Evidence map›Paper›PMID 40799478›Full record

ArticleBio-protocol2025

Accurate Identification of Cell Cycle Stages in RPE1 Cells Using the ImmunoCellCycle-ID Method.

Syon Reddy, Yu-Lin Chen, Aussie Suzuki

Abstract read
In one paragraph

Article in Bio-protocol, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Syon ReddyMcArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin-Madison, Madison, WI, USA.
Yu-Lin ChenMcArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin-Madison, Madison, WI, USA.
Aussie SuzukiMcArdle Laboratory for Cancer Research, Department of Oncology, University of Wisconsin-Madison, Madison, WI, USA.

Funding

Center for Structural Biology of HIV RNAU54AI170660 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ALICE TELESNITSKY · 2022 to 2026
$32.1M
Chromosome dynamics and organizations necessary for faithful chromosome segregationR35GM147525 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Aussie Suzuki · 2022 to 2026
$2.5M
NIAID NIH HHS U54 AI170660NIGMS NIH HHS R35 GM147525
6 · The paper itself

Abstract

Accurate identification of cell cycle stages is essential for investigating fundamental biological processes such as proliferation, differentiation, and tumorigenesis. While flow cytometry remains a widely used technique for such analyses, it is limited by its lack of single-cell resolution and its requirement for large sample sizes due to its population-based approach. These limitations underscore the need for alternative or complementary methods that offer single-cell precision with compatibility for small-scale applications. We present ImmunoCellCycle-ID, an immunofluorescence-based method that leverages the spatial distribution of endogenous markers, such as DNA, proliferating cell nuclear antigen (PCNA), centromere protein F (CENP-F), and centromere protein C (CENP-C), to reliably distinguish G1, early S, late S, early G2, late G2, and all mitotic sub-stages. This technique does not rely on precise signal quantification and utilizes standard immunofluorescence protocols alongside conventional laboratory microscopes, ensuring broad accessibility. Importantly, ImmunoCellCycle-ID detects endogenous proteins without the need for genetic modification, making it readily applicable to a wide range of human cell lines. Beyond its utility for single-cell resolution, the method can be scaled for population-level analyses, similar to flow cytometry. With its precision, versatility, and ease of implementation, ImmunoCellCycle-ID offers a powerful tool for high-resolution cell cycle profiling across diverse experimental platforms. Key features • Enables high-precision identification of cell cycle stages at single-cell resolution. • Broadly applicable to diverse human cell lines without genetic modification. • Fully compatible with standard fluorescence microscopy; no specialized equipment needed. • Requires only minimal image analysis and no complex quantification.

Indexed as

Cancer researchCell biologyCell cycleImmunofluorescenceSingle-cell analysis

Identifiers

PMID40799478
PMCPMC12336857

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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.