News

In RAS-related diseases, such as cancer, mutations in the RAS genes or their regulators render RAS proteins persistently active. Investigating RAS activation events is challenging when using conventional techniques. An unprecedented multiscale platform is using machine learning to change that.

A few of NCI’s Division of Cancer Biology grantees recently released publications on topics such as machine learning and artificial intelligence. These research results hold clues to how we research and develop various cancer treatments.

Staff from CBIIT and NCI, alongside partners from NIH, FDA, and a consortium of scientists from across the world, joined forces to create reference samples and data call sets to help the cancer community further decipher cancer-related gene mutations. Their findings were recently published in Nature Biotechnology.

Dr. Jill Barnholtz-Sloan, CBIIT’s associate director of Informatics and Data Science and DCEG senior investigator, together with research colleagues, used a direct data matching approach to compare brain tumors in U.S. Veteran and non-Veteran populations. The study indicates that direct and deterministic data matching approaches have the potential to compare the distribution of tumors, treatment trajectories, and clinical outcomes of other cancers and rare diseases among these populations.

Data science is one of the crosscutting themes in NIH’s newly released Strategic Plan for Fiscal Years 2021-2025. The Strategic Plan outlines how NIH will advance its mission and fulfill the requirements of the 21st Century Cures Act. NIH outlines how utilizing data and modernizing the NIH-funded data ecosystem is imperative to mission success.

CBIIT Director, Dr. Tony Kerlavage, along with NCI staff and a host of experts in childhood cancer research, recently published an article, “Cancer Informatics for Cancer Centers (CI4CC): Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult (AYA) Cancer,” in JCO Cancer Clinical Informatics. The article summarizes the Fall 2020 CI4CC Symposium and showcases the scope of initiatives underway to address childhood cancer, with a particular emphasis on how data science and informatics are helping to support these initiatives.

Data scientists, cancer biologists, and computational scientists are invited to submit abstracts to the Computational Approaches for Cancer Workshop (CAFCW21). Papers should focus on the application of computational approaches to cancer challenges, and those selected will be presented at the workshop. Abstract submissions are due by Monday, September 13.

In partnership with The Cancer Imaging Archive (TCIA), the American Association of Physicists in Medicine released a special virtual issue of Medical Physics in March 2021 titled, “Datasets Hosted in NCI’s Cancer Imaging Archive.” This special issue aims to highlight valuable examples of both Medical Physics Data Set Articles (MPDAs) and publicly available data sets that can be reused for future research endeavors and utilized for addressing emerging scientific or clinical questions.

NCI’s Office of Cancer Genomics’ data analysis and experimental observations tool—CTD² Dashboard—aims to make cancer-relevant results from the CTD² Network easier to use. Learn more about recent improvements to the Dashboard.

Drs. Daoud Meerzaman of NCI’s Center for Biomedical Informatics and Information Technology (CBIIT) and Barbara K. Dunn of NCI’s Biometry Research Group recently served as Guest Editors for a special virtual issue of the journal, Frontiers in Oncology. This collection of articles shows how ‘omics data are helping scientists to better understand the prevention, detection, and treatment of cancer. The issue explores the full range of ‘omics findings, from identifying biomarkers for diagnosing and treating cancer, to uncovering the mechanisms for disease.