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Cardio-Oncology in the Modern Era: Innovative Tools for a Complex Problem

Cardio-Oncology in the Modern Era: Innovative Tools for a Complex Problem

Abstract
The field of cardio-oncology (or the adverse cardiovascular effects of cancer treatments) is evolving due to the emergence of multiple new cancer treatments, many of which can have implications on cardiovascular health. Most physicians are forced to simply react to cardiovascular damage due to cancer treatment, and the tools for preventative medicine in this setting are minimal. Awareness about cardio-oncology is crucial, and there is a need to identify potential intervention tools that enable clinicians to be at the forefront of care. Innovative approaches, such as personalized medicine, 3-D cardiac modeling, and machine learning can uncover mechanisms related to adverse cardiovascular events during cancer treatment and improve patient care.
Cardio-oncology is a growing field positioned to elaborate upon and treat cardiovascular side-effects resulting from cancer treatment. In a salient 2017 article by Mitchel Zoler for Frontline Medical, numerous physician perspectives highlight the increasing fervor and necessity of such a subspecialty.1 Indeed, the sheer volume of publications mentioning “cardio-oncology” grew from 60 in 2014 to a staggering 195 in 2017, only three years later (Figure 1). Adverse cardiovascular events arise from oncologic treatment regimens, most commonly those that involve anthracyclines, anti-HER2 compounds, and VEGF inhibitors. Interestingly, specific publication trends that mention cardio-oncology in the context of these treatments (as indicated in the title or abstract) reveal a more gradual increase over the past 5 years. These preliminary results could reflect magnified overall awareness from the medical community of the importance of cardio-oncology as new studies are published.

Figure 1: The total number of articles that mention at any point ‘cardio-oncology’ is highlighted in the background in grey. The foreground shows the publication segmentation for those articles that mention ‘cardio-oncology’ at any point while indicating in either their title or abstract specifically those therapies shown including VEGF inhibitors (blue), anti-HER2 compounds (orange), and anthracyclines (green).
The possibility for cardiotoxicity resulting from chemotherapy treatment is not a matter to be taken lightly, as dyssynchronous heart failure in general has been shown to have lasting effects on a cellular and molecular level. Kirk and Kass highlight cardiomyocytes from dyssynchronous hearts in a canine model showing sarcomere shortening and slower contraction.2 Correspondingly, calcium handling is altered, a finding echoed on a molecular level where decreased mRNA expression of phospholamban and sarcoplasmic reticular Ca2+ ATPase has been noted. Irregularities in these and other membrane channels can alter overall signaling in the organ, leading to a prolonged action potential duration characteristic of heart failure. Such aberrant signaling places unusual energetic demands on the heart, resulting in increased basal mitochondrial oxygen consumption.2 Cardiac complications like heart failure and cardiac-induced cardiomyopathy are a sizeable problem for the oncology community, as these events have been reported in 1%-5% of cancer survivors.3,4 As the NCI predicts the number of people living beyond a cancer diagnosis to reach nearly 19 million by 2024, this could equate to roughly 190,000-950,000 patients who may suffer from adverse cardiac events during chemotherapy.5
“I involve the cardiologist once there is evidence of damage,”
Zoler quotes Dr. Swain, a professor of medicine at Georgetown University in Washington1; but in the burgeoning era of preventative medicine, it may be more cost-effective in the long run to develop measures to protect against this cardiotoxicity on the front-end of a treatment regimen. Such is true for some personalized medicine projects, in which a diagnostic test for genetic-based responsiveness to a given drug may be favored by providers on the basis of long-term cost savings. In such a hypothetical scenario, drug A would only be prescribed to those patients who were the most likely to improve, while others would be placed on a different (and more likely efficacious) regimen B. In so doing, likely ‘nonresponsive’ patients to drug A would also be spared the side effects of an unsuccessful treatment. Here, genetic testing holds promising potential in the world of diagnostics to facilitate customized, and optimized treatment while minimizing patient risk. However digital approaches too, like the BlueStar app, are also gaining traction in the insurance marketplace as they’ve highlighted an average savings of $470 per diabetic patient per month as a result of those prophylactic choices it encourages in its user population. In some instances, the app’s artificial intelligence was even more accurate in predicting adverse events like hypoglycemia than the endocrinologist.6 To this end, what if it was possible to non-invasively model, monitor, and predict those cardiovascular changes that occur as a result of chemotherapy? Which technologies are positioned to be the most useful for this purpose, and what are their current states of development and applications?
Genetic information has demonstrated increasing utility throughout the past decade, especially when examined against patient health records. Sheng, et al. highlights how one particular study found a rare kinase gene variant that was associated with osteoporosis; revealing the potential for exacerbation of this side effect should a patient be treated with kinase inhibitors. Authors continued to elaborate that analyses of genetic information may yield similar insights as to the potential genetic susceptibility for adverse cardiovascular effects resulting from chemotherapy, including heart failure, sudden cardiac death, and myocardial infarction.7 However, our predictive power is not limited alone to genetic information. Computational 3D modeling is another technique which may be of particular use for these endeavors. Drs. Auricchio and Prinzen have recently published their “3B perspective” standing for a “bench, bits, and beside” approach in which these digital methods may be used in conjunction with understanding gained from basic bench science and clinical studies to provide optimal CRT placement and pacing for patients. Here, these studies yield insight as to the heart’s fiber orientation, ion channel function, and contractility.8 The results of such interdisciplinary ventures are astounding, where both enhanced imaging techniques and overall computational power have allowed for the development of what Lopez-Perez, et al. accurately describes as “patient-specific 3D cardiac models”.9 In theory, one goal would be to incorporate such an analysis into a strategic pacemaker implantation process for each patient; however, there is no reason why such techniques could not be similarly applied towards monitoring those cardiac effects in chemotherapy patients. In fact, Ultrasound Medical Device Inc. based out of Ann Arbor, Michigan, has filed one of the only method patents in a cardio-oncology context, indicating the use of ultrasound image data loops to continuously monitor the heart of a patient.10
The dearth of appearances ‘cardio-oncology’ has made in the patent world sits in stark contrast to the recent spike in publication interest, potentially indicating that those gene-based diagnostic, imaging, and modeling tools common for conventional oncology or cardiology have yet to be widely tailored to this emerging subspecialty. Therefore, a similar 3-pronged approach utilizing information on genetic susceptibility, 3D modeling, and machine learning, may be especially useful in the mechanistic elaboration, and ultimately prediction and prevention, of these adverse cardiotoxic effects in chemotherapy patients. Continued awareness of cardio-oncology however, remains crucial, as this alongside collaborative projects between physicians and scientists will indelibly improve the quality of cancer care provided to patients of the future.
Alexis Karandrea, Ph.D., is a Technology Analyst with IDTechEx specializing in life science technologies.

