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Faux, M.

Publications and source records attributed to Faux, M..

2 recordsLinked to original sources

EGFR-targeted affibody-polyIC polyplex kills EGFR-overexpressing cancer cells without activating the EGFR

The epidermal growth factor receptor (EGFR) is aberrantly activated in many human epithelial cancers. This report presents the preparation, purification, and the anti-cancer potency of an anti-EGFR affibody (ZEGFR 1907)-polyethylenimine (PEI)-polyIC complex (PPEA-polyplex). Surface plasmon resonance analysis showed that the ZEGFR 1907 affibody binds tightly to full-length sEGFR with an average equilibrium dissociation constant, KD, value of 6.74 nM. The PPEA-polyplex does not activate the EGFR kinase, but kills tumor cells expressing medium to high levels of EGFR. The PPEA-polyplex stimulates the release of chemotactic cytokines (e.g., GRO-, IFN-{gamma}-inducible protein-10) and promoted PBMC-mediated bystander killing of non-transfected tumor cells. The PPEA-polyplex inhibited the growth of human epidermoid vulval carcinoma (A431) xenografts growing in immunocompromised nude mice. PPEA-polyplexes have the potential to inhibit the growth of tumors in Triple-negative breast cancer (TNBC) patients and other cancers which over-express the EGFR.

cancer biology↗

Application of spatial transcriptomics across organoids: a high-resolution spatial whole-transcriptome benchmarking dataset

Stem cell-derived organoids hold promise to model tissue-specific disease. To enable this, it is crucial to assess how transcriptional signatures, cellular organisation and composition of organoids compare to in vivo counterparts. However, technologies which elucidate regional molecular identity, like spatial transcriptomics, have been challenging to apply to organoids. This study presents the first systematic profiling of multiple stem cell derived organoid models (brain, heart muscle, heart valve, kidney, lung, cartilage, and haematopoietic) with Stereo-seq, a full transcriptome, spatial transcriptomics assay using on-chip in situ RNA capture at subcellular resolution. It describes optimisation of this assay to characterise organoids, use of multiple organoid samples on a single chip, assess differences in RNA capture efficiency compared to reference tissues and its limitations. This study introduces a bespoke analysis method that partitions samples into regions and further characterises them. These findings inform future works to characterise organoids using spatial transcriptomics, providing insights in optimising RNA capture of multiple organoids across a chip and novel methods for regional analysis.

bioinformatics↗