q&more
My watch list
my.chemie.de  
Login  

News

New algorithm detects even the smallest cancer metastases across the entire mouse body

Exposing the enemy

©Helmholtz Zentrum München

DeepMACT makes use of artificial intelligence to find even the smallest metastases in the entire mouse body. The picture shows single disseminated cells spreading though the lung.

16-Dec-2019: Teams at Helmholtz Zentrum München, LMU Munich and the Technical University of Munich (TUM) have developed a new algorithm that enables automated detection of metastases at the level of single disseminated cancer cells in whole mice.

Cancer is one of the leading causes of death worldwide. More than 90% of cancer patients die of distal metastases rather than as a direct result of the primary tumor. Cancer metastases usually develop from single disseminated cancer cells, which evade the body’s immune surveillance system. Up to now, comprehensive detection of these cells within the entire body has not been possible, owing to the limited resolution of imaging techniques such as bioluminescence and MRI. This has resulted in a relative lack of knowledge of the specific dissemination mechanisms of diverse cancer types, which is a prerequisite for effective therapy. It has also hampered efforts to assess the efficacy of new drug candidates for tumor therapy.

Transcending human detection capabilities with deep learning

In order to develop new techniques to overcome these hurdles, the team led by Dr. Ali Ertürk, Director of the Institute for Tissue Engineering and Regenerative Medicine at Helmholtz Zentrum München, had previously developed vDISCO – a method of tissue clearing and fixation which transforms mouse bodies into a transparent state allowing the imaging of single cells. Using laser-scanning microscopes, the researchers were able to detect the smallest metastases down to individual cancer cells in cleared the tissue of the mouse bodies.

However, manually analyzing such high-resolution imaging data would be a very time-consuming process. Given the limited reliability and processing speed of currently available algorithms for this kind of data analysis, the teams have developed a novel deep-learning based algorithm called DeepMACT. The researchers have now been able to detect and analyze cancer metastases and map the distribution of therapeutic antibodies in vDISCO preparations automatically. The DeepMACT algorithm matched the performance of human experts in detecting the metastases – but did so more than 300 times faster. “With a few clicks only, DeepMACT can do the manual detection work of months in less than an hour. We are now able to conduct high-throughput metastasis analysis down to single disseminated tumor cells as a daily routine”, says Oliver Schoppe, co-first-author of the study and Ph.D. student in the group of Prof. Dr. Bjoern Menze at TranslaTUM, the Center for Translational Cancer Research at TUM.

Detecting cells, gathering data, learning about cancer

Using DeepMACT, the researchers have gained new insights into the unique metastatic profiles of different tumor models. Characterization of the dissemination patterns of diverse cancer types could enable tailored drug targeting for different metastatic cancers. By analyzing the progression of breast-cancer metastases in mice, DeepMACT has uncovered a substantial increase in small metastases throughout the mouse body over time. “None of these features could be detected by conventional bioluminescence imaging before. DeepMACT is the first method to enable the quantitative analysis of metastatic process at a full-body scale”, adds Dr. Chenchen Pan, a postdoctoral fellow at Helmholtz Zentrum München and also joint first author of the study. “Our method also allows us to analyze the targeting of tumor antibody therapies in more detail.”

How effective are current cancer therapies?

With DeepMACT, the researchers now have a tool with which to assess the targeting of clinical cancer therapies that employ tumor-specific monoclonal antibodies. As a representative example, they have used DeepMACT to quantify the efficacy of a therapeutic antibody named 6A10, which had been shown to reduce tumor growth. The results demonstrated that 6A10 can miss up to 23% of the metastases in the bodies of affected mice. This underlines the importance of the analysis of targeting efficacy at the level of single metastases for the development of novel tumor drugs. The method can potentially also track the distribution of small-molecule drugs when they are conjugated to fluorescent dyes.

On the way to stop the metastatic process

Taken together, these results show that DeepMACT not only provides a powerful method for the comprehensive analysis of cancer metastases, but also provides a sensitive tool for therapeutic drug assessment in pre-clinical studies. “The battle against cancer has been underway for decades and there is still a long way to go before we can finally defeat the disease. In order to develop more effective cancer therapies, it is critical to understand the metastatic mechanisms in diverse cancer types and to develop tumor-specific drugs that are capable to stop the metastatic process,” explains Ertürk.

DeepMACT is publicly available and can be easily adopted in other laboratories focusing on diverse tumor models and treatment options. “Today, the success rate of clinical trials in oncology is around 5%. We believe that the DeepMACT technology can substantially improve the drug development process in preclinical research. Thus, could help finding much more powerful drug candidates for clinical trials and hopefully help to save many lives”.

