Publication success!
Congratulations to Deola Sara and colleagues at Sidra Medicine (Qatar) and the Università degli Studi del Piemonte Orientale (Italy) on their recent publication in Blood Advances just last month!
Deola and colleagues conducted an impactful study to improve #genetherapy approaches for #hemophilia. For those of you unsure, hemophilia is a bleeding disorder that occurs as a result of a blood-clotting protein deficiency or dysfunction. Treatment options are currently limited, but progress has been made in recent #clinicaltrials that have looked at replacing the blood clotting protein factor VIII in autologous hematopoietic stem cells (HSCs) using viral delivery systems.
Here, Deola et al. identified exactly which cell types should be targeted for such gene therapy, by looking at which HSCs and their progeny produce factor VIII. They achieved this by leveraging a flow cytometry method to generate a comprehensive map of native and lentivirus-based transgenic factor VIII production right from the HSC stage to the mature blood cell stage. Their map showed that factor VIII is produced during the progenitor-cell stages after cytokine stimulation. In the mature blood-cell stages, monocytes are responsible for most factor VIII production.
Moving to a zebrafish model of transient HA to validate their findings, Deola et al. found that promoting HSC self-renewal by treating these cells with the agonist UM171 resulted in the specific expansion of CD14+/CD31+ monocytes. These monocytes could carry the factor VIII transgene, thus correcting HA in zebrafish!
These findings might signal an advance towards a permanent treatment for patients with HA! Check out the details here: https://lnkd.in/drmBuRgT
Well done to everyone involved in this really exciting project: Insight Editing London’s Ilya Demchenko really enjoyed getting a sneak peek of these results before submission and assisting with the editing.
This latest paper we are delighted to announce comes from Jin Liu and colleagues, and describes a new method known as PRECAST that can integrate multiple spatial transcriptomics datasets from multiple tissue slides and possibly even multiple individuals.
As detailed in their Nature Communications paper, Jin Liu et al. show that PRECAST is computationally scalable and applicable to spatial transcriptomics datasets deriving from different platforms.
You can find out more about how PRECAST was developed and tested on both simulated and real datasets, here: https://lnkd.in/d7jetuK5
Well done to everyone involved in this important project – we are delighted to see it available to read online!