{"id":25096,"date":"2018-07-16T16:12:38","date_gmt":"2018-07-16T20:12:38","guid":{"rendered":"https:\/\/www.tun.com\/blog\/?p=25096"},"modified":"2022-03-16T10:41:58","modified_gmt":"2022-03-16T14:41:58","slug":"method-revolutionizes-tracking-spread-of-cancer","status":"publish","type":"post","link":"https:\/\/www.tun.com\/blog\/method-revolutionizes-tracking-spread-of-cancer\/","title":{"rendered":"Method Revolutionizes Tracking the Spread of Cancer"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">A team of researchers has developed <\/span><a href=\"https:\/\/engineering.princeton.edu\/news\/2018\/06\/29\/researchers-apply-computing-power-track-spread-cancer\"><span style=\"font-weight: 400;\">a new method<\/span><\/a><span style=\"font-weight: 400;\"> to track the spread of cancer cells, yielding a clearer understanding of cancer migration than ever before. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The spread of tumor cells to different locations in the body, known as metastasis, is the most dangerous element of cancer. M<\/span><span style=\"font-weight: 400;\">etastatic disease causes close to 90 percent of cancer deaths from solid tumors. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Understanding what causes metastasis is crucial to developing treatments capable of halting the spread of cancer. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">In May, the researchers presented an algorithm called MACHINA that can track the spread of cancer cells by combining DNA sequence data with information on the location of the cells in the body. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">MACHINA stands for \u201cmetastatic and clonal history integrative analysis.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Recently, they have made improvements to MACHINA and are using the algorithm to develop a clearer understanding of metastasis.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cThe main contribution of our paper is that we introduced an algorithm that infers patterns of metastasis from sequencing data,\u201d said <\/span><a href=\"https:\/\/cs.illinois.edu\/directory\/profile\/melkebir\"><span style=\"font-weight: 400;\">Mohammed El-Kebir<\/span><\/a><span style=\"font-weight: 400;\">, an assistant professor of computer science at the University of Illinois at Urbana-Champaign who co-authored the study while he was a post-doctoral researcher at Princeton University. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cIn contrast to previous methods that have been developed for use in species evolution, our algorithm MACHINA incorporates an evolutionary model that is tailored to cancer.\u201d<\/span><\/p>\n<h2><b>MACHINA<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Some of the information gathered through the use of MACHINA suggests cancer-cell migration patterns that don\u2019t match the current understanding of cancer biology. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the study, MACHINA simultaneously traced the mutations and movements of cells to prove that metastatic disease can result from fewer cell migrations than previously assumed. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">In a study of a breast cancer patient, MACHINA suggested that a secondary tumor in the lung caused metastatic disease through five cell migrations. A previously conducted analysis suggested it was caused by 14 migrations. &nbsp;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cWe decided to develop MACHINA after realizing that current analyses of metastasis might be incorrect due to inappropriate assumptions in the used algorithms, which were initially developed for use in species evolution,\u201d said El-Kebir. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The researchers also used their algorithm to analyze metastasis in patients with melanoma, prostate and ovarian cancers. &nbsp;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">They added multiple features to improve MACHINA\u2019s accuracy. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Because it has been proven that tumor cells can travel in clusters, the algorithm includes a model for the co-migration of cells. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The algorithm also is set to recognize the uncertainty in DNA data resulting from the mixtures of healthy cells and tumor cells. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">A paper describing the team\u2019s full efforts is published in the journal <\/span><a href=\"https:\/\/www.nature.com\/articles\/s41588-018-0106-z\"><span style=\"font-weight: 400;\">Nature Genetics<\/span><\/a><span style=\"font-weight: 400;\">. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Gryte Satas, a doctoral student at Princeton, was also a co-author of the study.<\/span><\/p>\n<h2><b>Implications of MACHINA<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Through the use of MACHINA, researchers could uncover key patterns and mutations that cause the spread of cancer. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cA better algorithm is like a better microscope,\u201d <\/span><a href=\"https:\/\/lsi.princeton.edu\/ben-raphael\"><span style=\"font-weight: 400;\">Ben Raphael<\/span><\/a><span style=\"font-weight: 400;\">, a professor of computer science at Princeton and senior author of the research, said in a statement.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cWhen you look at nature with a magnifying glass, you may miss important details. If you look with a microscope you can see much more.\u201d<\/span><\/p>\n<h2><b>What\u2019s next?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The next step in this development is to apply MACHINA to a large amount of matched primary and metastasis samples, explained El-Kebir. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cThis will enable one to identify common patterns of metastatic progression, including the mutations that drive metastasis,\u201d he said.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Before the technology can be actively used by doctors to track the spread of cancer, the researchers wish to improve the accuracy of MACHINA by advancing the sequencing technology with longer reads and less errors, explained El-Kebir. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Additionally, the researchers plan to improve their method by incorporating data from tumor cells and DNA in the bloodstream, and they want to recognize data regarding reversible chemical modifications of DNA. &nbsp;&nbsp;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Altogether, the development is promising and imperative in the fight against cancer. <\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cI predict this new method will be of widespread use to the genomic community and will shed new light on the most deadly phase of cancer evolution,\u201d <\/span><a href=\"https:\/\/www.icr.ac.uk\/our-research\/researchers-and-teams\/dr-andrea-sottoriva\"><span style=\"font-weight: 400;\">Andrea Sottoriva<\/span><\/a><span style=\"font-weight: 400;\">, the Chris Rokos Fellow in Evolution and Cancer at The Institute of Cancer Research in London, said in a statement. <\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A team of researchers has developed a new method to track the spread of cancer cells, yielding a clearer understanding of cancer migration than ever before. The spread of tumor cells to different locations in the body, known as metastasis, is the most dangerous element of cancer. Metastatic disease causes close to 90 percent of [&hellip;]<\/p>\n","protected":false},"author":32,"featured_media":45683,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[241,230,229,507,243],"tags":[],"class_list":["post-25096","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-medical-breakthrough","category-news","category-lead-stories","category-university-of-illinois-at-urbana-champaign","category-health"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg",830,533,false],"thumbnail":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer-224x144.jpg",224,144,true],"medium":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer-300x193.jpg",300,193,true],"medium_large":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg",830,533,false],"large":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg",830,533,false],"1536x1536":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg",830,533,false],"2048x2048":["https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg",830,533,false]},"uagb_author_info":{"display_name":"Jackson Schroeder","author_link":"https:\/\/www.tun.com\/blog\/author\/jackson-schroeder\/"},"uagb_comment_info":0,"uagb_excerpt":"A team of researchers has developed a new method to track the spread of cancer cells, yielding a clearer understanding of cancer migration than ever before. The spread of tumor cells to different locations in the body, known as metastasis, is the most dangerous element of cancer. Metastatic disease causes close to 90 percent of&hellip;","featured_media_src_url":"https:\/\/www.tun.com\/blog\/wp-content\/uploads\/2018\/07\/Method-Revolutionizes-Tracking-The-Spread-Of-Cancer.jpg","_links":{"self":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts\/25096","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/users\/32"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/comments?post=25096"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/posts\/25096\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/media\/45683"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/media?parent=25096"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/categories?post=25096"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/blog\/wp-json\/wp\/v2\/tags?post=25096"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}