Successful treatment of cancer frequently depends on early detection. However, many cancers are detected late, often after metastasizing to other sites. Participants at the 7th USA-Japan Workshop on Biomarkers for Cancer Early Detection presented cutting-edge research to improve early detection and cancer prevention using advanced biomarkers and radiomics. Their findings and recommendations are published in a special issue of Cancer Biomarkers.
The National Cancer Institute (NCI), the Early Detection Research Network (EDRN), and the Japan Agency for Medical Research and Development (AMED) hold an annual USA-Japan Workshop on Biomarkers for Cancer Early Detection. The 7th USA-Japan Workshop was held at the Ito International Research Center at the University of Tokyo in January 2020.
Researchers from Japan and the US have been meeting annually to exchange ideas for the early diagnosis and detection of cancer since 2016. These pipelines and platforms for early detection of cancer will contribute to the implementation of attractive new methods for early cancer diagnosis, with the potential to decrease cancer."
Kazufumi Honda, DDS, PhD, Guest Editor, Department of Bioregulation, Graduate School of Medicine, Nippon Medical School, Tokyo, Japan
The papers in this special issue describe new technologies for comprehensively measuring proteins and metabolites using mass spectrometry; validation studies to evaluate the clinical utility of new diagnostic methods; use of computational science to analyze large volumes of information acquired by new technology; and blood biomarkers that facilitate the early detection of pancreatic cancer and also help identify high-risk individuals.
Mortality rates of pancreatic cancer are the worst among solid cancers. However, this is an uncommon cancer with an age-adjusted annual incidence of 12.9 cases per 100,000 person-years. To efficiently identify patients with potentially surgically-curable pancreatic cancer, high-risk individuals should be identified by easily and minimally invasive methods from the general population. Dr. Honda and colleagues described blood biomarkers that facilitate not only the early detection of pancreatic cancer, but also help identify high-risk individuals. The clinical usefulness of apolipoprotein A2-isoforms (apoA2-i), which are formed by post-translational modification via enzymatic activity in pancreatic lesions, for the early detection and risk stratification of pancreatic cancer were reviewed. The results of a large-scale prospective screening study for pancreatic cancer that used the apoA2-i blood test were also presented.
The large volume of information acquired by new technology cannot be analyzed without computational science. Matthew B. Schabath, PhD, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, and colleagues utilized peritumoral and intratumoral radiomics and volume doubling time (VDT) to identify high-risk subsets of lung cancer patients diagnosed by lung cancer screening who tend to have poor survival outcomes. They generated a model that identifies the high-risk group of screen-detected lung cancers that is associated with poor survival outcomes.
Sumio Ohtsuki, PhD, and colleagues from Kumamoto University, Kumamoto, Japan, reported on rapid validation methods for protein biomarkers using targeted proteomics and mass spectrometry.
A team co-led by Yoshihiro Shimizu, PhD, from RIKEN Center for Biosystems Dynamics Research, Osaka, Japan, and Alireza Mashaghi, MD, PhD, from Leiden University, Leiden, The Netherlands, presented a novel exploration method using capillary microsampling-based single-cell metabolomics with high-resolution mass spectrometry, which can identify the metabolomic profile of a single circulating tumor cell.
Pierre Massion, MD, presented at this conference but unexpectedly passed away on June 4, 2021. He was the Lead Primary Investigator of the Clinical Validation Center (CVC) of the Early Detection Research Network (EDRN) along with Eric L. Grogan, MD, MPH, from Vanderbilt University Medical Center, and Tennessee Valley Healthcare System, Veterans Affairs, Nashville, TN, USA. In honor of Dr. Massion's decade of work developing and validating lung cancer biomarkers, Michael N. Kammer, PhD, also from Vanderbilt University Medical Center, Dr. Grogan, and colleagues described the roles of the Vanderbilt University EDRN Lung CVC in phase-1, -2, and, -3 lung cancer biomarker validation studies.
Jennifer B. Permuth, PhD, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA, and colleagues covered the importance of implementing quality control procedures when designing multicenter evaluations of miRNA abundance.
D.J. Crichton, MS, Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, USA, and colleagues presented the collaborative work of the National Aeronautics and Space Administration (NASA), JPL, NCI EDRN, and the Molecular and Cellular Characterization of Screen-Detected Lesions (MCL), which will enable data-driven discovery in cancer biomarker research using artificial intelligence and machine learning with automated annotation and data science.
"The development of biomarkers requires sizeable investment and infrastructure-related resources, and it takes several years to bring biomarkers to clinical use," noted Sudhir Srivastava, PhD, Chief of the Cancer Biomarkers Research Group, National Cancer Institute Division of Cancer Prevention, NIH, Bethesda, MD, USA, and Editor-in-Chief of Cancer Biomarkers. "The US-Japan partnership will strengthen collaborations by creating a vehicle for each country to interact with and co-fund the development of the required infrastructure."
Dr. Srivastava continued, "There is an urgent need to discover and validate biomarkers for less common cancers and the collaboration between the US and Japan could enhance the discovery process. It is hoped that such sharing of data and knowledge will continue to help tackle the complex issues surrounding biomarkers for early detection."
Posted in: Medical Science News | Medical Condition News
Tags: Apolipoprotein, Artificial Intelligence, Biomarker, Blood, Blood Test, Cancer, Cancer Biomarker, Cancer Diagnosis, Cancer Prevention, Cell, Circulating Tumor Cell, Diagnostic, Healthcare, Laboratory, Lung Cancer, Machine Learning, Mass Spectrometry, Medical Research, Medical School, Medicine, Metabolites, Metabolomics, Mortality, Pancreatic Cancer, Protein, Proteomics, Research, Spectrometry, Tumor, Veterans Affairs
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