Presence of human breast cancer xenograft changes the diurnal profile of amino acids in mice.

Human xenografts are extremely useful models to study the biology of human cancers and the effects of novel potential therapies. Deregulation of metabolism, including changes in amino acids (AAs), is a common characteristic of many human neoplasms. Plasma AAs undergo daily variations, driven by circadian endogenous and exogenous factors. We compared AAs concentration in triple negative breast cancer MDA-MB-231 cells and MCF10A non-tumorigenic immortalized breast epithelial cells. We also measured plasma AAs in mice bearing xenograft MDA-MB-231 and compared their levels with non-tumor-bearing control animals over 24 h. In vitro studies revealed that most of AAs were significantly different in MDA-MB-231 cells when compared with MCF10A. Plasma concentrations of 15 AAs were higher in cancer cells, two were lower and four were observed to shift across 24 h. In the in vivo setting, analysis showed that 12 out of 20 AAs varied significantly between tumor-bearing and non-tumor bearing mice. Noticeably, these metabolites peaked in the dark phase in non-tumor bearing mice, which corresponds to the active time of these animals. Conversely, in tumor-bearing mice, the peak time occurred during the light phase. In the early period of the light phase, these AAs were significantly higher in tumor-bearing animals, yet significantly lower in the middle of the light phase when compared with controls. This pilot study highlights the importance of well controlled experiments in studies involving plasma AAs in human breast cancer xenografts, in addition to emphasizing the need for more precise examination of exometabolomic changes using multiple time points

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease