Evidence map›Paper›PMID 38968069›Full record

ArticleCell reports2024

Interface-guided phenotyping of coding variants in the transcription factor RUNX1.

Kivilcim Ozturk, Rebecca Panwala, Jeanna Sheen, Kyle Ford, Nathan Jayne, Andrew Portell, Dong-Er Zhang, Stephan Hutter, Torsten Haferlach, Trey Ideker and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports, 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Kivilcim OzturkDivision of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA.
Rebecca PanwalaDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Jeanna SheenSchool of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
Kyle FordDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Nathan JayneSchool of Biological Sciences, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
Andrew PortellDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Dong-Er ZhangMoores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
Stephan HutterMLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, 81377 Munich, Germany.
Torsten HaferlachMLL Munich Leukemia Laboratory, Max-Lebsche-Platz 31, 81377 Munich, Germany.
Trey IdekerDivision of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA.
Prashant MaliDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA. Electronic address: pmali@ucsd.edu.
Hannah CarterDivision of Medical Genetics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA; Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA. Electronic address: hkcarter@health.ucsd.edu.

Funding

Bridge2AI: Cell Maps for AI (CM4AI) Data Generation ProjectOT2OD032742 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jean-Christophe Bélisle-Pipon, TIMOTHY W CLARK · 2022 to 2026
$21.5M
TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BADER, GARY D. · 2012 to 2024
$17.3M
The Cancer Cell Map Initiative v2.0U54CA274502 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Trey Ideker, Nevan J Krogan · 2022 to 2026
$14.2M
Using Networks to Seed Hierarchical Whole-cell Models of CancerU54CA209891 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KROGAN, NEVAN J · 2017 to 2021
$10.9M
The impact of genomic variation on environment-induced changes in pancreatic beta cell statesU01HG012059 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Hannah Kathryn Carter, Kyle Jeffrie Gaulton · 2021 to 2026
$7.5M
Synergestic roles of SRSF2 and RUNX1 in blood cell development and pathologyR01DK098808 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ZHANG, DONG-ER · 2013 to 2022
$4.8M
Next generation massively multiplexed combinatorial genetic screensR01HG012351 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Trey Ideker, Prashant Mali · 2023 to 2026
$2.7M
NCI NIH HHS U54 CA209891NCI NIH HHS U54 CA274502NHGRI NIH HHS R01 HG012351NHGRI NIH HHS U01 HG012059NIDDK NIH HHS R01 DK098808NIGMS NIH HHS P41 GM103504NIH HHS OT2 OD032742
6 · The paper itself

Abstract

Single-gene missense mutations remain challenging to interpret. Here, we deploy scalable functional screening by sequencing (SEUSS), a Perturb-seq method, to generate mutations at protein interfaces of RUNX1 and quantify their effect on activities of downstream cellular programs. We evaluate single-cell RNA profiles of 115 mutations in myelogenous leukemia cells and categorize them into three functionally distinct groups, wild-type (WT)-like, loss-of-function (LoF)-like, and hypomorphic, that we validate in orthogonal assays. LoF-like variants dominate the DNA-binding site and are recurrent in cancer; however, recurrence alone does not predict functional impact. Hypomorphic variants share characteristics with LoF-like but favor protein interactions, promoting gene expression indicative of nerve growth factor (NGF) response and cytokine recruitment of neutrophils. Accessible DNA near differentially expressed genes frequently contains RUNX1-binding motifs. Finally, we reclassify 16 variants of uncertain significance and train a classifier to predict 103 more. Our work demonstrates the potential of targeting protein interactions to better define the landscape of phenotypes reachable by missense mutations.

Indexed as

Core Binding Factor Alpha 2 SubunitBinding SitesCell Line, TumorHumansMutationMutation, MissensePhenotypeSingle-Cell AnalysisCore Binding Factor Alpha 2 SubunitRUNX1 protein, humancancercoding variantCP: GenomicsCP: Molecular biologyinterfacePerturb-seqprotein-protein interactionRNA-seqsingle-celltranscription factor

Identifiers

PMID38968069
PMCPMC11345852

What OpenQuestion holds

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Registered trials

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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.