ETH Zurich
ORCID: 0000-0002-1502-4801Publishes on Single-cell and spatial transcriptomics, Pluripotent Stem Cells Research, Bladder and Urothelial Cancer Treatments. 149 papers and 5.1k citations.
Add your photo, update your bio, and get notified when your ranking changes.
BACKGROUND: No new agent has improved overall survival in patients with unresectable or metastatic urothelial carcinoma when added to first-line cisplatin-based chemotherapy. METHODS: In this phase 3, multinational, open-label trial, we randomly assigned patients with previously untreated unresectable or metastatic urothelial carcinoma either to receive intravenous nivolumab (at a dose of 360 mg) plus gemcitabine-cisplatin (nivolumab combination) every 3 weeks for up to six cycles, followed by nivolumab (at a dose of 480 mg) every 4 weeks for a maximum of 2 years, or to receive gemcitabine-cisplatin alone every 3 weeks for up to six cycles. The primary outcomes were overall and progression-free survival. The objective response and safety were exploratory outcomes. RESULTS: A total of 608 patients underwent randomization (304 to each group). At a median follow-up of 33.6 months, overall survival was longer with nivolumab-combination therapy than with gemcitabine-cisplatin alone (hazard ratio for death, 0.78; 95% confidence interval [CI], 0.63 to 0.96; P = 0.02); the median survival was 21.7 months (95% CI, 18.6 to 26.4) as compared with 18.9 months (95% CI, 14.7 to 22.4), respectively. Progression-free survival was also longer with nivolumab-combination therapy than with gemcitabine-cisplatin alone (hazard ratio for progression or death, 0.72; 95% CI, 0.59 to 0.88; P = 0.001). The median progression-free survival was 7.9 months and 7.6 months, respectively. At 12 months, progression-free survival was 34.2% and 21.8%, respectively. The overall objective response was 57.6% (complete response, 21.7%) with nivolumab-combination therapy and 43.1% (complete response, 11.8%) with gemcitabine-cisplatin alone. The median duration of complete response was 37.1 months with nivolumab-combination therapy and 13.2 months with gemcitabine-cisplatin alone. Grade 3 or higher adverse events occurred in 61.8% and 51.7% of the patients, respectively. CONCLUSIONS: Combination therapy with nivolumab plus gemcitabine-cisplatin resulted in significantly better outcomes in patients with previously untreated advanced urothelial carcinoma than gemcitabine-cisplatin alone. (Funded by Bristol Myers Squibb and Ono Pharmaceutical; CheckMate 901 ClinicalTrials.gov number, NCT03036098.).
combined with single-cell genomic technologies provide opportunities to examine gene regulatory networks underlying human brain development. Here we acquire single-cell transcriptome and accessible chromatin data over a dense time course in human organoids covering neuroepithelial formation, patterning, brain regionalization and neurogenesis, and identify temporally dynamic and brain-region-specific regulatory regions. We developed Pando-a flexible framework that incorporates multi-omic data and predictions of transcription-factor-binding sites to infer a global gene regulatory network describing organoid development. We use pooled genetic perturbation with single-cell transcriptome readout to assess transcription factor requirement for cell fate and state regulation in organoids. We find that certain factors regulate the abundance of cell fates, whereas other factors affect neuronal cell states after differentiation. We show that the transcription factor GLI3 is required for cortical fate establishment in humans, recapitulating previous research performed in mammalian model systems. We measure transcriptome and chromatin accessibility in normal or GLI3-perturbed cells and identify two distinct GLI3 regulomes that are central to telencephalic fate decisions: one regulating dorsoventral patterning with HES4/5 as direct GLI3 targets, and one controlling ganglionic eminence diversification later in development. Together, we provide a framework for how human model systems and single-cell technologies can be leveraged to reconstruct human developmental biology.
differentiation of neural progenitors during cortical development. Here, we have searched for such differences by analysing cerebral organoids from human and chimpanzees using immunohistofluorescence, live imaging, and single-cell transcriptomics. We find that the cytoarchitecture, cell type composition, and neurogenic gene expression programs of humans and chimpanzees are remarkably similar. Notably, however, live imaging of apical progenitor mitosis uncovered a lengthening of prometaphase-metaphase in humans compared to chimpanzees that is specific to proliferating progenitors and not observed in non-neural cells. Consistent with this, the small set of genes more highly expressed in human apical progenitors points to increased proliferative capacity, and the proportion of neurogenic basal progenitors is lower in humans. These subtle differences in cortical progenitors between humans and chimpanzees may have consequences for human neocortex evolution.
BACKGROUND: Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. METHODS/PRINCIPAL FINDINGS: To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. CONCLUSION/SIGNIFICANCE: Our results indicate that the network prediction system thus established is quite promising and encouraging.
Coming soon — researchers in similar fields and career stages