    References:

    1. Mitchel Zoler. Cardio-oncology booms but awareness lags. Frontline Medical. https://www.pm360online.com/cardio-oncology-booms-but-awareness-lags/. September 21, 2017. Accessed January 18, 2018.
    2. Kirk, Jonathan A., and David A. Kass. "Cellular and molecular aspects of dyssynchrony and resynchronization." Heart failure clinics 13.1 (2017): 29-41.
    3. Cardinale, Daniela, et al. "Prognostic value of troponin I in cardiac risk stratification of cancer patients undergoing high-dose chemotherapy." Circulation 109.22 (2004): 2749-2754.
    4. Felker, G. Michael, et al. "Underlying causes and long-term survival in patients with initially unexplained cardiomyopathy." New England Journal of Medicine 342.15 (2000): 1077-1084.
    5. National Cancer Institute. Cancer Statistics. https://www.cancer.gov/about-cancer/understanding/statistics March 22, 2017. Accessed January 18, 2018.
    6. Kowitt, Sarah D., et al. "Combining the High Tech with the Soft Touch: Population Health Management Using eHealth and Peer Support." Population health management 20.1 (2017): 3-5.
    7. Sheng, Calvin Chen, et al. "21st Century Cardio-Oncology: Identifying Cardiac Safety Signals in the Era of Personalized Medicine." JACC: Basic to Translational Science 1.5 (2016): 386-398.
    8. Auricchio, Angelo, and Frits W. Prinzen. "Enhancing Response in the Cardiac Resynchronization Therapy Patient: The 3B Perspective—Bench, Bits, and Bedside." JACC: Clinical Electrophysiology 3.11 (2017): 1203-1219.
    9. Lopez-Perez, Alejandro, Rafael Sebastian, and Jose M. Ferrero. "Three-dimensional cardiac computational modelling: methods, features and applications." Biomedical engineering online 14.1 (2015): 35.
    10. Hamilton, James, Eric J. Sieczka, and Eric T. Larson. "Method and system for acquiring and analyzing multiple image data loops." U.S. Patent Application No. 13/796,126.

    Volume

    July 2018 | Vol. 1 Q3