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Ibarra-Arellano, M.A.* ; Caprio, L.A.* ; Hada, A.* ; Stotzem, N. ; Cai, L.L.* ; Shah, S.B.* ; Walsh, Z.H.* ; Melms, J.C.* ; Wünneman, F.* ; Bestak, K.* ; Mansaray, I.* ; Izar, B.* ; Schapiro, D.*

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

Comm. Biol. 8:361 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Scoring Criteria; Mechanisms; Cancer
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 2399-3642
e-ISSN 2399-3642
Zeitschrift Communications Biology
Quellenangaben Band: 8, Heft: 1, Seiten: , Artikelnummer: 361 Supplement: ,
Verlag Springer
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of AI for Health (AIH)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-540004-001
Förderungen Heidelberg University
National Institute of Health
Deutsche Forschungsgemeinschaft (DFG)
German Federal Ministry of Education and Research
German Research Foundation (DFG)
State of Baden-Wuerttemberg through bwHPC
Pershing Square Sohn Cancer Research Alliance Award
Burroughs Wellcome Fund Career Award for Medical Scientists
AI Health Innovation Cluster"
Health + Life Science Alliance Heidelberg Mannheim
MSTP Training Grant
NIH/NCI
CRI Lloyd J. Old STAR
V Foundation Scholars Award
Scholars Program
Tara Miller Melanoma Research Alliance Young Investigator Award
Bundesministerium fr Bildung und Forschung (Federal Ministry of Education and Research)
DOI 10.1038/s42003-025-07796-4
WOS ID 001439240900001
Scopus ID 86000092199
PubMed ID 40038430
Erfassungsdatum 2025-05-05
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