Literature DB >> 33369114

A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids.

Vito Rt Zanotelli1,2, Matthias Leutenegger3, Xiao-Kang Lun2,3,4, Fanny Georgi2,3, Natalie de Souza1,5, Bernd Bodenmiller1.   

Abstract

Cells react to their microenvironment by integrating external stimuli into phenotypic decisions via an intracellular signaling network. To analyze the interplay of environment, local neighborhood, and internal cell state effects on phenotypic variability, we developed an experimental approach that enables multiplexed mass cytometric imaging analysis of up to 240 pooled spheroid microtissues. We quantified the contributions of environment, neighborhood, and intracellular state to marker variability in single cells of the spheroids. A linear model explained on average more than half of the variability of 34 markers across four cell lines and six growth conditions. The contributions of cell-intrinsic and environmental factors to marker variability are hierarchically interdependent, a finding that we propose has general implications for systems-level studies of single-cell phenotypic variability. By the overexpression of 51 signaling protein constructs in subsets of cells, we also identified proteins that have cell-intrinsic and cell-extrinsic effects. Our study deconvolves factors influencing cellular phenotype in a 3D tissue and provides a scalable experimental system, analytical principles, and rich multiplexed imaging datasets for future studies.
© 2020 The Authors. Published under the terms of the CC BY 4.0 license.

Keywords:  high-throughput assay; multiplexed imaging; spatial signaling; spatial variance; tissue organization

Year:  2020        PMID: 33369114      PMCID: PMC7765047          DOI: 10.15252/msb.20209798

Source DB:  PubMed          Journal:  Mol Syst Biol        ISSN: 1744-4292            Impact factor:   11.429


  7 in total

Review 1.  3D-bioprinted cancer-on-a-chip: level-up organotypic in vitro models.

Authors:  Maria V Monteiro; Yu Shrike Zhang; Vítor M Gaspar; João F Mano
Journal:  Trends Biotechnol       Date:  2021-09-20       Impact factor: 19.536

2.  Intrinsic Differences in Spatiotemporal Organization and Stromal Cell Interactions Between Isogenic Lung Cancer Cells of Epithelial and Mesenchymal Phenotypes Revealed by High-Dimensional Single-Cell Analysis of Heterotypic 3D Spheroid Models.

Authors:  Maria L Lotsberg; Gro V Røsland; Austin J Rayford; Sissel E Dyrstad; Camilla T Ekanger; Ning Lu; Kirstine Frantz; Linda E B Stuhr; Henrik J Ditzel; Jean Paul Thiery; Lars A Akslen; James B Lorens; Agnete S T Engelsen
Journal:  Front Oncol       Date:  2022-04-22       Impact factor: 5.738

3.  Passiflora mollissima Seed Extract Induced Antiproliferative and Cytotoxic Effects on CAL 27 Spheroids.

Authors:  Angela Fonseca-Benitez; Sandra Johanna Morantes Medina; Diego Ballesteros-Vivas; Fabian Parada-Alfonso
Journal:  Adv Pharmacol Pharm Sci       Date:  2022-05-31

4.  In situ functional cell phenotyping reveals microdomain networks in colorectal cancer recurrence.

Authors:  Samantha A Furman; Andrew M Stern; Shikhar Uttam; D Lansing Taylor; Filippo Pullara; S Chakra Chennubhotla
Journal:  Cell Rep Methods       Date:  2021-09-15

Review 5.  24th "Nantes Actualités en Transplantation" and 4th "LabEx Immunotherapy-Graft-Oncology" NAT and IGO Joint Meeting "New Horizons in Immunotherapy".

Authors:  Noémie Joalland; Kathleen Ducoin; Gwenann Cadiou; Catherine Rabu; Carole Guillonneau
Journal:  Front Immunol       Date:  2021-09-03       Impact factor: 7.561

6.  Traject3d allows label-free identification of distinct co-occurring phenotypes within 3D culture by live imaging.

Authors:  Eva C Freckmann; Emma Sandilands; Erin Cumming; Matthew Neilson; Alvaro Román-Fernández; Konstantina Nikolatou; Marisa Nacke; Tamsin R M Lannagan; Ann Hedley; David Strachan; Mark Salji; Jennifer P Morton; Lynn McGarry; Hing Y Leung; Owen J Sansom; Crispin J Miller; David M Bryant
Journal:  Nat Commun       Date:  2022-09-09       Impact factor: 17.694

7.  A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma.

Authors:  Amin Zadeh Shirazi; Mark D McDonnell; Eric Fornaciari; Guillermo A Gomez; Narjes Sadat Bagherian; Kaitlin G Scheer; Michael S Samuel; Mahdi Yaghoobi; Rebecca J Ormsby; Santosh Poonnoose; Damon J Tumes
Journal:  Br J Cancer       Date:  2021-04-29       Impact factor: 7.640

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.