Evidence map›Paper›PMID 37919548›Full record

ArticleNature chemical biology2024

Live-cell target engagement of allosteric MEKi on MEK-RAF/KSR-14-3-3 complexes.

William M Marsiglia, Arthur Chow, Zaigham M Khan, Liu He, Arvin C Dar

Open access · greenAbstract read
In one paragraph

Article in Nature chemical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. 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 3 institutions in 1 country.

William M MarsigliaDepartment of Oncological Sciences, The Tisch Cancer Institute, Mount Sinai Center for Therapeutic Discovery, Icahn School of Medicine at Mount Sinai, New York, NY, USA. wmmarsig@uab.edu.
Arthur ChowDepartment of Oncological Sciences, The Tisch Cancer Institute, Mount Sinai Center for Therapeutic Discovery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Zaigham M KhanDepartment of Oncological Sciences, The Tisch Cancer Institute, Mount Sinai Center for Therapeutic Discovery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0002-2471-4054
Liu HeDepartment of Oncological Sciences, The Tisch Cancer Institute, Mount Sinai Center for Therapeutic Discovery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Arvin C DarDepartment of Oncological Sciences, The Tisch Cancer Institute, Mount Sinai Center for Therapeutic Discovery, Icahn School of Medicine at Mount Sinai, New York, NY, USA. dara1@mskcc.org.ORCID 0000-0003-0318-4848
Memorial Sloan Kettering Cancer Center · USIcahn School of Medicine at Mount Sinai · USUniversity of Alabama at Birmingham · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
TRAINING PROGRAM IN CANCER THERAPYT32CA078207 · NCI · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI James J Manfredi · 1999 to 2026
$11.6M
Targeting Oncogenic Ras-MAPK Signaling Complexes via the Scaffold KSRR01CA227636 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Arvin Dar · 2018 to 2026
$4.0M
AN INTEGRATED PLATFORM FOR NOVEL PERSONALIZED LIVER CANCER THERAPEUTICSR01CA256480 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DAR, ARVIN, GUCCIONE, ERNESTO · 2021 to 2025
$3.3M
A Chemical Genetic Approach to Exploring Novel Therapeutic Space for Colorectal CancerR01CA258736 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI DAR, ARVIN · 2021 to 2025
$3.2M
A Cytochrome P450 Therapeutic Space for TauopathiesR56AG066712 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CAGAN, ROSS LEIGH, DAR, ARVIN · 2021 to 2021
$802k
Defining the relationship between kinase inhibitor pharmacophores and pro-/anti-targets using in vivo models of colorectal cancerK00CA212474 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MARSIGLIA, WILLIAM M · 2019 to 2022
$374k
Mechanisms of resistance and activation conferred by kinases displaying hinge and gate-keeper mutationsF99CA212474 · NCI · NEW YORK UNIVERSITY · PI MARSIGLIA, WILLIAM M · 2016 to 2017
$89k
NCI NIH HHS F99 CA212474NCI NIH HHS K00 CA212474NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA227636NCI NIH HHS R01 CA256480NCI NIH HHS R01 CA258736NCI NIH HHS T32 CA078207NIA NIH HHS R56 AG066712
6 · The paper itself

Abstract

The RAS-mitogen-activated protein kinase (MAPK) pathway includes KSR, RAF, MEK and the phospho-regulatory sensor 14-3-3. Specific assemblies among these components drive various diseases and likely dictate efficacy for numerous targeted therapies, including allosteric MEK inhibitors (MEKi). However, directly measuring drug interactions on physiological RAS-MAPK complexes in live cells has been inherently challenging to query and therefore remains poorly understood. Here we present a series of NanoBRET-based assays to quantify direct target engagement of MEKi on MEK1 and higher-order MEK1-bound complexes with ARAF, BRAF, CRAF, KSR1 and KSR2 in the presence and absence of 14-3-3 in living cells. We find distinct MEKi preferences among these complexes that can be compiled to generate inhibitor binding profiles. Further, these assays can report on the influence of the pathogenic BRAF-V600E mutant on MEKi binding. Taken together, these approaches can be used as a platform to screen for compounds intended to target specific complexes in the RAS-MAPK cascade.

Indexed as

Biological AssayProto-Oncogene Proteins B-rafMAP Kinase Signaling SystemProtein Kinase InhibitorsProtein Kinase InhibitorsProto-Oncogene Proteins B-raf

Identifiers

PMID37919548
PMCPMC10948974
OpenAlexW4388217295

What OpenQuestion holds

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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.