Evidence map›Paper›PMID 40236136›Full record

ArticlebioRxiv : the preprint server for biology2025

Mapping cellular targets of covalent cancer drugs in the entire mammalian body.

Zhengyuan Pang, Verina H Leung, Cailynn C Wang, Ahmadreza Attarpour, Anthony Rinaldi, Hanbing Shen, Christopher Glynn, Logan H Sigua, Melaina Yender, Alexandra Selke and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Zhengyuan Pang
Verina H Leung
Cailynn C Wang
Ahmadreza Attarpour
Anthony Rinaldi
Hanbing Shen
Christopher Glynn
Logan H Sigua
Melaina Yender
Alexandra Selke
Senhan Xu
Peng Wu
Maged Goubran
Benjamin F Cravatt
Li Ye

Funding

Mapping brain-wide opioid actions by profiling neuronal activities and in vivo cellular target engagementR01DA059393 · NIDA · SCRIPPS RESEARCH INSTITUTE, THE · PI Laura M. Bohn, Ryan Ashok Shenvi · 2023 to 2026
$3.3M
Modulating somatosensory network to target metabolic diseasesDP2DK128800 · NIDDK · SCRIPPS RESEARCH INSTITUTE, THE · PI YE, LI · 2020 to 2020
$2.7M
A platform to identify in vivo targets of covalent cancer drugs in 3D tissuesR33CA281918 · NCI · SCRIPPS RESEARCH INSTITUTE, THE · PI CRAVATT, BENJAMIN F, YE, LI · 2023 to 2025
$1.3M
NCI NIH HHS R33 CA281918NIDA NIH HHS R01 DA059393NIDDK NIH HHS DP2 DK128800
6 · The paper itself

Abstract

As our understanding of biological systems reaches single-cell and high spatial resolutions, it becomes imperative that pharmacological approaches match this precision to understand drug actions. This need is particularly urgent for the targeted covalent inhibitors that are currently re-entering the stage for cancer treatments. Therefore, we developed 3D volumetric clearing-assisted tissue click chemistry (vCATCH) to image in vivo target-bound drugs by leveraging the unique kinetics of click reactions. In mice, vCATCH overcomes limitations of existing methods to achieve high-throughput volumetric chemical labeling through simple and passive incubation steps, thus enabling unbiased cellular resolution drug imaging in entire animals. We combined vCATCH with HYBRiD imaging and virtual reality to visualize and quantify in vivo targets of two clinical cancer drugs, afatinib and ibrutinib, which recapitulated their known pharmacological distribution and revealed previously unreported tissue and cell type engagement potentially linked to off-target effects. vCATCH provides a body-wide, unbiased platform to map covalent drug engagements at unprecedented scale and precision.

Identifiers

PMID40236136
PMCPMC11996413

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.