Evidence map›Paper›PMID 41044455›Full record

ArticleNature communications2025

A deep single cell mass cytometry approach to capture canonical and noncanonical cell cycle states.

Meelad Amouzgar, Patricia Favaro, Daniel Ho, Trevor Bruce, Sean C Bendall

Abstract read
In one paragraph

Article in Nature communications, 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. Cell Cycle Sensing Shapes Human T Cell Fate and Exhaustion Programs.bioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Meelad AmouzgarDepartment of Pathology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-0521-9223
Patricia FavaroDepartment of Pathology, Stanford University, Stanford, CA, USA.
Daniel HoDepartment of Pathology, Stanford University, Stanford, CA, USA.
Trevor BruceDepartment of Pathology, Stanford University, Stanford, CA, USA.
Sean C BendallDepartment of Pathology, Stanford University, Stanford, CA, USA. bendall@stanford.edu.ORCID http://orcid.org/0000-0003-1341-2453

Funding

Wnt signaling in muscle stem cell agingP01AG036695 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ANNE BRUNET · 2011 to 2026
$29.3M
MOLECULAR &CELLULAR IMMUNOBIOLOGYT32AI007290 · NIAID · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Olivia M Martinez · 1985 to 2026
$27.0M
Stanford Cancer Immune Monitoring and Analysis Center (CIMAC)U24CA224309 · NCI · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Holden T. Maecker · 2017 to 2026
$19.9M
The Bone Marrow Multi-modal Imaging CoreU54HL165445 · NHLBI · STANFORD UNIVERSITY · PI ANGELO, ROBERT MICHAEL, BENDALL, SEAN CURTIS · 2022 to 2025
$5.9M
Uncovering mechanisms of protection from Alzheimer's disease in CHIP using human cohorts and biosamplesR01AG088656 · NIA · STANFORD UNIVERSITY · PI Sean Curtis Bendall, Siddhartha Jaiswal · 2024 to 2026
$4.3M
Deciphering the Glycan Code in Human Alzheimer’s Disease BrainR01AG078702 · NIA · UNIVERSITY OF KENTUCKY · PI Peggi M Angel, Sean Curtis Bendall · 2022 to 2026
$3.8M
Origins of human blood lineages in regenerative medicineDP2EB024246 · NIBIB · STANFORD UNIVERSITY · PI BENDALL, SEAN CURTIS · 2016 to 2016
$2.4M
Uncoupling Age- Versus Cognitive-Related Cellular Senescence in Alzheimer's DiseaseR01AG068279 · NIA · STANFORD UNIVERSITY · PI BENDALL, SEAN CURTIS · 2020 to 2024
$1.9M
Innate-adaptive immune bridging in gravidity-dependent immunity against placental malaria: a multi-omics approachR01AI189963 · NIAID · STANFORD UNIVERSITY · PI Robert michael Angelo, Prasanna Jagannathan · 2025 to 2026
$1.6M
NCI NIH HHS U24 CA224309NHLBI NIH HHS U54 HL165445NIAID NIH HHS R01 AI189963NIAID NIH HHS T32 AI007290NIA NIH HHS P01 AG036695NIA NIH HHS R01 AG068279NIA NIH HHS R01 AG078702NIA NIH HHS R01 AG088656NIBIB NIH HHS DP2 EB024246U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01AG068279U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01AG078702U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01AG088656U.S. Department of Health & Human Services | National Institutes of Health (NIH) U24CA224309U.S. Department of Health & Human Services | National Institutes of Health (NIH) U54HL165445
6 · The paper itself

Abstract

The cell cycle (CC) underpins diverse cell processes like cell differentiation, cell expansion, and tumorigenesis but current single-cell (sc) strategies study CC as: coarse phases, rely on transcriptomic signatures, use imaging modalities limited to adherent cells, or lack high-throughput multiplexing. To solve this, we develop an expanded, Mass Cytometry (MC) approach with 48 CC-related molecules that deeply phenotypes the diversity of scCC states. Using Cytometry by Time of Flight, we quantify scCC states across suspension and adherent cell lines, and stimulated primary human T cells. Our approach captures the diversity of scCC states, including atypical CC states beyond canonical definitions. Pharmacologically-induced CC arrest reveals that perturbations exacerbate noncanonical states and induce previously unobserved states. Notably, primary cells escaping CC inhibition demonstrated aberrant CC states compared to untreated cells. Our approach enables deeper phenotyping of CC biology that generalizes to diverse cell systems with simultaneous multiplexing and integration with MC platforms.

Indexed as

Cell CycleFlow CytometrySingle-Cell AnalysisCell Line, TumorHumansT-Lymphocytes

Identifiers

PMID41044455
PMCPMC12494979

What OpenQuestion 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 OpenQuestion graph.