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Last Posted: Apr 03, 2024
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Genomes in clinical care
O Riess et al, NPJ Genomic Medicine, March 14, 2024

From the abstract: "In the era of precision medicine, genome sequencing (GS) has become more affordable and the importance of genomics and multi-omics in clinical care is increasingly being recognized. However, how to scale and effectively implement GS on an institutional level remains a challenge for many. Here, we present Genome First and Ge-Med, two clinical implementation studies focused on identifying the key pillars and processes that are required to make routine GS and predictive genomics a reality in the clinical setting. "

Challenges and best practices in omics benchmarking.
Thomas G Brooks et al. Nat Rev Genet 2024 1

From the abstract: "Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale biological data sets, such as transcriptomics, proteomics and metabolomics. With thousands of omics benchmarking studies published over the past 25 years, the field has matured to the point where the foundations of benchmarking have been established and well described. "

What Will 2024 Mean for NGS and Genomics?
J Lemieux, GenNew, January 12, 2024

From the article: "Recent technological innovations in next-generation sequencing (NGS) have users spoiled for choice. At first, new options began trickling in. But then the floodgates opened in 2022. Folding into this market expansion is the growth in the demand for sequencing, not only from directed genomic sequencing, but also from the growth of other omics technologies such as single-cell genomics and spatial transcriptomics, and of clinical applications such as liquid biopsy—all of which rely on sequencing."

Computational immunogenomic approaches to predict response to cancer immunotherapies.
Venkateswar Addala et al. Nat Rev Clin Oncol 2023 11

From the abstract: " Cancer immunogenomics is an emerging field that bridges genomics and immunology. The establishment of large-scale genomic collaborative efforts along with the development of new single-cell transcriptomic techniques and multi-omics approaches have enabled characterization of the mutational and transcriptional profiles of many cancer types and helped to identify clinically actionable alterations as well as predictive and prognostic biomarkers. Researchers have developed computational approaches and machine learning algorithms to accurately obtain clinically useful information from genomic and transcriptomic sequencing data. "

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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