Evidence map›Paper›PMID 41454442›Full record

ArticleMolecular oncology2026

LDAcoop: Integrating non-linear population dynamics into the analysis of clonogenic growth in vitro.

Nikko Brix, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger and 4 more

Abstract read
In one paragraph

Article in Molecular oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Nikko BrixDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.ORCID 0009-0007-1266-1278
Daniel SamagaResearch Unit Translational Metabolic Oncology (TMO), Institute for Diabetes and Cancer (IDC), Helmholtz Diabetes Center, Helmholtz Munich, Neuherberg, Germany.
Katharina GehrDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.
Benedek DankóDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.
Mohamed SchumannDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.
Guido DrexlerDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.
Ahmed AlnatshaDepartment of Internal Medicine II, University Hospital, LMU München, Munich, Germany.
Georg BeyerBavarian Center for Cancer Research (BZKF) partner site Munich, Munich, Germany.
Ujjwal MahajanBavarian Center for Cancer Research (BZKF) partner site Munich, Munich, Germany.
Martin SelmansbergerResearch Unit Translational Metabolic Oncology (TMO), Institute for Diabetes and Cancer (IDC), Helmholtz Diabetes Center, Helmholtz Munich, Neuherberg, Germany.
Julia MayerleBavarian Center for Cancer Research (BZKF) partner site Munich, Munich, Germany.
Claus BelkaDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.
Horst ZitzelsbergerResearch Unit Translational Metabolic Oncology (TMO), Institute for Diabetes and Cancer (IDC), Helmholtz Diabetes Center, Helmholtz Munich, Neuherberg, Germany.
Kirsten LauberDepartment of Radiation Oncology, University Hospital, LMU München, Munich, Germany.ORCID 0000-0002-8141-0452

Funding

Bundesministerium für Bildung und Forschung 02NUK047ABundesministerium für Bildung und Forschung 02NUK047CBundesministerium für Bildung und Forschung 02NUK061ABundesministerium für Bildung und Forschung 02NUK061CBundesministerium für Bildung und Forschung 02NUK086ABundesministerium für Bildung und Forschung 02NUK086BBundesministerium für Bildung und Forschung 02NUK087Deutsche Forschungsgemeinschaft 551613698
6 · The paper itself

Abstract

The limiting dilution assay (LDA) is a key method to quantify clonogenic cells with self-renewing capacity in vitro, crucial for preclinical cancer research and therapy response assessment. It estimates the frequency of individual clonogenic, stem-like cells within a population based on their ability to form colonies with ≥50 cells at limiting cell numbers. Standard LDA analysis relies on linear, single-hit Poisson models, yet clonogenic growth under single-cell conditions often involves cooperative or competitive dynamics, violating this linearity assumption. Here, we present a modeling framework incorporating non-linear population dynamics into LDA analysis and introduce LDAcoop, an R-based tool for universal quantification of clonogenic cells in LDA formats. Across multiple cancer cell types, we benchmarked LDA against the colony formation assay (CFA) and show that LDA outperforms CFA, especially for patient-derived organoids, suspension cultures, and higher throughput applications. This renders the LDA format particularly suitable for larger-scale pharmacogenomic screening and drug sensitivity testing in complex models. Our results establish LDA and LDAcoop as versatile, scalable tools for robust quantification of clonogenic growth, supporting preclinical drug development and molecular precision oncology research.

Indexed as

Nonlinear DynamicsCell Line, TumorCell ProliferationHumansModels, BiologicalNeoplasmsOrganoidsAllee effectcellular competitioncellular cooperationclonogenic growthclonogenic survivallimiting dilution assay

Identifiers

PMID41454442
PMCPMC13155136

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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.