Al Balushi, Noora;
Boyd-Moss, Mitchell;
Samarasinghe, Rasika M.;
Rifai, Aaqil;
Franks, Stephanie J.;
Firipis, Kate;
Long, Benjamin M.;
Darby, Ian A.;
Nisbet, David R.;
Pouniotis, Dodie;
Williams, Richard J.
Self-Assembled Peptide Habitats to Model Tumor Metastasis
Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
Medientyp:
E-Artikel
Titel:
Self-Assembled Peptide Habitats to Model Tumor Metastasis
Beteiligte:
Al Balushi, Noora;
Boyd-Moss, Mitchell;
Samarasinghe, Rasika M.;
Rifai, Aaqil;
Franks, Stephanie J.;
Firipis, Kate;
Long, Benjamin M.;
Darby, Ian A.;
Nisbet, David R.;
Pouniotis, Dodie;
Williams, Richard J.
Erschienen:
MDPI AG, 2022
Erschienen in:
Gels, 8 (2022) 6, Seite 332
Sprache:
Englisch
DOI:
10.3390/gels8060332
ISSN:
2310-2861
Entstehung:
Anmerkungen:
Beschreibung:
Metastatic tumours are complex ecosystems; a community of multiple cell types, including cancerous cells, fibroblasts, and immune cells that exist within a supportive and specific microenvironment. The interplay of these cells, together with tissue specific chemical, structural and temporal signals within a three-dimensional (3D) habitat, direct tumour cell behavior, a subtlety that can be easily lost in 2D tissue culture. Here, we investigate a significantly improved tool, consisting of a novel matrix of functionally programmed peptide sequences, self-assembled into a scaffold to enable the growth and the migration of multicellular lung tumour spheroids, as proof-of-concept. This 3D functional model aims to mimic the biological, chemical, and contextual cues of an in vivo tumor more closely than a typically used, unstructured hydrogel, allowing spatial and temporal activity modelling. This approach shows promise as a cancer model, enhancing current understandings of how tumours progress and spread over time within their microenvironment.