Evidence map›Paper›PMID 40038430›Full record

ArticleCommunications biology2025

micronuclAI enables automated quantification of micronuclei for assessment of chromosomal instability.

Miguel A Ibarra-Arellano, Lindsay A Caprio, Aroj Hada, Niklas Stotzem, Luke L Cai, Shivem B Shah, Zachary H Walsh, Johannes C Melms, Florian Wünneman, Kresimir Bestak and 3 more

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Miguel A Ibarra-Arellano *Institute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-8411-4854
Lindsay A Caprio *Department of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA.ORCID http://orcid.org/0000-0003-1370-8684
Aroj HadaInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Niklas StotzemInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Luke L CaiDepartment of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA.
Shivem B ShahDepartment of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA.ORCID http://orcid.org/0000-0001-9439-6509
Zachary H WalshDepartment of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA.
Johannes C MelmsDepartment of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA.ORCID http://orcid.org/0000-0002-5410-6586
Florian WünnemanInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Kresimir BestakInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Ibrahim MansarayInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Benjamin IzarDepartment of Medicine, Division of Hematology/Oncology, and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University Vagelos College of Physician and Surgeons, New York, NY, USA. bi2175@cumc.columbia.edu.ORCID http://orcid.org/0000-0003-2379-6702
Denis SchapiroInstitute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Heidelberg, Germany. Denis.Schapiro@uni-heidelberg.de.ORCID http://orcid.org/0000-0002-9391-5722

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007367 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI REINER, STEVEN L · 1985 to 2021
$25.1M
Studying the evolution of drug resistance in prostate cancer at the single cell levelU54CA274506 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Peter Alan Sims · 2023 to 2026
$9.1M
Medical Scientist Training ProgramT32GM145440 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STEVEN L REINER · 2022 to 2026
$7.3M
Multi-cellular interactions defining the human brain metastatic nicheR01CA280414 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Benjamin Izar, Ashley Marie Laughney · 2023 to 2026
$2.8M
Mechanisms of liver metastasis and associated resistance to immunotherapyR37CA258829 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Benjamin Izar · 2021 to 2026
$2.6M
The role of the CD58:CD2 axis in cancer immune evasion and resistance to immunotherapyR01CA266446 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI FRANGIEH, CHRISTOPHER · 2022 to 2025
$2.0M
Chromosomal instability as a driver of non-small cell lung cancer immune evasion and brain metastasisF30CA281104 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Lindsay Anne Caprio · 2023 to 2026
$201k
Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) BMBF 01ZZ2004Deutsche Forschungsgemeinschaft (German Research Foundation) INST 35/1597-1 FUGGFoundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.) R01CA266446Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.) U54CA274506NCI NIH HHS F30 CA281104NCI NIH HHS R01 CA266446NCI NIH HHS R01 CA280414NCI NIH HHS R37 CA258829NCI NIH HHS U54 CA274506NIGMS NIH HHS T32 GM007367NIGMS NIH HHS T32 GM145440
6 · The paper itself

Abstract

Chromosomal instability (CIN) is a hallmark of cancer that drives metastasis, immune evasion and treatment resistance. CIN may result from chromosome mis-segregation errors and excessive chromatin is frequently packaged in micronuclei (MN), which can be enumerated to quantify CIN. The assessment of CIN remains a predominantly manual and time-consuming task. Here, we present micronuclAI, a pipeline for automated and reliable quantification of MN of varying size and morphology in cells stained only for DNA. micronuclAI can achieve close to human-level performance on various human and murine cancer cell line datasets. The pipeline achieved a Pearson's correlation of 0.9278 on images obtained at 10X magnification. We tested the approach in otherwise isogenic cell lines in which we genetically dialed up or down CIN rates, and on several publicly available image datasets where we achieved a Pearson's correlation of 0.9620. Given the increasing interest in developing therapies for CIN-driven cancers, this method provides an important, scalable, and rapid approach to quantifying CIN on images that are routinely obtained for research purposes. We release a GUI-implementation for easy access and utilization of the pipeline.

Indexed as

Chromosomal InstabilityMicronuclei, Chromosome-DefectiveAnimalsCell Line, TumorHumansImage Processing, Computer-AssistedMiceMicronucleus Tests

Identifiers

PMID40038430
PMCPMC11880189

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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.