Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci.

Considering polygenic risk scores (PRSs) in individual risk prediction is increasingly implemented in genetic testing for hereditary breast cancer (BC) based on next-generation sequencing (NGS). To calculate individual BC risks, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) with the inclusion of the BCAC 313 or the BRIDGES 306 BC PRS is commonly used. The PRS calculation depends on accurately reproducing the variant allele frequencies (AFs) and, consequently, the distribution of PRS values anticipated by the algorithm.

Effects of Contagious Respiratory Pathogens on Breath Biomarkers.

Due to their immediate exhalation after generation at the cellular/microbiome levels, exhaled volatile organic compounds (VOCs) may provide real-time information on pathophysiological mechanisms and the host response to infection. In recent years, the metabolic profiling of the most frequent respiratory infections has gained interest as it holds potential for the early, non-invasive detection of pathogens and the monitoring of disease progression and the response to therapy. Using previously unpublished data, randomly selected individuals from a COVID-19 test center were included in the study.

Targeting glioblastoma tumor hyaluronan to enhance therapeutic interventions that regulate metabolic cell properties.

Unlabelled: Despite extensive advances in cancer research, glioblastoma (GBM) still remains a very locally invasive and thus challenging tumor to treat, with a poor median survival. Tumor cells remodel their microenvironment and utilize extracellular matrix to promote invasion and therapeutic resistance. We aim here to determine how GBM cells exploit hyaluronan (HA) to maintain proliferation using ligand-receptor dependent and ligand-receptor independent signaling.

Protocol for visualizing complex volatile metabolomics data in clinical setups using EDaViS software.

Here, we present a protocol for using Early Data Visualization Script, a user-friendly software tool to visualize complex volatile metabolomics data in clinical setups. We describe steps for tabulating data and adjusting visual output to visualize complex time-resolved volatile omics data using simple charts and graphs. We then demonstrate possible modifications by detailing procedures for the adaptation of four basic functions.

Clinical implications of incorporating genetic and non-genetic risk factors in CanRisk-based breast cancer risk prediction.

Background: Breast cancer (BC) risk prediction models consider cancer family history (FH) and germline pathogenic variants (PVs) in risk genes. It remains elusive to what extent complementation with polygenic risk score (PRS) and non-genetic risk factor (NGRFs) data affects individual intensified breast surveillance (IBS) recommendations according to European guidelines.

Methods: For 425 cancer-free women with cancer FH (mean age 40·6 years, range 21-74), recruited in France, Germany and the Netherlands, germline PV status, NGRFs, and a 306 variant-based PRS (PRS) were assessed to calculate estimated lifetime risks (eLTR) and estimated 10-year risks (e10YR) using CanRisk.