Tyler O'Neal, Staff Editor ACADEMIA

University of Bonn, Dutch state-of-the-art algorithms identify aggressive breast cancer

The study by the University of Bonn shows to what extent cancer research can benefit from the results of mouse models

Aggressive forms of breast cancer often manipulate the immune response in their favor. This manipulation is revealed in humans by the same immunological "signature" as in mice. This is shown by a study carried out by scientists from the University of Bonn together with Dutch colleagues. Their method makes it possible to obtain an indication of the prognosis of the disease using patients' tumor tissue. The results are published in the journal Cell Reports.

When a tumor starts to grow in the body, it usually does not go unnoticed by the immune system: Macrophages, a certain form of the body's own defense troops, migrate to the cancer cells. They are supposed to flow around the diseased cells, digest them and thus eliminate them. But sometimes tumor cells manage to escape their adversaries. Not just that: They even use the macrophages for their own purposes and grow even faster as a result. CAPTION Macrophages (brown), the scavengers of the immune system, migrate into the diseased tissue (cancer cells: blue) without destroying it. CREDIT © Karin E. de Visser/the Netherlands Cancer Institute{module In-article} 

To do this, they reprogram the immune cells: They ensure that certain genes in the macrophages are switched off and others switched on. This changes the genetic "signature" of the macrophages. "This changed signature, in turn, reveals whether the tumor has a good or bad prognosis," explains Dr. Thomas Ulas from the LIMES Institute (the acronym stands for "Life and Medical Sciences") at the University of Bonn.

Gene activity also depends on the tissue

In order to identify the changes caused by the tumor, it is necessary to know which genes are normally active in the macrophages. However, this varies considerably, depending on the organ in which the scavenger cells perform their service. Experts also speak of "tissue painting": The tissue makes its mark on the immune cells.

In addition, tumor-induced changes are not always identical but differ from one patient to another. "Depending on which mutation is responsible for breast cancer, other functions are switched on or off in the macrophages," stresses Ulas. It is therefore very difficult to study these complex correlations directly using patients' tissue samples.

To overcome this obstacle, the scientists cooperated with a working group from the Netherlands. Tumor biologist Prof. Dr. Karin de Visser has been working for many years on mouse lines affected by certain, strictly defined types of breast cancer. "We have now searched these animals for the signature of the scavenger cells in the tumors," says Ulas. To this end, the bioinformatics expert and his colleagues isolated macrophages from mice affected by breast cancer and compared them with those from healthy breast tissue. They were able to identify the genetic differences between the scavenger cells using state-of-the-art supercomputer algorithms.

Mouse results transferable to humans

They also found almost identical signatures in the scavenger cells of many breast cancer patients. "In this case, it was possible to transfer the mouse results directly to humans," explains Prof. Dr. Joachim Schultze, head of the Genomics and Immunoregulation team at the LIMES Institute. "However, the prerequisite was that the patients suffered from the same form of breast cancer as the animals." The results also demonstrate how important it is to develop specific mouse models depending on the type of cancer.

The results can be used not just to predict tumor aggressiveness: After all, the signature also provides information on the cancer cells' survival strategies. This may eventually lead to the development of new countermeasures. Ulas: "However, it will certainly take many years for new treatment options to emerge, if any."

Hokkaido University develops a simple way to control swarming molecular machines

Tyler O'Neal, Staff Editor ACADEMIA

The swarming behavior of about 100 million molecular machines can be controlled by applying simple mechanical stimuli such as extension and contraction. This method could lead to the development of new swarming molecular machines and small energy-saving devices.

Conceptual drawing of the swarming molecular machines that change moving patterns upon mechanical stimuli.{module In-article} Conceptual drawing of the swarming molecular machines that change moving patterns upon mechanical stimuli.

The swarming molecules in motion aligned in one direction exhibited zigzag patterns or formed a vortex responding to varying mechanical stimuli. They could even self-repair the moving pattern after a disruption, according to a study led by Hokkaido University scientists.

In recent years, many scientists have made efforts to miniaturize machines found in the macroscopic world. The 2016 Nobel laureates in chemistry were awarded for their outstanding research on molecular machines and design and synthesis of nanomachines. 

In previous studies, the research team led by Associate Professor Akira Kakugo of Hokkaido University developed molecular machines consisting of motor proteins called kinesins and microtubules, which showed various swarming behaviors. “Swarming is a key concept in modern robotics. It gives molecular machines new properties such as robustness and flexibility that an individual machine cannot have,” says Akira Kakugo. “However, establishing a methodology for controlling swarming behaviors has been a challenge.”

