Evidence map›Paper›PMID 41083674›Full record

ArticleScientific reports2025

Redefine tumor spheroids heterogeneity via PCA-coupled biophysical characterization.

Domenico Andrea Cristaldi, Martina Bedeschi, Gianfranco Cavallaro, Azzurra Sargenti, Simone Pasqua, Simone Bonetti, Daniele Gazzola, Noemi Marino, Cosimo Gianluca Fortuna, Anna Tesei

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

10 authors.

Domenico Andrea Cristaldi *CellDynamics iSRL, Bologna, 40136, Italy.
Martina Bedeschi *Bioscience Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, 47014, Italy.
Gianfranco CavallaroLaboratory of Molecular modelling and Heterocyclic compounds (ModHet), Department of Chemical Sciences, University of Catania, Catania, 95125, Italy.
Azzurra SargentiCellDynamics iSRL, Bologna, 40136, Italy.
Simone PasquaCellDynamics iSRL, Bologna, 40136, Italy.
Simone BonettiISMN-CNR, via Gobetti 101, Bologna, 40129, Italy.
Daniele GazzolaCellDynamics iSRL, Bologna, 40136, Italy.
Noemi MarinoBioscience Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, 47014, Italy. noemi.marino@irst.emr.it.
Cosimo Gianluca FortunaLaboratory of Molecular modelling and Heterocyclic compounds (ModHet), Department of Chemical Sciences, University of Catania, Catania, 95125, Italy.
Anna TeseiBioscience Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, 47014, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spheroids, a part of 3D cell culture systems, are crucial models for bridging in-vitro and in-human studies. However, achieving reliable standardization remains difficult, even when comparing spheroids of similar diameters. The challenge arises due to their cross-sectional architecture, which increases heterogeneity and affects biological outcomes. Here we present a novel solution that integrates Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) with Biophysical Characterization (PCA-BC). This approach allows for the identification and classification of variability within and across spheroid populations, offering insights into factors that contribute to heterogeneity. Additionally, it highlights the impact of different operators on spheroid development. The PCA-BC method enables real-time analysis of spheroid samples, facilitating the identification of variability across 3D populations. The integration of PCA and HCA with biophysical characterization provides a clear and efficient means to monitor sample heterogeneity. It also helps track how different operators influence the results, improving overall standardization in 3D cell cultures. By offering structural insights into spheroid heterogeneity, the PCA-BC approach supports more informed decision-making. This significantly improves workflow efficiency, conserving both time and resources, and enhances the reliability of 3D cell culture experiments.

Indexed as

NeoplasmsPrincipal Component AnalysisSpheroids, CellularBiophysical PhenomenaCell Culture TechniquesCell Line, TumorCluster AnalysisHumansTumor Cells, Cultured3D cell cultureBiophysical characterizationMass densitySpheroidsTumor models

Identifiers

PMID41083674
PMCPMC12518622

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.