{"id":1661,"date":"2008-01-16T17:38:41","date_gmt":"2008-01-16T22:38:41","guid":{"rendered":"https:\/\/engineering.jhu.edu\/magazine-archive\/?p=1661"},"modified":"2014-12-16T17:39:16","modified_gmt":"2014-12-16T22:39:16","slug":"diagnosing-cancer-numbers","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2008\/01\/diagnosing-cancer-numbers\/","title":{"rendered":"Diagnosing Cancer By the Numbers"},"content":{"rendered":"<figure id=\"attachment_1662\" class=\"wp-caption alignright\" style=\"width: 667px\"><a href=\"https:\/\/engineering.jhu.edu\/magazine-archive\/wp-content\/uploads\/2014\/07\/winter200801.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-1662\" src=\"https:\/\/engineering.jhu.edu\/magazine-archive\/wp-content\/uploads\/2014\/07\/winter200801.jpg\" alt=\"The above figure shows four samples of normal tissue and three samples of cancerous tissue. Using microarray analysis, researchers can determine the level of expression of each gene in each sample. Here, we see that in cancerous tissue there is a tendency for gene 2 to express more frequently than gene 1 and the opposite is true for normal tissue. Geman and Naiman\u2019s diagnostic approach involves searching for pairs of genes that exhibit such a tendency to switch levels of expression between one tissue type and the other.\" width=\"657\" height=\"395\" srcset=\"https:\/\/engineering.jhu.edu\/magazine-archive\/wp-content\/uploads\/2014\/07\/winter200801.jpg 657w, https:\/\/engineering.jhu.edu\/magazine-archive\/wp-content\/uploads\/2014\/07\/winter200801-300x180.jpg 300w\" sizes=\"auto, (max-width: 657px) 100vw, 657px\" \/><\/a><figcaption class=\"wp-caption-text\">The above figure shows four samples of normal tissue and three samples of cancerous tissue. Using microarray analysis, researchers can determine the level of expression of each gene in each sample. Here, we see that in cancerous tissue there is a tendency for gene 2 to express more frequently than gene 1 and the opposite is true for normal tissue. Geman and Naiman\u2019s diagnostic approach involves searching for pairs of genes that exhibit such a tendency to switch levels of expression between one tissue type and the other.<\/figcaption><\/figure>\n<p>If you\u2019re trying to create a diagnostic test for cancer, you\u2019d expect that the more information you consider, the better. But recent work by Whiting School mathematicians shows that winnowing down the information you\u2019re looking at can be a better strategy.<\/p>\n<p>Advances in gene chip technology now allow researchers to take a tissue sample and easily construct gene expression profiles for thousands of individual genes. Computer programs can then compare the profiles of healthy tissue to cancerous tissue and decide whether a particular kind of cancer is present.<\/p>\n<p>It\u2019s not always easy, and even when the prediction works, it often depends on the combined expression levels of hundreds or even thousands of genes. So the information isn\u2019t much help for researchers looking for clues about what causes the cancer.<\/p>\n<p>Now the winnowing method developed by department chair Daniel Q. Naiman and Donald Geman, both professors in applied mathematics and statistics, is proving itself not only effective but simple enough for humans to understand, apply, and draw hypotheses from.<\/p>\n<p>Rather than consider the levels of hundreds or thousands of genes, their method depends on the relative levels of only two genes. \u201cWe decided to go to the other extreme, to do something as simple as possible,\u201d says Geman.<\/p>\n<p>The idea occurred to him when he was reading an article about programmed cell death. It turned out that by finding the levels of only two proteins, called Bax and Bad, you could tell if a cell was programmed to die. If there was more Bax than Bad, the cell would die; otherwise it would live.<\/p>\n<p>Geman and Naiman wondered if the same thing would work with a test for specific cancers. They obtained microarray data for tissue samples that had been confirmed to be cancerous and took all of the gene-expression levels, threw away the actual numbers, and simply ranked each gene from lowest to highest. Then they compared every gene to every other gene, until they found two genes that by themselves predicted whether a sample was cancerous or not.<\/p>\n<p>\u201cIt\u2019s cancer if the expression level of A is less than B. It\u2019s normal if vice versa,\u201d Geman explains.<\/p>\n<p>Although the technique requires a fair amount of number crunching to find the two genes in the first place, it\u2019s something that can be done in a fairly short time on a laptop. And once the pair for each kind of cancer is found, subsequent tests only have to look for those two genes.<\/p>\n<p>Geman and Naiman proposed the idea in a 2004 paper, showing that it worked to predict breast, prostate, and leukemia cancers.<\/p>\n<p>Then earlier this year, researchers from the Institute for Systems Biology in Seattle and the University of Texas in Houston confirmed that the technique also works in telling the difference between two cancers\u2014 gastrointestinal stromal tumor and leiomyosarcoma\u2014that can appear similar to diagnosticians but require different treatments. Their results appeared in the <em>Proceedings of the National Academy of Sciences<\/em>.<\/p>\n<p>And because researchers have an idea of what those two genes do, they have a new lead to follow in trying to understand the underlying mechanism of the cancers.<\/p>\n<p>The technique has its limitations. It doesn\u2019t provide a universal test for cancer\u2014each particular kind of cancer has to be analyzed to see if two genes can be found that predict it. \u201cIt\u2019s not a magic bullet,\u201d Geman acknowledges. \u201cSo far, none of these methods has made it to the point where it\u2019s part of your blood test.\u201d But stay tuned.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>If you\u2019re trying to create a diagnostic test for cancer, you\u2019d expect that the more information you consider, the better. But recent work by Whiting School mathematicians shows that winnowing down the information you\u2019re looking at can be a better strategy. Advances in gene chip technology now allow researchers to take a tissue sample and&#8230;<\/p>\n","protected":false},"author":4,"featured_media":1662,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[75],"tags":[],"class_list":["post-1661","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-development","issue-winter-2008"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Diagnosing Cancer By the Numbers - JHU Engineering Magazine<\/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:\/\/engineering.jhu.edu\/magazine-archive\/2008\/01\/diagnosing-cancer-numbers\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Diagnosing Cancer By the Numbers - JHU Engineering Magazine\" \/>\n<meta property=\"og:description\" content=\"If you\u2019re trying to create a diagnostic test for cancer, you\u2019d expect that the more information you consider, the better. 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