Evidence map›Paper›PMID 39864897›Full record

ReviewInternational review of cell and molecular biology2025

DOGMA-seq and multimodal, single-cell analysis in acute myeloid leukemia.

JangKeun Kim, Nathan Schanzer, Ruth Subhash Singh, Mohammed I Zaman, J Sebastian Garcia-Medina, Jacqueline Proszynski, Saravanan Ganesan, Dan Landau, Christopher Y Park, Ari M Melnick and 1 more

Abstract readReview
In one paragraph

Review in International review of cell and molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

11 authors.

JangKeun KimDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States.
Nathan SchanzerSchool of Medicine, New York Medical College, Valhalla, NY, United States.
Ruth Subhash SinghDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States.
Mohammed I ZamanDepartment of Biophysics and Physiology, Stony Brook University, Stony Brook, NY, United States.
J Sebastian Garcia-MedinaDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States.
Jacqueline ProszynskiDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States.
Saravanan GanesanDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States; Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States; New York Genome Center, New York, NY, United States.
Dan LandauDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States; Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States.
Christopher Y ParkNew York University Langone Medical Center, New York, NY, United States.
Ari M MelnickDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States; Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States.
Christopher E MasonDepartment of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, United States; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States. Electronic address: chm2042@med.cornell.edu.

Funding

Clinical and Molecular Heterogeneity in the Myelodysplastic SyndromesR01CA249054 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI MASON, CHRISTOPHER EDWARD, PARK, CHRISTOPHER Y · 2020 to 2024
$3.5M
NCI NIH HHS R01 CA249054
6 · The paper itself

Abstract

Acute myeloid leukemia (AML) is a complex cancer, yet advances in recent years from integrated genomics methods have helped improve diagnosis, treatment, and means of patient stratification. A recent example of a powerful, multimodal method is DOGMA-seq, which can measure chromatin accessibility, gene expression, and cell-surface protein levels from the same individual cell simultaneously. Previous bimodal single-cell techniques, such as CITE-seq (Cellular indexing of transcriptomes and epitopes), have only permitted the transcriptome and cell-surface protein expression measurement. DOGMA-seq, however, builds on this foundation and has implications for examining epigenomic, transcriptomic, and proteomic interactions between various cell types. This technique has the potential to be particularly useful in the study of cancers such as AML. This is because the cellular mechanisms that drive AML are rather heterogeneous and require a more complete understanding of the interplay between the genetic mutations, disruptions in RNA transcription and translation, and surface protein expression that cause these cancers to develop and evolve. This technique will hopefully contribute to a more clear and complete understanding of the growth and progression of complex cancers.

Indexed as

Leukemia, Myeloid, AcuteSingle-Cell AnalysisAnimalsHumansTranscriptomeAcute myeloid leukemiaDOGMA-seqLeukemic stem cellMulti-omicsSingle cell analysis

Identifiers

PMID39864897
PMCPMC12368869

What OpenQuestion holds

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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.