{"id":27608,"date":"2021-11-04T12:00:00","date_gmt":"2021-11-04T12:00:00","guid":{"rendered":"https:\/\/www.cancer.gov\/news-events\/cancer-currents-blog\/2021\/protein-interactions-mapping-cancer-pathways"},"modified":"2024-11-03T15:14:10","modified_gmt":"2024-11-03T15:14:10","slug":"studies-delve-deep-into-the-protein-machinery-of-cancer-cells","status":"publish","type":"post","link":"https:\/\/ogkologos.com\/en\/studies-delve-deep-into-the-protein-machinery-of-cancer-cells\/","title":{"rendered":"Studies Delve Deep into the Protein Machinery of Cancer Cells"},"content":{"rendered":"
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An “interactome” of protein\u2013protein interactions detected in two head and neck cancer cell lines and one normal cell line.<\/p>\n

Credit: From Science. October 1, 2021. doi: 10.1126\/science.abf2911. Reprinted with permission from AAAS.<\/p>\n<\/div>\n<\/figcaption><\/figure>\n<\/div>\n

Proteins are often called the workhorses of cells, the machinery that makes cells go. They act as key players in the many chemical reactions constantly occurring in cells, collect cellular garbage, provide structure, repair damaged DNA<\/a>, and much more. But individual proteins<\/a> rarely act on their own. Instead, like molecular LEGO bricks, they join together with other proteins in precise configurations to carry out their duties.<\/p>\n

Now, a team of researchers has used advanced technologies and computational techniques to identify the interactions among proteins that commonly form in head and neck and breast cancer cells. They also created a map of how the interacting proteins\u2014also called protein complexes\u2014function in key communication networks, or pathways, in those cells.<\/p>\n

Three studies describing the initial fruits of this work were published September 30 in Science<\/em>.<\/p>\n

In one of the studies, mapping protein\u2013protein interactions in this fashion allowed them to identify a potentially effective treatment for people with head and neck cancers<\/a> whose tumors have specific mutations<\/a> in a gene<\/a> called PIK3CA<\/em>. <\/p>\n

But unlike most targeted therapies, the drug doesn\u2019t block the altered PIK3CA proteins in cancer cells that have mutations in the PIK3CA<\/em> gene. Rather, the drug blocks the action of a different protein in the cell, called HER3.<\/p>\n

The pathway map the team created revealed a strong interaction between the mutated PIK3CA proteins\u2014which are part of a larger protein complex called PI3K<\/a>\u2014and HER3 proteins. Disrupting HER3, the researchers showed, provides a backdoor way of targeting the cancer-promoting actions of mutant PIK3CA.<\/p>\n

This discovery, and important findings from the other two studies, provide some of the first true demonstrations of the potential of systematically mapping protein communication pathways in cancer cells, said one of the study leaders, Nevan Krogan, Ph.D., director of the Quantitative Biosciences Institute at the University of California, San Francisco (UCSF).<\/p>\n

The effort builds on the many studies that have mapped cancer genomes while also addressing some of the shortcomings of gene-centric approaches to studying the biology of cancer, Dr. Krogan said.<\/p>\n

\u201cWe need an approach that addresses the complexity [of cancer]. So we have to go to that next step,\u201d he explained. That next step \u201cis the functional unit of the cell: proteins.\u201d<\/p>\n

The studies are part of a larger NCI-supported research initiative by researchers at UCSF and the University of California San Diego (UCSD) to comprehensively map protein networks in cancer cells. The researchers believe these maps will open up new avenues for understanding and treating cancer. <\/p>\n

At its core, the mapping effort is intended to provide \u201ca higher-level view of cancer processes,\u201d said Shannon Hughes, Ph.D., of NCI\u2019s Division of Cancer Biology<\/a>. \u201cIt\u2019s not just focusing on one gene or one protein, but how [genes and proteins] act in a system.\u201d<\/p>\n

This line of research can provide important new insights into the biology of cancer, but also has the potential to impact cancer care, Dr. Hughes explained. \u201cIt broadens the potential targets for treatment,\u201d she said. \u201cAnd by taking that broader view, you can identify more patients who might be candidates for those treatments.\u201d<\/p>\n

From Genetic Mutations to Pathways<\/h2>\n

People with cancer are increasingly treated based on the genetic alterations present in their tumors. For example, several drugs are approved to treat patients with breast cancer and leukemia whose cancers have mutations in genes that provide the blueprints for the proteins that are part of the PI3K complex.<\/p>\n

An ever-expanding collection of targeted cancer therapies block the actions of proteins produced as a result of mutations in genes like EGFR<\/a><\/em>, HER2<\/a><\/em>, BRAF<\/em>, and many others. But with a few exceptions, most of these treatments only work in a modest portion of patients whose tumors express that target. Or, if they do initially shrink or stabilize tumors, in many cases the cancers become resistant to the treatment and begin growing again. <\/p>\n

Researchers believe one reason these treatments don\u2019t work or stop working is that specific alterations in cancer-related genes\u2014even those that studies have shown are major \u201cdrivers\u201d of a specific cancer\u2014don\u2019t represent the complete picture of how those mutations affect a cell\u2019s protein machinery, explained the studies\u2019 co-leader, Trey Ideker, Ph.D., a professor in the UCSD departments of medicine, bioengineering, and computer science.<\/p>\n

Although it has had tremendous value, the more traditional gene-centric approach to studying cancer \u201cis like looking at the nuts and bolts in a car engine,\u201d Dr. Ideker said. \u201cWe\u2019ve now got to look at the [cell\u2019s] bigger machines.\u201d<\/p>\n

The groundwork for this bigger picture approach has already been laid, wrote Ran Chang, Ph.D., and Peter Jackson, Ph.D., of the Stanford University School of Medicine, in an editorial in<\/a> Science<\/a><\/em> that accompanied the three studies.<\/p>\n

\u201cFor many cancers, there is an extensive catalog of genetic mutations,\u201d they wrote. \u201cBut a consolidated map that organizes these mutations into pathways that drive tumor growth is missing.\u201d <\/p>\n

With funding from NCI\u2019s Cancer Systems Biology Consortium<\/a>, that consolidated map is precisely what the UCSF and UCSD researchers are hoping to help create with their Cancer Cell Map Initiative.<\/p>\n

A linchpin of their research is a technology known as affinity purification\u2013mass spectrometry, which they use to identify protein\u2013protein interactions that include known cancer-related proteins. In meticulous fashion, the researchers systematically analyze mutations in genes and their impact on protein\u2013<\/span><\/span><\/span><\/span>protein interactions in cells and use advanced computational methods to parse the resulting data and generate the network maps.<\/p>\n

These maps, Dr. Hughes said, \u201cget us close to knowing what\u2019s happening in a cell at any given time.\u201d<\/p>\n

Other studies have created network maps, Dr. Krogan noted, but they have been much more limited in scope.<\/p>\n

\u201cNobody has done it to this scale,\u201d he stressed. Integrating genomics<\/a>, proteomics<\/a>, and biochemistry with the mass spectrometry analyses and advanced computational tools, he added, \u201cmakes this a flagship set of studies, in my opinion.\u201d<\/p>\n