Ketogenic diet does not promote triple-negative and luminal mammary tumor growth and metastasis in experimental mice.

Ketogenic diets (KDs) can improve the well-being and quality of life of breast cancer patients. However, data on the effects of KDs on mammary tumors are inconclusive, and the influence of KDs on metastasis in general remains to be investigated. We therefore assessed the impact of a KD on growth and metastasis of triple negative murine 4T1 mammary tumors, and on the progression of luminal breast tumors in an autochthonous MMTV-PyMT mouse model. We found that KD did not influence the metastasis of 4T1 and MMTV-PyMT mammary tumors, but impaired 4T1 tumor cell proliferation in vivo, and also temporarily reduced 4T1 primary tumor growth. Notably, the ketogenic ratio (the mass of dietary fat in relation to the mass of dietary carbohydrates and protein) that is needed to induce robust ketosis was twice as high in mice as compared to humans. Surprisingly, only female but not male mice responded to KD with a sustained increase in blood ß-hydroxybutyrate levels. Together, our data show that ketosis does not foster primary tumor growth and metastasis, suggesting that KDs can be safely applied in the context of luminal breast cancer, and may even be advantageous for patients with triple negative tumors. Furthermore, our data indicate that when performing experiments with KDs in mice, the ketogenic ratio needed to induce ketosis must be verified, and the sex of the mice should also be taken into account.

The crosstalk between glomerular endothelial cells and podocytes controls their responses to metabolic stimuli in diabetic nephropathy.

In diabetic nephropathy (DN), glomerular endothelial cells (GECs) and podocytes undergo pathological alterations, which are influenced by metabolic changes characteristic of diabetes, including hyperglycaemia (HG) and elevated methylglyoxal (MGO) levels. However, it remains insufficiently understood what effects these metabolic factors have on GEC and podocytes and to what extent the interactions between the two cell types can modulate these effects. To address these questions, we established a co-culture system in which GECs and podocytes were grown together in close proximity, and assessed transcriptional changes in each cell type after exposure to HG and MGO. We found that HG and MGO had distinct effects on gene expression and that the effect of each treatment was markedly different between GECs and podocytes. HG treatment led to upregulation of "immediate early response" genes, particularly those of the EGR family, as well as genes involved in inflammatory responses (in GECs) or DNA replication/cell cycle (in podocytes). Interestingly, both HG and MGO led to downregulation of genes related to extracellular matrix organisation in podocytes. Crucially, the transcriptional responses of GECs and podocytes were dependent on their interaction with each other, as many of the prominently regulated genes in co-culture of the two cell types were not significantly changed when monocultures of the cells were exposed to the same stimuli. Finally, the changes in the expression of selected genes were validated in BTBR ob/ob mice, an established model of DN. This work highlights the molecular alterations in GECs and podocytes in response to the key diabetic metabolic triggers HG and MGO, as well as the central role of GEC-podocyte crosstalk in governing these responses.

The LIM domain protein nTRIP6 modulates the dynamics of myogenic differentiation.

The process of myogenesis which operates during skeletal muscle regeneration involves the activation of muscle stem cells, the so-called satellite cells. These then give rise to proliferating progenitors, the myoblasts which subsequently exit the cell cycle and differentiate into committed precursors, the myocytes. Ultimately, the fusion of myocytes leads to myofiber formation. Here we reveal a role for the transcriptional co-regulator nTRIP6, the nuclear isoform of the LIM-domain protein TRIP6, in the temporal control of myogenesis. In an in vitro model of myogenesis, the expression of nTRIP6 is transiently up-regulated at the transition between proliferation and differentiation, whereas that of the cytosolic isoform TRIP6 is not altered. Selectively blocking nTRIP6 function results in accelerated early differentiation followed by deregulated late differentiation and fusion. Thus, the transient increase in nTRIP6 expression appears to prevent premature differentiation. Accordingly, knocking out the Trip6 gene in satellite cells leads to deregulated skeletal muscle regeneration dynamics in the mouse. Thus, dynamic changes in nTRIP6 expression contributes to the temporal control of myogenesis.

Quantitative Detection of Disseminated Melanoma Cells by Trp-1 Transcript Analysis Reveals Stochastic Distribution of Pulmonary Metastases.

A better understanding of the process of melanoma metastasis is required to underpin the development of novel therapies that will improve patient outcomes. The use of appropriate animal models is indispensable for investigating the mechanisms of melanoma metastasis. However, reliable and practicable quantification of metastases in experimental mice remains a challenge, particularly if the metastatic burden is low. Here, we describe a qRT-PCR-based protocol that employs the melanocytic marker Trp-1 for the sensitive quantification of melanoma metastases in the murine lung. Using this protocol, we were able to detect the presence of as few as 100 disseminated melanoma cells in lung tissue. This allowed us to quantify metastatic burden in a spontaneous syngeneic B16-F10 metastasis model, even in the absence of visible metastases, as well as in the autochthonous Tg(Grm1)/Cyld-/- melanoma model. Importantly, we also observed an uneven distribution of disseminated melanoma cells amongst the five lobes of the murine lung, which varied considerably from animal to animal. Together, our findings demonstrate that the qRT-PCR-based detection of Trp-1 allows the quantification of low pulmonary metastatic burden in both transplantable and autochthonous murine melanoma models, and show that the analysis of lung metastasis in such models needs to take into account the stochastic distribution of metastatic lesions amongst the lung lobes.