Chronodisruption and Ambulatory Circadian Monitoring in Cancer Patients: Beyond the Body Clock

Abstract

Purpose of Review Circadian rhythms impose daily rhythms a remarkable variety of metabolic and physiological functions, such as cell proliferation, inflammation, and DNA damage response. Accumulating epidemiological and genetic evidence indicates that circadian rhythms’ disruption may be linked to cancer. The integration of circadian biology into cancer research may offer new options for increasing cancer treatment effectiveness and would encompass the prevention, diagnosis, and treatment of this disease. Recent Findings In recent years, there has been a significant development and use of multi-modal sensors to monitor physical activity, sleep, and circadian rhythms, allowing, for the very first time, scaling accurate sleep monitoring to epidemiological research linking sleep patterns to disease, and wellness applications providing new potential applications. Summary This review highlights the role of circadian clock in tumorigenesis, cancer hallmarks and introduces the state-of-the-art in sleep-monitoring technologies, discussing the eventual application of insights in clinical settings and cancer research.

Prospects of Testing Diurnal Profiles of Expressions of TSH-R and Circadian Clock Genes in Thyrocytes for Identification of Preoperative Biomarkers for Thyroid Carcinoma

“…(e.g., [ 47 ]) gave rise to the hypotheses that the dysfunction of these clocks may have such a serious pathological effect as cancer [ 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ]. Indeed, accumulating fundings indicate that the disruptions of circadian rhythms are often linked to cancer [ 57 , 58 , 59 , 60 , 61 , 62 , 63 ]. Therefore, several research groups suggested a possibility to establish a relationship between thyroid cancer and circadian clockwork dysfunctions (e.g., [ 2 , 39 , 64 , 65 ]).…”

An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study

“…The promising tools of AI could be the only able to manage the big amount of data from different types of analysis, including information derived from DNA and RNA sequencing. Also, in addition to the terabytes of data being produced by EHRs, the use of PREMs and PROMs, or the incorporation of telemedicine with wearable devices in the clinical practice, AI tools that allow clinicians to analyze real-world data from their patients are needed [ 11 , 12 ]. In this sense, patterns and profiles may be obtained from specific patients or populations and AI-based predictions and algorithms can assist clinicians in medical decisions based on real-world medical evidence.…”

“…Analysis and sharing of these kinds of clinical data has become increasingly paramount as our knowledge of the extreme heterogeneity of cancer continues to grow. The application of AI algorithms has the potential to transform health and healthcare delivery by helping solve complex problems, such as quality of life improvement, increase in the chances of survival, and maximizing safety [ 11 , 12 , 13 ]. Common applications of AI algorithms in health care include identifying conditions, events, risk factors, associations, and patterns of difference or similarity, which can be used to support clinical decision making, improve treatment outcome, evaluate cost-effectiveness of tests, increase efficiency, and facilitate discovery [ 14 ].…”

Holistic Needs Assessment of Cancer Survivors—Supporting the Process Through Digital Monitoring of Circadian Physiology

“… 41 Circadian disruption could also account for digestive complaints, 101 sleep troubles, 102 and altered metabolism. 103 Thus, the accurate evaluation of circadian function through remote monitoring of cancer patients 83 could represent a biomarker of physiological and behavioral alteration, 75 a surrogate of symptom burden and of subjective complaints, 100 , 104 , 105 as well as a potential novel target of intervention, both pharmacological and behavioral. 79 …”