Evidence map›Paper›PMID 40857673›Full record

ArticleBlood2025

Plasma lipid levels predict chemotherapy response and survival in acute myeloid leukemia.

Cristiana O'Brien, Nirvana Nursimulu, Anit Tyagi, Rachel Culp-Hill, Andrea Arruda, Tracy Murphy, Mark D Minden, Andrew Kent, Brett Stevens, Daniel A Pollyea and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Blood, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Cristiana O'BrienDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-2870-4918
Nirvana NursimuluPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.ORCID 0000-0001-5962-5863
Anit TyagiDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.ORCID 0000-0001-9455-2591
Rachel Culp-HillDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.ORCID 0000-0003-3000-083X
Andrea ArrudaDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Tracy MurphyDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Mark D MindenDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-9089-8816
Andrew KentDivision of Hematology, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.
Brett StevensDivision of Hematology, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.
Daniel A PollyeaDivision of Hematology, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.ORCID 0000-0001-6519-4860
Kristin HopeDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Sushant KumarDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
Julie A ReiszDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.ORCID 0000-0002-7296-4963
Angelo D'AlessandroDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO.ORCID 0000-0002-2258-6490
Courtney L JonesDepartment of Medical Biophysics, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0672-1493

Funding

University of Colorado Cancer Center Support Grant - Lung Cancer Patient-Derived Xenografts with Autologous Human Immune SystemsP30CA046934 · NCI · UNIVERSITY OF COLORADO DENVER · PI James V Degregori · 1988 to 2026
$117.0M
Alterations in fatty acid metabolism in the pathogenesis of leukemic stem cells from Acute Myeloid Leukemia patientsF31CA250361 · NCI · UNIVERSITY OF COLORADO DENVER · PI CULP-HILL, RACHEL · 2020 to 2022
$91k
NCI NIH HHS F31 CA250361NCI NIH HHS P30 CA046934
6 · The paper itself

Abstract

abstractAcute myeloid leukemia (AML) is characterized by a low 5-year survival rate. Despite having many clinical metrics to assess patient prognosis, there remain opportunities to improve risk stratification. We hypothesized that an underexplored resource to examine the prognosis of patients with AML is plasma metabolome. Circulating metabolites are influenced by patients' clinical status and can serve as accessible cancer biomarkers. To establish a resource of circulating metabolites in genetically diverse patients with AML, we performed an unbiased metabolomic and lipidomic analysis of 231 diagnostic AML plasma samples before treatment with intensive chemotherapy. Intriguingly, circulating metabolites were highly associated with the mutation status within the AML cells. Furthermore, lipids were associated with refractory status. We established a machine learning algorithm trained on chemotherapy-refractory-associated lipids to predict patient survival. Cox regression and Kaplan-Meier analysis demonstrated that the high-risk lipid signature predicted overall survival in this patient cohort. Impressively, the top lipid in the high-risk lipid signature, sphingomyelin (d44:1), was sufficient to predict overall survival in both the original data set and an independent validation data set. Overall, this research underscores the potential of circulating metabolites to capture AML heterogeneity and lipids to be used as potential AML biomarkers.

Indexed as

Biomarkers, TumorLeukemia, Myeloid, AcuteLipidsAdultAgedFemaleHumansMachine LearningMaleMiddle AgedPrognosisSurvival RateBiomarkers, TumorLipids

Identifiers

PMID40857673
PMCPMC12824675

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.