A New Roadmap for Cancer Treatment Weill Cornell Medicine launches a predictive cancer database and patient portal with the help of the WorldQuant Foundation.

One of the most terrifying moments for any person awaiting a diagnosis is the sharp and shocking instant that follows the words: “You have cancer.”

Patients experience confusion, denial, anger and fear of an unknown future. Worried spouses, siblings, children and grandchildren of newly diagnosed patients grapple with the same uncertainty. How bad is the cancer? How far has it spread? How long can the patient live with therapy, and what therapies are even possible?

This basic question of therapeutic options and the choice of treatment is the first important step for a doctor and a patient. It can mean the difference between life and death. Normally, there is “standard therapy,” which is an established, reliable and predictable option. It includes broad chemotherapy, radiation and often combinations of both. These chemical and radiological therapies ravage healthy and cancer cells alike, hoping to kill more of the cancerous cells than the healthy ones. Patients typically lose their hair, their eyebrows and their strength. Success rates are limited, and, for the most part, the technology behind chemotherapy has not changed in decades.

In the past few years, however, entirely new kinds of treatment have emerged. Called “living therapies,” they include some immunotherapies and targeted therapies. These new approaches are built around the idea that the immune system’s cells already work very well to keep cancer away from most people for about a century of living. But sometimes these cells need a little help. Using recent cellular engineering technologies, scientists and clinicians have discovered new ways to modify immune cells, reprogramming them into better, stronger cells that can target only cancer cells. Some of these methods, called chimeric antigen receptor (CAR) therapies, use engineered cells with a hybrid (chimeric) receptor that can recognize cancer targets. These therapies, called CAR-T treatments, often use genetically modified immune cells derived from T cells. Some of the newer CAR therapies being tested use engineered natural killer (NK) cells — white blood cells that are part of the patient’s innate immune system. These methods can even create entirely new types of immune cells that can be programmed if the cancer evolves.

Excitingly, these new therapies may provide hope for some cancer patients who previously had untreatable or high-risk cancers. In 2017 and 2018, the U.S. Food and Drug Administration approved the first two CAR-T treatments for patients with certain forms of blood cancers. Success rates have been as high as 90 percent for some cancers, such as lymphoma, and the hope is that these methods could be used for other cancers. During the past couple of years, dozens of new trials began to appear, with a range of modifications for CAR-T. Unfortunately, it was not clear where all the clinical trials were located around the world, what immune cells were being engineered and how many patients were being recruited into these trials.

To address this issue, my team of researchers at Weill Cornell Medicine have built the first global database of CAR clinical trials that are genetically modifying immune cells. We profiled, annotated, mapped and then leveraged all publicly available trials to create a “therapeutic road map” for all current therapies and the additional cancers that can be treated with them. Our new road map also reveals cellular designs for entirely new CAR therapies. This work is supported by WorldQuant founder Igor Tulchinsky and the WorldQuant Foundation, the Pershing Square Sohn Cancer Research Alliance, the STARR Cancer Consortium, the Weill-Caulier Charitable Trusts, the Vallee Foundation, the National Institutes of Health (P01CA214274 and 1R01MH117406), and the Leukemia and Lymphoma Society.

The new map, which we published earlier this month in Nature Biotechnology, allows anyone — including patients, doctors and physicians — to filter and solve for CAR trials, guiding their therapeutic choices very quickly. In only a few seconds, anyone can find the immunotherapy trial options that match their age, cancer type and diagnosis. This road map is also a guide for bioengineers working on developing future generations of CAR therapies, including those with ‘programmable switches’ and customized receptors.

The CAR Global Trials database website — built using natural language processing (NLP), machine learning and predictive analytics — has leveraged a range of cancer and related datasets, including the National Institutes of Health’s clinical trial database and three other databases containing information about molecules being used in the clinic that could be candidates in CAR therapies: the Human Protein Atlas, the Genotype-Tissue Expression Portal and the Differentially Expressed Proteins in Cancer database. These datasets provide context for the rapidly expanding universe of CAR therapies on normal and cancerous cells.

There are now more than 500 CAR therapies around the world, with the majority taking place in the U.S. and China. From 2014 to 2018, the number of trials increased fourfold, and the data are just starting to come in for both the successes and the failures. Indeed, while some patients have experienced complete cancer remissions, others have shown severe side effects, such as cytokine release syndrome (CRS), in which there is a rapid release of inflammation and stress molecules that can lead to fever, a neurological event or even cardiac arrest. This indicates that although the therapies are already working well, they could work better. Specifically, our research has shown that it should be possible to create a cell that keeps normal cells safe but that is even better at finding and killing cancer cells.

This inspired our lab to try to redesign CAR therapies to be more predictive as well as more precise. First, we mapped out what is normally present on the outside of cells in healthy tissues, which we then compared with all known cancer cell data. We analyzed more than 13,000 potential targets to find candidates for potential CAR cell engineering, and found a new set of 65 molecules that are not yet being used, but that should have a lower risk of toxicity for patients. We also found 17 targets that should be safer for women and 12 that are likely better matches for males, as well as some age-specific and tissue-specific therapies. Finally, we designed a set of “logic switches” for the cells that can provide a “toggle” to turn on or off cell functions and provide more ways to identify cancer cells and protect normal cells, either alone (single target) or in combination. Our data suggest a landscape of more than 100 single targets and over 100,000 target pairs that could be used as logic switches for CAR cell engineering for 20 different types of cancer.

These new research tools, clinical road map, and patient and physician portal highlight the power of predictive algorithms to guide current and future cancer therapies. These methods also bring genetic engineering to a new era of customized and programmed immune cells, which should lead to lower toxicity for patients and improved outcomes. Some of the new cells are already being tested, engineered and modified in our laboratory. These new methods and cells provide new therapeutic options, more tools for doctors to fight cancer and safer treatments for patients, which have already opened up completely new directions of predictive medicine.

Perhaps, most importantly, there will be more hope for alternative options in the future that may provide advanced therapeutic treatments for patients struggling in those dark moments after they hear the words: “You have cancer.”

Dr. Christopher Mason is an associate professor of physiology and biophysics at Weill Cornell Medicine, and co-director of the WorldQuant Initiative for Quantitative Prediction at Weill Cornell with Dr. Olivier Elemento. He is also an associate professor of computational genomics in computational biomedicine in the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud Institute for Computational Biomedicine, an associate professor of neuroscience in the Feil Family Brain and Mind Institute, and a member of the Sandra and Edward Meyer Cancer Center at Weill Cornell Medicine.

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