{"id":46773,"date":"2024-09-11T12:00:00","date_gmt":"2024-09-11T12:00:00","guid":{"rendered":"https:\/\/www.cancer.gov\/news-events\/cancer-currents-blog\/2024\/new-cancer-drug-targets-from-proteogenomics-data"},"modified":"2024-11-03T15:11:47","modified_gmt":"2024-11-03T15:11:47","slug":"study-identifies-hundreds-of-potential-targets-for-cancer-drugs","status":"publish","type":"post","link":"https:\/\/ogkologos.com\/en\/study-identifies-hundreds-of-potential-targets-for-cancer-drugs\/","title":{"rendered":"Study Identifies Hundreds of Potential Targets for Cancer Drugs"},"content":{"rendered":"

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Using proteogenomic data from more than 1,000 tumors representing 10 cancer types, researchers have found hundreds of promising targets for existing drugs or possible new cancer drugs.<\/p>\n

Credit: iStock\/mathisworks<\/p>\n<\/p><\/div>\n<\/figcaption><\/figure>\n<\/p><\/div>\n

Most targeted cancer drugs work by blocking proteins in or on cancer cells that help tumors grow. But the process of identifying promising proteins to target can be painstaking and often leads to false starts and dead ends.<\/p>\n

Now, a team of researchers from the United States and China has identified hundreds of proteins that appear to be either promising targets<\/a> for existing drugs or leads for the development of new cancer treatments. <\/p>\n

Their findings were based in part on a comprehensive analysis of proteogenomic data\u2014that is, detailed information on genes<\/a> and proteins\u2014collected from more than 1,000 tumors representing 10 types of cancer. These data were compiled and made available by NCI\u2019s Clinical Proteomic Tumor Analysis Consortium (CPTAC)<\/a>. <\/p>\n

Published June 24 in Cell<\/em>, the study\u2019s findings open up entirely new avenues for attacking cancer, said the study\u2019s co-leader, Bing Zhang, Ph.D., of Baylor College of Medicine.<\/p>\n

\u201cThe potentially targetable space is much, much bigger than what we are currently pursuing,\u201d Dr. Zhang noted.<\/p>\n

In the study, the researchers put several of their predicted targets to the test. For example, in laboratory studies<\/a>, they showed that they could stunt the growth of cancer cells by blocking the production of several proteins that their predictions suggested would be good drug targets. <\/p>\n

Ana I. Robles, Ph.D., of NCI\u2019s Office of Cancer Clinical Proteomics Research and a program director for CPTAC, said that this proteogenomic approach to identifying new targets has the potential to substantially streamline the development of new cancer treatments. <\/p>\n

Focusing on targets identified in this way could help drug developers prioritize those that are most likely to be important in different cancers, potentially improving the currently low success rate in developing new cancer drugs, said Dr. Robles, who was not involved in the study.<\/p>\n

Shifting the search to proteins <\/h2>\n

Targeted drugs currently approved to treat cancer disrupt the activity of fewer than 200 proteins, which, according to some estimates, is only about 5% of the proteins that are potentially targetable.<\/p>\n

Past efforts to better understand the molecular underpinnings of cancer have focused on finding genetic alterations associated with the disease. But because of the complexity of how genes behave under different circumstances, such as in cancer cells residing in the hectic environment that surrounds tumors, researchers have begun looking more closely at proteins\u2014the end products of gene<\/a> activity.<\/p>\n

But proteins have been more difficult to study than genes, largely because the technology to analyze proteins has lagged behind the technology to analyze DNA<\/a> and RNA<\/a>, Dr. Zhang explained.<\/p>\n

That\u2019s changed in recent years, with new technologies that are allowing researchers to more precisely analyze proteins themselves rather than the genes that encode them\u2014that is, provide the blueprints for their creation.<\/p>\n

For more than a decade, Dr. Robles explained, CPTAC has been a leader in generating proteogenomic data, which meshes together information on tumors\u2019 genetic and protein makeup.<\/p>\n

Last year, for example, CPTAC-supported researchers released comprehensive proteogenomic data on 10 different cancer types<\/a>, including breast, lung, colon, and ovarian cancer, and made the data publicly available to researchers around the world. This huge repository of data has made investigating proteins and genes across different cancers much more practical, Dr. Zhang explained.<\/p>\n

\u201cOur goal is to translate the data generated by our collaborators in the consortium into actionable insights,\u201d he said.  <\/p>\n

The study by Dr. Zhang and his colleagues is an example of why it\u2019s important to make these data publicly available, Dr. Robles said. Their analysis \u201cis a beautiful use of the CPTAC data set,\u201d she said. <\/p>\n

Uncovering a trove of potential targets<\/h2>\n

For their study, Dr. Zhang and his colleagues integrated CPTAC data on genetic mutations and protein variations across the 10 different cancer types with data from other large data sources used to identify potential drug targets.<\/p>\n

Based on this information, the team identified more than 2,800 proteins as potential targets for the two most common types of cancer drugs, called small molecule drugs or antibodies<\/a>, then classified the target proteins into five groups, or tiers. (See box.)<\/p>\n