The molecular machines comprising microtubules and kinesins. Microtubules run on the kinesins attached on the surface of a silicone elastomer. (Daisuke I. et al., ACS Nano. October 4, 2019){module In-article}

The molecular machines comprising microtubules and kinesins. Microtubules run on the kinesins attached on the surface of a silicone elastomer. (Daisuke I. et al., ACS Nano. October 4, 2019)

In the current study published in ACS Nano, the team used the same system comprising motor protein kinesins and microtubules, both bioengineered. The kinesins are fixed on an elastomer substrate surface, and the microtubules are self-propelled on the kinesins, powered by the hydrolysis of adenosine triphosphate (ATP). 

“Since we know that applying mechanical stress can play a key role in pattern formation for active matters, we investigated how deformation of the elastomer substrate influences the swarming patterns of molecular machines,” says Akira Kakugo.

By extending and contracting the elastomer substrate, mechanical stimulation is applied to about 100 million microtubules that run on the substrate surface. The researchers first found that microtubules form wave patterns when no stress is applied. When the substrate is expanded and contracted 1.3 times or more one time, almost all of the 100 million microtubules perpendicularly aligned to the expansion and contraction axis, and when the substrate is expanded and contracted 1.3 times or less repeatably, it created zigzag patterns placed in diagonal directions.

The microtubules formed wave patterns when no stress is applied (left). When the elastomer substrate is expanded and contracted, they turned into an aligned pattern (middle) or a zigzag pattern (right). (Daisuke I. et al., ACS Nano. October 4, 2019)

The microtubules formed wave patterns when no stress is applied (left). When the elastomer substrate is expanded and contracted, they turned into an aligned pattern (middle) or a zigzag pattern (right). (Daisuke I. et al., ACS Nano. October 4, 2019)

Their supercomputer simulation suggested that the orientation angles of microtubules correspond to the direction to attain smooth movement without buckling, which is further amplified by the collective migration of the microtubules.

A large vortex was formed under radial strain on the substrate. (Daisuke I. et al., ACS Nano. October 4, 2019)

A large vortex was formed under radial strain on the substrate. (Daisuke I. et al., ACS Nano. October 4, 2019)

Another important finding was that the moving pattern of microtubules can be modulated by applying new mechanical stimuli and it can be self-repaired even if the microtubule arrangement is disturbed by scratching a part of it. 

“Our findings may contribute to the development of new molecular machines that perform collective motion and could also help advance technologies for energy-saving small devices,” Akira Kakugo commented.

This study was conducted in collaboration with scientists at the Tokyo Institute of Technology, Gifu University, and Columbia University.

Akira Kakugo (Left) and Daisuke Inoue (Right) of research team at Hokkaido University.

Akira Kakugo (Left) and Daisuke Inoue (Right) of research team at Hokkaido University.

US DOD awards £1m to Queen Mary of London University for AI research on treating injured soldiers

Tyler O'Neal, Staff Editor ACADEMIA

The US Department of Defense has awarded the Centre for Trauma Sciences (C4TS) at Queen Mary a $1.2 million (£976.500) grant to develop AI tools that could help save the lives of badly injured soldiers.

It is aimed at developing and validating a suite of accurate prediction models and Clinical Decision Support (CDS) tools that clinicians can use to treat wounded soldiers on the battlefield, traveling to the hospital and in hospitals.

Study lead and honorary senior lecturer at Queen Mary, Colonel Nigel Tai, consultant trauma and vascular surgeon at Barts Health NHS Trust and UK Defence Medical Service, said: “War zones are obviously very fraught environments for clinical decision making, and we know military clinicians have to make difficult decisions under time pressure, far away from the kind of sophisticated diagnostic equipment or senior, experienced advisors that are found in the NHS. So, deciding whether to employ particular surgical techniques, or whether to attempt salvage of a mangled limb or to use precious stocks of blood is ripe for the kind of decision support aids that Artificial Intelligence might help with.”

C4TS, which is part of Queen Mary’s Blizard Institute, will work in collaboration with Queen Mary’s Risk and Information Management research group in the School of Electronic Engineering and Computer Science.

The grant builds on joint work between Queen Mary’s Computer Science team – led by Dr. William Marsh – and C4TS over more than five years. It has drawn on major advances in computational modeling to develop Bayesian Network (BN) statistical analysis CDS tools for clinicians treating patients in the Royal London Hospital Major Trauma Centre. The tools generate accurate risk assessments of whether a seriously injured patient is likely to experience a major blood clotting problem – Trauma-Induced Coagulopathy (TIC) - and whether amputation is necessary for a badly damaged limb. The right treatment can then be matched to individual patients.

The grant will enable the University’s teams to extend this vital research to develop CDS models that improve the effectiveness of damage control surgery and resuscitation, limb salvage and other critical medical interventions in conflict zones.


Colonel Tai concluded: “The grant is an acknowledgment of the world-leading trauma research being undertaken by the C4TS team. The new CDS tools will first be developed and validated using sophisticated statistical models in London and the US. If successful, these AI clinical innovations could potentially be adopted by major trauma centers around the world to save civilian lives.”