{"id":4941,"date":"2020-01-10T15:00:30","date_gmt":"2020-01-10T14:00:30","guid":{"rendered":"https:\/\/saarland-informatics-campus.de\/piece-of-news\/research-collaboration-develops-new-method-that-could-facilitate-cancer-diagnosis\/"},"modified":"2020-01-10T15:00:30","modified_gmt":"2020-01-10T14:00:30","slug":"research-collaboration-develops-new-method-that-could-facilitate-cancer-diagnosis","status":"publish","type":"sic_news","link":"https:\/\/saarland-informatics-campus.de\/en\/piece-of-news\/research-collaboration-develops-new-method-that-could-facilitate-cancer-diagnosis\/","title":{"rendered":"Research collaboration develops new method that could facilitate cancer diagnosis"},"content":{"rendered":"

Researchers led by the European Molecular Biology Laboratory (EMBL) in Heidelberg and the Center for Bioinformatics at Saarland University in Saarbr\u00fccken, Germany, have developed a cheaper and faster method to check for genetic differences in individual cells, which outperforms existing techniques with respect to the information received. This new method could become a new standard in single cell research, and potentially for clinical diagnosis in disease genetics, including cancer. The results have been published in Nature Biotechnology.<\/strong><\/p>\n

\u201cOur new method to study genetic variations in individual cells could transform the field of mutation detection,\u201d highlights Ashley Sanders, one of the lead authors of the study, working at EMBL Heidelberg, Germany. The method she and her colleagues developed \u2013 termed scTRIP (single cell tri-channel processing) \u2013 allows them to study genetic variations within the DNA of a single cell and measure genetic variations directly as they form in new cells. In contrast to existing methods that were able to detect only large-scale changes in the genome, scTRIP can detect small-scale changes, along with many types of genetic variations that were invisible using other single cell methods.<\/p>\n

The researchers tested their method in studying patient-derived leukaemia cells. In their sample, the team found four times more variants in the patient than were detected by standard clinical diagnostics. These included a missed clinically relevant translocation that drove the overexpression of a cancer-causing gene. They also observed a catastrophic chromosome rearrangement that was missed in the initial leukaemia diagnosis. It probably occurred when a single chromosome shattered and was then glued back together in a rearranged order. <\/p>\n

\u201cThese first results show that our method is outperforming existing ones significantly. Our method is much faster and cheaper than methods currently in use to uncover genetic variants in single cells. This might be very useful for clinical applications,\u201d summarises Tobias Marschall, from the Center for Bioinformatics at Saarland University and the Max Planck Institute for Informatics. The team has begun to expand their use of the method to analyse different forms of leukaemia and evaluate its potential clinical utility. <\/p>\n

As the heterogeneity of a sample can best be studied at a single-cell level, researchers all over the world \u2013 including several groups at EMBL \u2013 are working on the development of technologies to improve the information received. \u201cWhile existing techniques show how different cells can behave or respond to manipulation or treatment, research and application have so far centred on measuring the RNA within a cell. However, measuring the DNA in a single cell has so far received much less attention,\u201d explains Tobias Marschall. As it is expected that looking at the DNA will provide a new level of understanding in how these genetic changes drive different cell behaviours, the new method addresses the needs of both researchers and medical doctors.<\/p>\n

scTRIP is based on a technology Ashley Sanders co-developed during her PhD in Vancouver. \u201cscTRIP combines signals from three distinct channels of information from within the genomic code of the individual cell,\u201d explains Jan Korbel, group leader at EMBL Heidelberg. \u201cDoing so, our method allows us to uncover the full spectrum of DNA rearrangements in individual cells.\u201d<\/p>\n

Now, using scTRIP, the researchers are continuing their research on a very basic question: How much does one cell in the body differ from any other cell, in the context of cancer as well as in normal cells? Until now, they were unable to address this question because they lacked the technology to do so. \u201cUsing scTRIP we can now directly measure the mutational processes that act in cells to generate new genetically distinct populations,\u201d says Ashley Sanders. For the next steps in their research, the team plans to study mutational processes in different human cell types, and to assess the consequences these differences have in terms of human diseases.<\/p>\n

More information:<\/strong>
\nSanders A. et al. Single-cell analysis of structural variations and complex rearrangements with tri-channel-processing; D. Nature Biotechnology, published online on 23 December 2019<\/p>\n

Questions can be directed to: <\/strong>
\nProfessor Tobias Marschall
\nCenter for Bioinformatics
\nSaarland Informatics Campus (SIC)
\nTel.: +49 681 302 70880
\nE-mail: marschall@cs.uni-saarland.de<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers led by the European Molecular Biology Laboratory (EMBL) in Heidelberg and the Center for Bioinformatics at Saarland University in Saarbrücken, Germany, have developed a cheaper and faster method to check for genetic differences in individual cells, which outperforms existing techniques with respect to the information received. This new method could become a new standard […]<\/p>\n","protected":false},"featured_media":2771,"menu_order":0,"template":"","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":""},"sic_news-types":[61,59],"class_list":["post-4941","sic_news","type-sic_news","status-publish","has-post-thumbnail","hentry","sic_news-types-migrated-en","sic_news-types-press-release-en"],"yoast_head":"\nResearch collaboration develops new method that could facilitate cancer diagnosis - Saarland Informatics Campus<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/saarland-informatics-campus.de\/en\/piece-of-news\/research-collaboration-develops-new-method-that-could-facilitate-cancer-diagnosis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Research collaboration develops new method that could facilitate cancer diagnosis - Saarland Informatics Campus\" \/>\n<meta property=\"og:description\" content=\"Researchers led by the European Molecular Biology Laboratory (EMBL) in Heidelberg and the Center for Bioinformatics at Saarland University in Saarbrücken, Germany, have developed a cheaper and faster method to check for genetic differences in individual cells, which outperforms existing techniques with respect to the information received. 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