Researchers at the University of Southampton have engineered cells with a ‘built-in genetic circuit’ that produces a molecule that inhibits the ability of tumours to survive and grow in their low oxygen environment.
The genetic circuit produces the machinery necessary for the production of a compound that inhibits a protein which has a significant and critical role in the growth and survival of cancer cells. This results in the cancer cells being unable to survive in the low oxygen, low nutrient tumour micro-environment.
As tumours develop and grow, they rapidly outstrip the supply of oxygen delivered by existing blood vessels. This results in cancer cells needing to adapt to low oxygen environment.
To enable them to survive, adapt and grow in the low-oxygen or ‘hypoxic’ environments, tumours contain increased levels of a protein called Hypoxia-inducible factor 1 (HIF-1). HIF-1 senses reduced oxygen levels and triggers many changes in cellular function, including a changed metabolism and sending signals for the formation of new blood vessels. It is thought that tumours primarily hijack the function of this protein (HIF-1) to survival and grow.
Professor Ali Tavassoli, who led the study with colleague Dr. Ishna Mistry, explains: “In an effort to better understand the role of HIF-1 in cancer, and to demonstrate the potential for inhibiting this protein in cancer therapy, we engineered a human cell line with an additional genetic circuit that produces the HIF-1 inhibiting molecule when placed in a hypoxic environment.
“We’ve been able to show that the engineered cells produce the HIF-1 inhibitor, and this molecule goes on to inhibit HIF-1 function in cells, limiting the ability of these cells to survive and grow in a nutrient-limited environment as expected.
“In a wider sense, we have given these engineered cells the ability to fight back – to stop a key protein from functioning in cancer cells. This opens up the possibility for the production and use of sentinel circuits, which produce other bioactive compounds in response to environmental or cellular changes, to target a range of diseases including cancer.”
The genetic circuit is incorporated onto the chromosome of a human cell line, which encodes the protein machinery required for the production of their cyclic peptide HIF-1 inhibitor. The production of the HIF-1 inhibitor occurs in response to hypoxia in these cells. The research team demonstrated that even when produced directly in cells, this molecule still prevents the HIF-1 signalling and the associated adaptation to hypoxia in these cells.
The next step for the researchers is to demonstrate the viability of this approach to the production and delivery of an anticancer molecule in a whole tumour model system.
Professor Tavassoli adds: “The main application for this work is that it eliminates the need for the synthesis of our inhibitor, so that biologists conducting research into HIF function can easily access our molecule and hopefully discover more about the role of HIF-1 in cancer. This will also let us understand whether inhibiting HIF-1 function alone is enough to block cancer growth in relevant models. Another interesting aspect to the work is that it demonstrates the possibility of adding new machinery to human cells to enable them to make therapeutic agents in response to disease signals.”
Physicians have long used visual judgment of medical images to determine the course of cancer treatment. A new program package from Fraunhofer researchers reveals changes in images and facilitates this task using deep learning.
The experts will demonstrate this software in Chicago from November 27 to December 2 at RSNA, the world’s largest radiology meeting.
Has a tumor shrunk during the course of treatment over several months, or have new tumors developed? To answer questions like these, physicians often perform CT and MRI scans. Tumors are usually evaluated only visually, and new tumors are often over-
looked. “Our program package increases confidence during tumor measurement and follow-up,” explains Mark Schenk from the Fraunhofer Institute for Medical Image Computing MEVIS in Bremen, Germany. “The software can, for example, determine how the volume of a tumor changes over time and supports the detection of new tumors.” The package consists of modular processing components and can help medical technology manufacturers automate progress monitoring.
The computer learns on its own
The package is unique in its use of deep learning, a new type of machine learning that reaches far beyond existing approaches. This method is helpful for image segmentation, during which experts designate exact organ outlines. Existing computer segmentation programs seek clearly defined image features such as certain gray values. “How-
ever, this can often lead to errors,” according to Fraunhofer researcher Markus Harz. “The software assigns areas to the liver that do not belong to the organ.” These errors must be corrected by physicians, a process which can often be quite time-consuming.
The new deep learning approaches promise improved results and should save physicians valuable time. To demonstrate their self-learning methods, Fraunhofer scientists trained the software with CT liver images from 149 patients. Results showed that the more data the program analyzed, the better it could automatically identify liver contours.
Finding hidden metastases
A further application of the approach is image registration, in which software aligns images from different patient visits so that physicians can easily compare them. Machine learning can aid the particularly difficult task of locating bone metastases in the torso in which hip bones, ribs, and spine are visible. Currently, these metastases are often overlooked due to time constraints in clinical practice. Deep learning methods can help reliably discover metastases and thus improve treatment outcomes.
Researchers focus on a combination of classical approaches and machine learning: “We wish to harness existing expertise to implement deep learning as effectively and reliably as possible,” stresses Harz. Fraunhofer MEVIS builds upon years of experience in practical application: for example, the algorithms for highly precise lung image registration have been integrated into several commercial medical software applications.
Learn more: Machine learning to help physicians
Researchers funded in part by NIBIB have recently shown that magnetic bacteria are a promising vehicle for more efficiently delivering tumor-fighting drugs. They reported their results in the August 2016 issue of Nature Nanotechnology.
One of the biggest challenges in cancer therapy is being able to sufficiently deliver chemotherapy drugs to tumors without exposing healthy tissues to their toxic effects. One way researchers have attempted to overcome this is by developing nanocarriers—extremely small particles packed with drugs. The nanocarriers are designed so they’re only taken up by cancer cells, thereby preventing the drugs from being absorbed by healthy tissues as they travel through the body’s circulation.
