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

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

7 authors at 2 institutions in 1 country.

Nirnoy DanDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. ndan@uthsc.edu.
Saini SetuaDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. ssetua@uthsc.edu.
Vivek K KashyapDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. vkashya1@uthsc.edu.
Sheema KhanDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. skhan14@uthsc.edu.
Meena JaggiDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. mjaggi@uthsc.edu.
Murali M YallapuDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. myallapu@uthsc.edu.
Subhash C ChauhanDepartment of Pharmaceutical Sciences and Cancer Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA. schauha1@uthsc.edu.
University of Tennessee Health Science Center · USCancer Research Center · US

Funding

MUC13 Mucin in Colorectal Cancer Health DisparityR01CA204552 · NCI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI CHAUHAN, SUBHASH C. · 2016 to 2020
$1.7M
Development of Targeted Nanotechnology Platform for Pancreatic CancerR01CA206069 · NCI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI CHAUHAN, SUBHASH C. · 2016 to 2021
$1.7M
Targeted Nanotherapy for Pancreatic CancerR01CA210192 · NCI · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI CHAUHAN, SUBHASH C. · 2016 to 2021
$1.7M
Targeted Nano-Chemosensitization of Breast CancersR15CA213232 · NCI · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI KUMAR, SANTOSH · 2017 to 2017
$440k
NCI NIH HHS R01 CA204552NCI NIH HHS R01 CA206069NCI NIH HHS R01 CA210192NCI NIH HHS R15 CA213232
6 · The paper itself

Abstract

Chemotherapy is one of the major therapeutic options for cancer treatment. Chemotherapy is often associated with a low therapeutic window due to its poor specificity towards tumor cells/tissues. Antibody-drug conjugate (ADC) technology may provide a potentially new therapeutic solution for cancer treatment. ADC technology uses an antibody-mediated delivery of cytotoxic drugs to the tumors in a targeted manner, while sparing normal cells. Such a targeted approach can improve the tumor-to-normal tissue selectivity and specificity in chemotherapy. Considering its importance in cancer treatment, we aim to review recent efforts for the design and development of ADCs. ADCs are mainly composed of an antibody, a cytotoxic payload, and a linker, which can offer selectivity against tumors, anti-cancer activity, and stability in systemic circulation. Therefore, we have reviewed recent updates and principal considerations behind ADC designs, which are not only based on the identification of target antigen, cytotoxic drug, and linker, but also on the drug-linker chemistry and conjugation site at the antibody. Our review focuses on site-specific conjugation methods for producing homogenous ADCs with constant drug-antibody ratio (DAR) in order to tackle several drawbacks that exists in conventional conjugation methods.

Indexed as

and cancer therapyantibodychemical linkerdrug conjugationdrug delivery

Identifiers

PMID29642542
PMCPMC6027311
OpenAlexW2796938019

What OpenQuestion 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 OpenQuestion graph.