Cancer is second only to heart disease in the number of annual fatalities in the United States. Cancer.org predicted more than 1.6 million new cases would be diagnosed in the country in 2017, with approximately 600,000 patients dying as a result.
While much focus is already trained on finding a cure, one sweeping change must be made to the healthcare sector if the medical research community hopes to solve this pervasive global health problem and meet the rising needs associated with a growing, socio-economically varied population. That change is the growth of the Convergence in Healthcare movement.
In the simplest terms, Convergence in Healthcare is an approach to medical research that integrates the knowledge of professionals from the life sciences, physical sciences, mathematics, computing and engineering industries. Convergence moves beyond simple collaboration. Instead, it aims to create a single, unified approach to healthcare research that leverages key concepts from each of these scientific disciplines to find more innovative ways to diagnose, treat and prevent illness.
While Convergence in Healthcare has yet to become the accepted norm within the medical sector, groups of researchers are already employing convergent principles and achieving promising results, especially in areas of the treatment and diagnosis of cancer. As detailed in the Massachusetts Institute of Technology-sponsored report “Convergence: The Future of Health,” listed below are three examples of how Convergence in Healthcare is already influencing the future of cancer research and what scientists in this area of study can achieve.
New Methods of Early Detection
The earlier cancer is diagnosed in a patient, the more likely for the treatment response to be successful and for the patient to survive the disease. A convergence-based approach has already enabled scientists from the academic institutions of Massachusetts Institute of Technology (MIT), Stanford and Johns Hopkins to develop new, more affordable ways of detecting cancer in the body.
At MIT, scientists created a paper-based test to detect the presence of synthetic biomarkers in a patient’s urine. The patient is injected with nanoparticles containing these synthetic biomarkers, which interact with specific proteins in the body. When the nanoparticles encounter a tumor in the body, the interaction triggers a release of the synthetic biomarkers. The presence of these biomarkers in the urine test is directly correlated to the quantitative measurement of the tumor.
Another convergent, early detection method developed by scientists at Stanford and Johns Hopkins uses blood instead of urine to identify the presence of tumors. Cancerous cells frequently shed DNA, nucleic acids or other tumor fragments that are absorbed into a patient’s bloodstream. As a result, scientists are developing a method of liquid biopsy based on the presence of these substances in the blood.
As of January 2018, Science published an article about this method’s potential as a future routine screening tool and outlined the promise it already holds. According to the article, Johns Hopkins researchers developed a test capable of detecting between 33 and 98 percent of cases of eight different forms of cancerous tumors. Ovary and liver cancer were the most easily identified and breast cancer was the hardest to identify. The test is named CancerSEEK and the team is pushing for it to be used more widely as a screening tool.
The body defends itself from illness caused by viruses or other foreign infectious agents. However, cancers often fool the immune system’s radar because tumors form from the body’s own cells, so the immune system doesn’t recognize cancer as a threat. If it can be activated, however, the immune system can be a more effective defense system than externally administered drug treatments, particularly for cancer in the early stages. This makes immunotherapy a promising prospect for the early detection and treatment of cancerous cells.
There are several key ways scientists have begun to leverage convergent principles to approach cancer immunotherapy. By combining antibody molecules with signaling molecules and targeting tumors, MIT scientists have activated an immune response to tumors that also activates the body’s T-cells. During animal tests, this method eradicated existing tumors while simultaneously creating a memory in the immune system to allow the body to destroy re-injected cancer cells months later.
The second avenue for cancer immunotherapy scientists are interested in pursuing is the prospect of a cancer vaccine to send the body’s T-cells into action when a tumor manifests in the body. To be truly effective, a vaccine would need to spread to the lymph nodes. Researchers are facilitating this journey by creating vaccines that attach to albumin, a protein that would take the treatment directly to the lymph nodes for maximum effect.
Another approach to cancer immunotherapy focuses on using nanoparticles containing chemotherapy drugs to penetrate T-cells. This brings the drugs to target sites within lymphatic tumors usually not accessible to other forms of nanoparticle therapeutics.
Faster Testing Models for Drug Therapies
Another important area of cancer research benefitting from Convergence in Healthcare is the ability of scientists to accelerate and reduce the cost of drug screening. Previous models of cancer drug testing have only permitted scientists to test a limited number of drugs within a single animal subject. This draws out the process and inflates the cost.
However, a new, convergent method designed by MIT engineers tests many different drugs at a micro level within single test subjects. With this method, microdevices are attached to a tumor within a test subject. They release a small amount of a given drug into small regions of the tumor, then accurately reflect the tumor’s response to a systematic delivery of the same drug.
By finding ways to precisely test a large number of drugs in a single tumor, scientists are developing a more cost-effective, efficient method of research into drug therapies. This has the potential to expedite the separation of effective and ineffective therapies.