cancer

A mechanism for activating the immune system against cancer cells allows immune cells to detect and destroy cancer cells better than before.

The study was led by Professor Nick Haining, at Harvard Medical School, and was co-authored by Professor Erez Levanon, doctoral student Ilana Buchumansky, of the Mina and Everard Goodman Faculty of Life Sciences at Bar-Ilan University, and an international team.

The focus of the study was to develop a mechanism that routinely serves the cell by marking human virus-like genes in order to avoid identifying them as viruses. 

Prof Levanon, together with the Harvard team, discovered during the study that when inhibiting this mechanism, the immune system can be harnessed to fight cancer cells in a particularly efficient manner, and also more effectively in both lung cancer and melanoma.

“We found that if the mechanism is blocked, the immune system is much more sensitive. When the mechanism is deactivated, the immune system becomes much more aggressive against the tumor cells,” said Prof Levanon.

In recent years, a new generation of cancer drugs has been developed which blocks proteins that inhibit immune activity against malignant tumors. These drugs have shown remarkably poisitve success in several tumor types, in some.

This year’s Nobel Prize in Medicine was awarded to James Allison and Tasuku Honjo, who discovered the key genes of this mechanism.

Despite this achievement, the current generation of drugs helps only a small number of patients, while most of the drugs fail to cause the immune system to attack the tumor.

The research team hope that the new discovery will allow enhanced activity of the immune system to attack cancer cells. A number of companies have already begun research to screen for drugs that will operate on the basis of this discovery.

The study was published in the journal Nature.

machine learning

Researchers at the University of Surrey have developed Artificial Intelligence that is able to predict symptoms and how severe they could be through the course of a patient’s treatment.

Two machine learning models were developed and are able to accurately predict the severity of common symptoms that affect cancer patients; namely depression, sleep disturbance and anxiety. Each of these symptoms can lead to a huge reduction in the patients’ quality of life.

The effective management of symptoms is critical in cancer treatment, and steps to assist oncology clinicians in planning their patients’ course of treatment could progress into more effective treatments, and ones that are more aggressive against the cancer.

Whilst patients were undergoing computed tomography x-ray treatment, researchers analysed symptoms they experienced. They used different time periods during the dataset, and tested whether the machine learning algorithms were able to accurately predict when and if symptoms surfaced.

The study, conducted through a collaboration between the University of Surrey and the University of California in San Francisco (UCSF), found that the actual symptoms undergone by the patients were very close to those predicted by the machine learning methods.

“These exciting results show that there is an opportunity for machine learning techniques to make a real difference in the lives of people living with cancer. They can help clinicians identify high-risk patients, help and support their symptom experience and pre-emptively plan a way to manage those symptoms and improve quality of life,” said Dr Payam Barnaghi, Professor of Machine Intelligence.

“I am very excited to see how machine learning and AI can be used to create solutions that have a positive impact on the quality of life and well-being of patients,” said Nikos Papachristou, who worked on designing the machine learning algorithms for this study.

The study was published in the journal PLO One.

spray

Many people who are diagnosed with cancer will undergo some type of surgery to treat their disease – almost 95 percent of people with early-diagnosed breast cancer will require surgery and it’s often the first line of treatment for people with brain tumors, for example. But despite improvements in surgical techniques over the past decade, the cancer often comes back after the procedure.

A UCLA-led research team has developed a spray gel embedded with immune-boosting drugs that could help. In a peer-reviewed study, the substance was successful half of the time in awakening lab animals’ immune systems to stop the cancer from recurring and inhibit it from spreading to other parts of the body.

The researchers, led by Dr Zhen Gu, a Professor of Bioengineering at the UCLA Samueli School of Engineering and member of the UCLA Jonsson Comprehensive Cancer Center, tested the biodegradable spray gel in mice that had advanced melanoma tumors surgically removed. They found that the gel reduced the growth of the tumor cells that remained after surgery, which helped prevent recurrences of the cancer: After receiving the treatment, 50 percent of the mice survived for at least 60 days without their tumors regrowing.

The spray not only inhibited the recurrence of tumors from the area on the body where it was removed, but it also controlled the development of tumors in other parts of the body, said Prof Gu, who is also a member of the California NanoSystems Institute at UCLA.

The substance will have to go through further testing and approvals before it could be used in humans. But Prof Gu said that the scientists envision the gel being applied to the tumor resection site by surgeons immediately after the tumor is removed during surgery.

“This sprayable gel shows promise against one of the greatest obstacles in curing cancer,” Prof Gu said. “One of the trademarks of cancers is that it spreads. In fact, around 90 percent of people with cancerous tumors end up dying because of tumor recurrence or metastasis. Being able to develop something that helps lower this risk for this to occur and has low toxicity is especially gratifying.”

The researchers loaded nanoparticles with an antibody specifically targeted to block CD47, a protein that cancer cells release as a “don’t-eat-me” signal. By blocking CD47, the antibody enables the immune system to find and ultimately destroy the cancer cells.

The nanoparticles are made of calcium carbonate, a substance that is the main component of egg shells and is often found in rocks. Researchers chose calcium carbonate because it can be gradually dissolved in surgical wound sites, which are slightly acidic, and because it boosts the activity of a type of macrophage that helps rid the body of foreign objects, said Dr Qian Chen, the study’s lead author and a postdoctoral researcher in Prof Gu’s lab.

“We also learned that the gel could activate T-cells in the immune system to get them to work together as another line of attack against lingering cancer cells,” Dr Chen said.

Once the solution is sprayed on the surgical site, it quickly forms a gel embedded with the nanoparticles. The gel helps stop at the surgical site and promotes would healing; the nanoparticles gradually dissolve and release the anti-CD47 antibodies into the body.

The researchers will continue testing the approach in animals to learn the optimal dose, best mix of nanoparticles and ideal treatment frequency, before testing the gel on human patients.

A paper describing the work was published in the journal Nature Nanotechnology.