In a new study conducted by the University of South Australia a number of have been identified metabolic biomarkers that could help assess cancer risk. Using artificial intelligence to analyze data from nearly 500,000 participants in the UK Biobank, 84 characteristics that could indicate increased cancer risk were identified. Many of the biomarkers also indicated the risk of chronic kidney disease or liver disease, underscoring the importance of exploring the underlying pathogenic mechanisms of these diseases and the potential connection to the occurrence of cancer.
Although further studies are needed to confirm causality and clinical relevance, the study suggests that through relatively simple blood tests and data about a person’s habits, physique and other individual characteristics, integrated with the help of AI, cancer risk assessment could be optimized. Further, the approach could enable interventions at early stages.
“More than 40% of the features identified by the model turned out to be biomarkers – biological molecules that can signal health or disease conditions, depending on their status. Several of these have been linked in common to cancer risk and kidney disease or liver disease,” said Dr. Iqbal Madakkatel, part of the research team, to the publication ScienceDaily.
By age, the increased level of urinary microalbumin was the most important predictor of cancer risk, indicating not only kidney disease. Albumin is a serum protein necessary for tissue growth and healing, but when it is present in the urine it indicates not only kidney disease but also the risk of cancer. Other indicators related to poor kidney function, such as high levels of cystatin C in the blood, increased urinary creatinine and lower total serum protein, have also been linked to cancer risk. The high difference between red blood cell sizes has been associated with an increased risk of cancer, suggesting increased inflammation and poor kidney function. Normally, red blood cells should be about the same size. High levels of C-reactive protein (indicator of systemic inflammation) and the enzyme gamma-glutamyl transferase (GGT) have also been associated with increased cancer risk.
The authors point out that although the model used included information on thousands of individual characteristics, including clinical, behavioral and social factors, the strongest predictors were blood biomarkersreflecting metabolic status before cancer diagnosis.
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Well-established risk factors for cancer, such as obesity, have been confirmed. Waist circumference and weight have also been linked to increased cancer risk. Inflammatory markers such as CRP and pulse rate have been associated with cancer risk, suggesting a possible role of inflammation in oncogenesis. Muscle mass has been directly associated with cancer risk due to mechanisms related to the basal metabolic rate, the higher the basal metabolic rate, the more toxic oxidants it generates during mitochondrial respiration. Certain blood cell characteristics, including total white blood cell count, monocyte count, lymphocyte count, and platelet count, were positively associated with cancer risk. Factors such as insulin-like growth factor 1 (IGF-1) and testosterone have been identified as risk factors for cancer, with testosterone being associated with breast and endometrial cancer in women.
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2023-11-03 10:53:38
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