Evidence map›Paper›PMID 38651410›Full record

ArticleAntibodies (Basel, Switzerland)2024

Enhanced Characterization of Lysine-Linked Antibody Drug Conjugates Enabled by Middle-Down Mass Spectrometry and Higher-Energy Collisional Dissociation-Triggered Electron-Transfer/Higher-Energy Collisional Dissociation and Ultraviolet Photodissociation.

Eleanor Watts, Aarti Bashyal, Sean D Dunham, Christopher M Crittenden, Jennifer S Brodbelt

Open access · goldAbstract read
In one paragraph

Article in Antibodies (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

Eleanor WattsDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712, USA.
Aarti BashyalDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0003-3559-4534
Sean D DunhamDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-6214-7468
Christopher M CrittendenSmall Molecule Pharmaceutical Sciences, Genentech Inc., South San Francisco, CA 94080, USA.
Jennifer S BrodbeltDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0003-3207-0217
The University of Texas at Austin · US

Funding

National Science Foundation CHE-2203602Welch Foundation F-1155
6 · The paper itself

Abstract

As the development of new biotherapeutics advances, increasingly sophisticated tandem mass spectrometry methods are needed to characterize the most complex molecules, including antibody drug conjugates (ADCs). Lysine-linked ADCs, such as trastuzumab-emtansine (T-DM1), are among the most heterogeneous biotherapeutics. Here, we implement a workflow that combines limited proteolysis with HCD-triggered EThcD and UVPD mass spectrometry for the characterization of the resulting middle-down large-sized peptides of T-DM1. Fifty-three payload-containing peptides were identified, ranging in mass from 1.8 to 16.9 kDa, and leading to the unambiguous identification of 46 out of 92 possible conjugation sites. In addition, seven peptides were identified containing multiple payloads. The characterization of these types of heterogeneous peptides represents an important step in unraveling the combinatorial nature of lysine-conjugated ADCs.

Indexed as

antibody drug conjugatebiotherapeuticpayloadtandem mass spectrometrytrastuzumab-emtansine

Identifiers

PMID38651410
PMCPMC11036284
OpenAlexW4394892077

What OpenQuestion holds

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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.