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New Research Consortium to Standardize Single-Cell Sequencing for Cancer Drug Resistance Studies

NEW YORK – A new public-private research partnership will attempt to build more reproducible single-cell sequencing workflows to study drug resistance in cancer.

Persist-Seq, a five-year program funded by the Innovative Medicines Initiative, will be led by the Oncode Institute in Utrecht, Netherlands, and AstraZeneca. The Hubrecht Institute, Netherlands Cancer InstituteSingle Cell DiscoveriesLygatureWellcome Sanger InstituteFondazione del Piemonte per l’OncologiaHubrecht Organoid Technology, Spain's Institute for Research in Biomedicine, Vall d'Hebron Institute of Oncology, Xenopat, Merck KGaA, Bayer, Transgene, and Charles River Laboratories are also joining the consortium.

Financial details were not disclosed.

"Drug resistance in cancer is one of the greatest causes of mortality, and despite increasing success with targeted therapies in the clinic, how cancer cells survive drug treatment is still not well understood," Ultan McDermott, chief scientist at AstraZeneca and the industrial co-lead of Persist-Seq, said in a statement. He noted that the project aims to characterize 5 million single cells over five years.

All experiments and pre-processing of data will be done at Single Cell Discoveries, a service provider based in Utrecht, to ensure standardization and continuity of experimental and bioinformatics workflows. It was not immediately clear which single-cell sequencing methods the consortium plans to use, but Single Cell Discoveries offers both 10x Genomics and plate-based methods, according to its website.

"The main goal of the Persist-Seq consortium is to generate a large single-cell cancer database," Mauro Muraro, CEO and cofounder of Single Cell Discoveries, said in a statement. "This database allows us to study and identify therapy-resistant cancer cells."

In a statement, the consortium said it will "employ an open access model to build and sustain its benchmarking procedures and centralized European data infrastructure. This model reduces duplication of effort, thereby promoting collaboration across disciplines and ensuring efficient adoption of state-of-the-art single-cell technologies."