Evidence map›Paper›PMID 39572533›Full record

ArticleNature communications2024

Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma.

Elizabeth G Fernandez, Wilson X Mai, Kai Song, Nicholas A Bayley, Jiyoon Kim, Henan Zhu, Marissa Pioso, Pauline Young, Cassidy L Andrasz, Dimitri Cadet and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Translational Theranostics in Glioblastoma: FAPI-46 as a Precision Medicine Tool.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
  4. Review
  5. Article
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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

20 authors.

Elizabeth G FernandezDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
Wilson X MaiDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.ORCID 0000-0002-2977-5673
Kai SongDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
Nicholas A BayleyDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.ORCID 0000-0003-0489-0592
Jiyoon KimDepartment of Biostatistics, Jonathan and Karin Fielding School of Public Health, Los Angeles, California, USA.
Henan ZhuDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
Marissa PiosoDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
Pauline YoungDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
Cassidy L AndraszDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.
Dimitri CadetDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.ORCID 0000-0003-3518-608X
Linda M LiauJonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA.ORCID 0000-0002-4053-0052
Gang LiDepartment of Biostatistics, Jonathan and Karin Fielding School of Public Health, Los Angeles, California, USA.
William H YongDepartment of Pathology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Fausto J RodriguezDepartment of Pathology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Scott J DixonDepartment of Biology, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0001-6230-8199
Andrew J SouersAbbVie, Inc., 1 North Waukegan Road, North Chicago, IL, 60064, USA.ORCID 0009-0002-5965-0633
Jingyi Jessica LiDepartment of Biostatistics, Jonathan and Karin Fielding School of Public Health, Los Angeles, California, USA.ORCID 0000-0002-9288-5648
Thomas G GraeberDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.ORCID 0000-0001-8574-9181
Timothy F CloughesyDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.ORCID 0000-0002-8656-7483
David A NathansonDepartment of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA. dnathanson@mednet.ucla.edu.ORCID 0000-0002-4919-9159

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert Damoiseaux · 1985 to 2026
$134.5M
UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Yvonne Yu-Hsuan Chen · 2017 to 2026
$25.2M
TUMOR CELL SURFACES AND CHROMOSOMEST32CA009056 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Gay M Crooks, David A. Nathanson · 1985 to 2026
$10.5M
Mammalian models for integrated metabolic and molecular profiling of malignant gliomaR01CA227089 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GRAEBER, THOMAS G, NATHANSON, DAVID A. · 2018 to 2022
$2.7M
Quantitative molecular MR-PET imaging of glycolysis in glioblastomaR01CA279984 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Benjamin M. Ellingson, David A. Nathanson · 2023 to 2026
$2.4M
Statistical Methods for Elucidating Regulatory Mechanisms and Functional Impacts of Transcriptome Variation at Population and Single-Cell ScalesR35GM140888 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LI, JINGYI JESSICA · 2021 to 2025
$2.0M
NCI NIH HHS P30 CA016042NCI NIH HHS P50 CA211015NCI NIH HHS R01 CA227089NCI NIH HHS R01 CA279984NCI NIH HHS T32 CA009056NIGMS NIH HHS R35 GM140888NIGMS NIH HHS T32 GM008042U.S. Department of Health & Human Services | National Institutes of Health (NIH) P50CA211015U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01CA227089
6 · The paper itself

Abstract

Genomic profiling often fails to predict therapeutic outcomes in cancer. This failure is, in part, due to a myriad of genetic alterations and the plasticity of cancer signaling networks. Functional profiling, which ascertains signaling dynamics, is an alternative method to anticipate drug responses. It is unclear whether integrating genomic and functional features of solid tumours can provide unique insight into therapeutic vulnerabilities. We perform combined molecular and functional characterization, via BH3 profiling of the intrinsic apoptotic machinery, in glioma patient samples and derivative models. We identify that standard-of-care therapy rapidly rewires apoptotic signaling in a genotype-specific manner, revealing targetable apoptotic vulnerabilities in gliomas containing specific molecular features (e.g., TP53 WT). However, integration of BH3 profiling reveals high mitochondrial priming is also required to induce glioma apoptosis. Accordingly, a machine-learning approach identifies a composite molecular and functional signature that best predicts responses of diverse intracranial glioma models to standard-of-care therapies combined with ABBV-155, a clinical drug targeting intrinsic apoptosis. This work demonstrates how complementary functional and molecular data can robustly predict therapy-induced cell death.

Indexed as

ApoptosisGliomaAnimalsAntineoplastic AgentsBrain NeoplasmsCell Line, TumorGene Expression Regulation, NeoplasticHumansMachine LearningMiceMitochondriaSignal TransductionTumor Suppressor Protein p53Antineoplastic AgentsTumor Suppressor Protein p53

Identifiers

PMID39572533
PMCPMC11582606

What Socratic 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 Socratic graph.