Research in the field of cancer prevention and early cancer detection has received significant attention and financial investment in the last decade with the development of more affordable next-generation sequencing (NGS) platforms and machine-learning–enhanced medical imaging and screening technologies.

In a recent study, scientists and clinicians at the company Human Longevity, Inc. (HLI), set out to test the utility of these genomic and phenotypic screening technologies in early disease detection using their precision health platform, Health Nucleus.1 According to HLI, “Health Nucleus is Human Longevity’s premier health intelligence platform utilizing state-of-the-art technology to provide an assessment of current and future risk for cardiac, oncologic, metabolic, and cognitive diseases and conditions.”2

In the prospective study that enrolled a volunteer-based cohort of 1190 adults (median age of 54 years), participants were screened with technologies employed by Health Nucleus to determine their utility in early disease detection. Clinical whole-genome sequencing was first used for pathogenic variant detection, finding that 1 in 6 (17.3%) participants harbored pathogenic or likely pathogenic (P/LP) variants.1 Deep phenotyping technologies including advanced imaging, metabolomic screening, and clinical lab tests were then used to test the association between genotype and observed chronic condition, indicating that 1 in 9 (11.5%) participants had direct pathogenic genotype to chronic disease phenotype associations.1

In the case of early cancer detection, deep phenotyping resulted in the identification of 20 participants with early-stage neoplasia.1 “Whole-body MRI had great success in early detection of prostate and kidney cancer[s],” said Ying-Chen Claire Hou, PhD, senior scientist at HLI and first author on the study. Other cancers identified with HLI’s deep phenotyping methods included lymphoma, transitional cell carcinoma, papillary thyroid cancer, pancreatic cancer, neurofibromatosis, and mediastinal thymoma. For the genomic risk assessment, Dr Hou continued, “we are able to detect variants associated with breast, ovarian, colon, and prostate cancer,” and this information was then made available to health care providers “to implement screening and prophylactic measures, aiding in the prevention of disease.” 


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The study’s results also indicated there were limitations to relying on genomic data alone for cancer risk assessment and early detection. “Genetic testing that identified a P/LP variant is not equivalent to diagnosing the patients with associated inherited cancer syndrome.” Dr Hou said. “Clinicians need to use family history and medical history to evaluate if the clinical diagnosis of inherited cancer syndrome is appropriate.”

So, while the study was able to determine a 75% genotype-to-phenotype association in cardiac conditions such as dyslipidemia and endocrine disorders such as diabetes,1 many participants with cancer-associated variants didn’t have observable neoplasia. The study stated, “30 out of 69 participants with P/LP variants associated with cancer predisposition did not have corresponding family history and phenotypes at the time of evaluation.” The low association likely reflected the somatic origins of many cancers, as opposed to inherited germline variants. In other words, in the instances where participants developed cancer in the absence of pathogenic germline variants, the use of germline-based risk assessments would not have been useful to predict the emergence of a malignancy.