Accumulating data suggest that metastatic dissemination often occurs early during tumour formation but the mechanisms of early metastatic spread have not yet been addressed. Here, we studied metastasis in a HER2-driven mouse breast cancer model and found that progesterone-induced signalling triggered migration of cancer cells from early lesions shortly after HER2 activation, but promoted proliferation in advanced primary tumour cells. The switch from migration to proliferation was regulated by elevated HER2 expression and increased tumour cell density involving miRNA-mediated progesterone receptor (PGR) down-regulation and was reversible. Cells from early, low-density lesions displayed more stemness features than cells from dense, advanced tumours, migrated more and founded more metastases. Strikingly, we found that at least 80% of metastases were derived from early disseminated cancer cells (DCC). Karyotypic and phenotypic analysis of human disseminated cancer cells and primary tumours corroborated the relevance of these findings for human metastatic dissemination.
Next-generation sequencing of the hypervariable V3 region of the 16s rRNA gene isolated from serial stool specimens collected from 31 patients receiving allogeneic stem cell transplantation (SCT) was performed to elucidate variations in the composition of the intestinal microbiome in the course of allogeneic SCT. Metagenomic analysis was complemented by strain-specific enterococcal PCR and indirect assessment of bacterial load by liquid chromatography-tandem mass spectrometry of urinary indoxyl sulfate. At the time of admission, patients showed a predominance of commensal bacteria. After transplantation, a relative shift toward enterococci was observed, which was more pronounced under antibiotic prophylaxis and treatment of neutropenic infections. The shift was particularly prominent in patients that developed subsequently or suffered from active gastrointestinal (GI) graft-versus-host disease (GVHD). The mean proportion of enterococci in post-transplant stool specimens was 21% in patients who did not develop GI GVHD as compared with 46% in those that subsequently developed GI GVHD and 74% at the time of active GVHD. Enterococcal PCR confirmed predominance of Enterococcus faecium or both E. faecium and Enterococcus faecalis in these specimens. As a consequence of the loss of bacterial diversity, mean urinary indoxyl sulfate levels dropped from 42.5 ± 11 µmol/L to 11.8 ± 2.8 µmol/L in all post-transplant samples and to 3.5 ± 3 µmol/L in samples from patients with active GVHD. Our study reveals major microbiome shifts in the course of allogeneic SCT that occur in the period of antibiotic treatment but are more prominent in association with GI GVHD. Our data indicate early microbiome shifts and a loss of diversity of the intestinal microbiome that may affect intestinal inflammation in the setting of allogeneic SCT.
The blood–brain barrier (BBB) and the environment of the central nervous system (CNS) guard the nervous tissue from peripheral immune cells. In the autoimmune disease multiple sclerosis, myelin-reactive T-cell blasts are thought to transgress the BBB and create a pro-inflammatory environment in the CNS, thereby making possible a second autoimmune attack that starts from the leptomeningeal vessels and progresses into the parenchyma. Using a Lewis rat model of experimental autoimmune encephalomyelitis, we show here that contrary to the expectations of this concept, T-cell blasts do not efficiently enter the CNS and are not required to prepare the BBB for immune-cell recruitment. Instead, intravenously transferred T-cell blasts gain the capacity to enter the CNS after residing transiently within the lung tissues. Inside the lung tissues, they move along and within the airways to bronchus-associated lymphoid tissues and lung-draining mediastinal lymph nodes before they enter the blood circulation from where they reach the CNS. Effector T cells transferred directly into the airways showed a similar migratory pattern and retained their full pathogenicity. On their way the T cells fundamentally reprogrammed their gene-expression profile, characterized by downregulation of their activation program and upregulation of cellular locomotion molecules together with chemokine and adhesion receptors. The adhesion receptors include ninjurin 1, which participates in T-cell intravascular crawling on cerebral blood vessels. We detected that the lung constitutes a niche not only for activated T cells but also for resting myelin-reactive memory T cells. After local stimulation in the lung, these cells strongly proliferate and, after assuming migratory properties, enter the CNS and induce paralytic disease. The lung could therefore contribute to the activation of potentially autoaggressive T cells and their transition to a migratory mode as a prerequisite to entering their target tissues and inducing autoimmune disease.
Aberrant regulation of the Wnt/β-catenin pathway has an important role during the onset and progression of colorectal cancer, with over 90% of cases of sporadic colon cancer featuring mutations in APC or β-catenin. However, it has remained a point of controversy whether these mutations are sufficient to activate the pathway or require additional upstream signals. Here we show that colorectal tumours express elevated levels of Wnt3 and Evi/Wls/GPR177. We found that in colon cancer cells, even in the presence of mutations in APC or β-catenin, downstream signalling remains responsive to Wnt ligands and receptor proximal signalling. Furthermore, we demonstrate that truncated APC proteins bind β-catenin and key components of the destruction complex. These results indicate that cells with mutations in APC or β-catenin depend on Wnt ligands and their secretion for a sufficient level of β-catenin signalling, which potentially opens new avenues for therapeutic interventions by targeting Wnt secretion via Evi/Wls.
BackgroundPersonalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media). While during recent years there has been a lot of enthusiasm about the potential of ‘big data’ and machine learning-based solutions, there exist only few examples that impact current clinical practice. The lack of impact on clinical practice can largely be attributed to insufficient performance of predictive models, difficulties to interpret complex model predictions, and lack of validation via prospective clinical trials that demonstrate a clear benefit compared to the standard of care. In this paper, we review the potential of state-of-the-art data science approaches for personalized medicine, discuss open challenges, and highlight directions that may help to overcome them in the future.ConclusionsThere is a need for an interdisciplinary effort, including data scientists, physicians, patient advocates, regulatory agencies, and health insurance organizations. Partially unrealistic expectations and concerns about data science-based solutions need to be better managed. In parallel, computational methods must advance more to provide direct benefit to clinical practice.
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