Yet while nanocarriers do a good job protecting healthy tissues, the amount of drug successfully delivered to tumors remains low. The main reasons for this shortcoming are that nanocarriers rely on the circulation system to carry them to the tumor, so a large percentage are filtered out of the body before ever reaching their destination. In addition, differences in pressure between the tumor and its surrounding tissue prevent nanocarriers from penetrating deep inside the tumor. As a result, nanocarriers aren’t able to reach the tumor’s hypoxic zones, which are regions of active cell division that are characterized by low oxygen content.
“Only a very small proportion of drugs reach the hypoxic zones, which are believed to be the source of metastasis. Therefore, targeting the low-oxygen regions will most likely decrease the rate of metastasis while maximizing the effect of a therapy,” says Sylvain Martel, Ph.D., Director of the Polytechnique Montréal NanoRobotics Laboratory and lead researcher of the study.
Martel and his research team were attempting to develop robotic nanocarriers that would travel to hypoxic zones when they realized nature may have already created one in the form of a bacteria called magnetococcus marinus or MC-1. MC-1 cells thrive in deep waters where oxygen is sparse. In order to find these areas, the bacteria rely on a two-part navigation system. The first part involves a chain of magnetic nanocrystals within MC-1 that acts like a compass needle and causes the bacteria to swim in a north direction when in the Northern Hemisphere. The second part consists of sensors that allow the bacteria to detect changes in oxygen levels. This unique navigation system helps the bacteria migrate to and maintain their position at areas of low oxygen.
With funding support from NIBIB and others, Martel’s research team conducted a series of experiments to show that the bacteria’s unique navigation system could be exploited to more efficiently deliver drugs to tumors.
In an initial experiment, mice that had been given human colorectal tumors were injected with either live MC-1 cells, dead MC-1 cells, or as a control group, non-magnetic beads (roughly the same size as the bacteria). The injection was made into the tissue directly adjacent to the tumors after which the mice were exposed to a computer-programmed magnetic field, meant to direct the cells or beads into the tumor. Upon examination of the tumors, the researchers found minimal penetration of the dead bacterial cells and the beads into the tumor, whereas the live bacterial cells were found deep within the tumor and especially in regions with low oxygen content.
“When they get inside the tumor, we switch off the magnetic field and the bacteria automatically rely on the oxygen sensors to seek out the hypoxic areas,” says Martel. “We constrain them to the tumor and then let nature do the rest.”
Next, the researchers wanted to see whether attaching vesicles loaded with drugs to the cells would affect their movement into the tumors. They attached approximately 70 drug-containing vesicles to each bacterial cell. The cells were then injected into another set of mice with colorectal tumors and exposed to the magnet. After examining the tumors of those mice, the researchers estimated that on average, 55% of the injected bacterial cells with attached vesicles made it into the tumor. For comparison, some researchers estimate that only approximately 2% of drugs delivered via current nanocarriers make it into tumors.
“This proof-of-concept work shows the potential to tap into the intricate and optimized cell machinery of single celled organisms such as bacteria,” said Richard Conroy, Ph.D., director of the Division of Applied Sciences and Technology at NIBIB. “The ability to actively and precisely target drug delivery to a tumor will help reduce side effects and potentially improve the efficacy of treatments.”
The next step for Martel’s team is to determine the effects of the drug-loaded bacterial cells on reducing tumor size. They would also like to test whether the bacteria can be used to deliver other types of cancer-killing medicines such as molecules that instruct the immune system to attack tumors.
In addition, the team is working to expand the types of tumors the bacteria could be used for. Currently, the bacteria have to be injected very close to the tumor because, if injected into arteries, the excessive blood flow and the distance needed to travel would impact the number of bacteria that reach the tumor. This limits the drug delivery approach to cancers that are easily accessible such as colorectal, prostate, and potentially breast cancer. However, Martel’s team has shown in animals that they can transport the bacteria through arteries and sufficiently close to the tumor by first encapsulating them in magnetic carriers and propelling them by the magnetic field of an MRI scanner. The bacteria can then be released from the carriers, like torpedoes from a submarine, once close to the tumor. This multi-step approach could potentially open the door for using the bacteria to deliver drugs to tumors deeper in the body.
Martel says that preliminary test results of the bacteria in mice and rats and the fact that the bacteria die within 30 minutes of being injected, suggest that they could potentially be safe in humans.
“These bacteria are really the perfect machine. They replicate, they’re cheap, and we can inject hundreds of millions or more at a time,” says Martel.
Macrophages are cells of the immune system that protect the host from invading pathogens. But in cancer, macrophages can be “hijacked” by tumors, and made to support their malignant growth and spread. This is a drawback for a major cancer treatment, immunotherapy, which turns the body’s immune system against the tumor. EPFL scientists, working with colleagues at the Roche Innovation Centers in Munich and Basel, have now identified a molecular “switch” that can convert the “hijacked” macrophages into cells that can stimulate the immune system to fight the growth and spread of cancer. The work is published in Nature Cell Biology.
Along with attacking foreign pathogens like bacteria, macrophages also help the body’s organs develop and its wounds heal. Their own behavior is fine-tuned by small molecules that they produce, called microRNAs.
When a tumor begins to develop, macrophages attempt to block its growth. But often tumors hijack them and convert them into what are known as “tumor-associated macrophages”, or TAMs for short.
Now corrupted, TAMs use their microRNAs to shield the tumor from the patient’s immune system, helping it grow and metastasize. This phenomenon is common across many tumor types. It is one of the major obstacles in treating cancer, and often leads to a poor prognosis for the patient.
Michele De Palma’s team at EPFL found how to reclaim TAMs. The researchers genetically modified TAMs to remove their ability to produce microRNAs. As a result, the TAMs were reprogrammed dramatically. Instead of protecting the tumor, the TAMs now signaled the presence of the tumor to the immune system, triggering attacks against it – and did so very efficiently.