Original publication:
C. Pan et al.; "Deep learning reveals cancer metastasis and therapeutic antibody targeting in the entire body"; Cell; 2019

Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt GmbH

Request information now

Recommend news PDF version / Print Add news to watchlist

Share on

Facts, background information, dossiers

  • metastases
  • cancer
  • deep learning

More about Helmholtz Zentrum München

More about LMU

  • News

    Structural biology: Special delivery

    Bulky globular proteins require specialized transport systems for insertion into membranes. Ludwig-Maximilians-Universitaet (LMU) in Munich researchers have determined the structure of such a system for the first time, and propose that it exploits the principle of the airlock. Many proteins ... more

    A fine sense for molecules

    At the biochemical level, organisms can be thought of as complex collections of different species of molecules. In the course of their metabolism, biological cells synthesize chemical compounds, and modify them in multifarious ways. Many of these products are released into the intercellular ... more

    Five-fold boost in formaldehyde yield

    Environmentally benign methods for the industrial production of chemicals are urgently needed. LMU researchers recently described such a procedure for the synthesis of formaldehyde, and have now improved it with the aid of machine learning. Formaldehyde is one of the most important feedstoc ... more

  • Authors

    Prof. Dr. Thomas Carell

    Thomas Carell graduated in chemistry, completing his doctorate at the Max Planck Institute for Medical Research under the tutelage of Prof. Dr Dr H. A. Staab. Following a research position in the USA, he accepted a position at ETH Zurich, setting up his own research group in the Laboratory ... more

More about TU München

  • News

    Benzene in cherry flavor - where it comes from and how to avoid it?

    In 2013, the Stiftung Warentest found harmful benzene in drinks with cherry flavor. But how did the substance get into the drinks? Was the source benzaldehyde, an essential component of the cherry flavoring? And if so, how could the problem be solved? A new study by the Leibniz-Institute fo ... more

    Blocking sugar structures on viruses and tumor cells

    During a viral infection, viruses enter the body and multiply in its cells. Viruses often specifically attach themselves to the sugar structures of the host cells, or present characteristic sugar structures on their surface themselves. Researchers at the Technical University of Munich (TUM) ... more

    Safe from over- or underdosing

    Using a mixture of oil droplets and hydrogel, medical active agents can be not only precisely dosed, but also continuously administered over periods of up to several days. The active agents inside the active droplets are released at a constant rate, decreasing the risk of over- or underdosa ... more

  • q&more articles

    Taste and aroma boost in the mouth

    The food trend towards healthy snacks is continuing. Snacks made from freeze-dried fruit meet consumer expectations of modern and high-quality food. However, freeze drying of whole fruits requires long drying times and substantially reduces sensorial quality, which is unappealing to consumers. more

    Diet, gut microbiota and host lipid metabolism

    Nature provides an enormous diversity of lipid molecules that originate from various pathways. Fatty acids are key modules for various lipids, including cell membrane lipids such as phospholipids or triacylglycerols, which are the major components of lipid droplets. Excess lipids or defects ... more

    Translation

    The structure of the big chemical and pharmaceutical companies has changed. Traditional centralised research departments conducting fundamental research have fallen victim to economic considerations. In exchange, young, dynamic start-up enterprises are increasingly brightening up the scene. ... more

  • Authors

    Prof. Dr. Ulrich Kulozik

    Ulrich Kulozik, born in 1955, studied food technology at the Technical University of Munich (TUM), where he received his doctorate in 1986 and qualified as a professor in food and bioprocess technology in 1991. Until 1999, he worked in the food industry as Department Manager Process & Produ ... more

    Mine Ozcelik

    Mine Ozcelik, born in 1984, graduated with Bachelor’s and Master’s of Engineering degrees in Chemical Engineering from Ankara University, Turkey in 2008 and 2012, respectively. She started working in the food industry as an R&D and laboratory head in September 2008 in Ankara, where she over ... more

    Dr. Josef Ecker

    Josef Ecker, born in 1978, studied biology at the University of Regensburg. He earned his doctorate in 2007, after which he researched as a postdoc at the University Hospital in Regensburg at the Institute of Clinical Chemistry. After several subsequent years in industry, working in executi ... more

q&more – the networking platform for quality excellence in lab and process

The q&more concept is to increase the visibility of recent research and innovative solutions, and support the exchange of knowledge. In the broad spectrum of subjects covered, the focus is on achieving maximum quality in highly innovative sectors. As a modern knowledge platform, q&more offers market participants one-of-a-kind networking opportunities. Cutting-edge research is presented by authors of international repute. Attractively presented in a high-quality context, and published in German and English, the original articles introduce new concepts and highlight unconventional solution strategies.

> more about q&more

q&more is supported by:

 

Your browser is not current. Microsoft Internet Explorer 6.0 does not support some functions on Chemie.DE